Challenges and Innovations in Conducting Clinical Trials in Rare and Orphan Diseases
Year: 2025
Type: article
Abstract: Clinical trials in rare and orphan diseases face unique and complex challenges due to limited patient populations, disease heterogeneity, and constrained economic incentives. This review provides a comprehensive analysis of the key barriers and emerging innovations in the design and execution of clinical trials targeting rare conditions. Regulatory frameworks such as the FDA’s Orphan Drug Act and the European Medicines Agency’s orphan designation process offer incentives like market exclusivity and accelerated approval to spur drug development. However, recruitment and retention difficulties, ethical concerns regarding placebo use, lack of natural history data, and variable disease progression hinder traditional randomized controlled trial designs. To overcome these barriers, adaptive methodologies—such as Bayesian statistics and seamless Phase II/III trials—have been introduced to enhance flexibility and efficiency. Real-world evidence, patient registries, N-of-1 trials, and basket trials provide valuable alternatives when conventional designs are unfeasible. Decentralized and virtual trial models, utilizing telemedicine and wearable devices, are reducing geographic and logistical barriers. Central to these efforts is the role of patient advocacy, which improves recruitment, retention, and trial relevance through community engagement. Global collaborations, including international consortia and harmonized data-sharing frameworks, are essential for maximizing research impact. Looking ahead, the integration of genomics, artificial intelligence, and supportive policy mechanisms will be pivotal in shaping the future landscape of rare disease research. The review emphasizes the need for multi-stakeholder coordination and patient-centric innovation to develop equitable, ethical, and scientifically robust trials for rare and orphan diseases.
Author: Mrudula Dhengale*1, Harsha Bathe1, Prajakta Hage1, Aachal Kawade1, Neha Phopse1, Nikita Sapkal1, Tejal Dharme1, Shivshankar Nagrik2
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6931040429