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Published in Science Advances, St. Jude Children’s Research Hospital scientists used a mix of genetic cancer dependency data, artificial intelligence (AI) and naturally occurring mutations to prioritize safer cancer drug targets. They focused their efforts on targets most likely to be effective while limiting unwanted toxicity, identifying IRS4 as a potential dependency across multiple tumor types. The work provides a proof of principle for evaluating potential toxicity early in the search for novel therapeutics.
Of the potential cancer therapeutics that enter phase 1 clinical trials, an estimated 85%-97% do not become Food and Drug…