Drug repurposing of dextromethorphan as a cellular target for the management of influenza

Low-volume plasma sampling for determination of dextromethorphan and dextrorphan in rat plasma: LC-MS/MS method and its application in pharmacokinetic study

Dextromethorphan (DM) and its metabolite dextrorphan (DX) continue to draw the attention of researchers owing to their diverse pharmacodynamics. Thus, there are possibilities for repurposing DM. Most of the pharmacodynamics of DM needs further validation in different preclinical models. Also, it is necessary to correlate the pharmacodynamics with relevant pharmacokinetics data. Multiple bioanalytical techniques developed for this purpose primarily use a high sample processing volume. Since sample volume is a limiting factor for many preclinical models, an effort was taken to develop an alternative method suitable for handling low sample processing volumes. An efficient solid-phase extraction technique, robust liquid chromatographic (LC) separation and highly sensitive tandem mass spectrometric detection (MS/MS) showed suitability for use of a 30 μl sample processing volume. This led to the development of a highly specific, selective, accurate and precise-bio-analytical method for simultaneous quantification of DM and DX in rat plasma. The validated method was linear in the range of 0.196-403.356 ng/ml for DM and 0.102-209.017 ng/ml for DX. The application of the method was demonstrated through the estimation of pharmacokinetic parameters that showed good congruence with earlier studies.

Computational drug repurposing based on electronic health records: a scoping review

Computational drug repurposing methods adapt Artificial intelligence (AI) algorithms for the discovery of new applications of approved or investigational drugs. Among the heterogeneous datasets, electronic health records (EHRs) datasets provide rich longitudinal and pathophysiological data that facilitate the generation and validation of drug repurposing. Here, we present an appraisal of recently published research on computational drug repurposing utilizing the EHR. Thirty-three research articles, retrieved from Embase, Medline, Scopus, and Web of Science between January 2000 and January 2022, were included in the final review. Four themes, (1) publication venue, (2) data types and sources, (3) method for data processing and prediction, and (4) targeted disease, validation, and released tools were presented. The review summarized the contribution of EHR used in drug repurposing as well as revealed that the utilization is hindered by the validation, accessibility, and understanding of EHRs. These findings can support researchers in the utilization of medical data resources and the development of computational methods for drug repurposing.