We're trying to create rewards for getting to proof-of-concept in the franchise or therapeutic area, and not just have a molecule
go into man. Peter Kim, our president of research, has talked about rewards for failing fast—for making a no-go as early as
possible based on biomarkers. We're also trying to share with people how expensive it is to delay making those early decisions.
The understanding is, We can do a lot more without spending a lot more.
How far along are you are in the overall process of implementing this across your entire R&D?
We're off to a great start. We launched in 2006. We now have 40 individuals in the group, including physician scientists for
every therapeutic area, and we have managed to become very well integrated into the fabric of the organization. We've recruited
individuals who are really passionate about translational science and about collaboration—the two pillars of this approach.
And we have had some successes in terms of clinical studies that will give Merck the opportunity to make decisions earlier.
We still have to see whether those will play out in development.
You've had some success with diabetes, your test case. There must be a lot of activity there now.
Diabetes is an important focus for Merck. The use of experimental medicine has been very well integrated into our thinking.
And there are other areas, mostly internal-based medicine, where the markers and tools are fairly proximal. They are there,
and it's just a matter of using them. The cultural challenge is having scientists who were used to working for years and years
on a program, now having to be able, maybe after a single dose, to say, "This doesn't appear to be working; let's stop. Let's
work on something else."
And on the other side, in late-stage development, people are trained to think about using traditional clinical endpoints—symptom
scores; global quality of life; or surrogates accepted by the FDA, like blood pressure or hemoglobin A—and now we will make
decisions using a biomarker. A pharmacological challenge requires some getting used to when it doesn't feel as certain as
those other approaches. But we're getting there.
With scientists you're really challenging a deeply held value in the tradition of proof. Yet you're asking them to trust—or
trust and validate.
Validation is a very high bar. That means you've proven that your early measure predicts outcomes. Very few things are truly
validated. We use the term qualify. And that means we've got evidence that gives us confidence and a reasonable early read on what's happening with the biology.
We also are asking, Why do you think this is going to work in the first place? What is your hypothesis based on what you know
about the biology and what you saw in your preclinical work? Let's corroborate the hypothesis in humans. Then let's plan to
turn this into a drug. People gravitate a little more to that, because that corresponds to their instincts to do good science.
We get traction there.
I think, too, that when people become aware of the consequences of not making these early decisions on our mission, they start
to have the courage to change their thinking.
Since you're putting experimental compounds into human bodies in a different way, are there different safety concerns in this
The requirements for safety and monitoring in this model are no different from the old ones. We are complementing traditional
approaches by getting additional information early so that we can get some insight about the biology. It still goes through
all the rigorous toxicology that any other small molecule or biologic would go through. We still do monitoring in patients
very, very carefully in the early stages. And if we see a positive outcome through an experimental endpoint, we still then
do all the traditional approaches. So we're not lowering the safety bar. We're getting additional information early.
Does this process change the kind of information you're providing FDA for drug approval?