Translational Research and Biomarkers

Translational research is really just a fancy term for the activities necessary to take a therapy from the laboratory – and particularly from laboratory animals, to actual patients.  Part of this process involves the concomitant development of biomarkers that allow us to establish that the drug is hitting its intended therapeutic target in patients, and provide early indications that the drug is doing something clinically beneficial. In translational research for Oncology at Pfizer, we often rely on a combination of molecular imaging to demonstrate drug effects in patients’ tumors as well as molecular profiling of cancers to ensure that we are testing the drug in the right patients. At Pfizer, we’re pretty committed to making early decisions about the potential of our drugs – sometimes even in Phase 1. This is a different paradigm from that of a biotech company for example, because Pfizer has a very large pipeline all of which could never be taken to late stage development. Hence, part of my role is to weed that pipeline of less promising drugs and bring forth into Phase II and Phase III only those that have a high probability of success.

Translational research, at least at Pfizer, is about 70 percent translation from the preclinical to clinical space. Many of the biomarkers that we employ in oncology are imaging-based endpoints – PET and MRI scans for example – and sometimes, those are mechanism endpoints. That is, one can infer something about whether or not a drug has hit its target using a functional imaging endpoint. But often these endpoints are simply outcome biomarkers if you will, and one needs to understand their relationship to a real target or mechanism-based biomarker, such as, for example, the phosphorylation status of some kinase substrate. This is done preclinically, where we try to understand the biology of the target and its relationship to the biomarker that we will actually use in clinical trials. We also try to understand exposure/response at this stage. That’s a real driver at Pfizer – we do a lot of exposure response modeling to try to select the right dose so that we can predict when we are reaching an efficacious drug exposure in patients. So, the translational piece of that is about doing that preclinical work where we try to understand these things and then applying the findings to the clinical evaluation of our drugs from the very beginning, even from Phase I.

The other 30 percent of translational research is the back-translation piece – what can we learn from our larger clinical trials and from hypothesis-generating work with pharmacogenomics and proteomics and so forth. What we learn here feeds back to the investigators and researchers in the discovery side of the company, so that the next generation of drugs can benefit from what we’ve learned in the clinic.

Moving forward collaboratively
The process of moving translational research into pre-competitive space, where companies, regulators and academics collaborate to validate biomarkers as actual surrogate endpoints (rather than internal decision-mailing tools) is becoming an important driver. People don’t really understand what it takes to validate a biomarker as a surrogate endpoint – the need for rigorously designed prospective studies that can discriminate between predictive and prognostic markers. It takes a great deal of effort, time and money, but I really believe that there is much that can be achieved in these precompetitive collaborations among companies and academics. We’re not talking about individual drug studies here – companies are understandably reluctant to share competitive information about their pipelines (although all of us are working on similar targets). I’m talking about biomarkers for broad mechanisms or pathways that all of us are interested in. So for example, what will it take to validate an imaging tool like PET as a surrogate outcome marker for lymphoma or non-small cell lung cancer? This is work that is being done now at the consortium level. Some of these precompetetive efforts are actually being driven by patient advocacy groups, particularly in oncology. I have participated in several of these group “think tanks” where the NCI, the FDA (as part of their Critical Path initiative), the AACR, as well as representatives from a variety of Pharma companies and patient advocacy groups are all present and all talking about what can we do in the pre-competitive space to make translational medicine more effective, to validate technologies, to validate individual markers for disease – all with the goal of speeding effective therapies to market. I think that’s the wave of the future and I suspect that we’re going to see a lot more of this kind of collaborations among companies.

Biomarker application strategy
What we are trying to do with biomarkers at Pfizer Oncology is to install a process by which we do a small but very focused study in the earliest clinical evaluation stages of our drugs, where we employ biomarkers to make project progression decisions. These are usually imaging endpoints that have been validated pre-clinically. However, we want to ensure that we are testing these drugs and biomarkers in select patient populations that represent the best test of the drug mechanism. Often that implies that one needs to understand the molecular profile of the cancer as determined by analysis of archival biopsy although sometimes, one can choose the patient population solely on the basis of what type of cancer that they have. In either case, the goal is to ensure that the drug target is indeed in play in these patients. We then do a small, focused Phase 1B or Phase 2a -type study usually employing functional imaging biomarkers, to evaluate these new agents.

Biomarkers are becoming increasingly crucial components of the drug development process and we all recognize that most of our drugs work in only a subset of the treated patient population. That may be somewhat frightening to our commercial colleagues who may be reluctant to cut the market size down. But we also all recognize that if we can really tailor the drugs to the right patient population, not only will the trials be smaller, more efficient and cheaper, but one can command a premium price for a drug that is much more likely to work in the patients who receive it. Pfizer, like most large pharmaceutical companies, and indeed smaller biotech companies, has embraced a biomarker approach to drug development – particularly in oncology. We are part of several collaborative biomarker development groups such as the Biomarkers Consortium of  the Foundation for the NIH, and we’ve contributed a lot of money to try to develop and validate biomarkers that can be used not only as surrogate endpoints for registrational approvals, but also for internal decision making.

About the author

Dominic Spinella leads  the clinical biomarker work for Pfizer’s oncology portfolio. He also serves on several national and international cancer biomarker development bodies, including the Cancer Steering Committee of the NIH Biomarkers Consortium, the FDA/NCI/Oncology Biomarker Think Tank, and the AACR Scientific Review Committee for Molecular Diagnostics in Cancer Therapeutic Development. Dr. Spinella received his PhD in Immunology from Rutgers University in 1982, and did his post-doctoral training as a Howard Hughes fellow at the Washington University School of Medicine in St. Louis.