The reality of modeling irritable bowel syndrome: progress and challenges.
Maryam S Fakhri Bafghi, Niloofar Khoshnam Rad, Ghazal Roostaei, Shekoufeh Nikfar, Mohammad Abdollahi
Author Information
Maryam S Fakhri Bafghi: Department of Internal Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. ORCID
Niloofar Khoshnam Rad: Thoracic Research Center, Imam Khomeini Hospital Complex, Tehran, Iran. ORCID
Ghazal Roostaei: Thoracic Research Center, Imam Khomeini Hospital Complex, Tehran, Iran. ORCID
Shekoufeh Nikfar: Department of Toxicology and Pharmacology, Faculty of Pharmacy and Pharmaceutical Sciences Research Center (PSRC), Tehran University of Medical Sciences, Tehran, Iran. ORCID
Mohammad Abdollahi: Department of Toxicology and Pharmacology, Faculty of Pharmacy and Pharmaceutical Sciences Research Center (PSRC), Tehran University of Medical Sciences, Tehran, Iran. ORCID
INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and treatment outcomes remains a significant hurdle. AREAS COVERED: This perspective provides an overview of the use of animal models alongside cutting-edge technologies used to bring drugs from bench to bedside.Furthermore, the authors examine the progress and limitations of IBS modeling. The authors further discuss the challenges of traditional animal models and gives a spotlight to the potential of innovative technologies, such as organ-on-chip systems, computational models, and artificial intelligence (AI). These approaches intend to enhance both the understanding and treatment of IBS. EXPERT OPINION: Although animal models have been central to understanding IBS research, they have limitations. The future of IBS research resides in integrating organ-on-chip systems and utilizing modern technological developments, such as AI. These tools will enable the design of more effective treatment strategies and improve patients' overall well-being. To achieve this, collaboration between experts from various disciplines is essential to improve these models and guarantee their clinical application and reliability.
