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Speaker 1: Hi everyone, Sophia Bush here. Welcome to Work in Progress,

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Speaker 1: where I talk to people who inspire me about how

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Speaker 1: they got to where they are and where they think

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Speaker 1: they're still going. Hi everyone, welcome to another special episode

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Speaker 1: of Work in Progress where we'll be continuing our video

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Speaker 1: series Need to Know. As you may know by now,

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Speaker 1: each week, I am sitting down with a different expert

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Speaker 1: to get answers to your most pressing questions about what

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Speaker 1: is going on in the world right now and what's

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Speaker 1: happening with this pandemic yea science today. I am so

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Speaker 1: excited for all of you to hear my conversation with

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Speaker 1: the wildly impressive and inspiring Esther otakun Lay. Esther is

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Speaker 1: a biochemist, neurobiologist, and antibody engineer currently working as a

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Speaker 1: scientist within the bio Farm Discovery Department at Glaxo Smith Klein,

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Speaker 1: where she is focused on exploring antibody selection as a

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Speaker 1: first step in the drug discovery and development pipeline. Beyond

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Speaker 1: her work as a scientist who is quite literally helping

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Speaker 1: to make life saving medications, Esther is directly involved in

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Speaker 1: science communication and public engagement. She regularly speaks out on

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Speaker 1: racism in academia and science, and is passionate about using

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Speaker 1: her platforms to uplift the marginalized and underserved while encouraging

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Speaker 1: an increased visibility of diverse STEM professionals. In my conversation

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Speaker 1: with Esther, we discuss her life growing up in the UK,

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Speaker 1: her education and career path, her past work with Starfish,

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Speaker 1: and future career goals for exploring unmet medical needs, systemic

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Speaker 1: racism in the science community, how Esther is adjusting to

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Speaker 1: working from home during the COVID nineteen crisis, the current pandemic,

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Speaker 1: and so much more enjoying well whip Smarties. We are

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Speaker 1: in another installation of our Need to Know Science investigation

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Speaker 1: series on the podcast, and today I am so excited

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Speaker 1: to be joined all the way from the UK via

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Speaker 1: Zoom of course by escun Lay. You are a biochemist

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Speaker 1: and a neurobiologist and an antibody engineer. Can you talk

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Speaker 1: to us a little bit about what that means. I'd

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Speaker 1: love to know how you communicate the science of what

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Speaker 1: you do to us folks who don't have PhDs. First

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Speaker 1: and foremost, really, um, where do I start? Okay? Um? Well,

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Speaker 1: the biochemistry part comes from my undergrad so I did

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Speaker 1: my undergrad calls in biochemistry. UM So during college I

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Speaker 1: wasn't really sure which route to go down, and I

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Speaker 1: literally made the choice of I like well the G

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Speaker 1: I like chemistry, so let's mix them together and just

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Speaker 1: do an undergrad in biochemistry. Um And that was mainly

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Speaker 1: around So biochemistry is studying the chemical reactions in biological systems,

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Speaker 1: so it's mainly looking at proteins, for example, and how

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Speaker 1: they function in healthy individuals, but also how they can

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Speaker 1: misfunction in disease models as well. UM So that's kind

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Speaker 1: of where I started and I was really interested in that.

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Speaker 1: And then um yeah, during my biochemistry courses, I actually

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Speaker 1: had some neuroscience lectures and that kind of really drawed

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Speaker 1: me in and that's what I found the most interesting

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Speaker 1: about my course. So from there I was actually able

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Speaker 1: to do a finally a research project with my neuroscience lecturer,

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Speaker 1: and that actually turned out to be the foundation for

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Speaker 1: why PhD would be in and that was looking at

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Speaker 1: like these I guess brain proteins called neuropeptides um specifically

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Speaker 1: in starfish, which is if it were to some people.

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Speaker 1: UM So yeah, just trying to understand that system in

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Speaker 1: starfish UM and also like a worm model as well. UM.

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Speaker 1: And then pretty much halfway through my PhD, I realized

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Speaker 1: that I wanted to apply my skills to discover medicines,

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Speaker 1: and so that sort of led me to then transition

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Speaker 1: into the pharmaceutical industry. And in pharmacutical industry, um, there

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Speaker 1: are different types of medicines that are being made. So

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Speaker 1: you have what's called biopharmaceuticals, which would be something like antibodies,

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Speaker 1: or you can have like small molecules as a drug.

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Speaker 1: So UM, so I found myself working on antibodies and yeah,

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Speaker 1: here we are now, I guess. So, so when we

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Speaker 1: think about COVID nineteen and and you know storrys covy

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Speaker 1: too being the virus that causes the disease, is it true?

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Speaker 1: I've I've read it. It's a you could call it

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Speaker 1: a smarter virus because of how transmissible it is, how

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Speaker 1: easy it is for people to pick up. UM. Not

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Speaker 1: dissimilar to stars or mers, but this particular strain of

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Speaker 1: coronavirus has reached pandemic proportions because it was first an

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Speaker 1: outbreak and then an epidemic and now a global pandemic

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Speaker 1: because of how easily it travels, which essentially signals to

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Speaker 1: scientists that the virus is quite smart. There are other

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Speaker 1: viruses that are even more deadly when caught, but they

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Speaker 1: don't transfer. They don't transmit at nearly the rate of

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Speaker 1: stars Cove two. So how does a virus learn to

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Speaker 1: be smart? Is that something that it has been evolving into?

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Speaker 1: Our scientists surmising that it's been working on this in

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Speaker 1: in whatever place it came from, you know, in its

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Speaker 1: zooonotic jump. Why is it so easy to catch? That's

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Speaker 1: a good question. Um, I mean what I would what

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Speaker 1: I would say is I mean, yes, people talk about

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Speaker 1: sort of the evolution of viruses. I think for me,

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Speaker 1: I kind of see it as you know, there are

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Speaker 1: you may have heard of, you know, random mutations that

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Speaker 1: occur um in viruses, and some of these random mutations

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Speaker 1: could lead to the virus being um you know, more

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Speaker 1: able to be transmitted to other people. And I think

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Speaker 1: it's just a case of I mean again I'm not

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Speaker 1: a super expert in this area, but I think it

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Speaker 1: seems to be a case of you know, having these

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Speaker 1: random mutations and the ones that do cause the virus

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Speaker 1: to be transmitted much more easily UM or be or

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Speaker 1: be more effective in in infecting people would be the

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Speaker 1: one that is then carry read through the population. Now,

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Speaker 1: we obviously need to talk about vaccines in terms of

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Speaker 1: COVID nineteen, because that's really on everybody's mind, But I'd

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Speaker 1: actually like to go back to some more simple science

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Speaker 1: and communication. What even is a vaccine? Can you work

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Speaker 1: us through it? So, a vaccine is a substance that

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Speaker 1: stimulates your body's immune system to fight against and therefore

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Speaker 1: protect you against, a pathogen, And a pathogen is anything

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Speaker 1: that causes disease. Now, being naturally infected by a pathogen

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Speaker 1: that say, a virus, would also stimulate your body's immune system,

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Speaker 1: but getting that immune protection will mean getting the disease,

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Speaker 1: which could come with some pretty nasty symptoms. So the

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Speaker 1: benefit of a vaccine is that it imitates an infection

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Speaker 1: and therefore provides immune protection against the pathogen without causing

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Speaker 1: the actual disease. It does this by exposing your body

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Speaker 1: to a non disease causing form of the pathogen, which

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Speaker 1: triggers your immune response. The immune response triggered by a

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Speaker 1: vaccine will typically involve the production of specific immune proteins

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Speaker 1: or cells that are critical for removing neutralizing and removing

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Speaker 1: the pathogen. And this means that if you are then

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Speaker 1: exposed to the actual pathogen that causes disease, you will

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Speaker 1: already have the immune protection through the immune proteins and

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Speaker 1: cells needed to fight this pathogen at a faster rate.

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Speaker 1: Depending on the effectiveness of the vaccine, it could provide

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Speaker 1: full immunity, which would mean you will not be infected

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Speaker 1: when exposed to the pathogen, or if full immunity is

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Speaker 1: not possible, it could lessen the severity or duration of

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Speaker 1: the infection. I find it so helpful to understand exactly

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Speaker 1: how vaccines work in the body and how they help

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Speaker 1: to make us immune to diseases that otherwise would be

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Speaker 1: life threatening. So thank you for that very clear translation.

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Speaker 1: And then I have a question. Because COVID nineteen is

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Speaker 1: a novel virus, we've never encountered it before. That means

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Speaker 1: we have no natural immunity. There's nothing in our bodies

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Speaker 1: that have created antibodies to fight a pathoge and like

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Speaker 1: this is that why it can be so fatal to

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Speaker 1: people who contract it? And that's why all scientists around

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Speaker 1: the world are collaborating on trying to find a vaccine

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Speaker 1: as quickly as possible. That's definitely one of the reasons. Um. Yeah,

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Speaker 1: as you said, our bodies haven't seen this virus before,

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Speaker 1: so if we are infected, you know, some people will have,

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Speaker 1: you know, really horrible symptoms and in some cases it

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Speaker 1: can be fatal. Um. I think it's important to note

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Speaker 1: as well, as we've seen different people react differently to

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Speaker 1: the virus, and you know, things like you know, people

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Speaker 1: having other health issues can definitely cause um, worse outcomes

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Speaker 1: for um when they have been infected by the virus. Yeah.

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Speaker 1: I think that's really helpful to understand it. Uh. Doctor

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Speaker 1: a friend of mine explained it in the following way,

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Speaker 1: which really sort of sobered me to the severe of this.

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Speaker 1: He said that COVID nineteen essentially operates as an investigative

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Speaker 1: grim reaper and will analyze your system and find any

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Speaker 1: weak point and attack you through it. So someone like me,

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Speaker 1: for example, who's had lifelong asthma, but it's never been

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Speaker 1: dangerous to me. I've always been able to manage it

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Speaker 1: with medications. It could prove fatal in my system because

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Speaker 1: my lungs are in terms of COVID compromised, but not compromised.

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Speaker 1: If I don't get COVID, and that that was really

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Speaker 1: something that helped me clarify how severe it can be

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Speaker 1: for people who otherwise have no kind of severe illness,

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Speaker 1: and it really sort of shook my shoulders. Now, when

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Speaker 1: we talk about vaccines and and you walked us through

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Speaker 1: how they work, you know, they expose your body, as

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Speaker 1: you said, to an antigen. That's what triggers your immune response.

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Speaker 1: They can either provide immunity or lessen the severity of

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Speaker 1: an infect action, which with a fetal disease like COVID

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Speaker 1: is so important. Do vaccines are work the same way

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Speaker 1: or are there multiple types of vaccines? So there are

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Speaker 1: four major types of vaccines. Um You firstly have what's

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Speaker 1: called whole pathogen vaccines. These can be whole bacteria or

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Speaker 1: viruses or parasites that cannot cause disease because they have

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Speaker 1: either been inactivated with chemicals, radiation, or heat, or they

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Speaker 1: have been weakened. In their inactivated or weakened form, the

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Speaker 1: pathogen either cannot replicate as well or they cannot replicate

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Speaker 1: at all in order to cause a disease. These types

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Speaker 1: of vaccines typically produce strong protective immune responses, and most

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Speaker 1: therapeutic vaccines have actually fallen into this category, but they

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Speaker 1: can be relatively harder to make or they can take

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Speaker 1: longer to develop. The second type of vaccines that we

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Speaker 1: have are called subunit vaccines. These are components or frag

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Speaker 1: months of a pathogen that the immune system can still

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Speaker 1: recognize and fight against. As you're only using the essential

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Speaker 1: components instead of the whole pathogen, this type of vaccine

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Speaker 1: might minimize side effects. However, including only these components tends

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Speaker 1: to produce relatively weak protective immune responses compared to whole

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Speaker 1: pathogen vaccines, and in such cases some additional ingredients or

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Speaker 1: proteins are added to give that extra buced to your

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Speaker 1: immune system. The third type of vaccines are called toxoids.

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Speaker 1: So some bacterial diseases aren't caused by the bacteria themselves.

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Speaker 1: They're actually caused by the toxin that the bacteria produces

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Speaker 1: and releases. Therefore, you would want your immune system to

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Speaker 1: protect you against the toxin rather than the bacterium. In

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Speaker 1: these cases, an inactivated form of the toxin, otherwise known

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Speaker 1: as a toxoid, is used as a vaccine. And the

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Speaker 1: fourth and final type of vaccines are nucleic acid vaccines.

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Speaker 1: So nucleic acids can carry genetic information, for example, our DNA,

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Speaker 1: and they are needed to produce proteins in all living things.

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Speaker 1: These nucleic acids, as I said, they can be DNA,

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Speaker 1: but they can also be RNA, which is a different type.

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Speaker 1: Many of the structures on pathogens that trigger our immune

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Speaker 1: system are proteins, so instead of scientists making these proteins

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Speaker 1: in the lab and then injecting them into patients, nucleic

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Speaker 1: acid vaccines are used. They introduce either the DNA or

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Speaker 1: the RNA that codes for that particular protein from the

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Speaker 1: pathogen into your body. Your body then uses its own

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Speaker 1: cells to read through that nucleic acid and make that

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Speaker 1: specific protein. Once the protein is made, your body can

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Speaker 1: then recognize this as something that it needs to fight

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Speaker 1: against with an immune response. These vaccines are new are

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Speaker 1: and presently only a few have been approved of for

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Speaker 1: use in animals not humans. However, they are much easier

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Speaker 1: to develop and manufacture compared to other vaccine types in

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Speaker 1: terms of the COVID nineteen vaccines in development. Many of

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Speaker 1: them are nucleic acid vaccines that code for a specific

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Speaker 1: protein on the virus called the spike protein, and others

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Speaker 1: are also whole pathogen vaccines. I'm honestly just fascinated with

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Speaker 1: the work that generations of science have done to lead

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Speaker 1: us here where you're capable of producing so many types

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Speaker 1: of vaccines that can literally teach our bodies to fight

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Speaker 1: a virus so well that it can't replicate inside of us.

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Speaker 1: It's it's a pretty fascinating time to be alive, yeah,

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Speaker 1: for sure. And I think just thinking about how vaccinations

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Speaker 1: used to work, or the primitive version of it, which

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Speaker 1: was called variolation, where they'd essentially, you know, take some

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Speaker 1: scabs from someone who was infected let's say a pots

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Speaker 1: and then giving that to a healthy person to try

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Speaker 1: and elicit this immune response coming from that To where

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Speaker 1: we are now, it's just mind blowing. So can you

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Speaker 1: talk to me a little bit about who is protected

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Speaker 1: when someone gets a vaccine, because there's a lot of

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Speaker 1: conversation out there about her immunity, about creating immunity. You

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Speaker 1: just reference that vaccines can either create immunity or a

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Speaker 1: good enough immune response that you won't get a fatal

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Speaker 1: version of a virus such as COVID nineteen. So how

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Speaker 1: how does this sort of larger protection structure work? In

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Speaker 1: terms of vaccines. Yeah, well, first of all, you are

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Speaker 1: protected when you get vaccine because vaccines mimic an infection.

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Speaker 1: As you said, you can develop immune protection without actually

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Speaker 1: contracting the actual disease UM And as has been said, UM,

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Speaker 1: depending on the effectiveness of the vaccine, you can you

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Speaker 1: could either be fully immune or you can have less

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Speaker 1: severe symptoms UM. But also what we're hearing about is

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Speaker 1: long COVID, where people who were infected months ago are

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Speaker 1: still experiencing symptoms such as crushing, fatigue and long damage

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Speaker 1: months after. So having a vaccine, even if it doesn't

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Speaker 1: provide full immunity UM, it can still protect you from

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Speaker 1: horrible symptoms caused by the disease. But secondly, other people

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Speaker 1: can be protected when you get a vaccine if vaccination

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Speaker 1: leads to full immunity. This means, even if you are

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Speaker 1: exposed to the virus, your immune system will act fast

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Speaker 1: enough to clear the virus before it has a chance

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Speaker 1: to replicate and cause disease. And it's possible that the

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Speaker 1: fast action of the immune system ensures that you aren't

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Speaker 1: harboring any infectious pathogens in your system that can be

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Speaker 1: transmitted to others. But there is a caveat hare in

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Speaker 1: that this all relies on having a vaccine that is

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Speaker 1: effective enough to provide full immunity. Right now, we are

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Speaker 1: racing against the clock, and so the first available COVID

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Speaker 1: minting vaccine may not provide full immunity, but could protect

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Speaker 1: you from severe symptoms. This means that even if your

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Speaker 1: symptoms aren't so bad, you could still be infected and

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Speaker 1: carry infectious particles and therefore be able to transmit this

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Speaker 1: to others, And in that particular case, the vaccine would

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Speaker 1: only be beneficial to you and not others, And that's

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Speaker 1: part of the reason. Would you say that it's so

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Speaker 1: important that when the vaccine becomes readily available everyone take it. Yeah,

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Speaker 1: I'll probably say everyone eligible to take it. Yeah, Yeah,

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Speaker 1: that's true. It does bear clarifying that there are some

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Speaker 1: people who aren't able to take vaccines. Cancer patients, for example,

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Speaker 1: who have very compromised immune systems cannot you know, depending

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Speaker 1: on the age of a child, they will or will

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Speaker 1: not be able to get a vaccine. So it's really

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Speaker 1: up to us everyone out there who's healthy and capable

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Speaker 1: to do it, because it really is how you care

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Speaker 1: for your community. In the same way that we've been

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Speaker 1: out there wearing masks. This is about community protection, not

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Speaker 1: simply just for you. Do you have any guidance to

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Speaker 1: give on the question of once we have a vaccine,

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Speaker 1: how long well we need to continue social distancing and

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Speaker 1: masking that will that be part of the fight against

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Speaker 1: the virus even once the vaccine launches. Yeah, I think

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Speaker 1: it's important to set the expectation that the first approved

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Speaker 1: COVID minting vaccine may not be the most effective one

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Speaker 1: that we will ever get. It should be safe, that's

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Speaker 1: the whole point of these clinical trials, but it may

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Speaker 1: not provide full immunity. And if it does provide full

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Speaker 1: immunity for how long you know, booster shots may be

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Speaker 1: needed to maintain a level of immunity that could reduce

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Speaker 1: the spread of the virus. Therefore, as of now, the

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Speaker 1: expectation is that there may still be a risk of

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Speaker 1: transmission if precautions such as social distance ing and wearing

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Speaker 1: masks are removed as soon as we have a vaccine.

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Speaker 1: Um quite a few vaccines are being developed at the moment,

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Speaker 1: and it could take months after that first approved vaccine

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Speaker 1: for others that are better or more effective to be

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Speaker 1: to be approved. Maybe ones that do provide full immunity

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Speaker 1: and for a longer period of time, but right now

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Speaker 1: we just don't know. And to complicate things even more,

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Speaker 1: different vaccines we have different levels of effectiveness, may be

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Speaker 1: approved in different countries, and so number one, I don't

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Speaker 1: think we should expect that the first arrival of a

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Speaker 1: vaccine would mean we're all safe and just stop social

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Speaker 1: distancing and wearing masks. And number two, dependent on the

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Speaker 1: vaccines that are available country to country, this would determine

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Speaker 1: whether it's deemed safe to start relaxing any kind of

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Speaker 1: social distancing restrictions. It also strikes me that what you're

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Speaker 1: highlighting that different vaccines may be approved in different countries

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Speaker 1: is on different timelines. Also means that we really need

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Speaker 1: robust contact tracing, because if vaccines begin getting approved by

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Speaker 1: the end of travel resooms and people are moving around,

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Speaker 1: we need to know who's been exposed, where they've been,

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Speaker 1: what communities they've been interacting with to make sure that

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Speaker 1: the agencies that are tracing outbreaks have data as quickly

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Speaker 1: as possible correct. Yeah, And I think another concern there

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Speaker 1: is that with we are looking at an issue when

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Speaker 1: it comes to production and widespread availability of the vaccine,

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Speaker 1: which could create a bottleneck, especially when it comes to

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Speaker 1: countries that aren't as wealthy and can't pre order hundreds

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Speaker 1: of millions of doses. This means that even aside from

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Speaker 1: the different types of vaccines, there could be a stark

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Speaker 1: difference country to country in terms of the vaccination rates

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Speaker 1: because people may not have access to it. And so

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Speaker 1: I know there are all conversations right now with different

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Speaker 1: government agencies around making sure that people from disadvantaged backgrounds

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Speaker 1: aren't being left behind. But until we can guarantee that

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Speaker 1: that's that everyone has access to the vaccine worldwide or

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Speaker 1: different types of vaccines worldwide, we should still have some

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Speaker 1: strategies in place to monitor, trace, and hopefully reduce the

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Speaker 1: spread of the virus. So it's a multi stage, coordinated effort.

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Speaker 1: It's not just about masks, it's not just about vaccines,

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Speaker 1: it's not just about distancing. It really requires all of

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Speaker 1: these things to be happening at the same time concurrently.

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Speaker 1: Mm hmm, So can I ask you a clarification question.

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Speaker 1: If the early vaccine only protects the individual who receives

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Speaker 1: the vaccine, well more people getting the vaccine actually help

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Speaker 1: us learn about the vaccine and its efficacy and create

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Speaker 1: more effective vaccines as time progresses to eventually hope to

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Speaker 1: create a vaccine that does provide full immunity. UM. I

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Speaker 1: think yeah, I mean so so with the so for example,

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Speaker 1: right now they're doing the stage. In some cases they're

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Speaker 1: doing phase three clinical trials, and in that case there

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Speaker 1: are they are actually going to be monitoring people over

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Speaker 1: the course of a few months and up to a

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Speaker 1: year maybe more. And so I think we need to

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Speaker 1: we need to monitor people in order to understand how

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Speaker 1: their body is reacting to UM and fighting against viruses

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Speaker 1: through the use of vaccines, and by understanding the immune response,

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Speaker 1: this may provide other strategies for making potentially more effective

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Speaker 1: vaccines UM. Currently, there are nearly two hundred vaccines that

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Speaker 1: are in development at the moment, So it could be

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Speaker 1: that one of these that are already in development may

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Speaker 1: actually provide that full immunity, but right now we just

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Speaker 1: don't know at the moment, so they're kind of just

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Speaker 1: going with one that we can get out really fast

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Speaker 1: that can um, you know, at least lower the severity

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Speaker 1: of the symptoms, but hopefully there will be some protective

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Speaker 1: immunity over a long period of time with it too.

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Speaker 1: M hm. That's something that's really striking to me as

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Speaker 1: the conversation around safety, because there's a lot of people

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Speaker 1: out there who want to claim that vaccines are not safe,

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Speaker 1: but that is simply untrue. That's not ever been proven

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Speaker 1: by any kind of data, and and the source of

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Speaker 1: that accusation has actually been debunked multiple times. But it

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Speaker 1: feels to me like the disinformation has become a bit

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Speaker 1: of a runaway train. How will any anti vactor's decisions

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Speaker 1: not to get the COVID nineteen vaccine impact other people

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Speaker 1: or overall human health around the globe? Yeah, I think

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Speaker 1: it comes in twofold. As we've seen this pandemic shows

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Speaker 1: that individualism isn't going to help us fight the spread

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Speaker 1: of this virus. So the decision of anti bax is

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Speaker 1: to not take the vaccine can first endanger them themselves

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Speaker 1: as they may be susceptible to the virus and therefore

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Speaker 1: contract the disease, possibly with all the horrible symptoms. But

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Speaker 1: their decision also puts the health and lies of others

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Speaker 1: ingecuty too, because if they are infected with the virus,

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Speaker 1: they can then transmit that to other people, but along

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Speaker 1: with their decision to not take the vaccine um It's

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Speaker 1: also been noted that anti baxes may also share misinformation

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Speaker 1: on vaccines, which could discourage others from taking the vaccine.

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Speaker 1: It's all well and good having an effective and save vaccine,

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Speaker 1: but if people don't take it, it it won't be effective

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Speaker 1: at all. And our hope is that with a vaccine

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Speaker 1: we will see a drop in transmission of the virus,

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Speaker 1: which will mean hopefully drops in COVID minting cases, and

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Speaker 1: this will mean that maybe things can start to go

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Speaker 1: back to normal. But all of this can be delayed

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Speaker 1: even longer if when there is a vaccine available, not

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Speaker 1: enough people actually take it. So I think those are

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Speaker 1: the impacts that anti vaxes and misinformation can have. So

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Speaker 1: I'm very curious if you can explain a little bit

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Speaker 1: about why vaccines are in fact so safe. I I

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Speaker 1: tried to go down the rabbit hole to figure out

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Speaker 1: where the disinformation was coming from, and a lot of

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Speaker 1: it was about you know, unsafe trace elements and vaccines.

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Speaker 1: And I saw a doctor put it into clear terms

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Speaker 1: where he said, sure, if you were exposed to a

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Speaker 1: high dose of mercury, it could poison you. But if

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Speaker 1: you've ever eaten a piece of fish for dinner, you've

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Speaker 1: had more of a trace amount of mercury then you've

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Speaker 1: had in all the vaccines you've ever gotten in your

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Speaker 1: life combined, which felt like an obvious and excellent fact

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Speaker 1: to combat some of this disinformation. So what do you

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Speaker 1: think are some of the key points that people who

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Speaker 1: are suspicious of vaccines need to know? As has been said, um,

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Speaker 1: there are a lot of concerns around the ingredients in vaccines,

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Speaker 1: and I think a lot of people have already shown

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Speaker 1: all the data does show that in terms of um,

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Speaker 1: you know, trace ingredients or elements that people may think

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Speaker 1: are harmful, and that may be harmful in very large quantities,

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Speaker 1: when it comes to actual vaccines, they are negligible in

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Speaker 1: their amounts, They shouldn't and don't cause any adverse effects

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Speaker 1: there um. So yeah. So in terms of timelines, and

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Speaker 1: there have been concerns around the super quick timelines for

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Speaker 1: COVID nineteen vaccine development, um, there is actually a worldwide

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Speaker 1: demand right now for an effective vaccine against COVID nineteen,

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Speaker 1: and so countless resources have been focused all at once

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Speaker 1: on providing this and this particular joint effort isn't something

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Speaker 1: that's typically available for vaccines that have been developed in

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Speaker 1: the past, and so historically vaccines have taken longer to

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Speaker 1: get through, to get to and through preclinical and clinical

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Speaker 1: trial stages. Also, funding hasn't always been available to facilitate

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Speaker 1: vaccine development, but in this case with COVID nineteen, there's

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Speaker 1: a lot of resources, including money, that has been made

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Speaker 1: available to develop a vaccine at a fast rate. It

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Speaker 1: really actually strikes me as quite beautiful what you're talking

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Speaker 1: about that never in human history has there been a

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Speaker 1: concerted and simultaneous global effort to solve one disease in particular.

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Speaker 1: And I don't know, it makes me feel oddly emotional,

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Speaker 1: and I just really appreciate the clarification on the fact

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Speaker 1: so that we can all feel hopeful about what all

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Speaker 1: of these scientists like you all around the world are

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Speaker 1: doing to contribute to solving this problem. It's great, I

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Speaker 1: think even just looking at the list of so I've

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Speaker 1: been keeping track of the w h O and the

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Speaker 1: vaccine tracker that they have and just seeing a different

435
00:28:11,960 --> 00:28:17,320
Speaker 1: um organizations or institutions worldwide that are currently developing developed

436
00:28:17,359 --> 00:28:21,800
Speaker 1: developing a vaccine it's just it's insane. I've never I've

437
00:28:21,840 --> 00:28:24,760
Speaker 1: never seen this before. Like collaborations happen in science, but

438
00:28:24,960 --> 00:28:29,400
Speaker 1: just not on this scale have I ever seen. It's amazing,

439
00:28:29,440 --> 00:28:31,840
Speaker 1: it's it's sort of the best of what we're capable

440
00:28:31,840 --> 00:28:40,560
Speaker 1: of as people. I would love to get into your

441
00:28:40,600 --> 00:28:43,840
Speaker 1: work specifically, and before we get into what you're doing now,

442
00:28:44,520 --> 00:28:47,280
Speaker 1: I want to know how you wound up here because

443
00:28:47,800 --> 00:28:50,400
Speaker 1: I so often get to sit across from people who

444
00:28:50,440 --> 00:28:54,400
Speaker 1: are wildly impressive and uh, you know who carry multi

445
00:28:54,600 --> 00:28:58,120
Speaker 1: multi letter titles as you do being a PhD. And

446
00:28:59,480 --> 00:29:02,960
Speaker 1: I want to know how, as a little girl growing

447
00:29:03,040 --> 00:29:07,160
Speaker 1: up in the UK, how how did your trajectory go?

448
00:29:07,560 --> 00:29:09,960
Speaker 1: You know, when you were eight or ten? Were you

449
00:29:10,000 --> 00:29:14,200
Speaker 1: obsessed with science in school? Did it come later? Uh?

450
00:29:14,440 --> 00:29:17,680
Speaker 1: Tell tell me about your childhood and I'd love to

451
00:29:17,760 --> 00:29:24,120
Speaker 1: trace trace through to today. Oh. Um, I would say

452
00:29:24,160 --> 00:29:28,800
Speaker 1: that as a really as a really young kid, I

453
00:29:28,880 --> 00:29:32,160
Speaker 1: just happened to pick things up really quickly, so I

454
00:29:32,200 --> 00:29:35,800
Speaker 1: was kind of all around her in school. Um, I

455
00:29:35,880 --> 00:29:39,320
Speaker 1: tended to do generally well in exams. So I think

456
00:29:39,440 --> 00:29:42,000
Speaker 1: my dad sort of saw that and held onto it

457
00:29:42,000 --> 00:29:43,840
Speaker 1: and said, Okay, this is the this is that, this

458
00:29:43,920 --> 00:29:46,160
Speaker 1: is the academic of the family, so let's just try

459
00:29:46,160 --> 00:29:51,120
Speaker 1: and keep her on that trajectory. So um, yeah, he

460
00:29:51,240 --> 00:29:53,400
Speaker 1: kind of you know, my dad definitely sort of pushed

461
00:29:53,440 --> 00:29:57,080
Speaker 1: me to um, you know, do a lot of maths,

462
00:29:57,800 --> 00:29:59,800
Speaker 1: do a lot of science as well. So we had

463
00:30:00,480 --> 00:30:05,320
Speaker 1: had science books at home. There was this encyclopedia shelf

464
00:30:05,400 --> 00:30:08,200
Speaker 1: that we still have in my family home. UM, and

465
00:30:08,360 --> 00:30:10,239
Speaker 1: I just kind of pick out a book and just

466
00:30:10,320 --> 00:30:14,200
Speaker 1: read stuff on. At the time, I was really fascinated

467
00:30:14,200 --> 00:30:17,520
Speaker 1: with photosynthesis, for example. I just thought it was amazing

468
00:30:18,360 --> 00:30:21,680
Speaker 1: that plants could do that. Um. And books on the

469
00:30:21,800 --> 00:30:26,240
Speaker 1: human body and that really kind of interested me. UM.

470
00:30:26,280 --> 00:30:28,760
Speaker 1: And when I was in school, I just one of

471
00:30:28,800 --> 00:30:33,600
Speaker 1: the key memories that I have just been fascinated with snails. Um.

472
00:30:33,640 --> 00:30:35,600
Speaker 1: I don't know why, but I just sit down in

473
00:30:35,600 --> 00:30:38,440
Speaker 1: the playground and just find a snail and just watch

474
00:30:38,480 --> 00:30:41,160
Speaker 1: it or pick it up, or just you know, look

475
00:30:41,160 --> 00:30:43,160
Speaker 1: at it and be like, hey, this is fascinating. This

476
00:30:43,240 --> 00:30:45,720
Speaker 1: is so different to what I am, but it's still

477
00:30:45,760 --> 00:30:51,000
Speaker 1: classes like, oh my god when I gets it. I

478
00:30:51,040 --> 00:30:54,160
Speaker 1: was so fascinated by them as a little kid, And

479
00:30:54,200 --> 00:30:57,760
Speaker 1: there was this enormous snail in our garden and I

480
00:30:57,920 --> 00:31:00,560
Speaker 1: built it a little garden in a cardboard by I

481
00:31:00,640 --> 00:31:03,920
Speaker 1: built it a little you know, micro climate essentially. I

482
00:31:04,040 --> 00:31:07,040
Speaker 1: named her Strawberry. I don't know that snails have gender,

483
00:31:07,440 --> 00:31:11,240
Speaker 1: but to me, she was like my little friend. I

484
00:31:11,320 --> 00:31:15,640
Speaker 1: love that about you. It's like such a little tiny

485
00:31:15,760 --> 00:31:18,760
Speaker 1: science nerd thing. I know everyone else thought I was with,

486
00:31:18,960 --> 00:31:21,680
Speaker 1: but it's just nice to have that like affirmation from

487
00:31:21,720 --> 00:31:25,920
Speaker 1: someone else finally after how many years. They're so cool.

488
00:31:26,080 --> 00:31:29,120
Speaker 1: They really are. I mean, we also ate them at home,

489
00:31:29,720 --> 00:31:32,360
Speaker 1: but it was also really nice to just sort of

490
00:31:32,400 --> 00:31:36,520
Speaker 1: see them in their natural state, just leaving a trail

491
00:31:36,560 --> 00:31:39,520
Speaker 1: of slime behind them. I just I just thought that

492
00:31:39,640 --> 00:31:43,720
Speaker 1: was fascinating. So that's literally one of the first memories

493
00:31:43,760 --> 00:31:47,040
Speaker 1: that I have just been fascinated with animals and just

494
00:31:47,080 --> 00:31:52,200
Speaker 1: the natural world. Yeah, and then, um, I don't know,

495
00:31:52,320 --> 00:31:56,160
Speaker 1: I think just from being in class, in the different

496
00:31:56,840 --> 00:32:00,320
Speaker 1: classes that we had, science and maths, way really the

497
00:32:00,320 --> 00:32:06,240
Speaker 1: ones that seemed to interest me the most. Um, I think, honestly,

498
00:32:06,400 --> 00:32:08,560
Speaker 1: I think it was just learning about the human body.

499
00:32:08,680 --> 00:32:11,520
Speaker 1: Just being able to have someone tell me, Okay, this

500
00:32:11,560 --> 00:32:14,840
Speaker 1: is actually what's happening inside your body right now. You

501
00:32:14,880 --> 00:32:17,160
Speaker 1: can't see it, but this is what's keeping you alive.

502
00:32:17,360 --> 00:32:20,280
Speaker 1: This is how you're functioning. I just thought that was

503
00:32:20,680 --> 00:32:24,480
Speaker 1: fascinated and so um yea. As I mentioned before, in college,

504
00:32:24,800 --> 00:32:29,520
Speaker 1: I did I did biology, chemistry and English literature for

505
00:32:29,680 --> 00:32:33,240
Speaker 1: like my A levels, and it was literally on result.

506
00:32:33,240 --> 00:32:35,560
Speaker 1: Today I got my results and that's when I thought,

507
00:32:35,640 --> 00:32:38,880
Speaker 1: you know what, I want to do biology chemistry together,

508
00:32:39,040 --> 00:32:42,680
Speaker 1: so let's just do biochemistry. Um. So that was pretty

509
00:32:42,720 --> 00:32:45,160
Speaker 1: much it. Um. I know a lot of people have

510
00:32:45,200 --> 00:32:48,480
Speaker 1: asked me if if I had any sort of science

511
00:32:48,560 --> 00:32:52,280
Speaker 1: role models growing up, and maybe that kind of got

512
00:32:52,280 --> 00:32:57,280
Speaker 1: me into science, But honestly, I I was never taught

513
00:32:57,360 --> 00:33:00,880
Speaker 1: science in the context of the scientists did the science.

514
00:33:01,040 --> 00:33:03,680
Speaker 1: I was just taught about them separately. So it was

515
00:33:03,760 --> 00:33:06,400
Speaker 1: kind of much later on when I was sort of

516
00:33:06,440 --> 00:33:10,560
Speaker 1: like a late teenager that I could actually um or

517
00:33:10,640 --> 00:33:13,360
Speaker 1: that I sort of looked up the actual scientists that

518
00:33:13,400 --> 00:33:16,840
Speaker 1: way behind the the scientific discoveries that I am, that

519
00:33:16,920 --> 00:33:20,520
Speaker 1: I have been learning about for how many years? It's

520
00:33:20,600 --> 00:33:24,120
Speaker 1: so cool. I'm I'm doing a bunch of research for

521
00:33:24,160 --> 00:33:28,440
Speaker 1: a project right now on cardiothoracic surgery and learning about

522
00:33:28,520 --> 00:33:32,680
Speaker 1: this surgeons who's pioneered the heart lung machine and and

523
00:33:32,800 --> 00:33:36,040
Speaker 1: stem cell research and all of these things. It's wild

524
00:33:36,240 --> 00:33:40,760
Speaker 1: because you read about them talking about their discoveries and

525
00:33:40,800 --> 00:33:44,400
Speaker 1: you realize these are just people trying to figure out

526
00:33:44,400 --> 00:33:49,680
Speaker 1: a problem so that less people will die. The pressure

527
00:33:49,720 --> 00:33:53,120
Speaker 1: you know, for for so many people in the science

528
00:33:53,120 --> 00:33:57,120
Speaker 1: world is uh, something I don't think we consider often enough.

529
00:33:57,160 --> 00:34:01,160
Speaker 1: And and as you said that I realized loving science

530
00:34:01,240 --> 00:34:04,120
Speaker 1: so much. I didn't learn much about scientists as a

531
00:34:04,200 --> 00:34:09,160
Speaker 1: kid either. It it was more in my adult life

532
00:34:09,680 --> 00:34:12,080
Speaker 1: trying to figure out, well, who created this and who

533
00:34:12,120 --> 00:34:16,440
Speaker 1: figured that out? And so that's really that's really interesting.

534
00:34:17,120 --> 00:34:22,280
Speaker 1: Did did your parents really foster your interest in science?

535
00:34:22,280 --> 00:34:25,560
Speaker 1: Were they interested in science? Do they do anything scientific?

536
00:34:25,680 --> 00:34:32,040
Speaker 1: What was the sort of experience there? Um my mom no, Um,

537
00:34:32,200 --> 00:34:39,960
Speaker 1: so she she was a primary school teacher, but she yeah,

538
00:34:39,960 --> 00:34:41,400
Speaker 1: I don't I don't know what. I wouldn't say that

539
00:34:41,440 --> 00:34:46,960
Speaker 1: there was much kind of advanced scientific knowledge there or

540
00:34:47,040 --> 00:34:49,239
Speaker 1: interest there. And for my dad, who was very much

541
00:34:49,280 --> 00:34:53,520
Speaker 1: interested in maths. So I remember from you know, my

542
00:34:53,640 --> 00:34:56,560
Speaker 1: memories just coming home and just sitting down with my

543
00:34:56,640 --> 00:35:00,080
Speaker 1: dad in him teaching me long division and all of

544
00:35:00,160 --> 00:35:02,920
Speaker 1: this stuff. And so he was very much the person

545
00:35:02,920 --> 00:35:07,080
Speaker 1: i'd go to for maths stuff. UM. Apart from that,

546
00:35:07,560 --> 00:35:10,520
Speaker 1: my brother, not really my sister. My sister ended up

547
00:35:11,239 --> 00:35:14,000
Speaker 1: so she she became a nurse and then she became

548
00:35:14,120 --> 00:35:18,080
Speaker 1: she's now a health care visitor UM. So she's probably

549
00:35:18,120 --> 00:35:21,680
Speaker 1: the closest person when it comes to sort of science

550
00:35:21,719 --> 00:35:25,520
Speaker 1: and health care. UM. But I would yeah, I would

551
00:35:25,560 --> 00:35:28,960
Speaker 1: just say that I kind of journeyed through on my

552
00:35:29,040 --> 00:35:32,800
Speaker 1: own and just found a way to get the knowledge

553
00:35:32,840 --> 00:35:36,040
Speaker 1: and do the research as I could. I just I

554
00:35:36,040 --> 00:35:38,200
Speaker 1: couldn't really rely on anyone to help me, especially with

555
00:35:38,239 --> 00:35:43,440
Speaker 1: the more advanced UM scientific courses that I had. I

556
00:35:43,480 --> 00:35:46,319
Speaker 1: just had to figure that out on my own pretty much.

557
00:35:46,880 --> 00:35:49,480
Speaker 1: I'm sure it's a crazy thing, as apparent when your

558
00:35:49,560 --> 00:35:54,280
Speaker 1: child is becoming a neurobiologist and you're just going, I can't,

559
00:35:54,320 --> 00:35:56,319
Speaker 1: I don't, I don't have it, I don't know what

560
00:35:56,440 --> 00:36:01,880
Speaker 1: I don't know what it means good for him. So literally,

561
00:36:01,880 --> 00:36:05,920
Speaker 1: throughout my whole PhD, no one really asked me what

562
00:36:06,040 --> 00:36:08,480
Speaker 1: I did. They all they would ask is, oh, how

563
00:36:08,560 --> 00:36:11,400
Speaker 1: is school going, And I'd be like, it's fine, and

564
00:36:11,440 --> 00:36:13,279
Speaker 1: that was the that was the end of the conversation.

565
00:36:13,800 --> 00:36:16,759
Speaker 1: Just kidd and I've been kind of tried multiple times

566
00:36:16,760 --> 00:36:18,359
Speaker 1: to explain what I did, but I just gave up

567
00:36:18,400 --> 00:36:23,360
Speaker 1: after after some time. But yeah, mm hmm, And I

568
00:36:23,440 --> 00:36:28,280
Speaker 1: have to ask because we we share a bit of overlap.

569
00:36:28,360 --> 00:36:32,080
Speaker 1: One of my dearest friends who actually grew up in

570
00:36:32,120 --> 00:36:35,799
Speaker 1: the Midwest but grew up because her parents had immigrated

571
00:36:35,880 --> 00:36:38,480
Speaker 1: here from Nigeria. And I know your parents moved to

572
00:36:38,520 --> 00:36:43,840
Speaker 1: the UK from Nigeria, and I've I always love hearing

573
00:36:43,880 --> 00:36:50,800
Speaker 1: about how how do people's experiences, you know, being first

574
00:36:50,840 --> 00:36:53,480
Speaker 1: generation suwhere my dad came to the US from Canada.

575
00:36:53,520 --> 00:36:55,960
Speaker 1: It's like, I feel like all of us kids have

576
00:36:56,120 --> 00:36:59,520
Speaker 1: these these things that we've inherited. But I like your

577
00:36:59,520 --> 00:37:04,160
Speaker 1: food better her. I'm always like, how was it you know,

578
00:37:04,560 --> 00:37:08,680
Speaker 1: what was your childhood? Like did did you did you

579
00:37:08,840 --> 00:37:12,319
Speaker 1: love being at this sort of intersection of culture and

580
00:37:12,360 --> 00:37:15,799
Speaker 1: tradition and food and was it was it fun for

581
00:37:15,840 --> 00:37:19,960
Speaker 1: you to to grow up in the UK but having

582
00:37:20,080 --> 00:37:22,800
Speaker 1: family who just moved there, you know, in the generation

583
00:37:22,880 --> 00:37:27,440
Speaker 1: right above yours, Yeah, I mean yeah, I feel like

584
00:37:27,480 --> 00:37:31,279
Speaker 1: I definitely had the best of both. Um. I think

585
00:37:31,320 --> 00:37:33,560
Speaker 1: just in terms of the access that I have two

586
00:37:33,640 --> 00:37:37,359
Speaker 1: different things in the UK, that's definitely a positive. Um.

587
00:37:37,400 --> 00:37:40,480
Speaker 1: But as you said, food, hands down, like one of

588
00:37:40,480 --> 00:37:43,520
Speaker 1: the best things to ever come out of Nigeria. It's

589
00:37:43,600 --> 00:37:49,480
Speaker 1: just it's perfect. Um And yeah, I just it's it's

590
00:37:49,520 --> 00:37:52,160
Speaker 1: kind of it's really funny because a kind of running

591
00:37:52,239 --> 00:37:57,080
Speaker 1: joke that's in I guess the first gen Nigerian community

592
00:37:57,160 --> 00:38:00,960
Speaker 1: or African community in general, is just around our parents

593
00:38:01,000 --> 00:38:06,720
Speaker 1: expectations for us. So like that generation, my like um

594
00:38:07,040 --> 00:38:10,239
Speaker 1: parents generation, it's there's kind of a running phrase where

595
00:38:10,239 --> 00:38:14,160
Speaker 1: it's like, we only accept that you're adoptor or lawyer

596
00:38:14,280 --> 00:38:16,360
Speaker 1: or engineer, Like those are the three options for you,

597
00:38:16,560 --> 00:38:20,240
Speaker 1: So just focus on your career and that's it basically.

598
00:38:20,280 --> 00:38:23,200
Speaker 1: So it's kind of a running joke. But um, but

599
00:38:23,320 --> 00:38:27,080
Speaker 1: I mean that, Yeah, there was that expectation. Luckily for

600
00:38:27,160 --> 00:38:31,400
Speaker 1: my parents, I was inclined to continue academically, so it

601
00:38:31,440 --> 00:38:36,200
Speaker 1: was fine for them. Um. But yeah, I definitely say

602
00:38:36,480 --> 00:38:42,640
Speaker 1: just having that, having that Nigerian culture growing up, I

603
00:38:42,680 --> 00:38:46,239
Speaker 1: do think it's made me who I am today. Um.

604
00:38:46,640 --> 00:38:50,120
Speaker 1: I just I find that the culture is very lighthearted,

605
00:38:50,320 --> 00:38:54,200
Speaker 1: light spirited. Um, there's a lot of joy that can

606
00:38:54,239 --> 00:38:58,720
Speaker 1: be found there. Um. If you haven't seen like the

607
00:38:58,840 --> 00:39:02,160
Speaker 1: Nigerian version of Hollywood, which is called No Hollywood, I

608
00:39:02,239 --> 00:39:06,279
Speaker 1: recommend you do that because it's it's ridiculously hilarious. So

609
00:39:06,400 --> 00:39:08,760
Speaker 1: we just need a laugh. I need a crazy film

610
00:39:08,760 --> 00:39:12,440
Speaker 1: to watch. Just pick one of them that they're just crazy.

611
00:39:13,040 --> 00:39:16,759
Speaker 1: But yeah, just kind of having that lightheartedness. Um and

612
00:39:16,800 --> 00:39:20,080
Speaker 1: then just you know from the UK, you know, having

613
00:39:20,120 --> 00:39:23,319
Speaker 1: people like me who are like first gen as well,

614
00:39:24,120 --> 00:39:27,440
Speaker 1: but having been able to have that access to to

615
00:39:27,680 --> 00:39:30,120
Speaker 1: education and resources and stuff like that. You know, I

616
00:39:30,480 --> 00:39:35,040
Speaker 1: definitely appreciate appreciate that as well. That's so cool. I'm

617
00:39:35,080 --> 00:39:37,120
Speaker 1: so curious and so in the beginning of your work,

618
00:39:37,200 --> 00:39:39,719
Speaker 1: I really do want to talk a little bit of

619
00:39:39,719 --> 00:39:45,759
Speaker 1: the science around starfish because you chose to study them,

620
00:39:45,800 --> 00:39:50,160
Speaker 1: I read because they have these little understood abilities around regeneration.

621
00:39:50,840 --> 00:39:55,239
Speaker 1: And strangely enough, this the book I'm currently reading, Open Heart,

622
00:39:55,280 --> 00:39:59,560
Speaker 1: by this phenomenal pioneering heart surgeon Stephen Westby. He talks

623
00:39:59,600 --> 00:40:05,200
Speaker 1: about doing a certain type of heart surgery on a

624
00:40:05,400 --> 00:40:08,560
Speaker 1: on a baby girl in the UK with al cappa,

625
00:40:08,640 --> 00:40:11,360
Speaker 1: which is a degenerative heart disease that causes infants to

626
00:40:11,400 --> 00:40:15,160
Speaker 1: have heart attacks which can't be reported because they're nonverbal.

627
00:40:15,200 --> 00:40:19,880
Speaker 1: It's really quite devastating and essentially long story longer, this

628
00:40:20,040 --> 00:40:23,359
Speaker 1: child was dying and he had to excise a piece

629
00:40:23,400 --> 00:40:26,319
Speaker 1: of her heart, and essentially, you know, he wrote that

630
00:40:26,320 --> 00:40:27,960
Speaker 1: when he stitched it back up, it looked more like

631
00:40:28,000 --> 00:40:30,960
Speaker 1: a banana in shape than what a heart is meant

632
00:40:31,040 --> 00:40:35,080
Speaker 1: to look like. But she survived, and over the next

633
00:40:36,080 --> 00:40:39,520
Speaker 1: years they monitored her until she turned eighteen, and by

634
00:40:39,560 --> 00:40:42,720
Speaker 1: the time she was a young kid, they were finding

635
00:40:42,719 --> 00:40:47,560
Speaker 1: on all these scans that her heart had completely healed itself,

636
00:40:47,600 --> 00:40:51,040
Speaker 1: It had regenerated, it had grown back into a normal size.

637
00:40:51,200 --> 00:40:53,760
Speaker 1: All of the fibrous scar tissue that had been inside

638
00:40:53,760 --> 00:40:57,440
Speaker 1: of it when they did this open heart surgery, the

639
00:40:57,480 --> 00:41:00,200
Speaker 1: scar tissue they found from these multiple heart attacks she'd

640
00:41:00,239 --> 00:41:04,680
Speaker 1: been having was all gone, and it was She was

641
00:41:04,680 --> 00:41:07,759
Speaker 1: one of the first patients on Earth who showed that

642
00:41:08,360 --> 00:41:12,000
Speaker 1: infant and young child stem cells, which occur naturally in

643
00:41:12,040 --> 00:41:15,640
Speaker 1: their bodies, can regenerate tissue. And that's where so much

644
00:41:15,640 --> 00:41:18,880
Speaker 1: stem cell therapy has come from, you know, the incredible

645
00:41:18,960 --> 00:41:22,400
Speaker 1: leaps and bounds we've made. And and I'm reading this

646
00:41:22,520 --> 00:41:24,759
Speaker 1: last night, going I can't believe I'm going to talk

647
00:41:24,760 --> 00:41:27,920
Speaker 1: to esther tomorrow about cellular regeneration. What are the chances?

648
00:41:28,560 --> 00:41:34,160
Speaker 1: So I'm really curious how you found that pathway because

649
00:41:34,200 --> 00:41:38,640
Speaker 1: so many people who are doing biochemistry, who are doing neurobiology,

650
00:41:38,680 --> 00:41:41,799
Speaker 1: are are studying on mice and rats, trying to replicate

651
00:41:41,840 --> 00:41:44,400
Speaker 1: study to begin to find out what can then go

652
00:41:44,480 --> 00:41:47,120
Speaker 1: into sheep and then what can potentially come come all

653
00:41:47,120 --> 00:41:51,839
Speaker 1: the way up the chain to humans safely. How did

654
00:41:51,880 --> 00:41:56,440
Speaker 1: you get there? Because we hear mice and rats and

655
00:41:56,440 --> 00:41:59,799
Speaker 1: we think it's common in scientific study. How do you

656
00:41:59,840 --> 00:42:03,319
Speaker 1: go from mice, rat to starfish? In undergrad? Talk to

657
00:42:03,400 --> 00:42:11,560
Speaker 1: me about how this happened? Um so Um. Yes, As

658
00:42:11,600 --> 00:42:15,200
Speaker 1: I mentioned a bit early on, so I like my

659
00:42:15,440 --> 00:42:19,759
Speaker 1: neuroscience lectures were the ones that really interested me, and

660
00:42:19,880 --> 00:42:23,839
Speaker 1: so UM in our final year of undergrad we had

661
00:42:23,880 --> 00:42:27,360
Speaker 1: the option to either write a dissertation UM like a

662
00:42:27,400 --> 00:42:32,080
Speaker 1: literature review, or do UM black a final year research project.

663
00:42:32,520 --> 00:42:35,680
Speaker 1: And it turns out that the that the lecturer that

664
00:42:35,719 --> 00:42:39,279
Speaker 1: I had for the neuroscience courses, so it was neuroscience

665
00:42:39,320 --> 00:42:43,360
Speaker 1: and animal physiology, and that's kind of where the starfish

666
00:42:43,400 --> 00:42:46,400
Speaker 1: bit came into it. So UM I was kind of

667
00:42:46,400 --> 00:42:50,160
Speaker 1: hooked on the neuroscience parts, so I kind of submitted

668
00:42:50,239 --> 00:42:54,320
Speaker 1: in a request to do a final year research projects

669
00:42:54,320 --> 00:43:00,400
Speaker 1: with him and his particular research lab. Focuses on starfish

670
00:43:00,440 --> 00:43:03,439
Speaker 1: and just like that whole family, so like the kind

671
00:43:03,440 --> 00:43:05,320
Speaker 1: of dom as we call them, so like sea urchins,

672
00:43:06,000 --> 00:43:10,280
Speaker 1: um cea, cucumbers, brittle stars, like all of that. UM

673
00:43:10,360 --> 00:43:13,839
Speaker 1: so yeah, so so his so his lab focuses on that.

674
00:43:14,520 --> 00:43:17,840
Speaker 1: UM and so I was just coming into UM to

675
00:43:17,960 --> 00:43:25,000
Speaker 1: basically work on a neurous neurobiology project on starfish. UM yeah.

676
00:43:25,040 --> 00:43:27,200
Speaker 1: So just kind of going a bit back. So actually

677
00:43:27,239 --> 00:43:30,560
Speaker 1: in my so the summer before I started that project,

678
00:43:31,000 --> 00:43:34,200
Speaker 1: I actually, um, I wanted to get a taste of

679
00:43:34,239 --> 00:43:36,719
Speaker 1: what research was like, because I actually wasn't sure if

680
00:43:36,760 --> 00:43:40,960
Speaker 1: I wanted to go into research. And so UM I

681
00:43:41,000 --> 00:43:43,840
Speaker 1: was able to do like a summer placement as a

682
00:43:43,880 --> 00:43:49,200
Speaker 1: research assistant in an investigative and medicine department. And there,

683
00:43:49,239 --> 00:43:51,360
Speaker 1: as you said, you know, they use myce and rats.

684
00:43:51,880 --> 00:43:55,000
Speaker 1: And I realized from that, even though it was a

685
00:43:55,120 --> 00:43:59,120
Speaker 1: very interesting thing to do that I just cannot handle

686
00:43:59,320 --> 00:44:02,080
Speaker 1: my some rat I they are just animals that I

687
00:44:02,160 --> 00:44:04,560
Speaker 1: just can't deal with on a daily basis and be

688
00:44:04,640 --> 00:44:09,200
Speaker 1: comfortable with. I got bittened so many times. I dropped

689
00:44:09,239 --> 00:44:13,000
Speaker 1: them because I just couldn't handle them properly. And I

690
00:44:13,040 --> 00:44:15,080
Speaker 1: just yeah, I just thought this is not for me, Like,

691
00:44:15,160 --> 00:44:16,960
Speaker 1: I don't want to go into a lab on a

692
00:44:17,040 --> 00:44:19,600
Speaker 1: daily basis, and my palms are sweaty, and I'm just

693
00:44:19,680 --> 00:44:22,680
Speaker 1: really nervous about touching an animal that I'm meant to

694
00:44:22,719 --> 00:44:26,000
Speaker 1: work with for three to four years. So I thought, yeah,

695
00:44:26,040 --> 00:44:27,600
Speaker 1: that's not really an option. Let me just go with

696
00:44:27,680 --> 00:44:34,600
Speaker 1: an animal that doesn't fly, doesn't buy, doesn't move very fast.

697
00:44:35,200 --> 00:44:38,520
Speaker 1: That was literally my criteria, and starfish fit all of

698
00:44:38,560 --> 00:44:43,319
Speaker 1: that for me, which is good. Um. So yeah, yeah,

699
00:44:43,360 --> 00:44:46,760
Speaker 1: So I didn't really kind of seek out a project

700
00:44:47,040 --> 00:44:51,920
Speaker 1: on starfish specifically. It just happened that the neuroscience lecturer

701
00:44:53,239 --> 00:44:55,319
Speaker 1: that I did my family a project with his lab

702
00:44:55,400 --> 00:45:02,200
Speaker 1: focuses specifically on um starfish and related species. So they

703
00:45:02,280 --> 00:45:08,200
Speaker 1: kind of found you. Yes, they did. My babies. Oh,

704
00:45:08,640 --> 00:45:11,080
Speaker 1: it's so sweet to see the way your face lights up.

705
00:45:11,080 --> 00:45:15,839
Speaker 1: You really, there's such like love there for them. I do. Yeah,

706
00:45:15,960 --> 00:45:19,520
Speaker 1: I got um yeah, I mean four years, four years

707
00:45:19,560 --> 00:45:22,359
Speaker 1: working with those with those guys. It was it was good.

708
00:45:22,400 --> 00:45:25,120
Speaker 1: It was good. So can you tell us a little

709
00:45:25,120 --> 00:45:29,239
Speaker 1: bit about what you learned and discovered about those regenerative

710
00:45:29,280 --> 00:45:33,160
Speaker 1: abilities in starfish? What what does that mean for those

711
00:45:33,200 --> 00:45:35,680
Speaker 1: of us who have never worked with them or learned

712
00:45:35,719 --> 00:45:40,239
Speaker 1: about this. So the thing is, I can't say much

713
00:45:40,280 --> 00:45:43,960
Speaker 1: about that because Okay, so when we generally talk about

714
00:45:44,360 --> 00:45:50,359
Speaker 1: why starfish are like an interesting model system, we generally say,

715
00:45:50,360 --> 00:45:54,360
Speaker 1: you know, something like regeneration is something of interest. But

716
00:45:54,560 --> 00:45:58,200
Speaker 1: that wasn't something that I was specifically working on in

717
00:45:58,280 --> 00:46:02,359
Speaker 1: my project. But we did have like collaborating labs who

718
00:46:02,360 --> 00:46:06,600
Speaker 1: so they were focusing on brittle stars. So are UM

719
00:46:06,600 --> 00:46:08,600
Speaker 1: sort of within the family of the kind of dons

720
00:46:09,200 --> 00:46:12,400
Speaker 1: and UM like brittle stars, they you know, have like

721
00:46:12,520 --> 00:46:15,919
Speaker 1: multiple arms, and they also regenerate their arms as well,

722
00:46:16,239 --> 00:46:18,359
Speaker 1: and they do it at a super fast rate. So

723
00:46:18,400 --> 00:46:22,560
Speaker 1: I think starfish, I want to say one to two months,

724
00:46:22,840 --> 00:46:25,000
Speaker 1: I think if I can remember that it takes them

725
00:46:25,040 --> 00:46:27,520
Speaker 1: to like regenerate their arms, but with brittle stars, it

726
00:46:27,600 --> 00:46:30,760
Speaker 1: takes is a much shorter time. So it's much easier

727
00:46:30,800 --> 00:46:35,520
Speaker 1: for you to to actually sort of look into UM

728
00:46:35,520 --> 00:46:38,279
Speaker 1: into like regeneration because you can quickly cut their arms

729
00:46:38,320 --> 00:46:40,440
Speaker 1: and they can regenerate. And so I know there are

730
00:46:40,440 --> 00:46:44,239
Speaker 1: groups that are looking at UM the sort of regulation

731
00:46:44,320 --> 00:46:48,720
Speaker 1: of different genes and how that changes when brittle stars

732
00:46:48,920 --> 00:46:52,440
Speaker 1: arms regenerating, and from that may give you some idea

733
00:46:52,560 --> 00:46:56,920
Speaker 1: of which genes are involved in this regeneration process, but

734
00:46:57,040 --> 00:46:59,960
Speaker 1: that's something that's um that's currently being done at them.

735
00:47:00,680 --> 00:47:03,799
Speaker 1: So can I ask a question there? So, if someone's examining,

736
00:47:04,920 --> 00:47:07,680
Speaker 1: as you just said, what genes might be involved in

737
00:47:07,760 --> 00:47:15,200
Speaker 1: regeneration in brittle stars, would that in theory eventually, hopefully,

738
00:47:15,200 --> 00:47:18,840
Speaker 1: I suppose, lead to the option to do gene therapy

739
00:47:18,920 --> 00:47:21,799
Speaker 1: on a human being who had been in an accident

740
00:47:21,880 --> 00:47:26,560
Speaker 1: and lost an arm or maybe lost in a you know,

741
00:47:26,640 --> 00:47:30,000
Speaker 1: a muscular skeletal accident, lost a piece of lung or liver,

742
00:47:30,520 --> 00:47:32,799
Speaker 1: although I do know the human lover can regenerate, so

743
00:47:33,360 --> 00:47:36,680
Speaker 1: hasa there's there's a key to something. But it is

744
00:47:36,719 --> 00:47:40,759
Speaker 1: the idea to eventually be able to toggle our genes

745
00:47:40,960 --> 00:47:45,399
Speaker 1: in therapy to regrow something that we've lost, rather than

746
00:47:45,480 --> 00:47:49,560
Speaker 1: have to wait for a transplant or rather than someone

747
00:47:49,640 --> 00:47:53,560
Speaker 1: having to be, you know, a lifelong amputee. Is that

748
00:47:53,640 --> 00:47:57,040
Speaker 1: why those areas of study are being pursued. I would

749
00:47:57,040 --> 00:48:01,840
Speaker 1: say that the I would say that the primary reason

750
00:48:01,920 --> 00:48:06,200
Speaker 1: for those studies is mainly around just trying to get

751
00:48:06,239 --> 00:48:10,320
Speaker 1: the scientific knowledge so to really understand in this particular system,

752
00:48:10,400 --> 00:48:13,399
Speaker 1: So this particular animal, this is what happens, and this

753
00:48:13,480 --> 00:48:17,040
Speaker 1: is what we think is contributing to their ability to

754
00:48:17,280 --> 00:48:22,120
Speaker 1: fully regenerate their arms. And so that's kind of the

755
00:48:22,160 --> 00:48:25,640
Speaker 1: main thing, just trying to get that scientific knowledge. Um.

756
00:48:25,680 --> 00:48:29,520
Speaker 1: I think you know, starfish or brittle stars and humans

757
00:48:29,520 --> 00:48:34,319
Speaker 1: are very different, and you know, humans are arguably more

758
00:48:34,360 --> 00:48:40,320
Speaker 1: complex than starfish. UM. So even if a specific gene

759
00:48:41,360 --> 00:48:45,400
Speaker 1: was found to be important in regeneration, there's no guarantee

760
00:48:45,440 --> 00:48:48,480
Speaker 1: that in humans that have a more sort of complex

761
00:48:48,520 --> 00:48:52,040
Speaker 1: system that that would be the same thing. Um. Also,

762
00:48:52,120 --> 00:48:56,560
Speaker 1: there are like other different, like interconnecting genes um that

763
00:48:56,680 --> 00:49:00,400
Speaker 1: are kind of working in tandem. So it would be

764
00:49:00,440 --> 00:49:03,000
Speaker 1: hard to kind of deconstruct all of that and then

765
00:49:03,160 --> 00:49:07,240
Speaker 1: find the best kind of gene therapy that would allow

766
00:49:07,760 --> 00:49:14,080
Speaker 1: someone's arm to fully regenerate. So short answer, no, but

767
00:49:14,400 --> 00:49:18,960
Speaker 1: you never know, right, it's it's too far off in

768
00:49:19,080 --> 00:49:24,279
Speaker 1: terms of species difference. But any of these sort of

769
00:49:24,480 --> 00:49:27,400
Speaker 1: fields of discovery could lead to something that maybe not

770
00:49:27,440 --> 00:49:29,600
Speaker 1: in our generation, but maybe the one or two after

771
00:49:29,680 --> 00:49:33,359
Speaker 1: us could could be a game changer. Sure, I read

772
00:49:33,400 --> 00:49:37,480
Speaker 1: that you talked about having a career goal of building

773
00:49:37,480 --> 00:49:40,440
Speaker 1: a profile that contributes to the discovery and development of

774
00:49:40,480 --> 00:49:45,040
Speaker 1: therapeutics for unmet medical needs. And that's that's what it

775
00:49:45,080 --> 00:49:47,839
Speaker 1: makes me think of, is is where we could go

776
00:49:47,920 --> 00:49:51,439
Speaker 1: in the future, problems we could solve as we have

777
00:49:51,520 --> 00:49:56,200
Speaker 1: more and more information. And I'm curious currently when you

778
00:49:56,480 --> 00:50:00,719
Speaker 1: refer to unmet medical needs, is there something specific that

779
00:50:00,840 --> 00:50:04,200
Speaker 1: stands out to you? Do you have particular medical needs

780
00:50:04,200 --> 00:50:08,600
Speaker 1: that are a priority as a scientist? UM? Have they

781
00:50:08,680 --> 00:50:12,800
Speaker 1: changed at all since the outbreak of COVID nineteen. Where

782
00:50:12,800 --> 00:50:15,040
Speaker 1: where do we find you today in terms of thinking

783
00:50:15,040 --> 00:50:18,520
Speaker 1: about those things? Yeah, it's a bit of a hard

784
00:50:18,520 --> 00:50:23,560
Speaker 1: one because working in the pharmaceutical industry, there is much

785
00:50:23,680 --> 00:50:26,400
Speaker 1: I can't say about the specifics of what we do,

786
00:50:26,520 --> 00:50:30,200
Speaker 1: just from like a confidential aspect of it. UM. But

787
00:50:30,960 --> 00:50:34,080
Speaker 1: I think for me, and it's probably why I've enjoyed

788
00:50:34,120 --> 00:50:36,480
Speaker 1: my time so far in the pharmaceutical industry, is that

789
00:50:38,320 --> 00:50:42,319
Speaker 1: we get to UM. We get to learn about lots

790
00:50:42,360 --> 00:50:45,600
Speaker 1: of different diseases because there are lots of projects that

791
00:50:45,640 --> 00:50:50,480
Speaker 1: are coming our way to UM to create antibodies for.

792
00:50:51,560 --> 00:50:54,200
Speaker 1: And so in that respect, I wouldn't say that I

793
00:50:54,239 --> 00:50:58,439
Speaker 1: have a specific unmet medical need that really stands out

794
00:50:58,480 --> 00:51:01,160
Speaker 1: to me UM, But because out of the ones that

795
00:51:01,239 --> 00:51:05,120
Speaker 1: I have been able to do research on and be

796
00:51:05,200 --> 00:51:10,600
Speaker 1: involved in. For me, they've all been equally as important UM,

797
00:51:10,640 --> 00:51:12,200
Speaker 1: and so it's really hard for me to kind of

798
00:51:12,200 --> 00:51:16,719
Speaker 1: pinpoint one but what I do find And I mean

799
00:51:16,760 --> 00:51:20,920
Speaker 1: that's kind of why I switched from or transitioned into

800
00:51:20,960 --> 00:51:23,759
Speaker 1: the pharmaceutical industry from academia, because I wanted to use

801
00:51:23,760 --> 00:51:29,600
Speaker 1: my skills UM to hopefully contribute to UM to you know,

802
00:51:29,920 --> 00:51:36,399
Speaker 1: creating therapeutics that do meet unmet medical needs. UM. But yeah,

803
00:51:36,480 --> 00:51:38,840
Speaker 1: I guess what what I what I definitely have been

804
00:51:39,000 --> 00:51:44,320
Speaker 1: very interested in. It's just trying to understand the strategies

805
00:51:44,440 --> 00:51:49,200
Speaker 1: used by different scientists to actually try and meet those

806
00:51:49,239 --> 00:51:53,120
Speaker 1: unmet needs. So it's really weird just kind of hearing

807
00:51:53,320 --> 00:51:56,239
Speaker 1: or reading about the different projects in our department and

808
00:51:57,440 --> 00:52:01,359
Speaker 1: reading the strategy behind how and making how they want

809
00:52:01,400 --> 00:52:04,920
Speaker 1: to make this antibody, what the way they wanted to act,

810
00:52:05,120 --> 00:52:08,600
Speaker 1: and so how they're going to engineer it in order

811
00:52:08,680 --> 00:52:13,560
Speaker 1: to make it have this specific action UM in a

812
00:52:13,640 --> 00:52:15,560
Speaker 1: in a disease model. I just for me, that just

813
00:52:15,680 --> 00:52:17,759
Speaker 1: fact that I just find that really really interesting. And

814
00:52:17,760 --> 00:52:20,279
Speaker 1: you get to see lots of different ones based on

815
00:52:20,480 --> 00:52:24,520
Speaker 1: the different diseases that we're trying to target. I'm fascinated

816
00:52:24,560 --> 00:52:28,600
Speaker 1: as well, and I uh, I was reading the Bill

817
00:52:28,640 --> 00:52:33,360
Speaker 1: Bryson's new book, The Body is so fascinating for anyone

818
00:52:33,400 --> 00:52:37,279
Speaker 1: who's interested in science but doesn't carry the number of

819
00:52:37,320 --> 00:52:40,279
Speaker 1: degrees that so many of you are professional scientists do.

820
00:52:41,080 --> 00:52:43,319
Speaker 1: And one of the things that he talked about when

821
00:52:43,320 --> 00:52:47,279
Speaker 1: he started getting into disease treatment and prevention was the

822
00:52:47,320 --> 00:52:51,520
Speaker 1: crisis that we're facing in the pharmaceutical industry is creating

823
00:52:51,680 --> 00:52:55,640
Speaker 1: far less medications now than they used to um in

824
00:52:55,760 --> 00:52:59,799
Speaker 1: terms especially of antibiotics and antibiotic resistance. And as he

825
00:53:00,040 --> 00:53:06,719
Speaker 1: is explaining the data around what that means, how bacteria

826
00:53:06,840 --> 00:53:10,400
Speaker 1: is changing what we need to find I realized in

827
00:53:10,480 --> 00:53:13,960
Speaker 1: real time, you know, reading the book and partially listening

828
00:53:13,960 --> 00:53:16,520
Speaker 1: to it on audio as well. I had this moment

829
00:53:16,719 --> 00:53:18,839
Speaker 1: one of the days when I was listening to him

830
00:53:18,880 --> 00:53:24,160
Speaker 1: and I thought, wow, I, like so many people, have

831
00:53:24,760 --> 00:53:28,640
Speaker 1: a certain amount of distrust in the pharmaceutical industry because

832
00:53:29,120 --> 00:53:31,160
Speaker 1: there have been so many stories that have come to

833
00:53:31,280 --> 00:53:34,000
Speaker 1: light about you know, abusive practices. You look at what

834
00:53:34,080 --> 00:53:38,239
Speaker 1: happened with OxyContin and um the over prescription of opioids

835
00:53:38,239 --> 00:53:40,680
Speaker 1: and what it's doing. You know, here in America and

836
00:53:40,880 --> 00:53:43,920
Speaker 1: really around the world to people, and and I and

837
00:53:43,960 --> 00:53:46,399
Speaker 1: then I thought about it for a second, and I thought, oh,

838
00:53:46,480 --> 00:53:51,720
Speaker 1: but when Pitt created the polio vaccine, it changed the world,

839
00:53:52,320 --> 00:53:55,160
Speaker 1: you know, it saved lives. My my grandfather was alive

840
00:53:55,239 --> 00:53:57,960
Speaker 1: to see the difference in that. I think about the

841
00:53:58,520 --> 00:54:01,319
Speaker 1: sort of generational break throughs that have been provided to

842
00:54:01,440 --> 00:54:04,800
Speaker 1: us by pharma, the fact that between two and three

843
00:54:04,880 --> 00:54:11,120
Speaker 1: million lives annually are saved because of vaccines. Yet there

844
00:54:11,200 --> 00:54:16,759
Speaker 1: is this sort of permeation of distrust. Uh some of

845
00:54:16,760 --> 00:54:19,360
Speaker 1: which comes from abuse of power, which we see in

846
00:54:19,400 --> 00:54:22,759
Speaker 1: every industry, not just the pharmaceutical one, but a lot

847
00:54:22,800 --> 00:54:26,680
Speaker 1: of it is also coming from really targeted disinformation campaigns

848
00:54:26,680 --> 00:54:29,520
Speaker 1: that we're seeing, you know, coming from shady foreign actors.

849
00:54:30,760 --> 00:54:35,480
Speaker 1: How do you deal with that as a person who

850
00:54:35,560 --> 00:54:40,760
Speaker 1: works in pharmaceuticals, how do you combat the misinformation? And actually,

851
00:54:40,760 --> 00:54:43,200
Speaker 1: maybe before you tell us about how you deal with

852
00:54:43,239 --> 00:54:46,160
Speaker 1: it in in present time, can you tell us why

853
00:54:46,360 --> 00:54:50,239
Speaker 1: you did decide to go from academia into pharmaceuticals. What

854
00:54:50,239 --> 00:54:53,320
Speaker 1: what's the what's the potential and the hope that the

855
00:54:53,320 --> 00:54:56,799
Speaker 1: pharmaceutical space gave to you to pull you there as

856
00:54:56,800 --> 00:54:59,360
Speaker 1: a researcher, because I think that would help some people

857
00:54:59,440 --> 00:55:03,799
Speaker 1: understand works as well. I would say for me, it

858
00:55:03,880 --> 00:55:09,960
Speaker 1: was really just trying to apply my skills into a

859
00:55:10,080 --> 00:55:15,319
Speaker 1: department or organization that was actually going to make that well,

860
00:55:15,360 --> 00:55:20,720
Speaker 1: whose focus was around trying to make actual drugs. And UM,

861
00:55:20,760 --> 00:55:22,759
Speaker 1: you know, there are different there are different stages to

862
00:55:22,880 --> 00:55:27,120
Speaker 1: the drug discovery process. Um. You kind of have to

863
00:55:27,160 --> 00:55:30,239
Speaker 1: first of all, find a drug target. UM, so that

864
00:55:30,280 --> 00:55:32,640
Speaker 1: can be a specific protein in your body, or can

865
00:55:32,680 --> 00:55:35,720
Speaker 1: be a virus or anything that you want to create

866
00:55:35,760 --> 00:55:40,520
Speaker 1: a drug against. All two um, and then there's the

867
00:55:40,560 --> 00:55:45,120
Speaker 1: whole um, the whole department around trying to discover and

868
00:55:45,200 --> 00:55:48,600
Speaker 1: develop that drug. And for me, I found I found

869
00:55:48,640 --> 00:55:56,160
Speaker 1: that really really interesting, UM, because I don't know, I guess.

870
00:55:56,520 --> 00:55:59,759
Speaker 1: I guess for me, I've always even growing up, I

871
00:55:59,800 --> 00:56:03,279
Speaker 1: guess I always wanted to have a career where I

872
00:56:03,360 --> 00:56:07,279
Speaker 1: would hopefully directly impact the lives of others in a

873
00:56:07,320 --> 00:56:11,080
Speaker 1: positive way. And I think just you know, seeing the

874
00:56:11,120 --> 00:56:15,719
Speaker 1: different drugs that are out that are available that do

875
00:56:16,000 --> 00:56:18,520
Speaker 1: amazing things, that do help people, that have prolonged the

876
00:56:18,560 --> 00:56:21,279
Speaker 1: lives of so many people, I think I wanted to

877
00:56:21,360 --> 00:56:23,880
Speaker 1: be part of that. And you know, I had the

878
00:56:24,000 --> 00:56:29,360
Speaker 1: scientific expertise too to be able to UM, to be

879
00:56:29,480 --> 00:56:32,080
Speaker 1: one of the people who who's involved in you know,

880
00:56:32,160 --> 00:56:36,719
Speaker 1: discovering or developing drugs, and so I definitely wanted to

881
00:56:36,760 --> 00:56:39,200
Speaker 1: be in that space. And so even though I was

882
00:56:39,239 --> 00:56:42,759
Speaker 1: working with Starfish and using my skills to focus on

883
00:56:42,880 --> 00:56:47,080
Speaker 1: that UM, luckily I was able to transfer those lab

884
00:56:47,160 --> 00:56:50,680
Speaker 1: skills into where I am now. And I really think

885
00:56:50,719 --> 00:56:59,680
Speaker 1: that it's important that people kind of understand that, yes,

886
00:56:59,719 --> 00:57:03,040
Speaker 1: they're our decisions that are made in the pharmaceutical industry

887
00:57:03,200 --> 00:57:07,560
Speaker 1: with commercial and everything, but in terms of the scientists

888
00:57:07,640 --> 00:57:09,560
Speaker 1: who are there, like on the ground doing the research,

889
00:57:09,680 --> 00:57:14,000
Speaker 1: doing the work. You know, scientists can spend years on

890
00:57:14,000 --> 00:57:17,160
Speaker 1: one particular project and it may not ever see the

891
00:57:17,240 --> 00:57:20,600
Speaker 1: light of day, and it may not get to clinical trials,

892
00:57:20,680 --> 00:57:25,200
Speaker 1: it may not get be approved, but they can literally

893
00:57:25,240 --> 00:57:27,960
Speaker 1: spend years of their life of their lives trying to

894
00:57:28,600 --> 00:57:33,280
Speaker 1: discover UM or design, discover and develop a drug that

895
00:57:33,360 --> 00:57:39,040
Speaker 1: could have a certain, hopefully beneficial effect on patients. And

896
00:57:39,080 --> 00:57:41,960
Speaker 1: I just think it's there should be that I'm trying

897
00:57:41,960 --> 00:57:45,720
Speaker 1: to stress that for scientists, and that's kind of our goal.

898
00:57:46,240 --> 00:57:48,760
Speaker 1: We're not really you know, here to just kind of

899
00:57:49,440 --> 00:57:52,120
Speaker 1: push something down the pipeline and just hope that, you know,

900
00:57:52,320 --> 00:57:55,160
Speaker 1: it does something in people. It's really about taking the

901
00:57:55,280 --> 00:57:58,840
Speaker 1: time and using our skills and knowledge to really create

902
00:57:58,920 --> 00:58:04,120
Speaker 1: something that could day, maybe ten years, fifteen years from

903
00:58:04,200 --> 00:58:08,200
Speaker 1: where we are now, one day, you know, save a

904
00:58:08,320 --> 00:58:11,480
Speaker 1: number of people. And that's really a lot. So now

905
00:58:11,520 --> 00:58:13,680
Speaker 1: that I am in the pharmaceutical industry, I work with

906
00:58:13,720 --> 00:58:15,400
Speaker 1: these scientists, I am a scientists. I work with these

907
00:58:15,440 --> 00:58:18,720
Speaker 1: scientists every day, and that's literally the motivation. It's literally

908
00:58:18,800 --> 00:58:22,600
Speaker 1: just can we create a drug that will do this

909
00:58:22,720 --> 00:58:26,600
Speaker 1: specific thing in patients? Can we actually meet this medical need?

910
00:58:26,680 --> 00:58:30,960
Speaker 1: And that's really the motivation for what we do. Mm hmm.

911
00:58:31,600 --> 00:58:33,960
Speaker 1: It sounds to me like there needs to be a

912
00:58:34,000 --> 00:58:39,760
Speaker 1: real separation in the eyes of the public between the

913
00:58:39,840 --> 00:58:43,680
Speaker 1: industry itself and really any industry and any titans of

914
00:58:43,720 --> 00:58:47,440
Speaker 1: industry who you know, are the point one percent of

915
00:58:47,440 --> 00:58:51,200
Speaker 1: the one of the one percent and and the everyday

916
00:58:51,200 --> 00:58:54,800
Speaker 1: folks who are contributing. And I think about that truth.

917
00:58:55,360 --> 00:58:58,560
Speaker 1: You know, even in the entertainment industry, I constantly am

918
00:58:58,560 --> 00:59:00,960
Speaker 1: trying to stress to people that the working on set

919
00:59:01,520 --> 00:59:03,840
Speaker 1: are like a bunch of hard working people who have

920
00:59:04,000 --> 00:59:07,440
Speaker 1: nothing to do with what's happening at the top. And

921
00:59:07,440 --> 00:59:09,560
Speaker 1: and as you were explaining that, I was thinking very

922
00:59:09,640 --> 00:59:12,680
Speaker 1: much about what the ecosystem of a set feels like.

923
00:59:12,960 --> 00:59:16,680
Speaker 1: And while we're doing vastly different things, it feels energetically

924
00:59:16,680 --> 00:59:19,080
Speaker 1: a bit like the way you're describing your lab. You know,

925
00:59:19,120 --> 00:59:23,680
Speaker 1: a bunch of incredible scientists who are dedicating themselves day

926
00:59:23,680 --> 00:59:27,920
Speaker 1: in and day out to solving something. It's that that

927
00:59:28,040 --> 00:59:33,360
Speaker 1: group energy toward creation, um, whether it's the creation of

928
00:59:33,360 --> 00:59:35,200
Speaker 1: a piece of art or the creation of a of

929
00:59:35,240 --> 00:59:41,320
Speaker 1: a new medical technology, is really special, you know, dare

930
00:59:41,360 --> 00:59:44,320
Speaker 1: I even say kind of magical to be a part

931
00:59:44,360 --> 00:59:47,960
Speaker 1: of and and often so removed from the way that

932
00:59:48,000 --> 00:59:51,480
Speaker 1: the product itself gets monetized or distributed. And I think

933
00:59:51,520 --> 00:59:55,200
Speaker 1: it's important for people to remember that and to hold

934
00:59:55,280 --> 00:59:59,680
Speaker 1: scientists in the highest esteem, because you go into science

935
01:00:00,240 --> 01:00:04,320
Speaker 1: to create and save, you know, save lives. It's it's

936
01:00:04,360 --> 01:00:13,720
Speaker 1: certainly an honorable choice to make. You're gonna know what

937
01:00:13,800 --> 01:00:16,560
Speaker 1: I mean it I I just I think it's so incredible,

938
01:00:16,640 --> 01:00:21,880
Speaker 1: and you know, I'm curious. You know, you talked about

939
01:00:21,960 --> 01:00:25,439
Speaker 1: your family and and sort of this best of both

940
01:00:25,480 --> 01:00:28,320
Speaker 1: worlds experience that you had, you know, growing up in

941
01:00:28,360 --> 01:00:30,960
Speaker 1: the UK and also being a member of a family

942
01:00:30,960 --> 01:00:34,280
Speaker 1: who immigrated from Nigeria. You know you you mentioned that

943
01:00:34,320 --> 01:00:37,080
Speaker 1: as a child you were learning about scientific innovation, but

944
01:00:37,120 --> 01:00:42,200
Speaker 1: not often the scientists who had done it. And I know,

945
01:00:43,400 --> 01:00:47,360
Speaker 1: being part of the National Women's History Museum Coalition here

946
01:00:47,400 --> 01:00:52,439
Speaker 1: in the US, so often women have been erased from

947
01:00:52,680 --> 01:00:56,560
Speaker 1: scientific advancement. You know, folks didn't know that it was

948
01:00:56,560 --> 01:00:58,880
Speaker 1: a woman who wrote the code that landed Apollo on

949
01:00:58,880 --> 01:01:02,720
Speaker 1: the moon for so long. And I think about in particular,

950
01:01:03,040 --> 01:01:06,400
Speaker 1: how much, uh, not just the innovation of women, but

951
01:01:06,480 --> 01:01:10,240
Speaker 1: the innovation of scientists of color has been left left

952
01:01:10,280 --> 01:01:15,000
Speaker 1: out of the books and in that both and space

953
01:01:15,280 --> 01:01:21,080
Speaker 1: of your identities and their intersectionality and your place in

954
01:01:21,120 --> 01:01:25,200
Speaker 1: a world that revolves around STEM. There is such a

955
01:01:25,240 --> 01:01:27,480
Speaker 1: push to get more women in STEM. There has been

956
01:01:27,520 --> 01:01:33,520
Speaker 1: such public acknowledgement of the lack of opportunity for Black

957
01:01:33,560 --> 01:01:36,000
Speaker 1: people in STEM and Latin X people in STEM, and

958
01:01:36,040 --> 01:01:39,600
Speaker 1: the list goes on for folks of color. May I

959
01:01:39,640 --> 01:01:44,040
Speaker 1: ask about what your sort of experience is, both in

960
01:01:44,160 --> 01:01:47,960
Speaker 1: your personal identity and your identity as a scientist in

961
01:01:48,200 --> 01:01:54,880
Speaker 1: that big science pharma universe. Do you feel headways being

962
01:01:54,880 --> 01:01:57,960
Speaker 1: made do you feel supported, do you feel the responsibility

963
01:01:58,040 --> 01:02:01,120
Speaker 1: to be an advocate? Is that all of weight to carry?

964
01:02:01,440 --> 01:02:06,120
Speaker 1: You know, what is what is Esther's science world looking like?

965
01:02:06,240 --> 01:02:11,360
Speaker 1: To say, it's very complicated, It's very complicated. UM. So

966
01:02:11,440 --> 01:02:15,600
Speaker 1: I would say that there's definitely similarities between academia and

967
01:02:15,600 --> 01:02:18,400
Speaker 1: the farmer world when it comes to the progress that

968
01:02:18,480 --> 01:02:23,360
Speaker 1: has or hasn't been made. Um. What I have found

969
01:02:24,080 --> 01:02:28,320
Speaker 1: in both settings is that, as you said, there has

970
01:02:28,360 --> 01:02:32,440
Speaker 1: been a push for when it comes to gender, and UM,

971
01:02:32,480 --> 01:02:35,160
Speaker 1: I see it even you know now in the pharmaceutical

972
01:02:35,240 --> 01:02:38,920
Speaker 1: industry in leadership positions, you know there's I mean, what

973
01:02:39,080 --> 01:02:41,640
Speaker 1: more work can be done, but there's generally a good

974
01:02:41,680 --> 01:02:45,720
Speaker 1: representation of women in those positions. But when it comes

975
01:02:45,760 --> 01:02:50,960
Speaker 1: to you know, different people of color, um, it's pretty

976
01:02:51,000 --> 01:02:55,480
Speaker 1: much non existent at those leadership positions, um in lower

977
01:02:55,640 --> 01:03:00,440
Speaker 1: in in lower positions, um more junior positions, you do

978
01:03:00,560 --> 01:03:06,080
Speaker 1: get a bit of representation different ethnicities, but as you

979
01:03:06,080 --> 01:03:10,160
Speaker 1: get to those leadership positional positions, UM, you don't. You

980
01:03:10,200 --> 01:03:14,160
Speaker 1: don't see that at all. And that's something I've noticed

981
01:03:14,200 --> 01:03:17,520
Speaker 1: and actually i've kind of been you know, as as

982
01:03:17,560 --> 01:03:22,520
Speaker 1: you kind of mentioned, I have no onlier or knowingly

983
01:03:22,760 --> 01:03:26,040
Speaker 1: UM taken on this role as a STEM advocate and

984
01:03:26,640 --> 01:03:32,320
Speaker 1: trying to UM encourage the representation of all people of

985
01:03:32,680 --> 01:03:36,520
Speaker 1: different ethnicities within science and making sure that they're visible

986
01:03:36,640 --> 01:03:40,040
Speaker 1: and that they are occupying those leadership positions as well

987
01:03:40,200 --> 01:03:44,040
Speaker 1: and able to make important decisions because I can speak

988
01:03:44,080 --> 01:03:47,000
Speaker 1: as much as I want, but you know, in my

989
01:03:47,280 --> 01:03:48,760
Speaker 1: you know, when I was in academia and now in

990
01:03:48,800 --> 01:03:51,920
Speaker 1: the pharmaceutical industry, I'm not at a position where I

991
01:03:51,960 --> 01:03:55,959
Speaker 1: can make those important decisions on how departments are run,

992
01:03:56,400 --> 01:03:58,520
Speaker 1: what we need to do, the different strategies of different

993
01:03:58,520 --> 01:04:01,240
Speaker 1: policies that need to be in place to you know,

994
01:04:01,280 --> 01:04:04,800
Speaker 1: make the environment more inclusive, to you know, make sure

995
01:04:04,880 --> 01:04:10,080
Speaker 1: that when it comes to recruitment practices that they're recruiting UM,

996
01:04:10,120 --> 01:04:13,800
Speaker 1: you know, diverse applicant pools, or that they're having diverse

997
01:04:13,800 --> 01:04:16,360
Speaker 1: applicant polls. These are things that I can speak on,

998
01:04:16,840 --> 01:04:19,439
Speaker 1: but I don't have the power to actually make those

999
01:04:19,440 --> 01:04:24,600
Speaker 1: things happen. And yeah, you know, I've I've tried to

1000
01:04:24,680 --> 01:04:29,120
Speaker 1: use my voice for that, UM, but yeah, it's it's

1001
01:04:29,400 --> 01:04:33,280
Speaker 1: it's hard because I came to the realization UM a

1002
01:04:33,320 --> 01:04:35,440
Speaker 1: few weeks ago actually, and this was when I was

1003
01:04:35,480 --> 01:04:39,400
Speaker 1: talking to um someone in in the leadership position, a

1004
01:04:39,440 --> 01:04:42,680
Speaker 1: white man, and we're just discussing things about, you know, diversity,

1005
01:04:42,680 --> 01:04:48,680
Speaker 1: ext and inclusion, and then I literally thought that I

1006
01:04:48,720 --> 01:04:51,959
Speaker 1: had never been in the pharmaceutical industry. I had never

1007
01:04:52,480 --> 01:04:57,640
Speaker 1: considered that I would ever work towards a leadership position,

1008
01:04:58,520 --> 01:05:02,200
Speaker 1: mainly because I just didn't anyone like myself in that position.

1009
01:05:03,280 --> 01:05:06,320
Speaker 1: And it was kind of it was where to make

1010
01:05:06,360 --> 01:05:09,320
Speaker 1: that realization, because I've always been someone to say, you

1011
01:05:09,360 --> 01:05:11,760
Speaker 1: know what, Yes, you know, there may not be any

1012
01:05:11,880 --> 01:05:17,920
Speaker 1: representation in certain spaces, but I'm strong enough to pursue

1013
01:05:17,920 --> 01:05:19,960
Speaker 1: whatever I want to pursue, whatever a goal I want

1014
01:05:20,000 --> 01:05:22,960
Speaker 1: to I want to pursue, I'm going to make it happen.

1015
01:05:24,000 --> 01:05:25,960
Speaker 1: That's just the way it is. But I hadn't realized

1016
01:05:26,000 --> 01:05:30,960
Speaker 1: that I had actually just excluded myself from the running unknowingly,

1017
01:05:31,200 --> 01:05:34,440
Speaker 1: just because I couldn't see someone like myself in that position.

1018
01:05:35,360 --> 01:05:38,720
Speaker 1: And it's kind of a catch twenty two because I'm

1019
01:05:38,760 --> 01:05:41,560
Speaker 1: also the one advocating that we need to have more

1020
01:05:41,560 --> 01:05:44,400
Speaker 1: people in those leadership positions. But when you don't see

1021
01:05:44,400 --> 01:05:47,160
Speaker 1: people like yourself in that position, then you kind of

1022
01:05:47,200 --> 01:05:50,440
Speaker 1: put yourself out of the racing. To actually be someone

1023
01:05:50,520 --> 01:05:53,920
Speaker 1: who can hopefully work towards being in that in that position.

1024
01:05:54,760 --> 01:05:57,040
Speaker 1: And it's just like a horrible cycle when it comes

1025
01:05:57,080 --> 01:06:02,479
Speaker 1: to representation and just general systemic inequality and racism within

1026
01:06:02,920 --> 01:06:06,480
Speaker 1: the science community. And you know, it doesn't just stop

1027
01:06:06,520 --> 01:06:10,920
Speaker 1: at representation just in terms of the environment and making

1028
01:06:10,960 --> 01:06:15,560
Speaker 1: it inclusive, because you can recruit as many black scientists

1029
01:06:15,600 --> 01:06:18,720
Speaker 1: as you want, you can recruit as many Indigenous Latin

1030
01:06:18,840 --> 01:06:22,400
Speaker 1: X scientists as you want, but if you have an

1031
01:06:22,560 --> 01:06:25,240
Speaker 1: environment in place that makes them feel like they are

1032
01:06:25,280 --> 01:06:28,600
Speaker 1: the outsiders, that their voices aren't heard, then and what

1033
01:06:28,720 --> 01:06:31,560
Speaker 1: we have seen is that they then transition to another

1034
01:06:31,960 --> 01:06:34,240
Speaker 1: career path and because they just don't want to be

1035
01:06:34,280 --> 01:06:37,960
Speaker 1: in that environment day to day. And I've been lucky

1036
01:06:38,200 --> 01:06:42,800
Speaker 1: enough too, the scientific environments that I have been in,

1037
01:06:43,120 --> 01:06:46,720
Speaker 1: I've been lucky enough to not have them um to

1038
01:06:46,840 --> 01:06:48,919
Speaker 1: not kind of be faced with the things that other

1039
01:06:48,960 --> 01:06:52,120
Speaker 1: people have been faced with, the different aggressions, like really

1040
01:06:52,160 --> 01:06:55,160
Speaker 1: horrible things that other people have experienced. I wouldn't say

1041
01:06:55,160 --> 01:06:57,200
Speaker 1: that I have not experienced any kind of aggression on

1042
01:06:57,280 --> 01:07:00,960
Speaker 1: micro aggressions in the workplace at all, but compared to

1043
01:07:01,000 --> 01:07:04,680
Speaker 1: what I have heard from other people, mine hasn't been

1044
01:07:04,760 --> 01:07:08,920
Speaker 1: that way at all. But that with that being said, though, um,

1045
01:07:09,240 --> 01:07:12,280
Speaker 1: I remember the first scientific conference that I ever went to.

1046
01:07:13,200 --> 01:07:17,840
Speaker 1: This was my first year as a PhD student, and um,

1047
01:07:17,880 --> 01:07:21,160
Speaker 1: you know I went. It was like the reception, welcome reception,

1048
01:07:21,320 --> 01:07:25,120
Speaker 1: and I was in a group of predominantly white men

1049
01:07:25,280 --> 01:07:29,360
Speaker 1: scientists or early career researchers, and one of the one

1050
01:07:29,400 --> 01:07:32,120
Speaker 1: of the researchers, he was talking about the field research

1051
01:07:32,160 --> 01:07:35,600
Speaker 1: that he was doing in the Caribbean, and he referred

1052
01:07:35,640 --> 01:07:40,400
Speaker 1: to the Caribbean locals as guerrillas, and then he just

1053
01:07:40,640 --> 01:07:44,680
Speaker 1: started laughing. And then Alsomski remembered like looked my way

1054
01:07:44,680 --> 01:07:47,120
Speaker 1: and was like, Okay, I didn't realize that there was

1055
01:07:47,120 --> 01:07:49,880
Speaker 1: a black person here for me to say these things too.

1056
01:07:49,960 --> 01:07:52,920
Speaker 1: And it's like that one thing, like nothing like that

1057
01:07:52,960 --> 01:07:55,160
Speaker 1: has ever happened to me before, but that one thing

1058
01:07:56,000 --> 01:08:00,600
Speaker 1: has really like stuck with me, and I can, honestly

1059
01:08:00,720 --> 01:08:04,480
Speaker 1: till this day like remember how I felt at that time.

1060
01:08:04,600 --> 01:08:09,080
Speaker 1: And there weren't any policies in place with the like

1061
01:08:09,800 --> 01:08:13,480
Speaker 1: um conference organizers on where I could report this to,

1062
01:08:13,600 --> 01:08:15,480
Speaker 1: who I could talk to about this, So I literally

1063
01:08:15,520 --> 01:08:18,439
Speaker 1: just kind of left the conversation and just kind of

1064
01:08:18,439 --> 01:08:20,760
Speaker 1: tried to erase that from my mind, but there wasn't

1065
01:08:20,760 --> 01:08:23,600
Speaker 1: anyone that I can talk to about it. And it's like,

1066
01:08:23,680 --> 01:08:25,519
Speaker 1: that's one thing that happened to me that I can

1067
01:08:25,520 --> 01:08:28,879
Speaker 1: till this day still remember. And I can't even imagine

1068
01:08:28,880 --> 01:08:32,240
Speaker 1: what other people have gone through in the scientific community

1069
01:08:32,280 --> 01:08:35,480
Speaker 1: that have made them feel that they don't belong there.

1070
01:08:35,520 --> 01:08:38,000
Speaker 1: People don't think that they are as good a scientists

1071
01:08:38,120 --> 01:08:40,920
Speaker 1: as them, And this is something that you know, we

1072
01:08:41,000 --> 01:08:45,360
Speaker 1: definitely need to recognize it's an issue and then also

1073
01:08:45,520 --> 01:08:53,120
Speaker 1: try to try to fight against as well. Well. I mean,

1074
01:08:53,160 --> 01:08:59,040
Speaker 1: I would say I'm a bit speechless. What you said

1075
01:08:59,080 --> 01:09:05,360
Speaker 1: about not simply recruiting but changing environments feels incredibly important

1076
01:09:06,439 --> 01:09:12,840
Speaker 1: because in my own proximal experience to being the only

1077
01:09:12,880 --> 01:09:14,760
Speaker 1: one in the room, I know what it is to

1078
01:09:14,800 --> 01:09:18,640
Speaker 1: be the only woman in the room and sort of

1079
01:09:18,680 --> 01:09:21,840
Speaker 1: be seen as a token and as an interloper and

1080
01:09:21,920 --> 01:09:27,120
Speaker 1: maybe an invader and you know, maybe is she you know,

1081
01:09:27,280 --> 01:09:29,599
Speaker 1: quote unquote cool enough to be one of the guys,

1082
01:09:29,640 --> 01:09:33,160
Speaker 1: which really just means will I giggle uncomfortably when you

1083
01:09:33,200 --> 01:09:41,200
Speaker 1: say really misogynistic inappropriate things, and it's exhausting and for

1084
01:09:41,240 --> 01:09:42,880
Speaker 1: you to be put in a position in a room

1085
01:09:42,880 --> 01:09:47,759
Speaker 1: full of scientists, with your accreditations and all of the things,

1086
01:09:48,360 --> 01:09:50,880
Speaker 1: and to have someone so flippantly make a remark that

1087
01:09:51,160 --> 01:09:57,800
Speaker 1: like that to you. It feels so deeply cutting to

1088
01:09:57,880 --> 01:10:03,840
Speaker 1: me because it can't be unseid or unheard. And the

1089
01:10:03,960 --> 01:10:08,160
Speaker 1: experiences of people of color and environments like that, the

1090
01:10:08,240 --> 01:10:10,880
Speaker 1: experiences of women who are in these sort of toxically

1091
01:10:10,960 --> 01:10:16,760
Speaker 1: misogynistic workplaces. Once someone has communicated what they think of

1092
01:10:16,800 --> 01:10:20,840
Speaker 1: you in a really disparaging way, you know it, and

1093
01:10:20,880 --> 01:10:25,280
Speaker 1: it doesn't go away, and it affects how you feel

1094
01:10:25,720 --> 01:10:28,600
Speaker 1: returning to that space. So if rather than being a

1095
01:10:28,680 --> 01:10:33,240
Speaker 1: conference which unacceptable in a conference environment obviously, but if

1096
01:10:33,280 --> 01:10:35,040
Speaker 1: someone in your lab had said that to you, how

1097
01:10:35,040 --> 01:10:37,600
Speaker 1: are you supposed to go to that lab every day?

1098
01:10:37,840 --> 01:10:43,360
Speaker 1: You know, we we need to create, as you said,

1099
01:10:43,400 --> 01:10:48,040
Speaker 1: better systems. But I think the complexity of where we

1100
01:10:48,080 --> 01:10:52,040
Speaker 1: find ourselves today when we're acknowledging these needs but the

1101
01:10:52,080 --> 01:10:55,519
Speaker 1: systems don't yet exist, is you. If you do put

1102
01:10:55,560 --> 01:10:58,639
Speaker 1: yourself in that leadership position, you're then going to become

1103
01:10:58,760 --> 01:11:01,320
Speaker 1: even if your lab is to verse, if you move

1104
01:11:01,400 --> 01:11:04,000
Speaker 1: up the ladder and you become one of the people

1105
01:11:04,000 --> 01:11:08,120
Speaker 1: who's making decisions. There will most certainly be a time

1106
01:11:08,160 --> 01:11:11,000
Speaker 1: when you're the only one at the table, and then

1107
01:11:11,040 --> 01:11:13,840
Speaker 1: what does that mean for your experience every day? You know,

1108
01:11:14,560 --> 01:11:18,120
Speaker 1: I think it requires us as a society to have

1109
01:11:18,200 --> 01:11:22,280
Speaker 1: really realistic conversations not just about who's in the room,

1110
01:11:22,560 --> 01:11:24,479
Speaker 1: but what is their experience in the room, and what

1111
01:11:24,600 --> 01:11:27,000
Speaker 1: is the emotional labor we're requiring them to do to

1112
01:11:27,080 --> 01:11:31,880
Speaker 1: be there, and how do we change that? You know,

1113
01:11:32,040 --> 01:11:35,160
Speaker 1: I remember, in a very toxic environment that I was

1114
01:11:35,200 --> 01:11:37,920
Speaker 1: working in for a time before I actually finally quit

1115
01:11:37,960 --> 01:11:41,880
Speaker 1: the job, I just said, I want to be able

1116
01:11:41,920 --> 01:11:44,360
Speaker 1: to just come to work the way that guy does.

1117
01:11:45,200 --> 01:11:47,120
Speaker 1: I just want to come to work and do my job.

1118
01:11:48,080 --> 01:11:49,880
Speaker 1: I don't want to have to come to work and

1119
01:11:50,000 --> 01:11:52,840
Speaker 1: navigate a mind field every single day, and then once

1120
01:11:52,840 --> 01:11:55,000
Speaker 1: I'm to the other side of its, sweating and exhausted,

1121
01:11:55,040 --> 01:11:56,559
Speaker 1: have a bunch of people be like, well, we didn't

1122
01:11:56,560 --> 01:12:01,120
Speaker 1: know if you'd survived that one. You know, it's exhausting,

1123
01:12:02,400 --> 01:12:09,320
Speaker 1: and and again, my understanding and my exhaustion is only proximal.

1124
01:12:10,800 --> 01:12:15,280
Speaker 1: But I really encourage anyone listening to this conversation to

1125
01:12:15,400 --> 01:12:20,640
Speaker 1: think about what your relation to this kind of experiences

1126
01:12:21,120 --> 01:12:23,840
Speaker 1: and if you go, oh, me too. I've had that too.

1127
01:12:23,880 --> 01:12:26,320
Speaker 1: I've had a version of that too. I'm exhausted too.

1128
01:12:27,040 --> 01:12:29,080
Speaker 1: Who can you talk to about it? Who is your

1129
01:12:29,120 --> 01:12:31,559
Speaker 1: support system? And if you're one of the people who's

1130
01:12:31,600 --> 01:12:34,400
Speaker 1: been in a seat of greater sort of power where

1131
01:12:34,400 --> 01:12:38,400
Speaker 1: you've never had that experience, perhaps take the conversation and

1132
01:12:38,479 --> 01:12:41,680
Speaker 1: let it make you a more considerate coworker so that

1133
01:12:41,760 --> 01:12:45,799
Speaker 1: when you see something or hear something, you say something.

1134
01:12:47,120 --> 01:12:50,680
Speaker 1: Because ally ship, whether to women or you know, the

1135
01:12:50,760 --> 01:12:56,479
Speaker 1: black and bipop community, it requires action. And I know

1136
01:12:56,520 --> 01:12:59,479
Speaker 1: that that's something that you've talked about and and I

1137
01:12:59,520 --> 01:13:02,519
Speaker 1: know I keep talking about her, but it's why, like,

1138
01:13:02,800 --> 01:13:07,360
Speaker 1: you know, I have such an affinity for Nigerian culture

1139
01:13:07,479 --> 01:13:10,960
Speaker 1: because of my dear friend Lovey, and she's always like,

1140
01:13:11,000 --> 01:13:14,080
Speaker 1: I think you're a little Nigerian on the inside. She's like,

1141
01:13:14,439 --> 01:13:17,519
Speaker 1: nobody eats more food at my table than you, you know,

1142
01:13:17,680 --> 01:13:20,479
Speaker 1: and we give a lot about it. But but but

1143
01:13:20,600 --> 01:13:27,240
Speaker 1: in real talk, you know, that's that's our joyfulness that

1144
01:13:29,439 --> 01:13:35,240
Speaker 1: in a in a comical way, names our friendship, which

1145
01:13:35,240 --> 01:13:38,479
Speaker 1: is rooted in being accomplices for each other, you know,

1146
01:13:38,640 --> 01:13:42,320
Speaker 1: and when you have people who truly like not just

1147
01:13:42,439 --> 01:13:45,280
Speaker 1: stand up, you know, with you or behind you, or

1148
01:13:45,320 --> 01:13:48,320
Speaker 1: to support you, but who like roll with you into

1149
01:13:48,360 --> 01:13:52,840
Speaker 1: the thick of whatever you're experiencing. That to me is

1150
01:13:52,880 --> 01:13:56,719
Speaker 1: the kind of action energy that we need to put

1151
01:13:56,760 --> 01:14:03,040
Speaker 1: out in the world. So how do you see allies

1152
01:14:03,080 --> 01:14:05,599
Speaker 1: taking action? What does it mean to you for someone

1153
01:14:05,640 --> 01:14:10,639
Speaker 1: to be a true accomplice? I'm curious if there are

1154
01:14:12,640 --> 01:14:15,680
Speaker 1: answers to that question that you can share, because I

1155
01:14:15,720 --> 01:14:17,840
Speaker 1: know there's people who are listening to us talk about

1156
01:14:17,880 --> 01:14:20,120
Speaker 1: this who are saying, Okay, but what's something I can

1157
01:14:20,240 --> 01:14:24,559
Speaker 1: learn to do. What's an appropriate action for me to take? People?

1158
01:14:24,960 --> 01:14:28,040
Speaker 1: People want to show up for each other. I really

1159
01:14:28,040 --> 01:14:32,160
Speaker 1: do believe that. So for you, what what feels effective

1160
01:14:32,240 --> 01:14:36,320
Speaker 1: in your opinion? I mean, it can be quite complex

1161
01:14:36,320 --> 01:14:40,160
Speaker 1: and it depends person to person. UM. The first thing

1162
01:14:40,680 --> 01:14:46,760
Speaker 1: I would say, it's just educate yourself. And there are

1163
01:14:46,920 --> 01:14:51,960
Speaker 1: lots of resources out there, countless resources, books, videos, anything

1164
01:14:52,520 --> 01:14:56,040
Speaker 1: out there that really explains, you know, what it's like

1165
01:14:56,240 --> 01:15:00,040
Speaker 1: to be a person of color or what not, and

1166
01:15:00,160 --> 01:15:03,200
Speaker 1: just trying to navigate your way through not just science

1167
01:15:03,240 --> 01:15:07,120
Speaker 1: but the world. UM, and just educating yourself on the

1168
01:15:07,200 --> 01:15:11,360
Speaker 1: things that we have to go through. UM will definitely

1169
01:15:11,439 --> 01:15:15,120
Speaker 1: be the first step. And I found particularly in science community,

1170
01:15:15,160 --> 01:15:16,920
Speaker 1: and what I just can't get my head around is,

1171
01:15:17,600 --> 01:15:20,360
Speaker 1: you know, you have a lot of scientists who are

1172
01:15:20,560 --> 01:15:23,839
Speaker 1: like great scholars. They can find any book, any resource,

1173
01:15:23,920 --> 01:15:26,280
Speaker 1: anything on a scientific topic. But as soon as it

1174
01:15:26,320 --> 01:15:31,720
Speaker 1: comes to conversations around um, you know, systemic inequality and

1175
01:15:32,040 --> 01:15:34,400
Speaker 1: racism and different things, than all of a sudden, it's

1176
01:15:34,400 --> 01:15:36,960
Speaker 1: a case of I just I just don't know where

1177
01:15:36,960 --> 01:15:39,040
Speaker 1: where to look. I don't know where to get this information.

1178
01:15:39,080 --> 01:15:41,320
Speaker 1: And it's like you can use your skills that you

1179
01:15:41,360 --> 01:15:44,840
Speaker 1: already have to try and educate yourself, and there are

1180
01:15:44,880 --> 01:15:46,960
Speaker 1: countless resources out there, So that would definitely be the

1181
01:15:46,960 --> 01:15:51,920
Speaker 1: first thing. Um. The second thing I would I would

1182
01:15:51,960 --> 01:15:57,840
Speaker 1: say that's really effective for me. It's actually just I

1183
01:15:57,960 --> 01:16:03,720
Speaker 1: found that I can I can count true friends as allies. Um.

1184
01:16:03,960 --> 01:16:07,439
Speaker 1: Not just someone who kind of shows up and says, oh,

1185
01:16:07,680 --> 01:16:10,599
Speaker 1: tell me about a time when someone was racist to you. Oh,

1186
01:16:10,640 --> 01:16:13,840
Speaker 1: that's terrible, Okay, let's see what we can do about it.

1187
01:16:13,880 --> 01:16:16,240
Speaker 1: But someone who actually sees me as a human being.

1188
01:16:16,800 --> 01:16:21,000
Speaker 1: That's multifaceted, and we've kind of built that report that

1189
01:16:21,040 --> 01:16:24,559
Speaker 1: goes beyond my trauma, that goes beyond the things that

1190
01:16:24,600 --> 01:16:28,559
Speaker 1: I've had done to me in the society, because yes,

1191
01:16:28,600 --> 01:16:31,920
Speaker 1: we want to address these things, but also we don't

1192
01:16:31,960 --> 01:16:35,040
Speaker 1: want to address these things of the time. We want

1193
01:16:35,040 --> 01:16:37,439
Speaker 1: to have time to be human beings, to be who

1194
01:16:37,439 --> 01:16:41,280
Speaker 1: we are. And so I think, you know, if if

1195
01:16:41,280 --> 01:16:44,479
Speaker 1: different people want to be allies, you know, start with

1196
01:16:44,520 --> 01:16:48,040
Speaker 1: your friends, Start with people that you already have. Um.

1197
01:16:48,080 --> 01:16:51,120
Speaker 1: You know, that foundation, that friendship, of that foundation of

1198
01:16:51,160 --> 01:16:54,080
Speaker 1: friendship with and and see what you can. You know,

1199
01:16:54,160 --> 01:16:57,040
Speaker 1: you will see quite quite quickly that they will want

1200
01:16:57,080 --> 01:16:59,600
Speaker 1: to open up to you and let you know the

1201
01:16:59,640 --> 01:17:02,720
Speaker 1: ways in which you can help them in their unique situations.

1202
01:17:04,240 --> 01:17:07,200
Speaker 1: Another thing I think is really important and one thing

1203
01:17:07,240 --> 01:17:11,519
Speaker 1: that I've mentioned to count these people, just because a

1204
01:17:11,520 --> 01:17:15,040
Speaker 1: lot of conversations right now are around um or in

1205
01:17:15,040 --> 01:17:17,360
Speaker 1: the science community have been around sort of systemic racism

1206
01:17:17,400 --> 01:17:20,240
Speaker 1: and what we can do in our different departments. UM

1207
01:17:20,280 --> 01:17:22,519
Speaker 1: I just found out a lot of the conversations is around, Okay,

1208
01:17:22,560 --> 01:17:25,559
Speaker 1: let's sit down and let's get the black person in

1209
01:17:25,560 --> 01:17:28,879
Speaker 1: the room to tell us the horrible things that have happened,

1210
01:17:28,920 --> 01:17:31,599
Speaker 1: and so we can all feel really horrible about it,

1211
01:17:31,680 --> 01:17:36,960
Speaker 1: and then that's it. Basically, UM I've kind of spoken

1212
01:17:37,479 --> 01:17:40,760
Speaker 1: out about that and said, what would actually be more

1213
01:17:40,760 --> 01:17:45,400
Speaker 1: effective is if everyone in the room, not just the

1214
01:17:46,080 --> 01:17:49,920
Speaker 1: black person or personal color, if everyone in the room

1215
01:17:49,920 --> 01:17:52,360
Speaker 1: really sat down and thought about a time where they

1216
01:17:52,400 --> 01:17:58,960
Speaker 1: had witnessed someone else being discriminated against or um, you know,

1217
01:17:59,040 --> 01:18:01,519
Speaker 1: someone who has in or some kind of aggression or

1218
01:18:01,600 --> 01:18:05,840
Speaker 1: microaggression in the workplace. And you know, I just find

1219
01:18:05,880 --> 01:18:09,160
Speaker 1: that being instead of being passive, if you're active about

1220
01:18:09,640 --> 01:18:12,840
Speaker 1: trying to identify these things, then you can then be

1221
01:18:12,880 --> 01:18:15,559
Speaker 1: in a position when you do see these things happening

1222
01:18:15,600 --> 01:18:19,160
Speaker 1: to as you said, speak up, speak out. And I

1223
01:18:19,200 --> 01:18:22,320
Speaker 1: think it's really really important to um. You know, I've

1224
01:18:22,560 --> 01:18:25,200
Speaker 1: been in positions where you know, someone has said something

1225
01:18:25,840 --> 01:18:28,599
Speaker 1: you know, a bit where to me and I've sort

1226
01:18:28,600 --> 01:18:32,040
Speaker 1: of been taken back and there was the stereotype of,

1227
01:18:32,120 --> 01:18:35,520
Speaker 1: you know, the angry black woman. So in the workplace particularly,

1228
01:18:35,640 --> 01:18:39,960
Speaker 1: my my go to is just to not show any

1229
01:18:40,000 --> 01:18:42,880
Speaker 1: emotion because I don't want to be classed in that way,

1230
01:18:42,960 --> 01:18:45,400
Speaker 1: even though if someone says something inappropriate to me, I

1231
01:18:45,439 --> 01:18:50,920
Speaker 1: should quite rightly say something about it. And so if

1232
01:18:50,920 --> 01:18:53,880
Speaker 1: it's the emotional labor on you again that forces you

1233
01:18:53,920 --> 01:18:57,320
Speaker 1: to constantly be a teacher rather than simply a coworker.

1234
01:18:57,720 --> 01:18:59,920
Speaker 1: That means you don't get to just go to work

1235
01:19:00,080 --> 01:19:03,960
Speaker 1: the ways everyone who doesn't face your particular brand of

1236
01:19:04,000 --> 01:19:11,320
Speaker 1: oppression or discrimination does. And it's immensely taxing something. Something

1237
01:19:11,320 --> 01:19:14,840
Speaker 1: that I two pieces of advice that I've been given,

1238
01:19:15,800 --> 01:19:19,799
Speaker 1: which in my sort of cohort of women, we've talked about,

1239
01:19:19,880 --> 01:19:22,000
Speaker 1: you know, whether it's a gender issue or or a

1240
01:19:22,080 --> 01:19:26,439
Speaker 1: race issue, or an issue of you know, discrimination against

1241
01:19:26,439 --> 01:19:29,559
Speaker 1: the queer community is when something someone says something a

1242
01:19:29,600 --> 01:19:32,160
Speaker 1: bit off to go o, I'm so sorry, I don't

1243
01:19:32,200 --> 01:19:33,840
Speaker 1: I don't believe I understood you. Could you tell me

1244
01:19:33,880 --> 01:19:36,720
Speaker 1: a little more about what you mean? And it's an

1245
01:19:36,760 --> 01:19:42,280
Speaker 1: investigative question that will often force someone to explain that

1246
01:19:42,400 --> 01:19:46,920
Speaker 1: they're being deeply inappropriate, which I think for all of

1247
01:19:47,040 --> 01:19:51,800
Speaker 1: us to be armed with is important. And and secondarily,

1248
01:19:53,080 --> 01:19:57,680
Speaker 1: something that feels really important, especially for people listening at

1249
01:19:57,720 --> 01:20:01,479
Speaker 1: home will look like me, is to get conscious that

1250
01:20:01,560 --> 01:20:05,679
Speaker 1: you're not asking you know your friends who are black

1251
01:20:06,240 --> 01:20:09,960
Speaker 1: or Latin X or the list goes on and on

1252
01:20:10,040 --> 01:20:13,240
Speaker 1: through the bipop community, through any community that experiences any

1253
01:20:13,320 --> 01:20:16,800
Speaker 1: kind of oppression simply for being who they are, who

1254
01:20:16,920 --> 01:20:21,000
Speaker 1: is amazing, who they cannot change is to be clear

1255
01:20:21,160 --> 01:20:27,439
Speaker 1: about not trafficking in in trauma porn. You know, not

1256
01:20:27,920 --> 01:20:30,360
Speaker 1: as you said, having a meeting in your lab and

1257
01:20:30,439 --> 01:20:33,720
Speaker 1: saying you know esther tell us about your experiences, what

1258
01:20:33,880 --> 01:20:35,360
Speaker 1: you know in a room full of folks who look

1259
01:20:35,400 --> 01:20:39,000
Speaker 1: like me. That's not appropriate. And it's on us to

1260
01:20:39,200 --> 01:20:43,479
Speaker 1: understand that. It's not the responsibility of an oppressed person,

1261
01:20:43,520 --> 01:20:47,080
Speaker 1: a person who experiences racism, a person who experiences discrimination

1262
01:20:47,439 --> 01:20:51,840
Speaker 1: to relive and re traumatize themselves through reliving their traumas,

1263
01:20:51,920 --> 01:20:55,240
Speaker 1: to educate us on the ways that they've suffered. Just

1264
01:20:55,600 --> 01:21:00,360
Speaker 1: believe people when people say, yes, this is a discriminatory system. Oh,

1265
01:21:01,040 --> 01:21:03,439
Speaker 1: maybe don't have your first reaction, B will tell me

1266
01:21:03,479 --> 01:21:07,200
Speaker 1: how you've been discriminated against. Maybe make your first reaction,

1267
01:21:07,280 --> 01:21:10,760
Speaker 1: train yourself to have your first reaction be what would

1268
01:21:10,800 --> 01:21:14,559
Speaker 1: you suggest I could assist in doing about it? Is

1269
01:21:14,600 --> 01:21:16,760
Speaker 1: there do you have an idea? Is there something I

1270
01:21:16,840 --> 01:21:20,480
Speaker 1: can do? How can I be of support to you?

1271
01:21:20,479 --> 01:21:24,519
Speaker 1: You know, make make the emotional labor your work in

1272
01:21:24,600 --> 01:21:28,519
Speaker 1: fixing the problem, not the demand that someone explained to

1273
01:21:28,560 --> 01:21:33,880
Speaker 1: you repeatedly how bad the problem is. I think that

1274
01:21:35,760 --> 01:21:40,439
Speaker 1: these are the kinds of conversations that I hope, you know,

1275
01:21:40,600 --> 01:21:45,720
Speaker 1: can feel open and free enough where anyone can can

1276
01:21:45,760 --> 01:21:48,959
Speaker 1: say truly what they need and also where our audience

1277
01:21:49,000 --> 01:21:51,799
Speaker 1: gets to go home thinking I've learned a bit about

1278
01:21:51,800 --> 01:21:56,280
Speaker 1: how to support my colleagues and my community. That's that's

1279
01:21:56,320 --> 01:22:00,200
Speaker 1: always my goal. And I want to just thank you

1280
01:22:00,320 --> 01:22:05,800
Speaker 1: for being frank about you know, sharing and also, um,

1281
01:22:05,880 --> 01:22:08,880
Speaker 1: I hope that that doesn't feel like the kind of

1282
01:22:08,920 --> 01:22:11,280
Speaker 1: work I'm also trying to encourage people not to ask

1283
01:22:11,320 --> 01:22:16,720
Speaker 1: you to do It's it's like, yeah, I think yeah.

1284
01:22:16,760 --> 01:22:18,599
Speaker 1: I mean for me, I'm kind of the person if

1285
01:22:18,640 --> 01:22:21,000
Speaker 1: I want to just share something, I will. If I don't,

1286
01:22:21,400 --> 01:22:25,120
Speaker 1: I won't and you can't convince me otherwise. So I

1287
01:22:25,120 --> 01:22:27,879
Speaker 1: do find when I when I am in a space

1288
01:22:28,160 --> 01:22:32,280
Speaker 1: that I consider safe and it's appropriate, I'm you know,

1289
01:22:32,439 --> 01:22:35,280
Speaker 1: I'm someone who's happy to you know, share different things,

1290
01:22:35,840 --> 01:22:39,200
Speaker 1: and especially if it will enlighten people who are who

1291
01:22:39,240 --> 01:22:46,000
Speaker 1: actually want to do the work, then definitely cool. Thank you.

1292
01:22:47,360 --> 01:22:50,400
Speaker 1: Something that I've really loved that you've been doing is

1293
01:22:50,439 --> 01:22:53,880
Speaker 1: also encouraging people to do some self work as we've

1294
01:22:53,880 --> 01:22:57,080
Speaker 1: all been stuck at home. You know. The COVID lockdown

1295
01:22:57,120 --> 01:23:01,920
Speaker 1: has been immensely challenging for people. There's also surveys running

1296
01:23:01,920 --> 01:23:05,880
Speaker 1: around the globe which have been kind of lovely to

1297
01:23:05,960 --> 01:23:08,719
Speaker 1: me to see in terms of the social science data

1298
01:23:08,920 --> 01:23:11,519
Speaker 1: of huge numbers of people saying that they think that

1299
01:23:11,560 --> 01:23:15,120
Speaker 1: this lockdown has made them a better person. And you

1300
01:23:15,160 --> 01:23:18,040
Speaker 1: did an Instagram take over not long ago with a

1301
01:23:18,120 --> 01:23:22,439
Speaker 1: SAP science who I'm so obsessed with them. Oh my god,

1302
01:23:22,439 --> 01:23:26,800
Speaker 1: They're just so cool and yes, it's so please, Oh

1303
01:23:26,880 --> 01:23:30,439
Speaker 1: my god, I want to know everything. Okay, So, um,

1304
01:23:30,479 --> 01:23:32,599
Speaker 1: so I did a podcast with them a while back,

1305
01:23:32,840 --> 01:23:39,720
Speaker 1: and um, the topic of starfish sperm came up. That

1306
01:23:39,840 --> 01:23:46,080
Speaker 1: was the wrong day until you finishing. Um, But yeah,

1307
01:23:46,120 --> 01:23:47,880
Speaker 1: basically I was kind of talking about one of the

1308
01:23:47,920 --> 01:23:51,720
Speaker 1: times where I am like, didn't inject a starfish like

1309
01:23:51,800 --> 01:23:53,800
Speaker 1: the way I should, and so I kind of hit

1310
01:23:54,000 --> 01:23:57,680
Speaker 1: a male starfish like gonads, and so I put the

1311
01:23:57,680 --> 01:23:59,880
Speaker 1: starfish back in the water and then it was just

1312
01:24:00,000 --> 01:24:03,760
Speaker 1: cloudy with starfish sperm. And so actually myself and Gregg

1313
01:24:03,800 --> 01:24:06,160
Speaker 1: and Mitch from a science we have a WhatsApp group

1314
01:24:06,200 --> 01:24:10,559
Speaker 1: called starfish Spem. Oh my god, and I just smile

1315
01:24:10,640 --> 01:24:13,400
Speaker 1: anytime I see a notification coming up and just like, yes,

1316
01:24:14,880 --> 01:24:20,680
Speaker 1: that is honestly, like, I don't need to be invited

1317
01:24:20,720 --> 01:24:22,880
Speaker 1: to some fancy dinner party, but if I could be

1318
01:24:22,920 --> 01:24:25,120
Speaker 1: a fly on the wall in that science chat, I

1319
01:24:25,160 --> 01:24:32,960
Speaker 1: would just faint with excitement. I'm curious from this incredible

1320
01:24:33,360 --> 01:24:40,360
Speaker 1: point at which we're meeting, albeit digitally, as a woman

1321
01:24:40,479 --> 01:24:44,160
Speaker 1: with many degrees and who's been a researcher and who

1322
01:24:44,200 --> 01:24:46,960
Speaker 1: works in this incredible innovative lab, and you know, you

1323
01:24:47,000 --> 01:24:52,439
Speaker 1: look back at your career and your life and there's

1324
01:24:52,479 --> 01:24:55,880
Speaker 1: obviously much to come. But from this point at which

1325
01:24:55,920 --> 01:24:58,160
Speaker 1: I imagine so many young girls look at you and

1326
01:24:58,200 --> 01:25:00,559
Speaker 1: think like, oh, I wonder if I could do what

1327
01:25:00,720 --> 01:25:05,360
Speaker 1: she does. Is there any advice that you would give

1328
01:25:06,040 --> 01:25:09,400
Speaker 1: to your younger self or to other young girls out

1329
01:25:09,439 --> 01:25:14,680
Speaker 1: there who look up to you. Yeah, I would say

1330
01:25:15,920 --> 01:25:22,360
Speaker 1: my first thing would be to not have um not

1331
01:25:22,520 --> 01:25:26,759
Speaker 1: have a definitive plan that you can't be swayed from.

1332
01:25:26,800 --> 01:25:30,280
Speaker 1: I think the way my life has worked out in

1333
01:25:30,439 --> 01:25:33,920
Speaker 1: science is that, and I think it's generally for people

1334
01:25:33,960 --> 01:25:39,440
Speaker 1: in science, whether it's applying for different positions, applying for grants,

1335
01:25:40,400 --> 01:25:43,799
Speaker 1: trying to transition into different industries, you will be faced

1336
01:25:43,800 --> 01:25:46,200
Speaker 1: with a lot of rejections. It's just how it is

1337
01:25:46,240 --> 01:25:50,160
Speaker 1: in science. And so one thing that's helped me is

1338
01:25:50,200 --> 01:25:53,280
Speaker 1: to you know, yes, I am ambitious, Yes there are

1339
01:25:53,320 --> 01:25:56,960
Speaker 1: things that I want to achieve, but I also you know,

1340
01:25:57,160 --> 01:25:59,439
Speaker 1: and I try my hardest. I make sure that I prepare,

1341
01:26:00,800 --> 01:26:03,719
Speaker 1: but you know, I also kind of let life happen

1342
01:26:03,960 --> 01:26:06,320
Speaker 1: as well, and there are some things that are out

1343
01:26:06,320 --> 01:26:08,360
Speaker 1: of your control. There are things that you can't change.

1344
01:26:09,000 --> 01:26:11,720
Speaker 1: And to not be put down on that and to

1345
01:26:11,840 --> 01:26:15,120
Speaker 1: think that you're not a good scientist because you've had

1346
01:26:15,439 --> 01:26:18,760
Speaker 1: X amount of rejections, the best scientists have had the

1347
01:26:18,760 --> 01:26:23,640
Speaker 1: most rejections, to be quite frank, So just yeah, I

1348
01:26:23,640 --> 01:26:26,679
Speaker 1: don't think that a rejection means failure because it doesn't

1349
01:26:26,720 --> 01:26:29,560
Speaker 1: at all. And if you just keep going, if you

1350
01:26:29,680 --> 01:26:32,559
Speaker 1: keep keep on, you will find that. And I found

1351
01:26:32,560 --> 01:26:37,840
Speaker 1: for myself anyway that different opportunities have presented themselves in

1352
01:26:37,880 --> 01:26:40,800
Speaker 1: ways that I had never thought possible, but they've you know,

1353
01:26:40,880 --> 01:26:44,400
Speaker 1: I look back now and I'm really grateful for the

1354
01:26:44,520 --> 01:26:47,080
Speaker 1: route that I had taken and the person that I

1355
01:26:47,120 --> 01:26:49,960
Speaker 1: am now because of what I've gone through. So that

1356
01:26:50,000 --> 01:26:53,280
Speaker 1: would definitely be something that I would UM, that I

1357
01:26:53,280 --> 01:26:57,799
Speaker 1: would share with with others who want to UM pursue

1358
01:26:58,040 --> 01:27:01,240
Speaker 1: maybe stem or just any kind of career. To be honest,

1359
01:27:02,000 --> 01:27:05,000
Speaker 1: another thing I would say, based on my experience, is

1360
01:27:05,800 --> 01:27:09,679
Speaker 1: if you can try to have mentors or a mentor

1361
01:27:09,760 --> 01:27:12,800
Speaker 1: who can really help you navigate your way through your

1362
01:27:12,840 --> 01:27:17,639
Speaker 1: career and or life. UM. I haven't had a mentor

1363
01:27:18,240 --> 01:27:21,759
Speaker 1: UM at all, and I can look back and see

1364
01:27:21,800 --> 01:27:27,240
Speaker 1: that in key stages of my career or education, UM,

1365
01:27:27,280 --> 01:27:30,240
Speaker 1: I would have loved it would have been like critical

1366
01:27:31,240 --> 01:27:34,920
Speaker 1: to have someone who could have UM, you know, shared advice,

1367
01:27:35,280 --> 01:27:38,880
Speaker 1: UM shared you know, ways in which I could improve

1368
01:27:39,439 --> 01:27:41,760
Speaker 1: in order to you know, make me more competitive for

1369
01:27:41,880 --> 01:27:44,599
Speaker 1: whatever I was trying to apply for. And you know,

1370
01:27:44,680 --> 01:27:50,160
Speaker 1: being a first gen um scientist, you know, I didn't

1371
01:27:50,160 --> 01:27:54,240
Speaker 1: have parents or family members who I knew much about

1372
01:27:54,280 --> 01:27:57,400
Speaker 1: the scientific community and how to navigate in that, and

1373
01:27:57,439 --> 01:27:58,960
Speaker 1: so a lot of it had to just be from

1374
01:27:59,000 --> 01:28:02,360
Speaker 1: trial and error. And you know, if you can have

1375
01:28:02,479 --> 01:28:05,400
Speaker 1: a mental if you can find someone who is you know,

1376
01:28:05,479 --> 01:28:08,880
Speaker 1: invested in making you the best version of yourself, both

1377
01:28:09,000 --> 01:28:12,240
Speaker 1: like professionally and personally, I would recommend that you try

1378
01:28:12,280 --> 01:28:16,559
Speaker 1: to find that as soon as possible. Yeah, it's interesting

1379
01:28:16,600 --> 01:28:21,320
Speaker 1: that you say that because there's such a conversation now

1380
01:28:21,320 --> 01:28:25,360
Speaker 1: about mentorship. And when I was starting in my career,

1381
01:28:25,400 --> 01:28:28,200
Speaker 1: that was not a conversation either. That was not something

1382
01:28:28,240 --> 01:28:32,640
Speaker 1: I had access to. And I think about how transformational

1383
01:28:32,720 --> 01:28:36,439
Speaker 1: that would have been. So that's my roundabout way of saying,

1384
01:28:36,439 --> 01:28:39,439
Speaker 1: I second your advice to people. Uh, and I would

1385
01:28:39,439 --> 01:28:42,840
Speaker 1: have wanted that as well. I think. I think a

1386
01:28:43,000 --> 01:28:47,000
Speaker 1: sounding board and some guidance is so incredibly important, and

1387
01:28:47,000 --> 01:28:50,120
Speaker 1: I think it's actually one of the things that makes

1388
01:28:50,320 --> 01:28:55,519
Speaker 1: cross generational friendship, especially for women, so important, because we

1389
01:28:55,640 --> 01:28:59,280
Speaker 1: go through these stages of transition and having someone who's

1390
01:28:59,720 --> 01:29:06,280
Speaker 1: come just before you to ask questions of us so invaluable. Yeah. No,

1391
01:29:06,400 --> 01:29:08,760
Speaker 1: it's it's actually my to do list to actually find

1392
01:29:08,800 --> 01:29:12,920
Speaker 1: a mentor. Yeah. I love that. So one of my

1393
01:29:13,000 --> 01:29:15,519
Speaker 1: very favorite things to ask every single person who comes

1394
01:29:15,560 --> 01:29:20,120
Speaker 1: on the show, as the podcast is titled work in Progress,

1395
01:29:21,040 --> 01:29:29,280
Speaker 1: is whether it's professional, personal, pharmaceutical, What feels like a

1396
01:29:29,360 --> 01:29:31,920
Speaker 1: work in progress in your life right now? You know,

1397
01:29:32,040 --> 01:29:36,639
Speaker 1: I think i'd go personal with that. UM I'd say,

1398
01:29:36,680 --> 01:29:41,920
Speaker 1: just trying to like build or maybe rebuild the confidence

1399
01:29:41,960 --> 01:29:47,800
Speaker 1: that I once had. UM. I so during my transition

1400
01:29:47,880 --> 01:29:51,280
Speaker 1: from academia to the pharmaceutical industry, and you know why,

1401
01:29:51,280 --> 01:29:55,160
Speaker 1: I mentioned about rejections and stuff like that. Um, that

1402
01:29:55,280 --> 01:29:59,080
Speaker 1: was like a really really difficult time for me. UM.

1403
01:29:59,200 --> 01:30:02,639
Speaker 1: I was like writing my thesis. So I spent months,

1404
01:30:03,160 --> 01:30:07,200
Speaker 1: um literally like fourteen hours a day just like writing,

1405
01:30:07,760 --> 01:30:10,080
Speaker 1: you know, writing, eating, going to sleep, writing, eating, going

1406
01:30:10,120 --> 01:30:13,120
Speaker 1: to sleep. And while I was doing that, also trying

1407
01:30:13,120 --> 01:30:18,200
Speaker 1: to apply for different positions and getting rejected. Then it

1408
01:30:18,280 --> 01:30:22,240
Speaker 1: was like writing, get rejected, eat sleep, writing rejection, get eat,

1409
01:30:22,360 --> 01:30:28,439
Speaker 1: eating sleep, and going through that for a couple of months.

1410
01:30:28,720 --> 01:30:30,960
Speaker 1: It really just kind of got me to a level

1411
01:30:31,000 --> 01:30:35,080
Speaker 1: where I actually didn't feel like I was worthy of

1412
01:30:35,120 --> 01:30:39,360
Speaker 1: being a scientist because I had all of these rejections

1413
01:30:39,400 --> 01:30:45,120
Speaker 1: and UM, and kind of going through that it kind

1414
01:30:45,120 --> 01:30:47,920
Speaker 1: of left me. So when I had actually finished my

1415
01:30:47,960 --> 01:30:50,960
Speaker 1: PhD a couple of months later, it kind of left

1416
01:30:50,960 --> 01:30:56,040
Speaker 1: me kind of feeling very numb and just not really

1417
01:30:56,080 --> 01:30:59,320
Speaker 1: confident about who I was. And even when I was

1418
01:30:59,400 --> 01:31:02,439
Speaker 1: able to so, pretty much soon after I finished my PhD,

1419
01:31:02,520 --> 01:31:05,480
Speaker 1: I got the job in the pharmacy was call industry,

1420
01:31:06,000 --> 01:31:09,400
Speaker 1: And even when I started in that position, I can

1421
01:31:09,400 --> 01:31:12,919
Speaker 1: only say it took like a year into that position

1422
01:31:13,000 --> 01:31:16,200
Speaker 1: that I actually started to feel more like myself. It

1423
01:31:16,240 --> 01:31:19,120
Speaker 1: had taken so long for me to get to a

1424
01:31:19,160 --> 01:31:23,240
Speaker 1: stage where I felt like I belonged in science again.

1425
01:31:24,040 --> 01:31:26,920
Speaker 1: And I just feel like I'm definitely in a better

1426
01:31:26,960 --> 01:31:31,800
Speaker 1: place than I was a year ago, two years ago. Um,

1427
01:31:31,840 --> 01:31:35,200
Speaker 1: but there's still much work that needs to that needs

1428
01:31:35,200 --> 01:31:38,320
Speaker 1: to be done, because I know how I was three,

1429
01:31:38,439 --> 01:31:43,120
Speaker 1: four or five years ago, and I've I've progressed like

1430
01:31:43,320 --> 01:31:46,200
Speaker 1: so much from where I was then, but in terms

1431
01:31:46,240 --> 01:31:49,760
Speaker 1: of my confidence levels, it's kind of gone the opposite way,

1432
01:31:50,240 --> 01:31:52,599
Speaker 1: and so it's just taken time. But just you know,

1433
01:31:52,680 --> 01:31:56,040
Speaker 1: making sure that you know, I am practicing self care,

1434
01:31:56,280 --> 01:31:59,000
Speaker 1: I am making sure that I'm kind to myself. I'm

1435
01:31:59,000 --> 01:32:02,120
Speaker 1: always the kind of person to um, you know, be

1436
01:32:02,200 --> 01:32:04,759
Speaker 1: kind to others and encourage others, but when it comes

1437
01:32:04,800 --> 01:32:09,519
Speaker 1: to speaking on myself then I'm super hypocritical. And so

1438
01:32:09,560 --> 01:32:13,160
Speaker 1: it's just trying to change that and just making making

1439
01:32:13,200 --> 01:32:15,880
Speaker 1: sure that I know that I am good enough to

1440
01:32:15,960 --> 01:32:19,360
Speaker 1: be in science. I'm a good enough scientist. I deserve

1441
01:32:19,439 --> 01:32:22,120
Speaker 1: to be here. But I would say that that's definitely

1442
01:32:22,160 --> 01:32:24,880
Speaker 1: a work in progress. I'm getting there, um, but I

1443
01:32:25,320 --> 01:32:29,160
Speaker 1: feel like there's still work to be done. I hold

1444
01:32:29,240 --> 01:32:32,840
Speaker 1: that and also I fully, I fully get it. I

1445
01:32:32,880 --> 01:32:35,600
Speaker 1: think that that's a lifelong journey. And I think that

1446
01:32:35,760 --> 01:32:40,200
Speaker 1: just when you build up a little more confidence in

1447
01:32:40,240 --> 01:32:43,360
Speaker 1: one arena, you you find a challenge with it in another.

1448
01:32:44,040 --> 01:32:46,960
Speaker 1: I don't know what the secret is there, but I

1449
01:32:47,000 --> 01:32:51,720
Speaker 1: will say it reminds me not to be discouraged. When

1450
01:32:51,760 --> 01:32:56,880
Speaker 1: I hear people who am so impressed by and amazed

1451
01:32:57,000 --> 01:33:03,120
Speaker 1: by say that they deal with that too, I go, okay, Okay, Well,

1452
01:33:03,760 --> 01:33:08,800
Speaker 1: maybe maybe that just means we're all hyper conscientious and

1453
01:33:08,840 --> 01:33:14,360
Speaker 1: aware and thus a little more um vulnerable to self doubt.

1454
01:33:14,760 --> 01:33:18,160
Speaker 1: But I I certainly hope is in an immense fan

1455
01:33:18,240 --> 01:33:20,400
Speaker 1: of yours that you know, I can be in the

1456
01:33:20,479 --> 01:33:24,479
Speaker 1: cheering section. Thank you. Yeah. And I'm you know, I'm

1457
01:33:24,479 --> 01:33:28,320
Speaker 1: trying to be more transparent about that because I think,

1458
01:33:28,479 --> 01:33:32,599
Speaker 1: um so, Actually I started, um So, I kind of

1459
01:33:34,240 --> 01:33:38,519
Speaker 1: more consistently started using Twitter like two years ago, and

1460
01:33:38,560 --> 01:33:40,479
Speaker 1: that was really because because I had moved to the

1461
01:33:40,479 --> 01:33:44,200
Speaker 1: pharmaceutical industry and I couldn't really speak on my research

1462
01:33:45,360 --> 01:33:50,000
Speaker 1: because of the confidentiality. Um I kind of thought, Okay,

1463
01:33:50,000 --> 01:33:52,040
Speaker 1: this is the perfect time to still try and be

1464
01:33:52,120 --> 01:33:55,200
Speaker 1: part of the science community online and still have a

1465
01:33:55,280 --> 01:33:59,479
Speaker 1: voice there. And you know, over the past two years,

1466
01:34:00,200 --> 01:34:02,240
Speaker 1: you know, I've tried to kind of be a positive

1467
01:34:02,320 --> 01:34:05,240
Speaker 1: voice and you know, have the jokes, have the laughs,

1468
01:34:05,520 --> 01:34:09,800
Speaker 1: um communicate with the science community, share different things. But

1469
01:34:10,800 --> 01:34:13,360
Speaker 1: you know, I'm definitely trying now to be more transparent

1470
01:34:13,400 --> 01:34:16,880
Speaker 1: about you know, when I don't have good days and

1471
01:34:16,920 --> 01:34:19,400
Speaker 1: not just kind of have it is. You know, everything's amazing.

1472
01:34:19,920 --> 01:34:22,040
Speaker 1: These are all the positive things that happening. But just

1473
01:34:22,160 --> 01:34:24,639
Speaker 1: be real because as you said, you know, there are

1474
01:34:24,720 --> 01:34:28,600
Speaker 1: people coming up who look to certain people, and I

1475
01:34:28,600 --> 01:34:31,720
Speaker 1: don't want to give the false impression that you know,

1476
01:34:31,800 --> 01:34:35,519
Speaker 1: everyone is okay all of the time. So yeah, just

1477
01:34:35,560 --> 01:34:40,600
Speaker 1: trying to be more transparent about that. Yeah. I I

1478
01:34:40,640 --> 01:34:46,280
Speaker 1: think a lot of people have fear around being vulnerable,

1479
01:34:46,560 --> 01:34:50,240
Speaker 1: that it might somehow signal a weakness or or make

1480
01:34:50,280 --> 01:34:53,679
Speaker 1: people lean out. Vulnerability, in my experience, always makes people

1481
01:34:53,720 --> 01:34:57,160
Speaker 1: lean in. It offers people such relief because everyone gets

1482
01:34:57,200 --> 01:34:59,559
Speaker 1: to go, oh, thank god, you two, how are you

1483
01:34:59,600 --> 01:35:02,160
Speaker 1: dealing at this and what are your coping strategies and

1484
01:35:02,160 --> 01:35:04,679
Speaker 1: how are you taking care of yourself? And and suddenly

1485
01:35:04,720 --> 01:35:06,720
Speaker 1: you get into these arenas where you do, as you

1486
01:35:06,800 --> 01:35:10,760
Speaker 1: said earlier, feel safe to have deeper conversations that are

1487
01:35:11,320 --> 01:35:14,880
Speaker 1: just more real. So I really want to thank you

1488
01:35:14,960 --> 01:35:17,840
Speaker 1: for coming and doing that with me today. It means

1489
01:35:17,840 --> 01:35:20,000
Speaker 1: a lot, thank for having me and that this has

1490
01:35:20,040 --> 01:35:26,840
Speaker 1: been great. This show is executive produced by Me, Sophia Bush,

1491
01:35:27,000 --> 01:35:31,200
Speaker 1: and sim Sarna. Our associate producer is Kate Linlee. Our

1492
01:35:31,360 --> 01:35:34,360
Speaker 1: editor is Josh Wendish, and our music was written by

1493
01:35:34,400 --> 01:35:37,600
Speaker 1: Jack Garrett and produced by Mark Foster. This show is

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