A Pragmatic PBPK-Driven Strategy to Guide ADME Characterization and Early Human PK Prediction for ECCS Class 1B/3B Compounds

Predicting human pharmacokinetics (PK) for ECCS class 1B/3B compounds often demands resource-intensive experiments and empirical scaling, especially when transporter-mediated processes dominate. We propose a tiered physiologically based pharmacokinetic (PBPK) framework for early discovery that (i) aims to identify which ADME processes warrant characterization by chemical class and (ii) provides guidance for human PK prediction with either minimal inputs (zwitterions) or targeted measurements (acids). Benchmarking against well-described molecules (Fexofenadine, Valsartan, Rosuvastatin, and the active metabolite of Valategrast) supports each tier. For the zwitterions we investigated allometrically scaled rat biliary/renal or nonhuman primate plasma clearance alone predicted human PK within 2-fold. For the acids, adjusting the tissue partition coefficient (Kp) was required to recapitulate plasma profiles. This structured PBPK strategy helps to identify essential experiments for acidic compounds and enables reliable early human PK predictions for zwitterions, contributing to a more informed screening cascade design and ultimately accelerating discovery cycle times.

Authors

Institutions

Publication Details

Journal
Journal of Medicinal Chemistry
Published
2026-02-17
DOI
https://doi.org/10.1021/acs.jmedchem.5c03019
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Pragmatic PBPK-Driven Strategy to Guide ADME Characterization and Early Human PK Prediction for ECCS Class 1B/3B Compounds

Daisy Liekens, Dries Van den Bossche, Line Oste, N. Vandeghinste et al.
Journal of Medicinal Chemistry
Pharmacogenetics and Drug Metabolism
article

A Pragmatic PBPK-Driven Strategy to Guide ADME Characterization and Early Human PK Prediction for ECCS Class 1B/3B Compounds

Daisy Liekens, Dries Van den Bossche, Line Oste, N. Vandeghinste, Simone Esposito, David Cebrián
article en

Abstract

Predicting human pharmacokinetics (PK) for ECCS class 1B/3B compounds often demands resource-intensive experiments and empirical scaling, especially when transporter-mediated processes dominate. We propose a tiered physiologically based pharmacokinetic (PBPK) framework for early discovery that (i) aims to identify which ADME processes warrant characterization by chemical class and (ii) provides guidance for human PK prediction with either minimal inputs (zwitterions) or targeted measurements (acids). Benchmarking against well-described molecules (Fexofenadine, Valsartan, Rosuvastatin, and the active metabolite of Valategrast) supports each tier. For the zwitterions we investigated allometrically scaled rat biliary/renal or nonhuman primate plasma clearance alone predicted human PK within 2-fold. For the acids, adjusting the tissue partition coefficient (Kp) was required to recapitulate plasma profiles. This structured PBPK strategy helps to identify essential experiments for acidic compounds and enables reliable early human PK predictions for zwitterions, contributing to a more informed screening cascade design and ultimately accelerating discovery cycle times.

Journal of Medicinal ChemistryVol. 69(4)
Drug Discovery Laboratory (Norway) (NO), Galapagos (Belgium) (BE)
Decent work and economic growth
Openalex Percentile: Top 52%
Pharmacogenetics and Drug Metabolism
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Pragmatic PBPK-Driven Strategy to Guide ADME Characterization and Early Human PK Prediction for ECCS Class 1B/3B Compounds — Daisy Liekens, Dries Van den Bossche, et al. · Journal of Medicinal Chemistry (2026) | TGRS Research Map | TGRS