Pioneer in Business Leadership to Advance Innovative Models and Speed Breakthroughs in Precision Medicine
Can you tell us a little bit about the Multiple Myeloma Research Foundation and its accomplishments?
I founded the MMRF in 1998, shortly after I was diagnosed with multiple myeloma, a rare and still fatal blood cancer. The mission of the MMRF remains the same as the first day we opened our doors: to accelerate a cure for multiple myeloma. From the beginning, the MMRF made it a priority to collaborate, building unprecedented partnerships with the biotech and pharmaceutical industries, academia, and the cancer community at-large to inject speed and efficiency into the drug discovery and development process. This resulted not only in a fundamental shift in how medical research is conducted, particularly in the field of oncology, but in meaningful results for patients: 10 multiple myeloma drugs to patients in just one decade—that’s the same amount of time it typically takes to bring a single drug to market. These advances have resulted in a 45% improvement in five-year multiple myeloma patient survival rates, a 60% improvement in the overall multiple myeloma survival rates, and the tripling of patient lifespans.
What sets the MMRF precision medicine model apart from other research efforts?
We believe that taking a similarly collaborative approach to precision medicine will lead us to a cure. We developed the only end-to-end precision medicine model in oncology to drive better, more effective treatments and identify optimal care pathways for the patients we serve.The first component of our model is a robust data ecosystem, including the first multicenter multiple myeloma tissue bank, which has amassed more than 4,000 patient samples and clinical data from newly diagnosed and relapsed patients. This data ecosystem provides the foundation for our efforts in sequencing the multiple myeloma genome and CoMMpass Study. The second is the MMRF Researcher Gateway, a virtual learning center that provides research worldwide with the data and analytic tools to needed to form new hypotheses and rapidly explore new and potentially more effective ways of treating myeloma. The thirdis our clinical consortium, a network of research institutions and cancer centers that are testing an arsenal of new drugs and combinations, targeted therapies, immunotherapies, and novel compounds that attack the cancer in entirely new ways. The MMRF has conducted more than 70 trials of 35 drugs; several more are set to launch later this year, including several genomically-informed trials. And finally, our precision medicine model would not be complete without having brought together a massive community of patients. These patients are stepping up to share knowledge they have gained on their cancer journey with fellow patients, learn which kind of myeloma they have, and share their data to advance research.
About 5 years ago, MMRF launched the CoMMpass Study. Can you provide an overview of this study?
The MMRF CoMMpass study is a longitudinal, observational clinical trial to accelerate personalized treatment approaches for myeloma patients. Now closed to enrollment, CoMMpass takes a deep dive into the genomes of 1,200 patients with multiple myeloma, and then links those data to patients’ clinical history — what treatments worked for them, what didn’t — to uncover mutations associated with the disease. Each patient participating in CoMMpass will have his or her tissue sequentially profiled at baseline, at best response to treatment, and at each relapse via three platforms—WES, WGS, and RNAseq—and will be followed for up to eight years. After an initial period of prioritized access, CoMMpass data are then funneled into an open-access public database. This allows the global research community to work collaboratively to mine what is now known as the largest, most robust longitudinal genomic data set in cancer for “signals,” decipher patterns for further exploration, and generate hypotheses for clinical trials. Last year, the MMRF contributed the CoMMpass dataset to the National Cancer Institute’s Genomic Data Commons (GDC), which enables data sharing across cancer genomic studies in support of precision medicine. The MMRF was the first nonprofit to place its data into the GDC, and we hope our leadership will inspire others to join us.
Have you seen any results from CoMMpass yet?
Yes. CoMMpass data are already yielding insights into new targets and pathways for drug development, as well as new ways to identify and potentially treat high-risk patients.For example, CoMMpass confirmed our previous findings that 5% of myeloma patients have a mutation in the BRAF gene that had previously never been linked to myeloma. This has informed the development of clinical trials for patients with this mutation, one of which will launch through our clinical network later in the next few months. And, most recently, we discovered that there are further subtypes within the t(4;14) subtype. One of these appears to confer no worse prognosis than is associated with other subtypes, while another appears to be associated with an extremely fatal form of the disease.Additionally, through CoMMpass, new technologies are being employed to help the community understand the role of minimal residual disease (MRD), or low-level disease that occurs during a period of remission. Improving our ability to detect and quantify MRD is critical to more accurately assess response to treatment, thereby enabling more appropriate and timely treatment decisions.
You also were selected to head up the Harvard Business School (HBS)Kraft Precision Medicine Accelerator. What is the goal of that program?
The HBS Kraft Precision Medicine Accelerator was established last year by an endowment from the Robert and Myra Kraft Family Foundation to speed breakthroughs in precision medicine. It’s co-chaired by myself and Richard Hamermesh, a senior fellow at Harvard Business School, with the goal of breaking down barriers preventing data-sharing and building bridges among the cancer community’s many disparate and siloed datasets. We do so by convening best-in-class leaders from the business, medical, scientific, and technological communities to roll up their sleeves and begin the hard work of actually solving challenges to data sharing and the advancement of precision medicine.
What are you working on?
The HBS Kraft PM Accelerator focuses on four areas as the world of oncology shifts toward efforts in evidence based. It brings together cancers that are leading the way in precision medicine, working with teams in breast cancer, prostate cancer, multiple myeloma, and pancreatic cancer, among others. First, we are focusing on data and analytics, surveying the landscape and understanding the role of crowd in driving analytics and insights. Second, we are focusing on patient engagement, data acquisition, retention through their journey, and the critical role of social media in working around data silos. In an effort to identify and share key best practices we brought together disruptive DTC companies including Peloton, Under Armour, and Wayfair to provide valuable insights to DTP companies. Third, will be bringing together the leaders in innovative trial design. And, finally, we are working on understanding new investment models to continue to drive the ecosystem forward.
Data-sharing is a real passion of yours. Why?
As patients, it is absolutely critical to know your data; doing so allows your health care team to act decisively in devising your treatment strategy and allows for the smart selection of treatments or clinical trials that might be best in treating your disease. It is just as critical that you share your data because it allows you to see your data in the context of others and begins to contribute to our collective understanding of the disease.
If data is shared, what is the next greatest obstacle that needs to be tackled?
Asking questions of the data that will have the most meaningful impact on patients and the providers who treat them—What are the best front-line treatments for patients? What are the best treatment at relapse? We are already trying to answer these questions, not only by generating our own data, but by building bridges across disparate data sets that allow for broad collaboration among researchers and incentivize analyses.