Can mathematics pave the way for pharmaceutical innovation?
François-Henri Boissel is the founder of 2010 startup Novadiscovery. Seeking ways to make testing drugs more efficient, Boissel's firm is building a community of virtual patients that can be accessed by medical professionals who are seeking out potential drug candidates.
This "first point of research" can help scientists quickly screen candidates by using mathematics and intelligent algorithms. A model-based approach won't replace clinical trials, but can inform pharmaceutical firms early on whether a drug is feasible to pursue -- and whether trial participants can be found.
Nova's goal is to build computational models that can represent "the fundamental fabric of disease," according to François. By making biological research more predictive, the pharmaceutical industry could save billions in drug research.
The firm's scientists are building up a pool of virtual patients using real-world data including clinical trials, census information and scientific publications. Using this data, equations have been developed that present relationships between disease and personal context -- which can also then be used to compute treatment outcomes.
Nova is currently developing models for cancer, cardiovascular disease, infectious diseases, and immunology. The technology has not yet been applied to large research programs.
If Nova's technology is widely adopted, then the personalized medicine trend is likely to receive a boost, as algorithms will be able to take into account individual factors including smoking, alcohol intake, weight, age and previous medical history. Given this digital profile, researchers can find trial patients more efficiently, and clinicians will be able to better decide on treatments and be aware of how side effects are likely to impact a patient.
François is confident that his technology will be the future. "This feels," he said, "like it"s just the beginning of our journey to accelerate the industry's transition to a model of sustainable innovation."
Read More: Wired
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