Top Medical Research Issues and Trends to Watch in 2017
Peering into the crystal ball, the trajectory for medical R&D over the next year may seem a bit hazy. But never fear – FasterCures has analyzed trends and determined some of the issues critical to the future of medical innovation that we’ll be tracking over the coming year and that we think you should as well. We recently published our Top 10 Medical Research Issues and Trends to Watch in 2017 and will explore these issues – including the biopharma business model, clinical trial innovation and the future of data sharing – during a free Webinar on Monday, Jan. 23, at 1 p.m. Eastern.
- Anna Barker, Professor and Director, Transformative Healthcare Networks; Co-Director, Complex Adaptive Systems Network, Arizona State University
- Bernard Munos, Founder, InnoThink
- John Wilbanks, Chief Commons Officer, Sage Bionetworks
- Margaret Anderson, Executive Director, FasterCures, a center of the Milken Institute (moderator)
Executive Director Margaret Anderson kicked off FasterCures’ first Webinar of 2017 by giving listeners a snapshot of the organization’s popular annual “Top Medical Research Issues and Trends to Watch in 2017” list and welcomed a trio of distinguished FasterCures senior fellows to offer their own expert insights.
The items on this year’s list fell roughly into three categories:
- continued innovation in National Institutes of Health (NIH) programs, at the Food and Drug Administration (FDA) and in clinical trial design and conduct;
- the explosion in sources and types of data, computing power and platforms;
- new patient-centric models of research and development (R&D) and value determination.
Anna Barker, who directs the Transformative Healthcare Networks and Complex Adaptive Systems Network programs at Arizona State University, took listeners on a whirlwind tour of the exciting possibilities opening up to make clinical trials more efficient and effective. Barker said that smarter designs like adaptive and platform trials “are really beginning to take hold.” “Big Data” is coming to clinical trials, and researchers are having to learn how to use imperfect, “scruffy data,” which many other industries have adapted to as well. Algorithms will increasingly drive more evidence-based trials and make “market-driven” trials less prevalent. And artificial intelligence is being increasingly brought to bear to filter through the flood of data being collected, particularly in a patient-centric context. The 21st Century Cures Act has created enormous opportunities to fill in the gulf of biomarkers needed to speed R&D.
Bernard Munos, founder of InnoThink and a former executive at Eli Lilly, believes there are resurgent reasons to be concerned as well as optimistic about the medical products industry. He reviewed the forces stressing the biopharma business model, most of which have been issues for years, including eroding patent life, rising R&D spending per new molecular entity, the domination of low-sales products and declining returns to R&D for large-cap pharma. “Almost everything that we’ve tried to improve our model has failed,” said Munos, such as various forms of financial engineering and creating patent fortresses. “None of this produces innovation.” He is optimistic for the future, however, and cited opportunities to be leveraged: amazing academic discoveries, new data-capture technologies that can slash costs and new infrastructure for smarter research such as the Precision Medicine Initiative (PMI).
John Wilbanks, chief commons officer at Sage Bionetworks, invoked Yogi Berra’s remark that “It’s tough to make predictions, especially about the future,” but did express confidence that three things would happen in 2017. First, the types of studies that underpin precision medicine will start to achieve critical mass. The PMI’s All of Us SM study cohort will have up to 100,000 participants within its first year, and data will be available in the cloud to be queried. Wilbanks explained that, “We’ll start to see what can be done with a large cohort and a lot of different kinds of data. There will be a significant increase in available phenotypes and a decrease in the cost.” Second, a mobile research ecosystem will emerge. The first wave of ResearchKit (an open source framework that allows researchers to develop apps for medical research) is now yielding peer-reviewed science, and the second wave of platforms is maturing. And, finally, experimentation with participant-centric business models, design models, technical models and research models that enable and incentivize participation will accelerate. Wilbanks rounded out his comments saying, “We’ll go into 2018 with more data around which models work and be able to make informed choices rather than ‘faith-based practice’ around patient-centricity.”
Despite a number of potential threats to progress cited by the speakers, Munos closed the discussion by declaring himself an optimist, saying, “We have everything we need to make the transformation that must happen – the technologies, the infrastructure. It’s just up to us to embrace it and do something with it. It tests our determination, our leadership. Ultimately some leaders in industry and among the other stakeholders will rise up and that transformation can happen.”