aceDeploying machine learning and metagenomics for predicting gut microbial drug biotransformation in colorectal cancer
Colorectal cancer (CRC) is one of the leading causes of death globally. Chemotherapy is considered as one of the standard treatment option for CRC. Although effective in many cases, drugs used in chemotherapy are often associated with adverse toxicity. Inter-individual variations in drug response are often attributed to pharmacogenomic associations, and current evidence suggests involvement of gut microbes as a contributor to drug response variations. While several studies have implemented machine learning to pr…
A machine learning tool combining enzyme prediction with species abundance in colorectal cancer metagenomes can identify gut microbial enzymes and species able to biotransform drugs, which may help explain variable chemotherapy response.
The cross-validation accuracy was lower and more variable than the headline figures, and the source describes only computational validation, so effects on patient treatment are not shown.
Evidence
- Peer-reviewedComputational Biology and Chemistry2026-10-13
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Truvace Impact Record TRV-2026-2006, v1: “Deploying machine learning and metagenomics for predicting gut microbial drug biotransformation in colorectal cancer.” Truvace, 2026-10-20. /record/TRV-2026-2006 (accessed at citation time). sha256 76e4e11cf3553d4c…
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