Author(s):
Komal Nimse, Avinash A. Gunjal, Rupali V. Karale, Aditi D. Bangar
Email(s):
avinashgunjal4247@gmail.com
DOI:
10.52711/2321-5836.2026.00024
Address:
Komal Nimse1, Avinash A. Gunjal2*, Rupali V. Karale3, Aditi D. Bangar3
1Student, Siddhi’s Institute of Pharmacy, Nandgaon, Murbad, Thane - 421401, Maharashtra, India.
2Assistant Professor, Siddhi’s Institute of Pharmacy, Nandgaon, Murbad, Thane - 421401, Maharashtra, India.
3Lecturer, Siddhi’s Institute of Pharmacy, Nandgaon, Murbad, Thane - 421401, Maharashtra, India.
*Corresponding Author
Published In:
Volume - 18,
Issue - 2,
Year - 2026
ABSTRACT:
Experimental pharmacology plays a pivotal role in understanding drug actions, mechanisms, and safety profiles through controlled laboratory investigations. Traditionally, this field has relied on animal models, organ bath experiments, bioassays, and histological evaluations to study pharmacokinetics, pharmacodynamics, dose-response relationships, and toxicity. While these methods have provided fundamental insights, they are often limited by ethical concerns, species variability, lower sensitivity, and restricted translational relevance. Recent advances have transformed experimental pharmacology, integrating cutting-edge approaches such as high-throughput screening (HTS), CRISPR-Cas9 gene editing, proteomics, and artificial intelligence-driven predictive modeling. Moreover, organ-on-chip devices, 3D bioprinting, and organoid cultures now enable human-relevant models that better replicate physiological systems and reduce reliance on animal testing. In silico pharmacology, including molecular docking and dynamics simulations, further enhances the predictive power of drug discovery by elucidating drug-target interactions at the molecular level. Together, these developments have improved accuracy, efficiency, and ethical standards, thereby accelerating the translation of preclinical findings into safe and effective therapeutics. This review highlights the evolution of experimental pharmacology from traditional models to modern technological innovations, emphasizing their collective role in advancing drug discovery and development.
Cite this article:
Komal Nimse, Avinash A. Gunjal, Rupali V. Karale, Aditi D. Bangar. Advances in Experimental Pharmacology: From Animal Models to Artificial Intelligence and Organs-on-Chip. Research Journal of Pharmacology and Pharmacodynamics.2026;18(2):117-6. doi: 10.52711/2321-5836.2026.00024
Cite(Electronic):
Komal Nimse, Avinash A. Gunjal, Rupali V. Karale, Aditi D. Bangar. Advances in Experimental Pharmacology: From Animal Models to Artificial Intelligence and Organs-on-Chip. Research Journal of Pharmacology and Pharmacodynamics.2026;18(2):117-6. doi: 10.52711/2321-5836.2026.00024 Available on: https://rjppd.org/AbstractView.aspx?PID=2026-18-2-9
REFERENCES:
1. Rang HP, Dale MM, Ritter JM, Flower RJ, Henderson G. Rang & Dale's Pharmacology. 9th ed. Elsevier; 2020.
2. Kashish R. Mulani, B.P. Chaudhari, V. K. Redasani, Kalyani Gardi. Drug Discovery and Development. Asian Journal of Research in Pharmaceutical Sciences. 2025; 15(2):185-0.
3. Katzung BG, Vanderah TW. Basic & Clinical Pharmacology. 16th ed. McGraw Hill; 2021.
4. Shoaib Ahmad. Recent advances in Pharmacology and Toxicology of Phytopharmaceuticals. Asian J. Pharm. Res. 2017; 7(4): 222-224.
5. Shalini A. Shinde, Manasi J. Mhetar, Avantika G. Parit, Akash R. Thombre. In-silico Investigation and ADMET Prediction of Potential Antifungal Phytochemicals against Lanosterol 14-Alpha Demethylase Inhibitors. Asian Journal of Pharmaceutical Research. 2024; 14(1): 33-8.
6. Kulkarni SK. Handbook of Experimental Pharmacology. 5th ed. Vallabh Prakashan; 2019.
7. Neha Singh, Kirti Zalma, Melica Khatri, Paul Ven, Arjun Singh. Screening and Validation of Natural Products for Drug Discovery: Key Points and Approaches. Asian Journal of Pharmaceutical Research. 2024; 14(2):162-8.
8. Vogel HG, Vogel WH. Drug Discovery and Evaluation: Pharmacological Assays. 3rd ed. Springer; 2008.
9. Franco NH. Animal experiments in biomedical research: a historical perspective. J Med Ethics Hist Med. 2013; 6:23.
10. Van Norman GA. Limitations of animal studies for predicting human drug safety. Curr Opin Toxicol. 2020; 19:61–8.
11. Bailey J, Thew M, Balls M. An analysis of the use of animal models in predicting human toxicology and drug safety. Altern Lab Anim. 2014;42(3):181–99.
12. Pound P, Ritskes-Hoitinga M. Is it possible to overcome issues of external validity in preclinical animal research? Why most animal models are bound to fail. J Transl Med. 2018; 16:304.
13. Akhtar A. The flaws and human harms of animal experimentation. Camb Q Healthc Ethics. 2015; 24(4): 407–19.
14. Sunildutt N, et al. Harnessing organ-on-chip technology for drug development and toxicology. Front Pharmacol. 2023; 14:117025.
15. Ravi Kumar. Drug Discovery (Lead Identification and High Throughput Screening). Research Journal of Pharmacology and Pharmacodynamics. 2021; 13(2):46-0.
16. Vishwajit S. Patil, Prithviraj A. Patil. Molecular Docking: A useful approach of Drug Discovery on the Basis of their Structure. Asian Journal of Pharmaceutical Research. 2023; 13(3):191-5.
17. Sudhakar P, Poorana Pushkalai S, Sabarinath C, Priyadharshini S, Haripriya S. Molecular docking and synthesis of 1, 2, 4 - triazin analogue of diclofenac as potential ligand for parkinson’s. Res. J. Pharmacology and Pharmacodynamics. 2018; 10(1): 08-12.
18. Apeksha P. Motghare, Parimal P. Katolkar, Tina S. Lichade. In-Silico Prediction of Phytoconstituents from Phyllanthus niruri for Anticancer Activity against Prostate Cancer Targeting MRCK kinases. Research Journal of Pharmacy and Technology. 2023; 16(9): 4105-1.
19. Suresh A. Marnoor. A Short Review on Organ-on-a-chip Technology. Asian Journal of Pharmacy and Technology. 2023; 13(2):111-4.
20. Klann MT, et al. Computational systems pharmacology: integrating network models and machine learning. NPJ Syst Biol Appl. 2021; 7:9.
21. Vanhaelen Q, et al. The coming age of artificial intelligence in pharmaceutical research. Drug Discov Today. 2020;25(1):37–50.
22. Murphy SV, Atala A. 3D bioprinting of tissues and organs. Nat Biotechnol. 2014; 32(8): 773–85.
23. Balls M. The principles of humane experimental technique: timeless insights and unheeded warnings. ALTEX. 2009; 26(2): 91–8.
24. European Medicines Agency (EMA). Guideline on strategies to identify and mitigate risks for first-in-human clinical trials. 2018.
25. Bhhatarai B, Walters WP. The role of predictive modeling in next-generation experimental pharmacology. Future Med Chem. 2015; 7(18): 2381–94.