biostudies-literatureUnknown26(5)Nishikiori KIn designing drug dosing for hemodialysis patients, the removal rate (RR) of the drug by hemodialysis is important. However, acquiring the RR is difficult, and there is a need for an estimation method that can be used in clinical settings. In this study, the RR predictive model was constructed using the RR of known drugs by quantitative structure-activity relationship (QSAR) analysis. Drugs were divided into a model construction drug set (75%) and a model validation drug set (25%). The RR was collected from 143 medicines. The objective variable (RR) and chemical structural characteristics (descriptors) of the drug (explanatory variable) were used to construct a prediction model using partial least squares (PLS) regression and artificial neural network (ANN) analyses. The determination coefMolecular diversity2647-2657https://www.ebi.ac.uk/biostudies/studies/S-EPMC9532302biostudies-literatureConstruction of a prediction model for drug removal rate in hemodialysis based on chemical structures.PMC9532302Uesawa YNishikiori KTanaka KfalseConstruction of a prediction model for drug removal rate in hemodialysis based on chemical structures.In designing drug dosing for hemodialysis patients, the removal rate (RR) of the drug by hemodialysis is important. However, acquiring the RR is difficult, and there is a need for an estimation method that can be used in clinical settings. In this study, the RR predictive model was constructed using the RR of known drugs by quantitative structure-activity relationship (QSAR) analysis. Drugs were divided into a model construction drug set (75%) and a model validation drug set (25%). The RR was collected from 143 medicines. The objective variable (RR) and chemical structural characteristics (descriptors) of the drug (explanatory variable) were used to construct a prediction model using partial least squares (PLS) regression and artificial neural network (ANN) analyses. The determination coef2022-01-01T00:00:00Z2022 Oct2026-04-28T03:19:07.543Z2025-04-04T13:46:29.312ZS-EPMC95323023497311610.1007/s11030-021-10348-7