Machine Learning Techniques Applied to the Study of Drug Transporters.

With the advancement of computer technology, machine learning-based artificial intelligence technology has been increasingly integrated and applied in the fields of medicine, biology, and pharmacy, thereby facilitating their development. Transporters have important roles in influencing drug resistance, drug-drug interactions, and tissue-specific drug targeting. The investigation of drug transporter substrates and inhibitors is a crucial aspect of pharmaceutical development. However, long duration and high expenses pose significant challenges in the investigation of drug transporters. In this review, we discuss the present situation and challenges encountered in applying machine learning techniques to investigate drug transporters. The transporters involved include ABC transporters (P-gp, BCRP, MRPs, and BSEP) and SLC transporters (OAT, OATP, OCT, MATE1,2-K, and NET). The aim is to offer a point of reference for and assistance with the progression of drug transporter research, as well as the advancement of more efficient computer technology. Machine learning methods are valuable and attractive for helping with the study of drug transporter substrates and inhibitors, but continuous efforts are still needed to develop more accurate and reliable predictive models and to apply them in the screening process of drug development to improve efficiency and success rates.

Research Methods and New Advances in Drug-Drug Interactions Mediated by Renal Transporters.

The kidney is critical in the human body's excretion of drugs and their metabolites. Renal transporters participate in actively secreting substances from the proximal tubular cells and reabsorbing them in the distal renal tubules. They can affect the clearance rates (CLr) of drugs and their metabolites, eventually influence the clinical efficiency and side effects of drugs, and may produce drug-drug interactions (DDIs) of clinical significance. Renal transporters and renal transporter-mediated DDIs have also been studied by many researchers. In this article, the main types of in vitro research models used for the study of renal transporter-mediated DDIs are membrane-based assays, cell-based assays, and the renal slice uptake model. In vivo research models include animal experiments, gene knockout animal models, positron emission tomography (PET) technology, and studies on human beings. In addition, in vitro-in vivo extrapolation (IVIVE), ex vivo kidney perfusion (EVKP) models, and, more recently, biomarker methods and in silico models are included. This article reviews the traditional research methods of renal transporter-mediated DDIs, updates the recent progress in the development of the methods, and then classifies and summarizes the advantages and disadvantages of each method. Through the sorting work conducted in this paper, it will be convenient for researchers at different learning stages to choose the best method for their own research based on their own subject's situation when they are going to study DDIs mediated by renal transporters.