Application of the novel framework has identified the dyslipidemia medication gemfibrozil as a candidate drug to reduce Alzheimer’s disease risk.
Big Patient Data Analyses Pinpoint Telmisartan as a Candidate Drug for Alzheimer’s in Black Adults
A combination of pharmacoepidemiologic studies and Mendelian randomization genetic analysis revealed preferential protection in Black but not white individuals. The findings support ongoing studies of telmisartan for Alzheimer’s, particularly in racially diverse cohorts.
Translating Genomics to Therapeutics for Atrial Fibrillation
A multifront Cleveland Clinic research project aims to use $14 million in NIH funding to identify mechanisms and targets underlying AF that may lead to personalized therapies.
Failed Alzheimer’s Drug Shows Promise for Treating Glioblastoma in Preclinical Study
Treatment of preclinical models of glioblastoma with a BACE1 inhibitor reprogrammed tumor-promoting macrophages into tumor-suppressing macrophages, destroying tumor cells in the process.
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Sildenafil Emerges as a Candidate Drug for Alzheimer’s Disease
A large insurance database analysis has found a 69% relative risk reduction for Alzheimer’s development over six years, prompting mechanistic and phase 2 randomized studies.
Network-Based Drug Discovery for the Emerging COVID-19 Epidemic
Traditional methods of drug discovery cannot keep up with the rapid emergence and mutation of human coronavirus epidemics. Feixiong Cheng, PhD, has applied a network-based prediction model to identify targets for drug repurposing for the treatment of COVID-19.
Harnessing Artificial Intelligence for Drug Repurposing
One driver of increased pharmaceutical spending is the high failure rate of expensive and time-consuming randomized control trials. deepDTnet, a network-based deep learning methodology for novel target identification and in silico drug repurposing, may aid in the development of novel, effective treatment strategies for complex diseases.