oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data

🤖 Plain-English Summary

Cell line drug screening datasets can be utilized for a range of different drug discovery applications from drug biomarker discovery to building translational models of drug response. Here, we unite and update these methodologies into one R package (oncoPredict) to facilitate the development and adoption of these tools.

🔑 Key Findings

• Previously, we described three separate methodologies to (1) correct for general levels of drug sensitivity to enable drug-specific biomarker discovery, (2) predict clinical drug response in patients and (3) associate these predictions with clinical features to perform in vivo drug biomarker discovery.
• Here, we unite and update these methodologies into one R package (oncoPredict) to facilitate the development and adoption of these tools.
• This new OncoPredict R package can be applied to various in vitro and in vivo contexts for drug and biomarker discovery.

🔗 Related Resources