WEBVTT - Using Gene Therapy to Help the Blind See

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<v Speaker 1>Pushkin. Think about the basic idea of gene therapy. You

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<v Speaker 1>string together a gene, put the gene inside a virus,

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<v Speaker 1>put the virus inside a patient, and then the virus

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<v Speaker 1>delivers the gene to the patient, sells, and then that

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<v Speaker 1>new gene, if everything goes according to plan, makes the

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<v Speaker 1>patient get better. It sounds hard, it is hard, but

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<v Speaker 1>after decades of research, gene therapy is starting to work.

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<v Speaker 1>I'm Jacob Goldstein and this is What's Your Problem, the

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<v Speaker 1>show where I talk to people who are trying to

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<v Speaker 1>make technological progress. My guest today is Shannon boy She's

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<v Speaker 1>a professor of genetics at the University of Florida and

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<v Speaker 1>the co founder and chief scientific officer of Atsina Therapeutics.

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<v Speaker 1>Shannon's problem is this, how do you use gene therapy

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<v Speaker 1>to cure blindness, or at least certain forms of blindness.

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<v Speaker 1>Shannon has been working on gene therapy for twenty years,

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<v Speaker 1>and I wanted to talk with her about the long

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<v Speaker 1>arc of the field, from the wild optimism of the

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<v Speaker 1>early two thousands to the realization that developing gene therapy

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<v Speaker 1>would be a long, hard slog, to the recent promising

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<v Speaker 1>results from an experimental drug that her company has developed

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<v Speaker 1>that drug treats a rare disease that Sharon started studying

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<v Speaker 1>as a grad student back in two thousand and four.

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<v Speaker 1>The disease is called LCA one.

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<v Speaker 2>So babies are born with the disease and usually within

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<v Speaker 2>the first few months of life, their moms or dads

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<v Speaker 2>notice that they're not looking at them directly, they're not

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<v Speaker 2>fixating on objects. Oftentimes the babies will have a roving

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<v Speaker 2>eye movement called nystagmus, and so they're diagnosed usually pretty

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<v Speaker 2>quickly with this condition, and unfortunately, it's profound visual impairment,

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<v Speaker 2>if not total blindness, and that remains with the patient

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<v Speaker 2>throughout the course of their life. So that's really the

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<v Speaker 2>reason that this lab was really interested in studying that

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<v Speaker 2>gene AHU.

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<v Speaker 1>So it's one of the somewhat rare instances where there

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<v Speaker 1>is like a single gene that maps to a single

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<v Speaker 1>in this case, profound problem basically blindness or severe problems

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<v Speaker 1>with vision, which is kind of you would think would

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<v Speaker 1>be the first wave of gene therapy, right exactly, This

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<v Speaker 1>is what the early two thousands, when you're and so

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<v Speaker 1>the human genome has just been mapped, there's like a

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<v Speaker 1>sense of oh, now we know all the genes, right,

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<v Speaker 1>let's figure out how to help people with this new knowledge.

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<v Speaker 2>That's exactly right. This was sort of the step one

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<v Speaker 2>in gene therapy was the simplest form, which is just

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<v Speaker 2>gene replacement. Can we take a healthy copy of a

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<v Speaker 2>gene and put it back into the patient's cells and

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<v Speaker 2>then have that gene go on to make the protein

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<v Speaker 2>it was supposed to make and then hopefully rett or

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<v Speaker 2>the function to those cells.

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<v Speaker 1>And so what as a grad student are you trying

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<v Speaker 1>to figure out?

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<v Speaker 2>The lab was studying the biochemical underpinnings of this disease,

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<v Speaker 2>and they were using a chicken model to do this.

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<v Speaker 2>That's kind of a unique thing in a lab. Usually

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<v Speaker 2>research labs are using mice or rats, but there was

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<v Speaker 2>a naturally occurring chicken model of this disease that had

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<v Speaker 2>profound visual impairment and blindness.

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<v Speaker 1>So naturally occurring chicken model basically means this happens to

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<v Speaker 1>chickens too, Yes, exactly, it is. That's right.

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<v Speaker 2>Yeah. So, at the same time that the lab was studying,

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<v Speaker 2>you know, what was going wrong in this chicken and

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<v Speaker 2>why it was happening, they wanted to ask the question

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<v Speaker 2>would gene therapy be a reasonable approach for treating these chickens.

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<v Speaker 2>Can we restore visions to these chickens with gene therapy.

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<v Speaker 2>So this was a collaborative effort with my other grad

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<v Speaker 2>students and I where we took a vector called Lenti

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<v Speaker 2>virus and we to the chicken embryos. I felt very

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<v Speaker 2>much in grad school like I was a poultry farmer,

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<v Speaker 2>because I would on my way into lab every day,

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<v Speaker 2>stop at the farm, pick up the eggs, burning them

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<v Speaker 2>into lab, and then my fellow grad students and I

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<v Speaker 2>we would make these tiny little holes in the chicken

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<v Speaker 2>egg and we would pull these glass micro needles and

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<v Speaker 2>use them to inject into the chicken embryo. And remember

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<v Speaker 2>this is a disease that you have from birth, so

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<v Speaker 2>we needed to treat these chickens very early. But it

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<v Speaker 2>was a difficult process to get that micro needle injection

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<v Speaker 2>into the head of the chicken embryo and then for

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<v Speaker 2>that chicken to make it all the way to hatch, right,

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<v Speaker 2>And that was I think one of the hardest parts

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<v Speaker 2>of that project. Actually, It's why I said I felt

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<v Speaker 2>like a poultry farmer. Is all of the machinations you know,

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<v Speaker 2>getting the humidity right, the temperature right, the position right,

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<v Speaker 2>making sure you close that egg right, just getting that

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<v Speaker 2>chicken to survive.

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<v Speaker 1>And so you injecting the non mutated form of the gene,

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<v Speaker 1>the good form of the gene, if you will, encased

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<v Speaker 1>in this virus, into the head of the chicken embryo. Yes,

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<v Speaker 1>did it work?

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<v Speaker 2>For a while it did not, because again, it was

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<v Speaker 2>difficult to manipulate a chicken embryo like that and actually

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<v Speaker 2>have it to survive to hatch. But my fellow grad

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<v Speaker 2>students and I did a lot of work to optimize

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<v Speaker 2>that process, and eventually it actually did work. We had

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<v Speaker 2>little chicks that were born, and I can distinctly remember

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<v Speaker 2>them walking around on the lab bench and pecking at

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<v Speaker 2>our jewelry or at Eminem's that we had laid out

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<v Speaker 2>on the surface of the bench. Very different from the

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<v Speaker 2>blind chickens. It was very clear. You know, chickens are

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<v Speaker 2>very visually guided creatures. It's very obvious when a chicken

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<v Speaker 2>can see versus Nazi.

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<v Speaker 3>It was so fun. We were all so so happy.

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<v Speaker 1>Okay, so that's two thousand and four as twenty years ago. Yeah, yeah,

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<v Speaker 1>at that time, is it like, well, we did it

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<v Speaker 1>in chickens, let's do it in people or what.

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<v Speaker 2>So that's actually where my thesis project comes in. So

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<v Speaker 2>all of that chicken work was a really collaborative effort

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<v Speaker 2>and it was exciting, but it had its drawbacks and

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<v Speaker 2>it wasn't clinically translatable for a number of reasons. First

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<v Speaker 2>and foremost, we were never going to do an embryonic

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<v Speaker 2>injection and a patient. Maybe that'll happen one day, honestly,

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<v Speaker 2>but it certainly wasn't close to happening in two thousand

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<v Speaker 2>and four. So we needed a gene therapy that could

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<v Speaker 2>be injected in a patient after birth, right, And unfortunately,

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<v Speaker 2>the virus that we were using in the chicken experiments,

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<v Speaker 2>the Lenti virus, is really poor at a gene delivery

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<v Speaker 2>to a developed retina. So we needed to find a

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<v Speaker 2>more clinically relevant vector to do the gene therapy.

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<v Speaker 1>Let's just pause for a moment and talk about this

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<v Speaker 1>idea of a vector in gene therapy. So the basic idea, right,

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<v Speaker 1>is like, you know what the good gene is, you

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<v Speaker 1>know the gene you want to get into, in this case,

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<v Speaker 1>the person's eye. But there's this weird question of how

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<v Speaker 1>do you get it there, right, Like, you can't just

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<v Speaker 1>put a string of genetic material randomly in someone's body, right,

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<v Speaker 1>It'll just get destroyed. And so there's this basic idea

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<v Speaker 1>that you put it in a virus, right, because a

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<v Speaker 1>virus is like, it's billions of years of evolution to

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<v Speaker 1>be a genetic material delivery mechanism.

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<v Speaker 3>That's exactly right.

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<v Speaker 1>But that's hard for a number of reasons. So like,

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<v Speaker 1>tell me sort of the state of vectors at this

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<v Speaker 1>time twenty years ago when you're figuring this out.

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<v Speaker 2>So there were a number of viral vectors that were

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<v Speaker 2>being used to deliver genes, and each of them had

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<v Speaker 2>their pros and their cons One was named adnovirus. This

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<v Speaker 2>was a good virus because it's big, you can fit

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<v Speaker 2>a lot of genetic material into it, and it was

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<v Speaker 2>used in the early days of gene therapy and on.

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<v Speaker 2>Fortunately it was discovered you know later on that it

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<v Speaker 2>came with you know, some downsides. It's more immunogenic than

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<v Speaker 2>the other viral vectors that are out there.

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<v Speaker 1>Meaning it generates an immune response. So the body's like, oh,

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<v Speaker 1>that's a virus. I'm going to destroy it, and you're like, no, no, no,

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<v Speaker 1>this is a virus that's going to help you exactly.

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<v Speaker 1>It's like, I don't care. I've gotten rid of it.

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<v Speaker 3>Yes, yeah.

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<v Speaker 2>And then of course there was lenty virus, which is

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<v Speaker 2>what we were using in the chickens. It is not

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<v Speaker 2>the vector of choice, for instance, in the eye where

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<v Speaker 2>I work, because it's not very good at delivering genes

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<v Speaker 2>to developed cells in the retina. And then in the

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<v Speaker 2>nineties some exciting work was going on evaluating a newer

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<v Speaker 2>vector called Adno associated virus or AAV. Since the nineties

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<v Speaker 2>early two thousands, AAV has become the gold standard gene

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<v Speaker 2>delivery vector for essentially all of gene therapy.

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<v Speaker 1>And so at this time in two thousand and four, like,

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<v Speaker 1>what was the state of gene therapy?

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<v Speaker 2>Oh, my gosh, it was the heyday. It was such

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<v Speaker 2>a fun time and it was so it was so exciting.

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<v Speaker 2>The my grad school days, my postdoc days, it was

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<v Speaker 2>an extremely exciting time in the field that I would

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<v Speaker 2>say it was filled with hope because there was so

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<v Speaker 2>much proof of concept work going on in animal models

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<v Speaker 2>of disease showing that gene therapy could restore vision, could

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<v Speaker 2>restore muscular function, could restore clotting.

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<v Speaker 3>You know, you name it.

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<v Speaker 2>It was these successes were being seen across neuromuscular disease,

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<v Speaker 2>CNS disease, ocular disease, but everybody was just really excited

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<v Speaker 2>about it, and that extended beyond the scientists in the lab.

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<v Speaker 2>That was true of the macro environment too, So you know,

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<v Speaker 2>I mean.

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<v Speaker 1>Like in the media or like the industry, like the

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<v Speaker 1>pharmaceutical industry.

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<v Speaker 2>Yeah, I'm talking more about like investors and big pharma.

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<v Speaker 2>So I mean investors were keen to throw their money

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<v Speaker 2>at gene therapy at the time because of how much

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<v Speaker 2>promise it was showing in these pre clinical studies, and

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<v Speaker 2>big Arma was keen to acquire, you know, startup companies

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<v Speaker 2>that were in this space because of that promise it

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<v Speaker 2>was showing. And I think their their reason at the

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<v Speaker 2>time was a sound one. They wanted to use. Even

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<v Speaker 2>if those companies were focused on rare disease, it was

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<v Speaker 2>like this platform for them to say, well, if I

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<v Speaker 2>can get gene therapy to work in this small, rare disease,

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<v Speaker 2>that proves that as a company, I'm capable of doing

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<v Speaker 2>this and that eventually I can do it in a

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<v Speaker 2>disease that affects millions of people. So it was a

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<v Speaker 2>really really exciting time, both scientifically and from kind of

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<v Speaker 2>a financial standpoint.

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<v Speaker 1>And then at some point, right there are these these

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<v Speaker 1>strong results using gene therapy to treat a disease called

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<v Speaker 1>LCA two, which is similar to LCA one, the disease

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<v Speaker 1>you work on, and that's like a big moment in

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<v Speaker 1>the field, right.

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<v Speaker 2>Yeah, the RP sixty five LCA two gene therapy trials

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<v Speaker 2>were a huge success, and then they went on to

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<v Speaker 2>form the basis of Luxterno, which is the first approved

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<v Speaker 2>ocular gene therapy, and so everybody was super excited that, Okay,

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<v Speaker 2>they got this approved. We're going to see this, you know,

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<v Speaker 2>flood of other gene therapies getting approved on the heels

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<v Speaker 2>of luxtern And I think that's I think that's when

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<v Speaker 2>it got hard, and you know, there was a little

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<v Speaker 2>bit of a reality check for the field.

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<v Speaker 1>What was that like for you? So you're working on

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<v Speaker 1>LCA one, a very similar disease. Everybody is very excited

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<v Speaker 1>about l c A two, are you like, yes, we

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<v Speaker 1>got l c A two, I'm about to get LCA one.

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<v Speaker 1>Like what what was your where were you at that? Oh?

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<v Speaker 3>I was I was super excited.

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<v Speaker 1>I was.

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<v Speaker 2>I was further behind obviously in my pursuit of l

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<v Speaker 2>c A one, but I had, you know, high hopes

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<v Speaker 2>that it would it would go, that it would work.

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<v Speaker 1>Why didn't it happen as fast as you thought?

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<v Speaker 2>So in twenty fourteen, I hit a stage where you know,

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<v Speaker 2>the technology had been developed, I had done everything that

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<v Speaker 2>I really could, you know, from the academic standpoint, to

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<v Speaker 2>get this ready to move forward. But at that stage

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<v Speaker 2>you hit what the NIH calls the valley of death,

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<v Speaker 2>which is, you know, a period of time where you

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<v Speaker 2>need a lot of capital and a lot of infrastructure

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<v Speaker 2>to move a gene therapy from bench to bedside, and

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<v Speaker 2>you can't do that in an academic lab.

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<v Speaker 1>So to put it to test it in people, basically

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<v Speaker 1>testing it in people is obviously complicated and expensive and

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<v Speaker 1>very at least some extent rightly so, right you're ingesting

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<v Speaker 1>things into people's eyes.

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<v Speaker 3>Yes.

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<v Speaker 2>In twenty fourteen, my husband and I who I work with,

0:12:35.116 --> 0:12:39.036
<v Speaker 2>we were very much in a pattern of developing technologies

0:12:39.156 --> 0:12:43.516
<v Speaker 2>and then out licensing them to different companies. So in

0:12:43.596 --> 0:12:47.036
<v Speaker 2>around twenty fourteen, we partnered with Genzyme, which was a

0:12:47.036 --> 0:12:51.076
<v Speaker 2>company focused on developing gene therapies for rare disease, and

0:12:51.116 --> 0:12:54.716
<v Speaker 2>they took that technology. Shortly thereafter they were acquired by

0:12:54.796 --> 0:12:59.596
<v Speaker 2>Santafie and together with Genzyme Slash Santafee, we conducted all

0:12:59.636 --> 0:13:02.556
<v Speaker 2>of the studies that were what we call I and

0:13:02.636 --> 0:13:06.276
<v Speaker 2>D enabling studies, sort of like the really well documented

0:13:06.356 --> 0:13:10.676
<v Speaker 2>careful safety studies and efficacy studies, dose ranging studies that

0:13:10.716 --> 0:13:13.476
<v Speaker 2>are required to show to the FDA before.

0:13:13.276 --> 0:13:14.476
<v Speaker 3>They let you go into people.

0:13:14.716 --> 0:13:18.036
<v Speaker 1>I INDA is an investigational new drug's exactly. So you're

0:13:18.116 --> 0:13:20.076
<v Speaker 1>like doing all the work to say, like, look, this

0:13:20.116 --> 0:13:22.556
<v Speaker 1>should be an investigational new drug that we can test

0:13:22.596 --> 0:13:24.676
<v Speaker 1>in a very small number of people just to see

0:13:24.716 --> 0:13:26.676
<v Speaker 1>if it's safe to start out with exactly.

0:13:27.156 --> 0:13:27.476
<v Speaker 3>Yeah.

0:13:27.516 --> 0:13:30.556
<v Speaker 2>So, and I'll be honest, that moved a little bit

0:13:30.796 --> 0:13:33.596
<v Speaker 2>slower than I would have liked. But I mean, when

0:13:33.596 --> 0:13:36.156
<v Speaker 2>you work with Big Pharma, and I will say they

0:13:36.196 --> 0:13:39.236
<v Speaker 2>were an amazing, amazing team, excellent group of people, but

0:13:39.636 --> 0:13:42.156
<v Speaker 2>Big Pharma is very siloed, and you know, it can

0:13:42.196 --> 0:13:45.636
<v Speaker 2>take a long time for things to move. And then unfortunately,

0:13:46.276 --> 0:13:50.756
<v Speaker 2>in around twenty eighteen, Cianna FI decided to pivot away

0:13:50.756 --> 0:13:55.476
<v Speaker 2>from ocular gene therapy altogether, so they wanted to give

0:13:55.476 --> 0:13:59.116
<v Speaker 2>the program away, and I was heartbroken. I remember the

0:13:59.196 --> 0:14:01.796
<v Speaker 2>night that someone told me it was happening. I couldn't

0:14:01.836 --> 0:14:04.476
<v Speaker 2>believe it because you know, we were just about to

0:14:04.516 --> 0:14:07.396
<v Speaker 2>treat the first patient and everything was ready to go,

0:14:07.476 --> 0:14:10.636
<v Speaker 2>and I just couldn't believe it. But you know, companies

0:14:10.676 --> 0:14:13.916
<v Speaker 2>make decisions like this all the time. So when that happened,

0:14:13.996 --> 0:14:16.516
<v Speaker 2>that was really what motivated my husband and I to

0:14:17.276 --> 0:14:20.396
<v Speaker 2>co found our own company because we wanted hopefully to

0:14:20.436 --> 0:14:23.796
<v Speaker 2>get that program back so that we could make sure

0:14:23.796 --> 0:14:26.796
<v Speaker 2>that it went forward. And that was just that was

0:14:26.876 --> 0:14:30.076
<v Speaker 2>one reason that we founded at Seena Therapeutics. I would

0:14:30.076 --> 0:14:32.596
<v Speaker 2>say that the broader reason we founded the company was

0:14:33.076 --> 0:14:35.876
<v Speaker 2>out of a sense of frustration because we had developed

0:14:35.916 --> 0:14:38.716
<v Speaker 2>a lot of technologies and we had outlcensed them to

0:14:38.796 --> 0:14:42.836
<v Speaker 2>a variety of companies, and there was a theme emerging

0:14:42.956 --> 0:14:46.436
<v Speaker 2>that the technologies weren't getting to patients. And whether that

0:14:46.556 --> 0:14:50.756
<v Speaker 2>was because of you know, business decisions overriding science decisions,

0:14:50.876 --> 0:14:53.836
<v Speaker 2>or just you know, companies being too big and siloed,

0:14:54.516 --> 0:14:57.356
<v Speaker 2>there were a variety of reasons, but it ultimately we

0:14:57.436 --> 0:14:59.716
<v Speaker 2>formed the company because we were frustrated. We wanted to

0:14:59.756 --> 0:15:02.916
<v Speaker 2>have some more control over the direction that the science

0:15:03.036 --> 0:15:03.516
<v Speaker 2>was taking.

0:15:03.836 --> 0:15:06.636
<v Speaker 1>It's like you want it more than anybody else can

0:15:06.716 --> 0:15:07.236
<v Speaker 1>want it.

0:15:07.356 --> 0:15:08.636
<v Speaker 3>Yes, it was.

0:15:08.676 --> 0:15:11.596
<v Speaker 2>I mean one is my baby, right, and so are

0:15:11.636 --> 0:15:13.876
<v Speaker 2>some of the other indications that I'm working on now.

0:15:13.876 --> 0:15:16.356
<v Speaker 2>But yeah, I wanted to be the one to help

0:15:16.436 --> 0:15:19.396
<v Speaker 2>usher them towards patients and keep it moving in the

0:15:19.436 --> 0:15:19.956
<v Speaker 2>right direction.

0:15:21.076 --> 0:15:24.196
<v Speaker 1>And you mentioned your husband, So is he in the

0:15:24.196 --> 0:15:25.796
<v Speaker 1>same field as you, like, is.

0:15:25.916 --> 0:15:26.556
<v Speaker 3>What's he doing?

0:15:26.676 --> 0:15:30.916
<v Speaker 2>Yeah, he's an AV vectorologist. When I was a grad

0:15:30.956 --> 0:15:34.396
<v Speaker 2>student and I was tasked with my thesis project, which

0:15:34.516 --> 0:15:37.636
<v Speaker 2>was okay, come up with a clinically relevant approach for

0:15:37.716 --> 0:15:40.636
<v Speaker 2>treating this disease. So to do that, I needed to

0:15:40.716 --> 0:15:43.756
<v Speaker 2>shift away from Lenti virus and start using ad no

0:15:43.876 --> 0:15:47.756
<v Speaker 2>associated virus AAV. I needed to shift into a mouse model,

0:15:47.796 --> 0:15:50.876
<v Speaker 2>a mammalian model of the disease, and so to get

0:15:50.916 --> 0:15:53.516
<v Speaker 2>help on the AAV aspect of the project, I went

0:15:53.596 --> 0:15:56.516
<v Speaker 2>to Bill Houseworth, who became my post docmentor, and he

0:15:56.596 --> 0:15:59.396
<v Speaker 2>pointed me in the direction of my now husband. He

0:15:59.436 --> 0:16:01.716
<v Speaker 2>was a scientific research manager at the time. He said,

0:16:01.756 --> 0:16:03.556
<v Speaker 2>you know, he can field any questions you have about

0:16:03.636 --> 0:16:05.956
<v Speaker 2>vector design, and so I went to him and then

0:16:05.996 --> 0:16:09.556
<v Speaker 2>that you know was an excellent collaboration obviously that lossoened

0:16:09.556 --> 0:16:12.316
<v Speaker 2>into a nerd romance and then eventually a marriage in

0:16:12.316 --> 0:16:12.676
<v Speaker 2>two k.

0:16:12.876 --> 0:16:16.276
<v Speaker 1>Yes, it is a very nerdy meet cute, yes.

0:16:17.396 --> 0:16:19.956
<v Speaker 2>But yeah, we're very much in the same field. But

0:16:20.476 --> 0:16:22.676
<v Speaker 2>we have very different skill sets, I would say, so

0:16:23.076 --> 0:16:24.196
<v Speaker 2>we compliment each other.

0:16:24.116 --> 0:16:24.996
<v Speaker 3>Which is nice.

0:16:26.396 --> 0:16:30.276
<v Speaker 1>Obviously to get from, you know, doing this in chickens

0:16:30.316 --> 0:16:32.476
<v Speaker 1>twenty years ago to doing it in people now. There

0:16:32.476 --> 0:16:34.476
<v Speaker 1>were many, many, many things I'm sure that you had

0:16:34.516 --> 0:16:38.316
<v Speaker 1>to figure out. There is there anything in particular that

0:16:38.436 --> 0:16:41.076
<v Speaker 1>was a thing you figured out? Maybe that was a

0:16:41.076 --> 0:16:43.636
<v Speaker 1>thing that people doing gene therapy more broadly were trying

0:16:43.636 --> 0:16:47.356
<v Speaker 1>to figure out, just in the sense of, yeah, something

0:16:47.436 --> 0:16:48.596
<v Speaker 1>you solved along the way.

0:16:49.196 --> 0:16:51.636
<v Speaker 2>In the early days, when I had first transitioned into

0:16:51.676 --> 0:16:55.676
<v Speaker 2>testing the AV vector in the mouse, I did it

0:16:55.716 --> 0:16:57.516
<v Speaker 2>over and over and over again, and it didn't work.

0:16:57.796 --> 0:17:00.956
<v Speaker 2>And I think one big mistake that I made was

0:17:00.996 --> 0:17:03.916
<v Speaker 2>that I was using the same gene, the same coding

0:17:03.996 --> 0:17:07.836
<v Speaker 2>sequence that we had used in the chicken experiments, and interestingly,

0:17:07.956 --> 0:17:12.156
<v Speaker 2>that gene was a bovine gene. In the early two thousands,

0:17:12.436 --> 0:17:15.196
<v Speaker 2>it was a lot easier to generate bovine sequences for

0:17:15.236 --> 0:17:18.556
<v Speaker 2>reasons I don't even actually remember. But what it took

0:17:18.756 --> 0:17:21.076
<v Speaker 2>was figuring out that we needed to deliver the species

0:17:21.116 --> 0:17:25.916
<v Speaker 2>specific gene. So the mouse gene worked, the human gene worked,

0:17:25.916 --> 0:17:29.116
<v Speaker 2>which was great because that was very translatable, So the

0:17:29.956 --> 0:17:33.836
<v Speaker 2>species of the gene was important. Another really important thing

0:17:33.956 --> 0:17:34.356
<v Speaker 2>was the foot.

0:17:34.556 --> 0:17:37.436
<v Speaker 1>So basically the versions of the gene exist in these

0:17:37.476 --> 0:17:39.316
<v Speaker 1>different animals, but they're slightly different.

0:17:39.516 --> 0:17:40.036
<v Speaker 3>Exactly.

0:17:40.316 --> 0:17:44.116
<v Speaker 1>Yes, I have to say retrospectively out of my armchair ignorance.

0:17:45.156 --> 0:17:49.236
<v Speaker 1>I feel like that one seems obvious in retrospect to me.

0:17:50.476 --> 0:17:53.596
<v Speaker 2>But it was strange to me because this bovine sequence

0:17:53.636 --> 0:17:54.796
<v Speaker 2>worked in a chicken, so.

0:17:54.956 --> 0:17:56.916
<v Speaker 1>I think, and a mouse and a person who's more

0:17:56.996 --> 0:18:02.436
<v Speaker 1>like a cow. Yes, okay, what's another one? What's another one?

0:18:02.476 --> 0:18:03.156
<v Speaker 1>You had to figure out?

0:18:03.316 --> 0:18:06.036
<v Speaker 2>Another one was the flavor of AAV that we needed

0:18:06.076 --> 0:18:06.396
<v Speaker 2>to use.

0:18:06.476 --> 0:18:09.316
<v Speaker 1>So the particular nature of the vector.

0:18:09.276 --> 0:18:10.076
<v Speaker 3>Yes, exactly.

0:18:10.156 --> 0:18:12.876
<v Speaker 2>So AV comes in a variety of flavors, and one

0:18:12.916 --> 0:18:15.716
<v Speaker 2>flavor of AV might be good at infecting neurons, and

0:18:15.756 --> 0:18:18.916
<v Speaker 2>another flavor of AV might be good at infecting skin cells,

0:18:18.956 --> 0:18:19.436
<v Speaker 2>for instance.

0:18:19.556 --> 0:18:23.396
<v Speaker 1>Yes, and interestingly, in this point, you want it to infect, right,

0:18:23.556 --> 0:18:26.996
<v Speaker 1>Infecting is delivering the gene exactly. Huh.

0:18:27.476 --> 0:18:30.636
<v Speaker 2>So we tested for the first time in non human

0:18:30.676 --> 0:18:34.956
<v Speaker 2>primates a certain flavor of AV called AAV five, and

0:18:35.236 --> 0:18:38.236
<v Speaker 2>we really for the first time showed that that flavor

0:18:38.236 --> 0:18:40.796
<v Speaker 2>of AV was really useful in the rod and the

0:18:40.836 --> 0:18:44.196
<v Speaker 2>cone foto receptors of the human of a primate retina rather,

0:18:44.676 --> 0:18:46.676
<v Speaker 2>so that was the flavor of AV that we needed

0:18:46.676 --> 0:18:48.276
<v Speaker 2>to figure out. And then I would say the third

0:18:48.316 --> 0:18:52.076
<v Speaker 2>thing that we figured out was a specific regulatory sequence

0:18:52.116 --> 0:18:55.716
<v Speaker 2>that we used to drive expression of the gene. So

0:18:55.916 --> 0:19:00.356
<v Speaker 2>it's called a promoter, and specifically it's the adoptin kinase promoter,

0:19:00.436 --> 0:19:03.276
<v Speaker 2>which drives expression exclusively in photo receptors.

0:19:03.476 --> 0:19:06.396
<v Speaker 1>And so just to be clear, just to unpack that

0:19:06.596 --> 0:19:10.036
<v Speaker 1>a little bit, so the idea is, you don't just

0:19:10.116 --> 0:19:15.356
<v Speaker 1>need to have the gene itself in this vector. You

0:19:15.436 --> 0:19:18.556
<v Speaker 1>need to have the genetic information that tells it in

0:19:18.636 --> 0:19:22.196
<v Speaker 1>what kinds of cells should this gene be expressed exactly,

0:19:22.236 --> 0:19:23.916
<v Speaker 1>and in what kinds of cells should it not be

0:19:23.956 --> 0:19:24.956
<v Speaker 1>expressed exactly.

0:19:24.996 --> 0:19:27.836
<v Speaker 2>And that's important from a safety standpoint, because ideally you

0:19:27.876 --> 0:19:31.196
<v Speaker 2>don't want this gene expressing a protein in cells where

0:19:31.196 --> 0:19:32.196
<v Speaker 2>it's not supposed to be.

0:19:32.276 --> 0:19:38.916
<v Speaker 1>In potent harm in your heart right exactly in a minute.

0:19:38.996 --> 0:19:41.996
<v Speaker 1>What happened when Shannon's drug finally made its way out

0:19:41.996 --> 0:19:54.796
<v Speaker 1>of the lab and into the eyes of patience. I

0:19:54.836 --> 0:19:57.676
<v Speaker 1>asked Shannon how she got from figuring everything out in

0:19:57.716 --> 0:20:01.516
<v Speaker 1>the lab and in animals to actually doing a clinical

0:20:01.556 --> 0:20:04.716
<v Speaker 1>trial to actually testing her drug in patience.

0:20:05.396 --> 0:20:09.156
<v Speaker 2>So I will say that, fortunately, before Santafie let the

0:20:09.196 --> 0:20:11.836
<v Speaker 2>program go, they did dose a couple of patients, so

0:20:11.876 --> 0:20:14.836
<v Speaker 2>we did get them to start the trial thankfully, and

0:20:14.916 --> 0:20:17.796
<v Speaker 2>they were absolutely critical and getting that off the ground.

0:20:18.436 --> 0:20:21.516
<v Speaker 2>But when they handed it back to at Sina, obviously

0:20:21.556 --> 0:20:24.876
<v Speaker 2>we had to build a clinical team and we worked

0:20:24.876 --> 0:20:27.476
<v Speaker 2>closely with Santa fe during that transition period to make

0:20:27.516 --> 0:20:30.276
<v Speaker 2>sure there were no bumps in the road, and then

0:20:30.796 --> 0:20:33.676
<v Speaker 2>we just continued with the trial. We had some amazing

0:20:33.676 --> 0:20:38.316
<v Speaker 2>clinical investigators at the University of Pennsylvania and OHSU, which

0:20:38.356 --> 0:20:42.116
<v Speaker 2>is Oregon Health Sciences University at the CACI Institute, and

0:20:42.156 --> 0:20:45.556
<v Speaker 2>so the surgeons there did the injections. We also had

0:20:45.596 --> 0:20:49.356
<v Speaker 2>a surgeon at Will's I Institute, and just excellent teams

0:20:49.396 --> 0:20:53.036
<v Speaker 2>of physicians focused on inherited retinal disease that we worked

0:20:53.036 --> 0:20:55.156
<v Speaker 2>closely with to monitor these patients over time.

0:20:55.956 --> 0:21:00.476
<v Speaker 1>So you have this virus that you have engineered to

0:21:00.596 --> 0:21:05.196
<v Speaker 1>have this gene and this promoter, you inject it into

0:21:05.716 --> 0:21:08.116
<v Speaker 1>the back of somebody's eye.

0:21:08.756 --> 0:21:13.876
<v Speaker 2>Then what happens, So the virus infects the photo receptors,

0:21:14.596 --> 0:21:18.716
<v Speaker 2>it unloads the DNA inside, and then that DNA remains

0:21:18.996 --> 0:21:22.636
<v Speaker 2>inside that cell over the lifetime of that living cell.

0:21:23.036 --> 0:21:26.876
<v Speaker 2>So the gene will persistently remain inside that cell and

0:21:26.956 --> 0:21:30.356
<v Speaker 2>express that protein that it needs to express. It does

0:21:30.396 --> 0:21:33.796
<v Speaker 2>not integrate into the genome. It remains outside the genome.

0:21:33.876 --> 0:21:37.356
<v Speaker 2>We call that episomal, but it leads to persistent expression

0:21:37.396 --> 0:21:40.476
<v Speaker 2>of that gene and continuous production of that therapeutic protein.

0:21:40.636 --> 0:21:44.476
<v Speaker 2>And when the cell dies that when the cell dies,

0:21:44.556 --> 0:21:47.516
<v Speaker 2>the gene dies with it. So in order for gene

0:21:47.516 --> 0:21:51.036
<v Speaker 2>therapy to be successful, those cells need to be retained.

0:21:51.196 --> 0:21:54.156
<v Speaker 2>If the cells degenerate, then that therapeutic effect can be lost.

0:21:54.596 --> 0:21:57.116
<v Speaker 1>And do cells Do those cells last forever?

0:21:57.716 --> 0:22:01.556
<v Speaker 2>It depends on the indication. So that's why LCA one

0:22:01.676 --> 0:22:04.556
<v Speaker 2>with such an attractive target is because those patients retain

0:22:04.596 --> 0:22:08.996
<v Speaker 2>their photoreceptor structure over their lifetime, So theoretically we could

0:22:09.156 --> 0:22:11.196
<v Speaker 2>at persistent rescue over their lifetime.

0:22:11.396 --> 0:22:14.756
<v Speaker 1>So photoreceptor celves just stay there, they develop, and then

0:22:14.796 --> 0:22:17.996
<v Speaker 1>they just hang out receiving photons forever.

0:22:18.276 --> 0:22:19.796
<v Speaker 3>Yes, in the syndication yep.

0:22:20.076 --> 0:22:22.716
<v Speaker 1>So like how many people are in this in this trial?

0:22:23.116 --> 0:22:23.636
<v Speaker 3>So we had.

0:22:23.556 --> 0:22:26.596
<v Speaker 2>Fifteen people total enrolled in this trial.

0:22:26.676 --> 0:22:30.716
<v Speaker 1>Okay, And how long does it take to find out

0:22:30.996 --> 0:22:31.636
<v Speaker 1>if it works?

0:22:32.316 --> 0:22:36.796
<v Speaker 2>So with this condition, typically we saw responses by about

0:22:37.076 --> 0:22:41.196
<v Speaker 2>four weeks post injection, and those responses get a little

0:22:41.236 --> 0:22:44.276
<v Speaker 2>bit better up until about two or three months post injection,

0:22:44.316 --> 0:22:46.596
<v Speaker 2>at which time the response is plateau. So it's a

0:22:46.716 --> 0:22:48.636
<v Speaker 2>very quick, very quick readout.

0:22:48.916 --> 0:22:52.796
<v Speaker 1>And the patients are they completely blind? Like what is

0:22:52.836 --> 0:22:55.716
<v Speaker 1>there before when they're coming to you? What is the

0:22:55.836 --> 0:22:56.876
<v Speaker 1>state of their vision?

0:22:57.196 --> 0:23:00.756
<v Speaker 2>That's a good question. So there's a range, but we

0:23:00.796 --> 0:23:04.396
<v Speaker 2>would consider all LCA one patients to be profoundly visually impaired,

0:23:04.476 --> 0:23:09.476
<v Speaker 2>so ranging from twenty two hundred all the way to

0:23:09.876 --> 0:23:14.716
<v Speaker 2>light perception only, so legally blind to folks that can

0:23:14.756 --> 0:23:15.636
<v Speaker 2>only see light.

0:23:16.476 --> 0:23:20.756
<v Speaker 1>And so when do you first hear about the results,

0:23:20.836 --> 0:23:22.556
<v Speaker 1>Like how do the results come into you?

0:23:23.596 --> 0:23:26.836
<v Speaker 2>Well, you have to be very careful as a you know,

0:23:27.316 --> 0:23:30.236
<v Speaker 2>co founder and CSO of a company, I you know,

0:23:30.436 --> 0:23:33.956
<v Speaker 2>don't have any direct interaction with the patients. That would

0:23:33.956 --> 0:23:35.876
<v Speaker 2>be it's kind of a conflict of interest, right, But

0:23:37.276 --> 0:23:40.116
<v Speaker 2>you know we do the data starts pouring in into

0:23:40.236 --> 0:23:42.516
<v Speaker 2>the you know, the software that we use to collect

0:23:42.516 --> 0:23:45.156
<v Speaker 2>that data as a company, and you start to see

0:23:45.276 --> 0:23:49.236
<v Speaker 2>the numbers, and on occasion, you know, a patient will

0:23:49.396 --> 0:23:52.956
<v Speaker 2>anecdotally tell the physician something and that physician will report

0:23:52.996 --> 0:23:56.436
<v Speaker 2>it back to the company, like wow, this this person

0:23:56.596 --> 0:23:58.836
<v Speaker 2>was able to see the lines and the crosswalk for

0:23:58.876 --> 0:24:03.396
<v Speaker 2>the first time outside last night. Or this woman was

0:24:03.476 --> 0:24:06.956
<v Speaker 2>really excited because this Halloween was the first time that

0:24:06.996 --> 0:24:09.636
<v Speaker 2>she could read the labels on her kids Halloween. So

0:24:09.676 --> 0:24:13.396
<v Speaker 2>you hear, you hear little stories like that, and it's

0:24:13.476 --> 0:24:16.396
<v Speaker 2>like they make you cry, right, Like you just can't

0:24:16.396 --> 0:24:19.396
<v Speaker 2>believe that it's happening. It's one thing to see a

0:24:19.436 --> 0:24:22.556
<v Speaker 2>mouse regain vision and be able to, you know, swim

0:24:22.596 --> 0:24:25.476
<v Speaker 2>through a maze. But to hear that a patient can

0:24:25.516 --> 0:24:28.236
<v Speaker 2>read something for the first time or navigate outside their

0:24:28.236 --> 0:24:30.116
<v Speaker 2>home for the first time, that's something else.

0:24:30.956 --> 0:24:33.236
<v Speaker 1>Yeah, So you're not spending your career trying to cure

0:24:33.236 --> 0:24:34.156
<v Speaker 1>blindness in mice.

0:24:34.316 --> 0:24:36.676
<v Speaker 3>Nope, Nope.

0:24:36.916 --> 0:24:39.836
<v Speaker 1>So what was the outcome of that trial?

0:24:40.596 --> 0:24:43.676
<v Speaker 2>Sure, so it was a very positive outcome. We just

0:24:43.716 --> 0:24:46.476
<v Speaker 2>published the results in the Lancet a few weeks ago,

0:24:46.916 --> 0:24:49.796
<v Speaker 2>looking at all all fifteen of the Phase one two

0:24:49.956 --> 0:24:52.916
<v Speaker 2>patients out to one year post treatment, and we showed

0:24:52.916 --> 0:24:56.116
<v Speaker 2>that the gene therapy had a very very good safety profile.

0:24:56.236 --> 0:24:59.636
<v Speaker 2>There were no you know, serious adverse events related to

0:24:59.676 --> 0:25:04.156
<v Speaker 2>the medicine itself, and we showed a very profound efficacy.

0:25:04.276 --> 0:25:08.516
<v Speaker 2>So we used a test called FST, which is just

0:25:08.556 --> 0:25:11.836
<v Speaker 2>a measure of retinal sensitivity, and we saw, for instance,

0:25:11.836 --> 0:25:15.436
<v Speaker 2>in one patient there was a ten thousandfold improvement in

0:25:15.476 --> 0:25:18.676
<v Speaker 2>retinal sensitivity. And what that means is it's akin to

0:25:18.676 --> 0:25:24.476
<v Speaker 2>someone being able to navigate under bright sunlight versus someone

0:25:24.516 --> 0:25:27.676
<v Speaker 2>being able to navigate in the light of the full moon.

0:25:28.116 --> 0:25:30.836
<v Speaker 2>So a huge improvement in retinal sensitivity.

0:25:30.876 --> 0:25:33.236
<v Speaker 1>And what is there like a median improvement.

0:25:33.516 --> 0:25:37.036
<v Speaker 2>Yeah, so the median improvement was about one hundredfold improvement,

0:25:37.476 --> 0:25:40.556
<v Speaker 2>so really exciting and significant. And then you know, of

0:25:40.556 --> 0:25:43.556
<v Speaker 2>course the anecdotes come in. We have one video of

0:25:43.596 --> 0:25:46.076
<v Speaker 2>a little girl who saw snowflakes for the first time,

0:25:46.916 --> 0:25:49.596
<v Speaker 2>so you know, it's more than the cold hard numbers

0:25:49.676 --> 0:25:53.196
<v Speaker 2>like one hundredfold improvement in retal sensitivity. It's you're seeing

0:25:53.556 --> 0:25:56.356
<v Speaker 2>a genuine improvement in the patient's quality of life, which

0:25:56.396 --> 0:25:56.956
<v Speaker 2>is amazing.

0:25:58.556 --> 0:25:59.836
<v Speaker 1>So what's next?

0:26:00.676 --> 0:26:04.476
<v Speaker 2>So next will be phase three. Before you can get

0:26:04.516 --> 0:26:06.956
<v Speaker 2>anything commercialized for broader use, you have to do a

0:26:06.956 --> 0:26:10.516
<v Speaker 2>phase three trial. So we're fortunate because our LCA one

0:26:10.556 --> 0:26:13.756
<v Speaker 2>program has received what's called an ARMAT designation, and put simply,

0:26:13.876 --> 0:26:17.836
<v Speaker 2>that is a designation given to programs that cause a

0:26:17.876 --> 0:26:22.596
<v Speaker 2>profound illness at birth and for which you have promising

0:26:22.636 --> 0:26:24.796
<v Speaker 2>proof of concept data showing that you might have a cure.

0:26:24.916 --> 0:26:27.796
<v Speaker 2>So we receive that designation and we need to align

0:26:27.996 --> 0:26:30.596
<v Speaker 2>on a path forward with the FDA. So, in other words,

0:26:30.636 --> 0:26:32.836
<v Speaker 2>what does our phase three trial design need to be?

0:26:33.276 --> 0:26:35.876
<v Speaker 2>And once we decide on that, then we will execute

0:26:35.876 --> 0:26:38.836
<v Speaker 2>that Phase three trial and then hopefully after that we'll

0:26:38.836 --> 0:26:42.516
<v Speaker 2>seek approval from the FDA to commercialize it for broader

0:26:42.556 --> 0:26:43.476
<v Speaker 2>patient access.

0:26:44.516 --> 0:26:48.796
<v Speaker 1>How many people more or less have LCA one.

0:26:49.516 --> 0:26:52.316
<v Speaker 2>So there's about three thousand patients I would say in

0:26:52.356 --> 0:26:55.636
<v Speaker 2>the US and the EU that have they indication.

0:26:56.156 --> 0:26:58.956
<v Speaker 1>So I mean a lot on a human level, but

0:26:59.036 --> 0:27:01.796
<v Speaker 1>on a kind of population level, not a lot. It's

0:27:01.916 --> 0:27:07.476
<v Speaker 1>very rare, that's correct. And so what does that mean? Well,

0:27:07.476 --> 0:27:09.076
<v Speaker 1>what does that mean. I guess on the on the

0:27:09.236 --> 0:27:11.036
<v Speaker 1>business side. Right on the science side, it sort of

0:27:11.076 --> 0:27:13.756
<v Speaker 1>doesn't matter. It's the same science whether a million people

0:27:13.796 --> 0:27:15.996
<v Speaker 1>have it or people have it. But what does it

0:27:16.036 --> 0:27:17.836
<v Speaker 1>mean on the business side.

0:27:17.556 --> 0:27:20.916
<v Speaker 2>It's you know, the pendulum has swung back since the

0:27:21.476 --> 0:27:24.916
<v Speaker 2>early two thousands where investors in big pharma were all

0:27:25.036 --> 0:27:29.196
<v Speaker 2>very eager to throw money into this space, and they're

0:27:29.276 --> 0:27:33.676
<v Speaker 2>less excited about rare disease obviously, But you know, as

0:27:33.676 --> 0:27:37.316
<v Speaker 2>a scientist who sees the obvious impact it's having on

0:27:37.356 --> 0:27:41.436
<v Speaker 2>these patients, I'm going to push it forward with full force.

0:27:41.796 --> 0:27:45.236
<v Speaker 2>We've successfully raised money at SENA to keep this program going.

0:27:45.756 --> 0:27:48.396
<v Speaker 2>We have plans for it moving forward, and I think

0:27:48.516 --> 0:27:52.596
<v Speaker 2>our ability to continue to raise money is increased or

0:27:52.796 --> 0:27:55.516
<v Speaker 2>strengthened by the fact that we have other ongoing clinical

0:27:55.556 --> 0:27:58.356
<v Speaker 2>programs that are also showing success. So you know, if

0:27:58.396 --> 0:28:00.556
<v Speaker 2>you have one rare disease that you have in clinic,

0:28:00.636 --> 0:28:03.716
<v Speaker 2>you might be only quasi interesting to investors are big pharma.

0:28:03.716 --> 0:28:05.396
<v Speaker 2>But we have a bunch of things going on at

0:28:05.476 --> 0:28:07.636
<v Speaker 2>SENA that I think will improve the chances that this

0:28:07.676 --> 0:28:08.636
<v Speaker 2>program is forward.

0:28:09.116 --> 0:28:10.036
<v Speaker 1>What else are you working on?

0:28:10.716 --> 0:28:14.436
<v Speaker 2>So we are working actively on another inherited retinal disease

0:28:14.516 --> 0:28:18.276
<v Speaker 2>called X linked retinoskeesis or XLRS. We're also in a

0:28:18.316 --> 0:28:22.436
<v Speaker 2>phase one two clinical trial and already showing structural and

0:28:22.436 --> 0:28:27.116
<v Speaker 2>functional improvements in those patients using a novel flavor of AV,

0:28:27.316 --> 0:28:30.636
<v Speaker 2>which has been interesting. So really excited.

0:28:31.196 --> 0:28:35.796
<v Speaker 1>So you have a separate indication where you're in clinical trials, yep,

0:28:37.476 --> 0:28:40.676
<v Speaker 1>and anything else. I feel like remember seeing a couple

0:28:40.756 --> 0:28:42.356
<v Speaker 1>more on the website.

0:28:41.876 --> 0:28:43.076
<v Speaker 3>Now, yeah, else.

0:28:43.236 --> 0:28:43.396
<v Speaker 1>Yeah.

0:28:43.436 --> 0:28:46.756
<v Speaker 2>So we're also working on a dual vector technology. So

0:28:47.076 --> 0:28:50.476
<v Speaker 2>there are some indications caused by mutations in large genes

0:28:50.476 --> 0:28:53.956
<v Speaker 2>that don't fit inside a standard AAV vector. So we've

0:28:53.996 --> 0:28:57.516
<v Speaker 2>developed a technology wherein we split that large gene in half.

0:28:57.796 --> 0:29:00.436
<v Speaker 2>We deliver the front half via one AAV in the

0:29:00.476 --> 0:29:02.156
<v Speaker 2>back half via a second AV.

0:29:02.716 --> 0:29:04.676
<v Speaker 3>Those two. Yeah, it's really cool.

0:29:05.636 --> 0:29:08.236
<v Speaker 1>Say one gene, it's one gene and you're putting it

0:29:08.276 --> 0:29:11.076
<v Speaker 1>into two different yes suitcases.

0:29:10.516 --> 0:29:12.316
<v Speaker 3>That's very sically Yeah, and.

0:29:12.276 --> 0:29:14.796
<v Speaker 1>Then dumb question, how does it get put back together?

0:29:15.676 --> 0:29:19.876
<v Speaker 2>So there's a complimentary sequence shared between the front and

0:29:19.916 --> 0:29:24.156
<v Speaker 2>the back half. So when the two suitcases unpack their

0:29:24.316 --> 0:29:27.316
<v Speaker 2>their respective front and back half genes, they find each

0:29:27.356 --> 0:29:30.556
<v Speaker 2>other via that complementary sequence and then they recombine to

0:29:30.636 --> 0:29:31.996
<v Speaker 2>form a full length gene.

0:29:32.036 --> 0:29:35.596
<v Speaker 1>That is wild. Have people done that technique in other

0:29:36.956 --> 0:29:40.516
<v Speaker 1>other you know, indications of gene therapy and other domains

0:29:40.556 --> 0:29:40.956
<v Speaker 1>they have.

0:29:41.116 --> 0:29:44.636
<v Speaker 2>Yes, there's a company recently that it is in the

0:29:44.636 --> 0:29:47.916
<v Speaker 2>hearing space actually, but they use dual vectors to deliver

0:29:48.516 --> 0:29:51.796
<v Speaker 2>a certain gene to patients that had hearing loss and

0:29:52.116 --> 0:29:53.676
<v Speaker 2>restored hearing to these children.

0:29:53.916 --> 0:29:57.156
<v Speaker 1>So, and is the issue the gene is just too long,

0:29:57.236 --> 0:30:00.436
<v Speaker 1>like it physically just doesn't fit inside. That's correct.

0:30:00.956 --> 0:30:03.876
<v Speaker 2>Yeah, So standard AV can only fit about five thousand

0:30:03.876 --> 0:30:06.676
<v Speaker 2>base pairs of DNA, and some of these genes are

0:30:06.756 --> 0:30:08.156
<v Speaker 2>are just too big to fit.

0:30:09.236 --> 0:30:11.836
<v Speaker 1>That is so clever. I love it when people are

0:30:11.876 --> 0:30:17.236
<v Speaker 1>so clever. So let's let's zoom out. And you know,

0:30:17.396 --> 0:30:22.956
<v Speaker 1>you've been working on gene therapy for twenty years ish,

0:30:23.396 --> 0:30:26.716
<v Speaker 1>which is close to the life of gene therapy. Right

0:30:26.756 --> 0:30:28.436
<v Speaker 1>of the field you got in or early, you've been

0:30:28.436 --> 0:30:31.196
<v Speaker 1>there a long time. A lot has happened. Like when

0:30:31.236 --> 0:30:35.436
<v Speaker 1>you zoom out, what do you see? Like where is

0:30:35.476 --> 0:30:38.116
<v Speaker 1>the field now? You know? Yeah, where is it now?

0:30:38.196 --> 0:30:40.356
<v Speaker 1>What's the big picture for gene therapy right now?

0:30:40.756 --> 0:30:43.516
<v Speaker 2>I think the big picture for gene therapy right now

0:30:43.676 --> 0:30:46.516
<v Speaker 2>is we're a little bit bruised, right. You know, we

0:30:46.596 --> 0:30:50.516
<v Speaker 2>have the success of Luxterna getting approved. Then you know

0:30:50.556 --> 0:30:54.236
<v Speaker 2>you've got zulgensimo, which is a huge success story. And

0:30:54.276 --> 0:30:58.316
<v Speaker 2>those were the successes. But we entered a period around

0:30:58.396 --> 0:31:01.556
<v Speaker 2>that same time where I think, unfortunately, folks were taking

0:31:01.556 --> 0:31:03.956
<v Speaker 2>a one size fits all approach to gene therapy. In

0:31:03.996 --> 0:31:06.556
<v Speaker 2>other words, like, Okay, if this flavor of av or

0:31:06.596 --> 0:31:10.436
<v Speaker 2>this regulatory region or this dose worked for lucerna, then

0:31:10.436 --> 0:31:13.276
<v Speaker 2>it's going to work for this other indication, right, And

0:31:13.836 --> 0:31:17.236
<v Speaker 2>I think that hasn't That hasn't played out right. It's

0:31:17.276 --> 0:31:20.356
<v Speaker 2>not a one size fits all approach. Every indication needs

0:31:20.756 --> 0:31:24.156
<v Speaker 2>a treatment tailored to that indication. What cell type is impacted,

0:31:25.236 --> 0:31:28.076
<v Speaker 2>you know, does the gene expression need to be restricted,

0:31:28.436 --> 0:31:31.076
<v Speaker 2>what dose needs to be used, what's the underlying immune

0:31:31.116 --> 0:31:34.196
<v Speaker 2>status of that patient's retina for instance. So it's not

0:31:34.276 --> 0:31:36.356
<v Speaker 2>a one size fits all approach, and I think I

0:31:36.356 --> 0:31:38.116
<v Speaker 2>think people have realized that.

0:31:38.636 --> 0:31:40.396
<v Speaker 1>So like, so does that mean it's going to be

0:31:40.516 --> 0:31:43.956
<v Speaker 1>hard every time? I mean it's going to be hard forever,

0:31:44.076 --> 0:31:46.316
<v Speaker 1>And it's not like great, we figured it out and

0:31:46.356 --> 0:31:49.116
<v Speaker 1>we can just put any gene into this vector and

0:31:49.596 --> 0:31:50.636
<v Speaker 1>will cure everything.

0:31:51.156 --> 0:31:53.596
<v Speaker 2>Yeah, I mean I think it's somewhere in the middle, right,

0:31:53.636 --> 0:31:56.436
<v Speaker 2>It's it's it's never going to be like just plug

0:31:56.476 --> 0:31:59.436
<v Speaker 2>and play, right, But there are certainly tools that are

0:31:59.436 --> 0:32:02.716
<v Speaker 2>being developed along the way that can be you know,

0:32:02.836 --> 0:32:05.116
<v Speaker 2>used in one trial and used in another trial. But

0:32:05.836 --> 0:32:07.236
<v Speaker 2>I think you always have to put a lot of

0:32:07.316 --> 0:32:09.796
<v Speaker 2>thought into it. It can't just simply be Okay, if

0:32:09.796 --> 0:32:12.236
<v Speaker 2>this worked for l c A two, then it's going

0:32:12.316 --> 0:32:15.596
<v Speaker 2>to work for disease X, right. There always has to

0:32:15.636 --> 0:32:16.756
<v Speaker 2>be a thoughtful process.

0:32:17.916 --> 0:32:19.796
<v Speaker 1>I mean, is it harder than you thought it was

0:32:19.836 --> 0:32:20.196
<v Speaker 1>going to be?

0:32:23.276 --> 0:32:23.516
<v Speaker 3>Yes?

0:32:24.836 --> 0:32:27.916
<v Speaker 2>You know, in my grad school days it was hope, hope, hope,

0:32:27.996 --> 0:32:32.396
<v Speaker 2>you know, excitement, excitement, excitement, and then forming my own

0:32:32.436 --> 0:32:35.196
<v Speaker 2>company and being in charge of kind of the fundraising

0:32:35.276 --> 0:32:38.916
<v Speaker 2>behind keeping these programs going. It's been it's been a

0:32:38.956 --> 0:32:42.316
<v Speaker 2>lot of work, but I believe strongly in what I

0:32:42.356 --> 0:32:45.036
<v Speaker 2>do and that it's having a positive impact on patient lives,

0:32:45.076 --> 0:32:46.756
<v Speaker 2>and so it's it's worth that effort.

0:32:50.516 --> 0:32:52.596
<v Speaker 1>We'll be back in a minute with the lightning round.

0:32:54.356 --> 0:33:06.156
<v Speaker 1>M hm hm. Let's finish with the lightning round. Okay,

0:33:08.276 --> 0:33:13.836
<v Speaker 1>what's the best thing about working with your husband.

0:33:13.396 --> 0:33:16.796
<v Speaker 2>Oh, let's see. I think that at the end of

0:33:16.796 --> 0:33:20.556
<v Speaker 2>the day, we can understand each other's stresses. You know,

0:33:20.636 --> 0:33:23.676
<v Speaker 2>It's not like coming home and you know he has

0:33:23.676 --> 0:33:25.556
<v Speaker 2>no idea what I'm talking about. It's like, if I

0:33:25.596 --> 0:33:28.676
<v Speaker 2>have a problem, he can think through it very clearly

0:33:28.756 --> 0:33:32.076
<v Speaker 2>because he understands it at its core and give me

0:33:32.116 --> 0:33:35.796
<v Speaker 2>advice on how to navigate the situation and vice versa.

0:33:36.196 --> 0:33:38.156
<v Speaker 1>What's the worst thing about working with your husband?

0:33:41.516 --> 0:33:44.676
<v Speaker 2>Sometimes there's you know, evenings where I'm done talking about

0:33:44.676 --> 0:33:46.636
<v Speaker 2>a vy. You know, I've done it all day long,

0:33:47.196 --> 0:33:49.756
<v Speaker 2>and we're sitting over the dinner table with our kids

0:33:49.756 --> 0:33:52.476
<v Speaker 2>and he's still talking about, you know, designing a vector

0:33:52.476 --> 0:33:54.276
<v Speaker 2>to do whatever, and I'm like, Okay, we're done here,

0:33:54.356 --> 0:33:57.316
<v Speaker 2>We're done for the night. But I mean it's with

0:33:57.396 --> 0:33:59.076
<v Speaker 2>us all the time, and I think that's what makes

0:33:59.116 --> 0:34:00.636
<v Speaker 2>us better scientists for it.

0:34:02.436 --> 0:34:06.196
<v Speaker 1>What's one interesting or surprising thing you've learned about the

0:34:06.276 --> 0:34:07.076
<v Speaker 1>human eye?

0:34:08.436 --> 0:34:12.276
<v Speaker 2>The human eye, I would say most of all that

0:34:13.356 --> 0:34:17.356
<v Speaker 2>you can be seventy years old and have had a

0:34:17.516 --> 0:34:20.836
<v Speaker 2>congenital form of blindness since you were a baby and

0:34:20.916 --> 0:34:24.476
<v Speaker 2>still benefit from gene therapy. And that's wild to me, Like,

0:34:24.796 --> 0:34:26.676
<v Speaker 2>you know, I got my PhD and neuroscience, so I'm

0:34:26.676 --> 0:34:29.756
<v Speaker 2>always thinking about you know, so what if we restore

0:34:29.796 --> 0:34:31.596
<v Speaker 2>function to the retina, what's that going to mean in

0:34:31.636 --> 0:34:33.676
<v Speaker 2>the brain? Is the brain going to be able to

0:34:33.796 --> 0:34:36.476
<v Speaker 2>be receptive to that message if it's been turned off

0:34:36.516 --> 0:34:39.436
<v Speaker 2>from that message input its entire life?

0:34:39.516 --> 0:34:39.716
<v Speaker 3>Right?

0:34:40.436 --> 0:34:42.476
<v Speaker 2>But we had a seventy year old patient in our

0:34:42.676 --> 0:34:46.396
<v Speaker 2>LCA one clinical trial that showed some benefit following gene therapy,

0:34:46.396 --> 0:34:48.996
<v Speaker 2>and that tells me that the brain is, you know,

0:34:49.156 --> 0:34:53.076
<v Speaker 2>extremely plastic, more plastic than I gave it credit for before.

0:34:53.676 --> 0:34:56.236
<v Speaker 1>Huh, So it's not the eye but the brain. Like

0:34:56.236 --> 0:34:59.036
<v Speaker 1>we're not really seeing with our eye. Our eye is

0:34:59.076 --> 0:35:01.396
<v Speaker 1>just like the window and the brain is really where

0:35:01.436 --> 0:35:02.396
<v Speaker 1>the seeing is happening.

0:35:02.436 --> 0:35:02.836
<v Speaker 3>That's right.

0:35:04.836 --> 0:35:06.996
<v Speaker 1>I read that you have a boat called wet Lab

0:35:07.636 --> 0:35:13.076
<v Speaker 1>we do. H What was the runner up name? Oh?

0:35:13.116 --> 0:35:16.036
<v Speaker 2>I don't think we had a runner up. We've planned

0:35:16.076 --> 0:35:17.076
<v Speaker 2>that one for years.

0:35:20.556 --> 0:35:23.116
<v Speaker 1>What's the biggest fish you ever caught? Oh?

0:35:23.156 --> 0:35:26.996
<v Speaker 2>My goodness. We go all the time and we catch

0:35:27.036 --> 0:35:29.436
<v Speaker 2>big fish so often. I don't remember the biggest one

0:35:29.636 --> 0:35:30.236
<v Speaker 2>that you catch.

0:35:30.316 --> 0:35:36.636
<v Speaker 1>So many big things to tell a first story. Thank

0:35:36.676 --> 0:35:39.316
<v Speaker 1>you so much, for your time. It was very interesting

0:35:39.356 --> 0:35:40.156
<v Speaker 1>to talk to you. I learned.

0:35:40.396 --> 0:35:42.636
<v Speaker 2>Thank you, Thank you. You're a great interviewer. This was

0:35:42.676 --> 0:35:43.156
<v Speaker 2>a pleasure.

0:35:46.476 --> 0:35:49.396
<v Speaker 1>Jennon boy is a professor of genetics at the University

0:35:49.396 --> 0:35:52.436
<v Speaker 1>of Florida and the co founder and chief scientific officer

0:35:52.516 --> 0:35:56.116
<v Speaker 1>of Atsina Therapeutics. Just a quick note, the show is

0:35:56.156 --> 0:35:58.876
<v Speaker 1>going to take a break. We'll be back with new

0:35:58.916 --> 0:36:01.676
<v Speaker 1>episodes in a couple of weeks. In the meantime, please

0:36:01.756 --> 0:36:03.956
<v Speaker 1>let us know who you'd like to hear on the show,

0:36:04.356 --> 0:36:06.556
<v Speaker 1>who I should interview, were, just how we can make

0:36:06.556 --> 0:36:10.156
<v Speaker 1>the show better. You can email us at at pushkin

0:36:10.276 --> 0:36:14.836
<v Speaker 1>dot fm. Today's show was produced by Gabriel Hunter Chang.

0:36:15.116 --> 0:36:18.476
<v Speaker 1>It was edited by Lyddy Jean Kott and engineered by

0:36:18.516 --> 0:36:22.076
<v Speaker 1>Sarah Buguer. You can email us at Problem at pushkin

0:36:22.156 --> 0:36:25.356
<v Speaker 1>dot fm. I'm Jacob Goldstein and we'll be back next

0:36:25.356 --> 0:36:35.556
<v Speaker 1>week with another episode of What's Your Problem.