Speaker 1: This is Bloomberg Business Week with Carol Masser and Jason
Speaker 1: Kelly on Bloomberg Radio. This is a really interesting discussion
Speaker 1: we're about to have and it actually harkens back and
Speaker 1: thanks to Carol Masser for pointing this out on Twitter
Speaker 1: earlier to a conversation. We actually had it in j
Speaker 1: I t earlier this year when we were still out
Speaker 1: about out and about in the world. It was a
Speaker 1: really live event. Yeah, they're in Newark. We were talking
Speaker 1: about the concept of digital twins. What is that, you ask,
Speaker 1: Let's get into it. Charles Fisher is founder and CEO
Speaker 1: of Unlearned AI. He joins us on the phone from
Speaker 1: San Francisco. Dr Fisher, thank you so much for joining us.
Speaker 1: Thank you for having me. All Right, So this is
Speaker 1: exciting in part because we are all now many experts,
Speaker 1: or at least we consider ourselves such on drug development.
Speaker 1: You know, we talked with the CEO of Teva Pharmaceuticals
Speaker 1: here on this program earlier and really got into a
Speaker 1: lot of the issues here. How does artificial intelligence play
Speaker 1: into this? How might it help us in an age
Speaker 1: where we're all really interested in accelerating development? Here? Yeah, well,
Speaker 1: I think there are a few different ways, starting all
Speaker 1: the way from the beginning of the cycle to saying
Speaker 1: how can we discover new compounds that might be effective therapies,
Speaker 1: all the way to the end of the process, and
Speaker 1: saying how can we leverage all of the data that
Speaker 1: we have from electronic health records to make more efficient
Speaker 1: clinical trials that can get drugs to patients faster. Well, okay,
Speaker 1: so what's interesting is, and we're hearing more and more
Speaker 1: about this, right, We've heard various time frames and what
Speaker 1: it will take to develop um a new vaccine, and
Speaker 1: the latest have been anywhere from nine months maybe the
Speaker 1: most optimistic too, maybe a couple of years. So tell us,
Speaker 1: you know, you shared with us some some some wisdom
Speaker 1: about when you normally develop a new medicine, it's between
Speaker 1: ten and fifteen years. How can digital cloning help skip
Speaker 1: through this vaccine creation process faster and also ensure that
Speaker 1: it's safe. Yeah, I think the biggest part of the
Speaker 1: problem in terms of the time when it takes to
Speaker 1: talk about how long will it take us to get
Speaker 1: new treatments or new vaccines, whether that be for for
Speaker 1: COVID nineteen or any disease, is the amount of time
Speaker 1: it takes for us to tell if those are safe
Speaker 1: and effective. So you know, one of the sort of
Speaker 1: bad parts about drug development is that actually about nine
Speaker 1: out of ten drugs that we try in clinical trials
Speaker 1: end up failing. So most of the time our guesses
Speaker 1: end up not working well. So it's what we'd like
Speaker 1: to be able to do is to speed that up,
Speaker 1: uh and in a variety of ways by postentially leveraging
Speaker 1: uh So, what we call these these digital patients is
Speaker 1: is leveraging data from electronic health records to make trials faster. Alright,
Speaker 1: so tell us how it works. Sure, So, basically, when
Speaker 1: a patient enrolls in the trial, we create a digital
Speaker 1: copy of that patient that tells us what would happen
Speaker 1: to that person if they were to receive a placebo,
Speaker 1: so a dummy treatment, and then at the end of
Speaker 1: the study, you give that real person the real treatment
Speaker 1: how it affects them, and then you can compare it
Speaker 1: to the digital twins prediction for what would have happened
Speaker 1: if they had received the placebo, and then you can
Speaker 1: estimate if that treatment was effective or not. And basically,
Speaker 1: because you can do this but these predicted placebo responses,
Speaker 1: you don't need to enroll as many subjects into a
Speaker 1: clinical trump so you can run a trial with up
Speaker 1: to half as many half as many subjects, So doing
Speaker 1: this are we doing this in this? In this you know,
Speaker 1: search um for a vaccine. I'm not aware of any
Speaker 1: trials that are doing this in COVID nineteen right now. UM.
Speaker 1: I think one of the difficulties there is because it's
Speaker 1: such a new disease, we need to have a lot
Speaker 1: of data for, you know, to say we know how
Speaker 1: this disease will progress if you don't receive a treatment.
Speaker 1: But since COVID nineteen is new, we really don't have
Speaker 1: that that those data yet. But lots and lots of
Speaker 1: data are being collected every day, So the ability to
Speaker 1: to apply these types of technologies may that may be
Speaker 1: something that could be done in the near future. All right,
Speaker 1: we are all aware, and you're much more aware than
Speaker 1: we are of the trials and tribulations as it were.
Speaker 1: When it comes to the regulatory side of this, and
Speaker 1: a lot of the regulatory framework exists for a reason.
Speaker 1: We want people to be safe. We want drugs when
Speaker 1: they get to the market to be as safe as
Speaker 1: they can possibly be. What is the reaction, what has
Speaker 1: been the reaction by organizations and institutions like the f
Speaker 1: D A two plans like this mhm. The FDA is
Speaker 1: actually doing a lot of work uh these days to
Speaker 1: modernized clinical trials really across the board, and so in
Speaker 1: general they're they're quite supportive of new approaches to bring
Speaker 1: in these kinds of data to make things more efficient.
Speaker 1: You really just have to work with them to demonstrate
Speaker 1: with real evidence that the approach you're taking works well,
Speaker 1: which is really how it should be anyway, right, um, So,
Speaker 1: so I would say that they're quite open to it. Uh.
Speaker 1: The approaches are also new, so there they have been
Speaker 1: some I think a handful now of of drugs for
Speaker 1: targeting different types of cancer where these types of evidence
Speaker 1: have been have been used. Um. And then you know,
Speaker 1: our company is applying some of these approaches in some
Speaker 1: trials for for all disease. Now wells then talk to
Speaker 1: us a little bit about you know, maybe it's not
Speaker 1: something that's applicable as you said to COVID nineteen and
Speaker 1: the hunt for a vaccine, but there are certainly some diseases,
Speaker 1: whether it's Alzheimer's and so on, that really have plagued
Speaker 1: us and trying to figure out some kind of cure
Speaker 1: or some kind of you know, more significant treatment than
Speaker 1: we currently have. Talked to us attle bit about those
Speaker 1: types of ailments that might there might be some promise
Speaker 1: using digital clones. Yeah, I think in you know, lots
Speaker 1: of these diseases, whether they be you know, cancer, or
Speaker 1: neurologic disease like Alzheimer's, or or rare genetic diseases. UM,
Speaker 1: the ability to leverage all of the data we have
Speaker 1: collected on those diseases to make those trials more efficient
Speaker 1: UM with digital twins is I think going to be
Speaker 1: very Uh. I think that's going to be the future
Speaker 1: of how trials are run. It also, you know, one
Speaker 1: of the sort of side effects of COVID nineteen that
Speaker 1: since we're all sheltering in place right now, no one's
Speaker 1: participating in clinical trial right so clinical trials for all
Speaker 1: of these other diseases, for Alzheimers, for cancer, they're all
Speaker 1: disruptive right now. And so figuring out ways to run
Speaker 1: those trials with fewer patients or where so that patients
Speaker 1: don't have to maybe go into the hospital by applying
Speaker 1: new technologies like like digital twins will really help to
Speaker 1: keep medical research going so that it's not all set
Speaker 1: back because we aren't able to participate because of COVID
Speaker 1: Night Team. All right, well, really interesting, interested to see
Speaker 1: where this goes from. Here are thanks to Charles Fisher,
Speaker 1: founders CEO of Unlearned AI, joining us on the phone
Speaker 1: from San Francisco and the idea of digital twins. It
Speaker 1: is cool, very cool. It makes sense, yes, and we
Speaker 1: need to do more on it because I do think
Speaker 1: this is going to be a big way for the
Speaker 1: medical arena and their way forward to in terms of
Speaker 1: tackling a lot of ailments.