René Geci

This study uses high-throughput PBK modelling to predict systemic pharmacokinetics from dermal exposure using in silico data, achieving reasonable accuracy for key metrics.

Dividing Cmax by lowest in vitro toxicity potency separates drugs by liver-injury (DILI) risk, AUC up to 96%; PBK-predicted Cmax without clinical data reaches 91%.

This paper develops a method to classify chemicals by Potential Systemic Availability (PSA) concern using physiologically based kinetic modeling and evaluates its alignment with expert judgment.

This study evaluates high-throughput PBK modelling strategies for predicting human intravenous and oral pharmacokinetics using in vitro and in silico data.

This paper models a gene drive design using Y-linked editors and sex ratio distorters to suppress pest populations efficiently and locally, showing it can work with low release rates and is sensitive to allele frequency changes.