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Review
. 2025 Sep 4;52(5):51.
doi: 10.1007/s10928-025-09999-y.

Computational approaches for toxicology and Pharmacokinetic properties prediction

Navid Kaboudi  1 , Tara Shekari  2 , Ali Shayanfar  3   4 , Andre Silva Pimentel  5
Affiliations
Review

Computational approaches for toxicology and Pharmacokinetic properties prediction

Navid Kaboudi et al. J Pharmacokinet Pharmacodyn. .

Abstract

Pharmacokinetics and toxicological studies how the body reacts to a specific administered substance, such as a drug, toxin, or food. Each substance experiences these four steps: absorption, distribution, metabolism, and excretion, which are the main parameters in pharmacokinetics studies. Many toxic endpoints exist. There are three main ways to measure toxicology and pharmacokinetic parameters: in vivo, in vitro, and in-silico. Knowing toxicological and pharmacokinetic parameters before developing a new drug candidate could save time and resources, as clinical studies are highly cost-demanding. This review aims to gather studies using in-silico methodologies to predict pharmacokinetic properties.

Keywords: Machine learning; Pharmacokinetics; Predicting; Toxicology.

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Conflict of interest statement

Declarations. Conflict of interest: The authors report there are no competing interests to declare. Moreover, no large language models such as chatGPT, openAI, or DeepSeek was used in design or writing this manuscript.

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