Chapter 23: Writing a Guidebook on Translational Research

Chapter 23: Writing a Guidebook on Translational Research

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Description

In this chapter, Dr. Bast talks about a book he is writing for young researchers interested in conducting translational research. He describes the sequence of chapters. While discussing his aims for the book, Dr. Bast touches on several subjects. First he talks about MD Anderson's Apollo Program that aids in diagnosis. He explains how important it is to bring academia and Pharma together in research project. He gives examples of chasms to overcome and explains that it's important to bridge the gap because pharmaceutical companies fund so much research. Dr. Bast also notes that his book aims to increase the pool of physician scientists.

Identifier

BastRC_03_20141218_C23

Publication Date

12-18-2014

Publisher

The Making Cancer History® Voices Oral History Collection, The University of Texas MD Anderson Cancer Center

City

Houston, Texas

Topics Covered

The Interview Subject's Story - The Researcher; The Researcher; The Educator; Industry Partnerships; On Pharmaceutical Companies and Industry; Business of Research; MD Anderson Culture

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

Disciplines

History of Science, Technology, and Medicine | Oncology | Oral History

Transcript

Tacey A. Rosolowski, PhD:

If it’s okay, I wanted to shift gears and ask you about your book.

Robert Bast, MD:

Okay. Just about to return to it.

Tacey A. Rosolowski, PhD:

Oh, cool.

Robert Bast, MD:

So—but that’s my—that’s my goal for the next six months to get that done. .

Tacey A. Rosolowski, PhD:

Mm-hmm. So what’s the scope of the book? Because if—the subject, of course, is translational research. And what’s the theme you’re taking?

Robert Bast, MD:

It’s a guidebook for young people about how translational research is actually conducted. I don’t know if we’ve covered this territory before, but the first couple of chapters are to provide enough background in translation—in tumor biology and immunology to understand the examples that are provided in the rest of the book. I’d like this to be something that a PhD graduate student could read and understand enough of the medicine to understand how things are accomplished. And you’ve—generally talk about how drugs have been developed and how targeted therapy does or doesn’t differ from that. How biological therapies are different from just conventional small molecular weight drugs. Then the book discusses how molecular diagnostics have been developed and how they’ve been used, and how you bring those together to personalize therapy and/or to make precision medicine. And what the role of academe has been in that, and what it could be, as well as what pharma has done, and the predicament that pharma is currently in. And that—also, what the role of government has been. And, again, where we are this week in terms of the gridlock in Washington, and how that’s impacting on our—what we can do scientifically. And also, the idea of—the FDA and regulation, and, you know, where that’s—has been headed. And to talk about career development in translational research, and what the many roles are on translational teams. And then what are the numbers of physician-scientists and clinician-investigators, and the other activities that make up part of translational research. And then talking about the community, and how we need to figure out how to relate this to the community in several different ways. First of all, to have enough patients to actually move forward, and to—and to test and to validate our approaches for predicting who will respond to which drugs, and what it’s going to take to be able to do that. And also, ultimately, educating the community in how you use targeted therapy, because we’re rapidly getting beyond just the usual algorithm that NCCN [National Comprehensive Cancer Network] puts out about how you treat a particular kind of lung cancer. And increasingly, as we have to go to combinations of targeted therapies to get decent, long-lasting responses, we’re going to have to have something more than the annotation on reference laboratories, tests, to help. So it’s going to be—there’s going to have to be some sort of informatics—some sort of consultative services between medical centers like MD Anderson and the community. It’s interesting that there’s some solutions to that in this whole Apollo program. I don’t know if you’ve heard about that, but one of the things—one of the other things that Ron has championed with Andy [Andrew] Futreal and others, has been the development of intelligent, or artificial intelligence, to provide a patient-care tool. Apollo is starting with leukemias and myelodysplastic syndrome syndromes [MDSs], but then moving to melanoma and, hopefully, to lung cancer and ovarian cancer and the like. So, trying to take advantage of all of our information here about how different patients respond to different drugs, but also how clinicians make decisions based on the information that’s in front of them. With the hope that you may—you know, usually we report out our results in terms of technical papers, or applying for grants, or getting drugs to a point of approval. This would really be providing aids in medical-diagnosis decision making that could come straight from MD Anderson, taking advantage of experience with patients. But I think—I think the—now there’s sort of—there’s a whole bunch of different suggestions that I’m trying to get across in the book. But one of them certainly—and this is one of Ron’s favorite topics—that we need to get academe and pharma and biotech working much more collaboratively than we have in the past. You know, there’s really been a chasm and a huge amount of distrust in—between the two groups, as well as the issues of conflict of interest and the like. Pharmaceutical companies are sometimes altruistic, but their fundamental function is to earn money for their stockholders. And their vision of how you do that, even for oncology, in the past has been to get a blockbuster drug that will bring in billions of dollars a year while it’s still on patent, and to move on. Increasingly, pharma is not being very effective. In part, it’s related to the fact we don’t have a lot of great preclinical models for predicting who will and won’t respond in the clinic to different drugs. At present, several hundred million dollars are invested to get a drug ready for clinical trials. It then takes several hundred million more dollars to get it through the necessary trials. Only one out of eight oncologic drugs that enters clinical trials actually gets approved by the FDA. It’s not because the FDA [Food and Drug Administration] is being too harsh. Tthe FDA, if anything, is being more lenient these days. They’re approving drugs if they’ll significantly prolong progression-free survival by two or three months. In the past, they’d insisted on an increase in overall survival by at least that much or more. The lack of approvals are largely because the companies think they’ll be—drugs will be effective, and seven times out of eight they’re wrong. And one way, perhaps, to improve that batting average is to use all we know about cancer with our deep biology to choose the right targets. Pharmaceutical companies are really good at making drugs if they know what they’re supposed to make a drug against. And the trouble is that they’ve just guessed wrong way too often in terms of the targets that they’re targeting. Academe could help hugely in choosing the right combination of targets. The IACS ought to have a better track record than one-in-eight, and we’ll find out. It’s, again, an experiment, but it’s an experiment that’s really worth doing. If you look at where all the money comes from for cancer research, about seventy percent of it’s from pharma. But it’s not for the kind of fundamental research that you need to do. That, unfortunately, has got to come from the government and, to some extent, maybe $3 billion or so from foundations and the like. And then, also, from the profit margins from clinical care, which is what we do here. But, you know, pharma is the 2,000-pound gorilla when it comes to funding sources. So if pharma were convinced that they could trust the data that comes out of academe—and often they don’t—that you could imagine some of the more fundamental research could be funded. It would be in the interest of the pharmaceutical company to find out what they really ought to be making drugs against, and certainly in the interest of investigators here. But it would take more of the Moon Shot attitude and culture to make that really work. With declining support for research, we’re going to have to choose our experiments and projects more wisely. On the clinical side, there are some clinical protocols that are “me too,” and there are other clinical protocols that are really working with innovative drugs. And if they worked, they’d end up in the New England Journal, or they’d end up in the Journal of Clinical Oncology. Not because—some academic artifact, but because they’re really going to help people, and they would change practice. In mentoring young people, I try to encourage them to really think hard about, if this experiment really worked Journal of Clinical Oncology because you’re going to spend two years of obtaining a drug, writing and executing a protocol. If the drug really worked, what would you have accomplished? Where could you publish it? How much of a chance would it stand to really help people? Another facet of the book addresses how we can to stabilize the physician-scientist pool. But that’s still not going to be enough. We’ve got to figure out how to utilize intelligent PhDs who want to do translational research. And we’ve got to have job opportunities for them at the end of the day. To some extent, that’s in pharma. But to some extent, it must also be in academe—that there should be career paths for those individuals. With regard to the community, groups like US Oncology have got to become more effective in conducting clinical trials. We need to try harder to instill the idea that even when you go into community practice, you’re still an investigator, you’re still a researcher at some level, doing something. And try to improve those statistics. Only four percent of the patients in private practice go onto any kind of a clinical research protocol. And then, only four percent of the patients overall end up on clinical protocols at all, even when you count the medical centers. So it’s a real challenge. We need to figure out ways to communicate the new knowledge now that it’s becoming so complex. Because if it takes a billion dollars and up to twelve years for a new drug that is approved once out of eight times to see the light of day, the outrageous costs for all of the targeted therapies these days were trying to make up for the batting average of seven out of eight failures.

Tacey A. Rosolowski, PhD:

Sure, well, it sounds like—it sounds like a very, very broad meditation, as well as, you know, practical information on the field of translational research and its context, economically and educationally.

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