Here's a brief, holiday-week post to catch up on several events at the intersection of biopharma and big data that occurred earlier this month.
Pharma Hires
First, several pharma companies announced important new hires:
Altshuler (who, disclosure, was several years ahead of me in our MD/PhD program and subsequently in internal medicine, and endocrinology) was a founding member of the Broad Institute and it’s first chief academic officer. For years, he’s been rumored to be under consideration for a range of top-tier academic positions, yet has consistently stayed put – until now. His hiring suggests Vertex (where Atshuler had previously served as a member of the board of directors) is prepared to double down on its genomics efforts, guided by one of the discipline’s leading luminaries.
Plump (disclosure: I worked with and deeply admired him a number of years ago at Merck) had until recently been Senior Vice President of Research and Translational Medicine at
Fried joins Biogen from Boston Children’s Hospital, where she was Chief Innovation Officer, and a widely-respected voice at the interface of technology and healthcare. Fried has deep experience in health-IT, including three-and-a-half years as Vice President of Innovation and Advanced Technology at Kaiser Permanente.
Panel Discussion
Second, I wanted to share a few insights I picked up at a panel discussion on big data and biopharma I recently moderated at an Xconomy Forum at UCSF organized by former In Vivo writer and current Xconomy national biotechnology correspondent Alex Lash.
Rick Morrison, CEO of Comprehend Systems highlighted the importance of using big data and precision medicine to identify additional indications for new molecules. He pointed out that while pharma’s largest blockbuster, atorvastin (Lipitor), achieved commercial success largely based on one predominant indication, it’s now increasingly important to learn from a more recent, highly successful molecule, adalimumab (Humira), which expanded its reach through demonstrating application to an ever-widening series of indications. Companies that want to maximize the value of their portfolio, Morrison suggests, will need to leverage big data and sophisticated analytics to figure out where else lead molecules might prove impactful.
Gini Deshpande, CEO of NuMedii, shared Morrison’s interest in drug positioning (it’s what her company does), but her most interesting comments related to the more general challenges of getting traction for big data in pharma. She suggested that big data advocates are still seeking their breakout pharma success story, an example of where the ability to gather and harness big data had led to insights and ultimately, molecules that wouldn’t have been identified otherwise. She noted that although many agree this approach makes intuitive sense, until it’s actually been done the skeptics will be hard to silence.
I mentioned this evoked for me the famous scene from The Princess Bride, in which Buttercup warns Westley not to enter the fire swamp – “We’ll never survive," she says. His response: “Nonsense. You’re only saying that because no one ever has.”
Finally, Dongliang Ge, Director of Bioinformatics, Gilead Sciences (disclosure: my wife also works at Gilead), emphasized his organization’s interest in collecting rich data in the context of clinical trials, to better identify responder populations. On a powerful and more personal note, he also described the contrasting satisfactions of academia and industry.
