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Drug treatment effects

Investigating drug safety and efficacy

Goal
To develop a computational platform that estimates both the beneficial and harmful effects of drugs, across an entire population, within different subpopulations, or in individual patients
Impact
Better and personalized prescriptions will reduce the burden of adverse events, increase adherence, and, importantly, improve treatment outcome

Randomized controlled trials, the gold standard of comparative effectiveness research, provide safety and efficacy estimates for a small fraction of drug pairs and outcomes. Scalable computational methodologies can fill these gaps using real-world data to generate richer quantitative drug susceptibility and effectiveness maps.

 

Our platform takes each drug and estimates the probability of various outcomes (harmful and beneficial), relative to a comparator drug (or set of drugs), from real-world clinical data and using causal inference methodologies. We aim to generate comprehensive drug-outcome estimate maps and visualize these in a semantically meaningful manner. The developed methodology will also be applied to specific use-cases to estimate drug effects on subpopulations (or individuals) of interest.

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