"Identifying Deadly Drug Combinations: New Model's Findings"
TL;DR
Researchers from MIT, Brigham and Women's Hospital, and Duke University have developed a strategy using tissue models and machine-learning algorithms to identify the transporters used by different drugs, revealing potential interactions between commonly prescribed medications. By understanding how drugs pass through the digestive tract and predicting potential toxicities, this approach aims to improve patient safety and treatment efficacy, as well as aid drug developers in enhancing drug absorbability and preventing interactions with other medications.
Topics:health#drug-development#drug-interactions#drug-transport#health#machine-learning#patient-safety
- New model identifies drugs that shouldn't be taken together Medical Xpress
- New model identifies drugs that shouldn't be taken together MIT News
- Doctors discover 58 new drug and supplement combinations you must NEVER take together - they could have deadly Daily Mail
- Multimodal CNN-DDI: using multimodal CNN for drug to drug interaction associated events | Scientific Reports Nature.com
- Drug Interactions Predicted with Tissue Model/Machine Learning Combo Genetic Engineering & Biotechnology News
Want the full story? Read the original reporting
Read on Medical Xpress