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While at the 2014 NYBIO conference, Dr. Sam Waksal from Kadmon had the opportunity to address the audience regarding the state of the biopharmaceutical industry.
While at the 2014 NYBIO conference, Dr. Sam Waksal from Kadmon had the opportunity to address the audience regarding the state of the biopharmaceutical industry. Below are Dr. Waksal’s perspectives on the need for innovation in the industry.
I always tell everyone the human memory evolved to predict the future; Bob Easton does not make videotapes in his mind to remember the night that he first did something. The reason for it is to predict the future, that’s why we have memory. We’re supposed to use all of the things we learned to be imaginative, to be innovative, and to get an idea of doing something that no one else has ever done. We have to get inside of molecules and our dreams to understand what they’re going to look like sometime in the future.
When a big pharmaceutical company acquires another, there’s a very good chance that things change, and when they do, it does not necessarily end up in a positive way for the future of science; when it happens, worlds change, but it doesn’t necessarily create, for those of us who believe in imagination and innovation, something good.
In about 30 years, nearly a third of Americans will have Alzheimer’s and the rest of us will be taking care of these patients. That will bankrupt America unless we do something, from the discovery point of view, to change that. Imagination is critical; it is going to be a young scientist at Rockefeller or Kadmon or somewhere, who’s going to come up with an idea that’s very risky because it’s risky to do that science, it’s risky to do the clinical trials and it’s risky to push forward that sort of development, but, when one tries to have a vision about what the world is going to look like, it’s going to be amazing when you are done. So, 30 years from now if someone has Alzheimer’s or is going to get it, we will be able to diagnose and cure it, and we won’t bankrupt society, neither here nor anywhere else in the world.
In the world of biotech, Genentech started in 1976, and it started because in 1975, graduate students at Stan Cohen’s lab at Stanford, and Herb Boyer’s lab at UCSF did a little experiment, where they did gene splicing (recombinant DNA) and it changed the world. Very interestingly, Herb Boyer and Robert Swanson, a venture capitalist, met at a bar in San Francisco, founded Genentech, and it changed the world. The guys at UCSF and Stanford went to their patent and licensing offices, they filed patents on recombinant DNA and the millions came in to Stanford and UCSF. Recombinant DNA tools and monoclonal antibodies are used by everyone now—not just biotech companies, Merck, Pfizer, Lilly, all of them use recombinant DNA molecular biological techniques and monoclonal antibodies, and yet they don’t necessarily innovate—that involves an entirely different set of tools—rare ones at that.
It’s not only about the science, but also much more than that, it’s about understanding while there is risk, there is the imagination, and when you use that properly, you can change the world, and that’s what imagination is for, and it isn’t often done in any industries, biotech included, but, when we do it and we do it correctly, it’s a big deal. For what we put in as human beings, as scientists, the output is infinite; it's limitless because if you use imagination correctly the sky’s the limit.
We live in a world right now when we talk about reimbursement, and reimbursement still plays a game with the biotech industry. The traditional method of reimbursement is not going to last much longer. Very soon, unless we can give real metrics to payers and make patients, payers and physicians feel that what we’re doing is really worth something, we’re not going to get reimbursed for it. We can change that.
Back in 1993, George Rathman and I were on a panel at a CEO conference, and it was during Hillary Care; Hillary Care didn’t change the world, everyone thought it would but it didn’t. People at the time were scared, Merck bought Medco because people were scared. But at the time, molecules were beginning to change things and George very nicely talked about his metrics, and he showed that when he looked at giving patients a very expensive molecule, Epogen, to bring back their red blood cells, the patients went back to work. Patients didn’t need transfusions, they didn’t have side effects associated with transfusions, how the drug saved the country money, people paid their taxes, kept them out of hospitals, and changed quality-of-life. There were metrics associated with that, and we certainly can do that right now. We’re all going to have to.
The metrics associated with innovation now are great, and if you do it correctly, you get paid for it and if we keep patient alive for years, and keep them at work, then things are easily worth whatever we charge for them. In the past, we experienced a pay-in and pay-out system; when a new drug came out, you would charge whatever for it; it was that easy. What is happening now is, we live in a world, where Germany and France don’t even put things on formulary unless there is a reason for having it there because of outcomes.
Big data is like having a large telephone book full of numbers with no names; great data but we have no idea what it meant and most of the time we still don’t. So, big data becomes data and there still is that moment that is critical in a morass of information: identifying what is important.
For example, during the days of early development of antibodies for cancer treatment, I thought I really got it; I knew there was a receptor, an ‘on switch,’ the switch that goes on in the cancer and makes it grow. We found a way to shut that switch off. I thought, done, that was just going to change all of it. Well, I was wrong. I wasn’t wrong about the ‘on switch,’ but I didn’t have all the information to understand that, like a train going down a track, a switch was like going down another track and there are other ‘on signals’ and cancer cells are the perfect sort of cells to try to use multiple pathways to escape every regulatory signal in the body.
Now we have to look at things differently. We use all of this morass of data to drive decisions. At Kadmon, we have a very cool drug in HER-2 positive breast cancer, it hits multiple ‘on switches’ and shuts them off. This is not only important in moving the cancer cell replicated pathway, but it also has an effect on where it goes in the brain, when it metastasizes, and how it escapes and becomes resistant. We’re making new generations of molecules to really try to, in a sea change fashion, to beat these diseases that are still killing people. Big data becomes very important only if you’re clever enough to look through the morass of big data and figure out how to use it.
One still needs imagination to deal with this onslaught of knowledge and I think the knowledge is important; we never thought we would be able to generate the amounts of data as quickly as we are these days in the field of biology. I certainly didn’t think we could make antibodies as quickly as we make them now. We still have to have those Aha! Moments of understanding and what that beautiful event is going to look like. We have to still have the aesthetic of science, and masses of data do not have that aesthetic.