An exciting development in digital health care is the use of artificial intelligence (AI) machine learning as a predictive tool for better patient outcomes. A new study published in Nature Biomedical Engineering by Massachusetts Institute of Technology (MIT), Brigham and Women\u2019s Hospital at Harvard Medical School, Duke University, and their research collaborators demonstrates how AI can predict which drugs could interfere with another drug\u2019s efficacy.<\/p>\n
Prescription drugs to treat mental health are among the leading drug classes in the U.S., along with pain relievers and antihypertensives, according to 2021 data from Statista. Total drug prescriptions in the U.S. increased significantly from roughly 3.95 billion in 2009 to 6.7 billion in 2022, and by 2025, an estimated 4.38 billion retail prescriptions will be filled, according to Statista.<\/p>\n
To understand the potential of AI in predicting which drugs should not be prescribed concurrently, the team had to first identify the drug transporters. In pharmacokinetics, the study of the absorption, distribution, metabolism, excretion, and toxicity of medication, drug transporters are membrane proteins that enable drugs to penetrate barriers.<\/p>\n