Cell therapy, informatics/machine learning and precision medicine will tremendously impact healthcare in the next ten years—but there is some need for rethinking priorities. So concluded experts who spoke on a panel entitled “What’s Next: 2020 and Beyond,” held on September 11, 2019, at BioPharm America™ in Boston.
The panelists were Christiana Bardon, MD, MBA, a portfolio manager at Burrage Capital; Christiana lyasere, MD, MBA, director, Department of Medicine Innovation, Mass General Hospital, and co-founder, Dynamix, Inc; and Chandra Ramanathan, PhD, MBA, VP and head of Bayer’s Open Innovation Center North America East. Roger Kitterman, VP, Venture and Managing Partner of the Partners Innovation Fund, served as moderator.
Areas of promise
Asked by Kitterman which new technologies and modalities will likely be getting “hotter,” Bardon said that one of the most potentially transformative new arenas is cell therapy—the transplantation of human cells to replace or repair damaged tissue or cells and the reprogramming of cells.
“I think that we've really turned the corner in terms of actually seeing efficacy of the next stage, which is solid tumors,” Bardon said. “If we could actually approach lung cancer and other solid tumors, that would be transformative.” Regarding the ability to reprogram cells and “differentiate them into whatever profile we're interested in,” Bardon described the company Semma Therapeutics, which, among other projects, is involved in reprogramming cells to become pancreatic cells, which manufacture insulin.
Informatics, machine learning and digital health
Iyasere pointed out that, over the last ten years, science and medicine have collected a wealth of data, but have had a difficult time gaining clinical insights. But informatics, machine learning, digital health and personalized medicine are all “beginning to unlock clues to complex biological systems and impact patient care,” she said. “In the past five years, the ability of machine learning informatics to help us understand convoluted, very complicated biological systems, and make useful clinical impacts has become really quite apparent. And in the past two-to-three years we've seen a transition from thinking about the data to its now becoming clinically actionable information.”
For example, “it’s been very challenging to think about the relationship of RNA to disease, and we’ve been unable to discern exactly what is critically important. But, now, because we're able to integrate RNA with multiple different data streams, we are able to understand, for the individualized patient, how their composite portfolio of risk relates to a variety of diseases.
“Similarly, with digital health, we haven't had a lot of impact on the patient side. But I think that, finally, we're starting to understand how we can leverage access to patients to both engage them in their own care, to help them think about what wellness means and to transition from a disease to a wellness state.
“And when it comes to pharmaceutical design, we’re able to be smarter about how we engage with patients, design clinical trials, and actually get side effect profiles. I think the consequences of these innovations—informatics, machine learning and digital health—which are on the cusp, is that we're able to get a composite picture of what's happening to a given patient and their given disease state.
“As a consequence, we're able to think about how we design personalized medicine for neurology, rheumatology, cardiovascular disease, diabetes, and have direct impact on patients and providers."
Solid tumors, cell/gene therapy, precision medicine
Ramanathan, of Bayer‘s Open Innovation Center, agreed that biologic and technological breakthroughs leading to better understanding of disease and increased patient engagement are on the near horizon. He foresees breakthroughs in treatment options for solid tumors and cell/gene therapy, and said that precision medicine will bring greater insight into disease prognosis. Despite what he termed initial “hype” in data science, he said artificial intelligence will have huge impact on new drug targets selection, lead optimization, patient selection and patient engagement.
Asked what new treatments are likely to come as a result of these breakthroughs, Bardon pointed out that much progress has already been made in monogenetic illnesses—those caused by a mutation of a single gene—such as lung cancer. “We are now starting to make inroads in neurological diseases where there are monogenetic markers—such as Huntington’s disease, and ALS (amyotrophic lateral sclerosis)." She suggested that in the next ten years, new genetic databases and big data will help bring about cures for epigenetic disease (involving changes caused by modification of gene expression); “multi-genetic” disease; those with environmental components and those such as Alzheimer’s disease, “where you have no idea of the etiology.”
In Iyasere’s view, regarding diabetes and cardiovascular disease, “we have a much better understanding of the role of RNA and other factors in terms of how those diseases play out…. So, as we transition from thinking about the role of DNA and monitor that to sorting out the role of epigenetic factors, we will be able to re-address new disease entities.” What is more, most current clinical trials for neurological and cardiovascular diseases have a multi-year timeline—but new methods are leading to the discovery of new markers and ways to determine whether drugs are working—thus shortening the drug development process and enhancing patient care.
Ramanathan pointed out that despite scientific and technological breakthroughs, regulatory, funding and investment issues have “a very direct impact on how treatments will evolve.” For example, in the Boston ecosystem, approximately 40 percent of companies focus on oncology, 20 percent on orphan diseases, and the “remainder in various other indications,” he said. “Are there other things we should be looking at?” According to the World Health Association, he added, “the number one killer, hands down, is cardiovascular disease. But if you look at the percentage of cardiovascular-related companies in the Boston ecosystem, it's less than 5 percent,” he said. “There is a lack of correlation between investment focus and disease states. The scientific know-how coupled with clarity of regulatory path might be ripe for previously difficult-to-treat diseases. Do we need to revisit our priorities?”
Health Information Technology (HIT): Traction vs. hype
Kitterman pointed out that in the last few years, there has been “an explosion of venture dollars” into AI and digital health, and asked, “Which areas are getting traction and which are not?”
In Iyasere’s view, “there's a lot of investment into areas where being able to create clinically actionable, useful insights from clean structured data is not actually happening.” But there are some entities like radiology pathology, in which “it's much more straightforward in terms of the integration of machine learning. And I do think that will truly be successful.”
It is not yet clear if “the hope for digital therapeutics is actually bearing fruit,” she said. But use of smartphone apps increases the ability of healthcare professionals to engage with patients in order to reinforce behavior—in those with diabetes or depression, for example—and can help reduce post-traumatic stress disorder in cancer patients. By reaching patients in their homes, it can positively influence their health.
Bardon suggested that HIT could save healthcare money by streamlining systems and helping determine which drugs will be effective. But, she said, “more evidence of positive clinical outcomes is needed if those models are to be reimbursed.” She asked, “What are the business models for digital health? How do you make money?” She foresees “a long road ahead, with a glimmer on the horizon.”
According to Ramanathan, artificial intelligence and machine learning are having an impact in drug discovery but “in the patient space, they are just getting there.”
Ripe for breakthrough?
Kitterman pointed out that immunotherapy and gene therapy efforts failed many times but are now often successful. He asked if there are other areas in which the industry has stalled—but might be “ripe for a final breakthrough.”
Bardon replied that early failures in those fields were largely due to problems in the manufacturing process. “We did not have the ability to manufacture consistent and high-quality product, and we didn't have the assays for measuring and determining those. Just like in protein manufacturing, which used to be a huge pain, people had difficulty getting living cells to manufacture proteins at scale.” Now, she said, “it’s hard to find contract gene therapy manufacturing places but I think we have turned the corner.” In fact, she said, MPM Capital recently founded a company, ElevateBio, aimed at making contract manufacturing for gene therapy scientifically and economically feasible.
In Iyasare’s view, many cardiovascular and neurological trials failed largely because it was impossible to identify which patients should receive the drugs. But personalized medicine—which takes into account a person’s unique molecular and genetic profile—allows advance measurements so that drugs can be tried in a particular cohort. And the development of “surrogate” endpoints—biomarkers making it possible early on to identify patients for whom a drug will likely work—will be “transformative” for the field.
Ramanathan asked why some companies pull out of drug development after trial failures for some disease states, and why drug development for others continues. He pointed out that the mortality or survival rates for certain cardiovascular or renal diseases are not dramatically different from those of certain cancers. “While there is much advancement in science, we need to have the courage to address these questions. I think that could be something one would like to see in 2020 and beyond as research for more complex diseases advances.”
Anita Harris is a writer and communications consultant based in Cambridge, MA.
Attend more panels on cell and gene therapies and digital medicine at BIO-Europe® 2019, coming up November 11–13 in Hamburg, Germany.