Kentaro Handa

<i>In Silico</i> Prediction of Input Parameters for Simplified Physiologically Based Pharmacokinetic Models for Estimating Plasma, Liver, and Kidney Exposures in Rats after Oral Doses of 246 Disparate Chemicals

Yusuke Kamiya, Kentaro Handa, Tomonori Miura et al. · Chemical Research in Toxicology · 2021 · 47 citations

Prediction of permeability across intestinal cell monolayers for 219 disparate chemicals using in vitro experimental coefficients in a pH gradient system and in silico analyses by trivariate linear regressions and machine learning

Yusuke Kamiya, Asuka Omura, Riku Hayasaka et al. · Biochemical Pharmacology · 2021 · 34 citations

Engineering, Machine Learning, Disparate Chemicals +13

Machine Learning Prediction of the Three Main Input Parameters of a Simplified Physiologically Based Pharmacokinetic Model Subsequently Used to Generate Time-Dependent Plasma Concentration Data in Humans after Oral Doses of 212 Disparate Chemicals

Yusuke Kamiya, Kentaro Handa, Tomonori Miura et al. · Biological and Pharmaceutical Bulletin · 2021 · 31 citations · Full text

Absorption Rate Constants, Disparate Chemicals, Simplified Physiologically +20

An Updated <i>In Silico</i> Prediction Method for Volumes of Systemic Circulation of 323 Disparate Chemicals for Use in Physiologically Based Pharmacokinetic Models to Estimate Plasma and Tissue Concentrations after Oral Doses in Rats

Yusuke Kamiya, Kentaro Handa, Tomonori Miura et al. · Chemical Research in Toxicology · 2021 · 11 citations