Artificial Intelligence and Computational Approaches for Pain Therapeutics

The development of safe and effective pain therapeutics remains a major challenge despite significant advances in our understanding of pain mechanisms and pharmacology. Although advances in molecular neuroscience and pharmacology have expanded our understanding of pain mechanisms, translating these discoveries into clinically effective therapies remains slow, costly, and associated with high clinical attrition. In recent years, advances in computational pharmacology, molecular modeling, bioinformatics, systems pharmacology, and artificial intelligence (AI) are helping researchers identify therapeutic targets, optimize lead compounds, predict pharmacological and toxicological properties, and integrate experimental, pharmacological, and clinical datasets. These approaches have the potential to improve decision-making throughout drug development, enhance translational success, and accelerate the discovery of safer and more effective pain therapeutics. As the use of these tools continues to expand, it is important to critically evaluate their applications, limitations, and impact on pain therapeutics.This Research Topic aims to highlight how computational approaches and artificial intelligence can address key challenges in the discovery and development of pain therapeutics. Despite rapid advances in computational methods, their application to pain research remains fragmented across multiple disciplines, with limited integration between computational predictions and experimental or clinical validation. We aim to bring together studies that demonstrate how computational approaches can support target identification, lead optimization, prediction of pharmacological properties, and the translation of discoveries into clinically relevant therapies. We welcome contributions that integrate computational methods with medicinal chemistry, behavioral and cellular pharmacology, systems neuroscience, translational research, and clinical investigation. We also encourage manuscripts that address model validation, reproducibility, interpretability, and other challenges associated with the application of AI and computational methods to pain therapeutics. By highlighting both methodological advances and practical applications, this Research Topic aims to provide a comprehensive view of the current state of the field and identify areas where computational approaches can have the greatest impact on future pain research.We welcome Original Research, Reviews, Mini Reviews, Perspectives, Methods, and Systematic Reviews that apply computational approaches or artificial intelligence (AI) to advance pain therapeutics. Topics of interest include, but are not limited to, computational pharmacology, machine learning, molecular modeling, molecular docking, molecular dynamics, pharmacophore modeling, QSAR, structure-based drug design, virtual screening, drug repurposing, systems and network pharmacology, PK/PD modeling, target identification and validation, multi-omics integration, prediction of pharmacological, toxicological, and pharmacokinetic properties, and experimental or clinical validation of computational predictions. Studies integrating computational methods with medicinal chemistry, pharmacology, neuroscience, or translational and clinical research are particularly encouraged. Topic editors: S. Stevens Negus, Piyusha Pagare Source: https://www.frontiersin.org/research-topics/84838/artificial-intelligence-and-computational-approaches-for-pain-therapeutics