Marc Tessier-Lavigne

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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.

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

And then a third key step is to actually match the drug and the target to the right patients.

You can have the best drug in the world against the best target.

If you go into clinical trials and give it to the wrong patients who aren't going to benefit, then you will fail.

In fact, a lot of the failure in drug discovery occurs at that stage, where you might have a pretty good drug against a good target, but you don't know who the patients are who are responding.

So those three steps—choosing the right target, making the right drug, and matching to the right patients—

Currently, our industry really approaches this as an artisanal process.

A lot of science, of course, at each stage, but a lot of empiricism, trial and error, a lot of art.

People talk about intuition in making the drugs.

And as a result, there's very high failure rates, very long timelines, and very great expense.

Currently, to go from choosing molecular target to having an FDA-approved drug on average takes about 12 years.

So, and 90% of the drugs that enter clinical trials fail.

And that is a broken process that we have to improve.

At the highest level, the promise of AI is that with the right kinds of data in the right amounts, we should be able to transform each of those three steps so that much more of the work can be done in silico on the computer with higher success rates, lower attrition, shorter timelines, lower expense.

So that's the vision for the industry as a whole.

So when we look at how AI is being applied to this process and what the different companies are doing, we are actually focused on all three steps.

I'll tell you how.

Many companies are focused on one or other of those steps.

And I haven't even mentioned a fourth application of AI.

So there's AI applied to choosing targets, AI applied to making drugs, AI applied to patient stratification, identifying the right patients to treat with the drug.

There's a fourth step, which I won't talk about because we're not focused on that ourselves, which is just using AI to improve logistics and operations.

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