What we doWe de-risk research & development decisions by predicting the clinical benefits of new drugs before human trials
#insilicomedicine #predictiveanalytics #biomodeling #computersciences
In silico medicine that works
Developing new drugs is risky, costly and time-intensive, which translates into a dismal 4% industry-wide RoI according to Nature Drug Discovery. This points to a broken R&D model putting too much emphasis on a capital-intensive trial-and-error approach.
The pharma industry is the most R&D intensive of all research-driven industries, yet it lags in applying Modeling & Simulation (M&S) to improve its productivity.
NOVA is a pioneer in the field of in silico clinical trials, which are poised to become an industry standard as regulators now see M&S as a strategic priority. We unlock the potential of M&S and allow our clients to accelerate and de-risk the R&D of new therapies by establishing their clinical benefits upstream of human trials.
To predict drug efficacy, NOVA applies a proprietary methodology (the Effect Model) with WISE® (Whitebox In Silico Engine), an open ecosystem which brings together the modeling and simulation expertise of the company.
Located at the heart of the top European life sciences cluster Lyonbiopôle, NOVA harnesses the expertise of a team of scientists, engineers and clinicians who work at the interface of systems biology, pharmacology, meta-analysis, mathematics and computer sciences.
The drug R&D paradigm shift
What we do
Totem HealthTech organisé par BpifranceHub : Dans quelle mesure intégrer l’IA dans le parcours de soin ?
François-Henri BOISSEL est invité lors du Totem HealthTech de BpifranceHub aux côtés de @therapixel et du Dr Jean Sébastien Hulot
It is now important for the European Medicines Agency to recognize and integrate into its regulatory processes these new methods of in silico simulation and prediction.
With the help of in silico models we can integrate the right patients in clinical trials and reduce the size of these trials.
Let’s think the human body as a machine and start to look at it as engineers look at machines. In a normal state and at time of dysfunction.