Editorial: The Potential of Machine Learning in Pharmacogenetics, Pharmacogenomics and Pharmacoepidemiology
Augusto García-Agúndez, Elena García‐Martín, Carsten Eickhoff · Frontiers in Pharmacology · 2022
One of the potential applications of ML in pharmacogenomics is to improve dose prediction accuracy, improving outcomes and reducing adverse drug events (ADEs). In this context, Steiner et al.(https://www.frontiersin.org/articles/10.3389/fphar.2021.749786/full) employ regression to predict stable warfarin dosages in a diverse cohort that includes US Latinos and Latin Americans, concluding that the inclusion of ethnicity and warfarin indication, in addition to the International Warfarin Pharmacogenetics Consortium's recommended set of variables can result in a small but significant improvement in correct dose prediction. Adversome, a new approach to detect ADEs and other disease-and comorbidity-related syndromes in rapidly changing and low-resource environments such as the COVID epidemic. This network also uses FAERS as their data source to better pinpoint ADEs caused by drugs repurposed for COVID, better adapted than conventional approaches in the aforementioned context.We are happy to announce that this Research Topic has been re-launched and we look forward to new contributions in the coming months.