AI-Driven Drug Repurposing for Post-Viral Arthralgia: In Vitro and In Vivo Validation of Doxycycline, Sofosbuvir, and Pranlukast

Research Article | Open Access

Volume 2025 - 4 | Article ID 270 | http://dx.doi.org/10.51521/IJFMPH.2025.41117

AI-Driven Drug Repurposing for Post-Viral Arthralgia: In Vitro and In Vivo Validation of Doxycycline, Sofosbuvir, and Pranlukast

Academic Editor:

Received 2025-04-11
Revised 2025-04-30
Accepted 2025-05-06
Published 2025-05-10

Dr. Sagam Dinesh Reddy, Dr. Sharathchandra Nibhanpudi, MD, Dr. Sunitha Patil, MD

Dr. Sagam Dinesh Reddy, MD (Physician), DFM (Family Medicine), DIMCH/CCPMH (Community Mental Health), PGPN (Pediatric Nutrition), AFIH (RLI Kanpur/DGFASLI-GOVT of India), LMR Hospital, G Konduru, NTR District, Andhra Pradesh, India, 521229, ORCID: [0000-0001-7659-9441], Email: dineshsagam143@gmail.com

Dr. Sharathchandra Nibhanpudi, MD (Pharmacology), Department of Pharmacology, SVMC Tirupathi, Andhra Pradesh, India, Email: nschandra82@gmail.com

Dr. Sunitha Patil, MD (Microbiology), Group Captain, Assistant Professor, Department of Microbiology, AFMC Pune, Maharashtra, India, Email: drsunitpat@gmail.com

Corresponding Author: Dr. Sagam Dinesh Reddy, LMR Hospital, G Konduru, NTR District, Andhra Pradesh, India, 521229, ORCID: [0000-0001-7659-9441], Email: dineshsagam143@gmail.com

Citation: Dr. Sagam Dinesh Reddy, Dr. Sharathchandra Nibhanpudi, MD, Dr. Sunitha Patil, MD (2025) AI-Driven Drug Repurposing for Post-Viral Arthralgia: In Vitro and In Vivo Validation of Doxycycline, Sofosbuvir, and Pranlukast. Int J Fam Med Pub Health, 4(1);1-12.

Copyrights: © 2025, S. Dinesh Reddy, Sharathchandra N, Sunitha P,. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

Abstract

Post-viral arthralgia, particularly following dengue and chikungunya infections, poses a significant clinical challenge due to its persistent and debilitating nature, with limited therapeutic options available. Our research aimed to address this gap by leveraging AI-driven drug repurposing to identify effective treatments for post-viral arthralgia. Utilizing advanced computational techniques, including machine learning models and molecular docking studies, we analyzed vast datasets to predict and validate the efficacy of existing drugs. Our methodological approach involved training AI algorithms on specific biomolecules and conducting in vitro and in vivo assays to assess the anti-inflammatory effects of candidate drugs. Our results identified doxycycline, sofosbuvir, and pranlukast as promising candidates, demonstrating significant reductions in pro-inflammatory cytokine levels and joint inflammation in treated animal models. These findings suggest that AI-driven drug repurposing can efficiently identify novel therapeutic uses for existing drugs, offering a faster and cost-effective alternative to traditional drug discovery processes. The implications of our study are substantial, providing new therapeutic options for managing post-viral arthralgia and highlighting the potential of AI in addressing other viral infections and inflammatory conditions. Our work underscores the transformative potential of AI-driven drug repurposing in developing effective treatments for post-viral arthralgia, marking a significant step forward in the field. Future research should focus on clinical validation of these findings and exploring the broader applications of AI in drug discovery.