Researchers Use AI to Safely Lower Drug Dosage for HIV Patients
A first-of-its kind method to determine the drug cocktail for HIV patients that avoids serious side effects has been developed by a UCLA engineer, Chih-Ming Ho, and international collaborators. The technique uses artificial intelligence to determine the lowest and safest dose, and thereby less toxic, combination therapy for HIV patients. The team’s finding is published in Advanced Therapeutics, and could pave the way to effectively lower dosage for other diseases, such as cancer and tuberculosis. HIV therapy drugs have successfully extended the lives of individuals, but they also can cause serious side effects including kidney failure, the softening of bones or pancreatitis. Under current practice, the various prescriptions used in combination therapy are maintained at the same level even if there is a significant decline of the virus, potentially leading to an excess of the medication in the bloodstream. Until now, lowering the dose without sacrificing effectiveness has proven challenging since guidelines are typically set by...