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Breaking Barriers Between Species: Integrated Multi-Species PK Models Improve Human PK Predictions
Miriam S R Happ1,2,3, Jens M Borghardt1, Charlotte Kloft2,3
1Research DMPK, Global Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Ingelheim am Rhein, Germany.
CPT: Pharmacometrics & Systems Pharmacology
|May 23, 2026
Summary
This study enhances human pharmacokinetic (PK) prediction by integrating a multi-species model, improving the accuracy of shape-defining parameters like intercompartmental clearance (Q) and late concentrations (C24h). The new framework offers a promising approach for drug discovery, especially for challenging compounds.
Area of Science:
- Pharmacokinetics and Drug Metabolism
- Computational Chemistry and Cheminformatics
- Drug Discovery and Development
Background:
- Accurate human pharmacokinetic (PK) prediction is vital for drug discovery, guiding compound selection and dose determination.
- Existing methods often struggle with predicting PK shape-defining parameters beyond clearance (CL) and volume of distribution (Vss).
- Predicting parameters like absorption rate constant (ka), distribution volumes (Vc, Vp), and intercompartmental clearance (Q) remains an underexplored area.
Purpose of the Study:
- To improve the prediction of human PK shape-defining parameters.
- To develop an updated PK prediction framework leveraging a multi-species approach.
- To enhance the prediction of key exposure metrics like maximum (Cmax) and trough (Ctrough) concentrations.
Main Methods:
- Developed an updated PK prediction framework incorporating a multi-species PK model.
- Integrated allometric scaling for joint prediction of shape-defining parameters.
- Retained mechanism-based prediction methods for bioavailability (F) and CL.
- Validated the framework on 40 small molecules with known human PK profiles.
Main Results:
- The multi-species model demonstrated reduced geometric mean fold-error (GMFE) compared to a benchmark framework.
- Improved prediction accuracy was observed for the overall PK profile and its shape.
- Significant improvements noted in predicting intercompartmental clearance (Q) and late concentrations (C24h).
- Enhanced performance was particularly evident for compounds with inconsistent PK structures across species.
Conclusions:
- The integrated multi-species PK model framework shows promise for human PK prediction.
- This approach is particularly beneficial for compounds with cross-species modeling challenges.
- The framework offers improved accuracy for predicting trough concentrations, crucial for efficacy and toxicity assessments.
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