Learning and actioning general principles of cancer cell drug sensitivity
Francesco Carli,
Pierluigi Di Chiaro,
Mariangela Morelli
et al.
Abstract:High-throughput screening platforms for the profiling of drug sensitivity of hundreds of cancer cell lines (CCLs) have generated large datasets that hold the potential to unlock targeted, anti-tumor therapies. In this study, we leveraged these datasets to create predictive models of cancer cells drug sensitivity. To this aim we trained explainable machine learning algorithms by employing cell line transcriptomics to predict the growth inhibitory potential of drugs. We used large language models (LLMs) to expan… Show more
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