Abstract

*Shinde Snehal Vitthal, Mansi Tikone, Madhuri Yadav, Shruti Sonawane, Ajaykumar Shirsat

ABSTRACT

Antihistaminic agents remain essential in the management of allergic, gastric and neurologic disorders, yet many candidates fail during development because of poor absorption, metabolic instability or unexpected toxicity. Early evaluation of absorption, distribution, metabolism, excretion and toxicity (ADMET) is therefore a critical step in optimising safety and efficacy. Computational approaches provide rapid, cost-effective screening by predicting pharmacokinetic and toxicological behaviour from chemical structure. This article presents an overview of in-silico ADMET profiling applied to commonly used antihistamines across the H1–H4 receptor spectrum. Molecular descriptors were retrieved from freely available databases and assessed using web-based platforms such as SwissADME, pkCSM and admetSAR. Predicted properties—including lipophilicity, polar surface area, intestinal permeability, blood–brain barrier transport, cytochrome P450 interactions, clearance and potential cardiotoxicity—were compared with information reported in clinical literature. Second-generation H1 antagonists demonstrated favourable oral absorption with minimal central penetration, whereas several first-generation agents showed higher lipophilicity and a risk for hERG channel blockade, consistent with their sedative and cardiac profiles. The study highlights how software-assisted prediction can complement experimental data, support rational drug design and guide safer selection of antihistaminic candidates for further development.