Marc Tessier-Lavigne

speaker

407 appearances 1 recordings 1 series first heard Mar 2026 last heard 12 Mar

Marc Tessier-Lavigne’s voice in public audio — every appearance, attributed to the second.

Trend

recordings per month · last 12 months

Recordings per month over the last 12 months — 1 in all, peaking in Mar 2026 with 1.

Appearances

newest first · ▶ plays the moment

Vanguards of Healthcare by Bloomberg Intelligence · Xaira’s War on Trial-and-Error Drug Development · 12 Mar 2026 podcast

But much more value is derived, will be derived by generating data sets where you have, you know, thousands upon thousands of antibody structures and ideally closely related.

And you see which ones work, which ones bind with high affinity and which ones don't.

That's the kind of data that the model will learn best from.

So your point is correct that there's a paucity of negative data out there, but we can definitely make advances with just positive data.

You know, AlphaFold was trained on the protein data bank, and there was enough richness of interactions there, and I should say cleverness of the DeepMind team, that they were able to extract the information or train the AI to predict the structures of most proteins.

So it is, one can certainly make advances based just on positive data, but there's no question that one can make further advances and perhaps more rapid advances by having data, both the positive and the negative data.

Well, thank you.

Well, let's start.

And I'm glad that you asked the question the way you did about, you know, the 12 years of making drugs.

Because I think what we should do is set ourselves a goal that is...

Highly aspirational, but also realistic, something that we could achieve.

I would like to see us, and currently the data takes about 12 years, actually 13 years on average to make a drug.

That's five years to go from target to making a drug that enters clinical trials.

And then on average, eight years to conduct the clinical trials and get FDA approval.

So total of 13 years.

And 90%, depending on the statistics that you look at, 90% to 95% of the drugs that enter clinical trials will fail and not make it over the finish line.

Which let's put in terms of the success rate there, let's say 10% of the drugs that enter clinical trials will make it over the finish line.

I think we should set a goal for ourselves of by over the next decade, reducing the time from target to FDA approval in half, six and a half years, and multiply the success rate from 10% on average to something realistic that would make a huge difference would be 30%, 30 to 40%.

I'd love it to be 50%, but even a 30% success rate would...

make a huge difference.

Showing 321–340 of 407 · page 17 of 21