"Machine-Learning Model Identifies Deadly Drug Combinations for Safer Prescribing"
TL;DR
Researchers at MIT, Brigham and Women’s Hospital, and Duke University have developed a strategy to identify the transporters used by different drugs, which could help improve patient treatment by identifying potential drug interactions. By using tissue models and machine-learning algorithms, they identified interactions between a commonly prescribed antibiotic and a blood thinner, as well as other drugs. This approach could also be applied to drugs in development to prevent interactions with other drugs or improve their absorbability.
Topics:healthhealth-and-medicine#drug-development#drug-interactions#drug-transport#gastrointestinal-tract#health-and-medicine#machine-learning
- New model identifies drugs that shouldn't be taken together MIT News
- Multimodal CNN-DDI: using multimodal CNN for drug to drug interaction associated events | Scientific Reports Nature.com
- New machine-learning model identifies drug interactions for safer prescribing Open Access Government
- Doctors discover 58 new drug and supplement combinations you must NEVER take together - they could have deadly Daily Mail
- Drug Interactions Predicted with Tissue Model/Machine Learning Combo Genetic Engineering & Biotechnology News
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