AI Medical Compendium Journal:
Biological & pharmaceutical bulletin

Showing 1 to 4 of 4 articles

Trivariate Linear Regression and Machine Learning Prediction of Possible Roles of Efflux Transporters in Estimated Intestinal Permeability Values of 301 Disparate Chemicals.

Biological & pharmaceutical bulletin
A system for predicting apparent bidirectional permeability (P) across Caco-2 cells of diverse chemicals has been reported. The present study aimed to investigate the relationship between in silico-generated P (from apical to basal side, P) for 301 s...

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.

Biological & pharmaceutical bulletin
Physiologically based pharmacokinetic (PBPK) modeling has the potential to play significant roles in estimating internal chemical exposures. The three major PBPK model input parameters (i.e., absorption rate constants, volumes of the systemic circula...

Prediction of Vancomycin-Associated Nephrotoxicity Based on the Area under the Concentration-Time Curve of Vancomycin: A Machine Learning Analysis.

Biological & pharmaceutical bulletin
Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxicity; however, they have notable limitations. Specifically, they do not use the area under the concentration-time curve (AUC) as recommended in the la...

Data-Driven Clinical Pharmacy Research: Utilizing Machine Learning and Medical Big Data.

Biological & pharmaceutical bulletin
To conduct clinical pharmacy research, we often face the limitations of conventional statistical methods and single-center observational study. To overcome these issues, we have conducted data-driven research using machine learning methods and medica...