Artificial Intelligence is tremendously growing and improving day by day in drug
development. New AI techniques used for disease detection and diagnosis include machine
learning (ML) and deep learning (DL). To design and simulate pharmacokinetic-
pharmacodynamic (PK-PD) models of medications and their effects on the human body as well
as drug development, users can now use Open Systems Pharmacology, an AI-based software
tool. MoBi and PK-Sim are both come under OSP tools. In all phases of preclinical and clinical
drug development as well as health risk evaluations, the mathematical modeling technique
known as physiologically-based pharmacokinetic (PBPK) modeling is employed.
Pharmacokinetics can be applied to medicine to calculate the best drug dosage and timing
schedules. Recently PBPK modeling particularly focuses on the application to the treatment of
cancer. The systems pharmacology database and analytic platform for traditional Chinese
medicine (TCMSP) was developed using this approach. It includes 499 Chinese herbs, 29,384
constituents, 3,311 targets, and 837 related disorders. In order to predict ADMET, drug-druginteractions, drug-likeness screening, physicochemical properties, pharmacophore modeling,
and the blood brain barrier penetration property of any medications quickly and accurately,
users have access to a variety of AI-based pharmacokinetic tools. There are plenty of them,
including (1) PKQuest, (2) SwissADME, (3) admetSAR, (4) OSIRIS, etc. Every tool is
available online and has an intuitive user interface. Most of them are free to use, while some
have paid or commercial version also along with free version. However, due to privacy
concerns, open source or free software is not commonly utilized in the research and
development (R&D) and pharmaceutical industries. The aim of this review is based on in-depth
current information about a few AI-based pharmacokinetic tools and how they can accurately
and efficiently estimate pharmacokinetics & pharmacodynamics within pharmaceutical
compounds.
Keywords: PK-PD, Artificial intelligence, ADMET determination, OSP, ADMET
software, Pharmacokinetic tool, Drug interaction
Publication date: 01/12/2024
https://ijbpas.com/pdf/2024/December/MS_IJBPAS_2024_8539.pdf
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https://doi.org/10.31032/IJBPAS/2024/13.12.8539
