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Personalized anti-tumor drug efficacy prediction based on clinical data

Heliyon, ISSN: 2405-8440, Vol: 10, Issue: 6, Page: e27300
2024
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Study Findings on Personalized Medicine Described by Researchers at Anhui Jianzhu University (Personalized anti-tumor drug efficacy prediction based on clinical data)

2024 MAR 22 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Drug Daily -- New research on personalized medicine is the subject of

Article Description

Anti-tumor drug efficacy prediction poses an unprecedented challenge to realizing personalized medicine. This paper proposes to predict personalized anti-tumor drug efficacy based on clinical data. Specifically, we encode the clinical text as numeric vectors featured with hidden topics for patients using Latent Dirichlet Allocation model. Then, to classify patients into two classes, responsive or non-responsive to a drug, drug efficacy predictors are established by machine learning based on the Latent Dirichlet Allocation topic representation. To evaluate the proposed method, we collected and collated clinical records of lung and bowel cancer patients treated with platinum. Experimental results on the data sets show the efficacy and effectiveness of the proposed method, suggesting the potential value of clinical data in cancer precision medicine. We hope that it will promote the research of drug efficacy prediction based on clinical data.

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