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ORAL PRESENTATION / TAM METİN SÖZLÜ SUNUM

Artificial Intelligence–Assisted Physiologically Based Pharmacokinetic (PBPK)
Modelling in Veterinary Pharmacology and Toxicology

Hikmet Özgün İŞCAN¹ Abdurrahman AKSOY¹
,*

¹Department of Veterinary Pharmacology and Toxicology, Faculty of Veterinary
Medicine, Ondokuz Mayıs University, Samsun, TÜRKİYE

* Correspound Author: hikmetozgun.iscan@omu.edu.tr

Abstract

In recent years, artificial intelligence (AI) and machine learning (ML) have been increasingly
applied in veterinary medicine for diagnosis, treatment planning, and data analysis. Drug research

and development also benefit from the predictive power and efficiency of these technologies.
Physiologically based pharmacokinetic (PBPK) models mathematically simulate the absorption,
distribution, metabolism, and excretion (ADME) of drugs based on species-specific anatomical

and physiological characteristics. These models are valuable tools for dose adjustment,
interspecies extrapolation, evaluation of drug–drug interactions, and toxicological risk
assessment. Widely used PBPK software platforms include GastroPlus™, PK-Sim®, and Simcyp

Animal. Such models facilitate the prediction of key pharmacokinetic parameters such as volume
of distribution and clearance, support model calibration, and enable dose simulations. AI-assisted
PBPK approaches not only accelerate experimental workflows but also align with the 3Rs

principle, offering an ethical alternative that reduces animal use. The inclination to minimize
animal use, motivated by ethical and economic considerations, has substantially enhanced the
appeal of these methods. Although PBPK modelling is well established in human medicine, its

application in veterinary medicine remains limited. This is largely due to the scarcity of species-
specific physiological data, incomplete databases on transporter proteins and enzyme expression,
and challenges in model validation. Limited datasets for less-studied species, such as goats or

exotic animals, further constrain model reliability. In conclusion, AI-assisted PBPK modelling
represents an innovative, ethical, and scientifically robust approach for veterinary drug
development, dose optimisation, and toxicological risk assessment. This methodology holds

substantial potential to facilitate the design of individualised treatment strategies and to promote
safe and effective drug use in veterinary practice.
Keywords: Pharmacokinetics; drug development; machine learning; veterinary; artificial

intelligence.

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