Ripa, Joya Datta, Ali, Sarfaraz, Field, Matt, Smithson, John, and Wangchuk, Phurpa (2025) From AI-Assisted In Silico Computational Design to Preclinical In Vivo Models: A Multi-Platform Approach to Small Molecule Anti-IBD Drug Discovery. Pharmaceuticals, 18 (10). 1536.

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Abstract

Background: Inflammatory Bowel Disease (IBD), including Ulcerative Colitis and Crohn’s Disease, is a multifactorial inflammatory condition of the intestinal tract driven by a complex interplay of genetic factors, immune system dysfunction, and gut microbiota alterations. This review aims to synthesize current advancements in modern drug development strategies for IBD. It emphasizes the integration of computational modelling, cell-based experiments, and animal model studies to enhance translational outcomes. Methods: To compile this review, an extensive literature search was performed utilizing PubMed, Scopus, and Google Scholar databases for English-language research and review articles published between 2000 and 2025 using keywords such as “IBD,” “molecular docking,” “bioinformatics,” “organoids,” “animal models,” and “network pharmacology,” among others. A total of 199 peer-reviewed studies were identified for inclusion based on relevance, transparency, and methodological robustness. Results: The review outlines a range of cutting-edge approaches to IBD drug discovery. These include computer modelling, molecular docking, and network analysis to accelerate early-stage target prediction and drug screening. The review further highlights the critical importance of utilizing 2D and 3D cell culture systems in parallel with advanced animal models. It emphasizes the critical integration of computational predictions with biologically relevant in vitro and in vivo validations to improve the reliability and efficiency of drug development. Conclusions: The integration of computer modelling, cell culture systems, and animal studies provides a revolutionary paradigm for accelerating drug discovery to IBD and other diseases enabling personalized and more effective treatment approaches.

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