Patterns
DescriptorPredicting drug approvals: The Novartis data science and artificial intelligence challenge
The bigger picture
The probability of success is a key parameter that clinical researchers, biopharma executives and investors, and portfolio managers focus on when making important scientific and business decisions about drug development. We describe an in-house data science and artificial intelligence challenge organized by Novartis in collaboration with MIT researchers. Using state-of-the-art machine-learning algorithms and extensive feature engineering augmented by domain expertise in drug development, two winning teams developed models that outperformed the baseline MIT model proposed in a prior study. These new predictive models can be used to augment human judgment to make more informed data-driven decisions in portfolio risk management and capital allocation. These results suggest the possibility of developing even more accurate models using more comprehensive and informative data, and a broader pool of challenge participants.
Data science maturity
Keywords
Cited by (0)
- 7
Lead contact