Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learning.

Despite effective medications, rates of uncontrolled glucose levels in type 2 diabetes remain high. We aimed to test the utility of machine learning applied to big data in identifying the potential role of concomitant drugs not taken for diabetes which may contribute to lowering blood glucose. Success in controlling blood glucose was defined as achieving HgA1c levels < 6.

Clinical pharmacology of old age.

: With the majority of elderly persons consuming multiple drugs, inappropriate drug use is a major issue in geriatric medicine. : We reviewed PubMed, Embase, and Cochrane from inception to 1 May 2019 for potentially inappropriate use of medications, polypharmacy, and age-dependent changes in pharmacokinetics and pharmacodynamics. We selected to highlight new aspects that have emerged in recent years: appropriate monitoring of drug adherence and the introduction of Big Data analysis in advancing geriatric pharmacology.

Machine learning of big data in gaining insight into successful treatment of hypertension.

Despite effective medications, rates of uncontrolled hypertension remain high. Treatment protocols are largely based on randomized trials and meta-analyses of these studies. The objective of this study was to test the utility of machine learning of big data in gaining insight into the treatment of hypertension.