Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development
and risk assessment of environmental chemicals. PBPK model development requires the …

Optimisation of compound pharmacokinetics (PK) is an integral part of drug discovery and
development. Animal in vivo PK data as well as human and animal in vitro systems are …

In this review, we describe the current status and challenges in applying machine-learning
techniques to the analysis and prediction of pharmacokinetic data. The theory of …

During the development of a pharmaceutical formulation, a powerful tool is needed to extract
the key points from the complicated process parameters and material attributes. Artificial …

Pharmacokinetic research plays an important role in the development of new drugs.
Accurate predictions of human pharmacokinetic parameters are essential for the success of …

Although computational predictions of pharmacokinetics (PK) are desirable at the drug
design stage, existing approaches are often limited by prediction accuracy and human …

Artificial intelligence (AI) development imitates the workings of the human brain to
comprehend modern problems. The traditional approaches such as high throughput …

Background The demand for physiologically based pharmacokinetic (PBPK) model is
increasing currently. New drug application (NDA) of many compounds is submitted with …

Introduction Analyses of orally administered FDA-approved drugs from 1990 to 1993
enabled the identification of a set of physiochemical properties known as Lipinski's Rule of …

The past decade witnessed substantial discoveries related to the psychosis spectrum. Many
of these discoveries resulted from pursuits of objective and quantifiable biomarkers in …