Technological advancements in wearables, machine learning, and data mining are poised to revolutionize evidence-based medicine and next-generation clinical trials. However, despite these scientific advances, translating research breakthroughs into clinical practice remains a challenge. The pandemic, by highlighting the importance of patient-centered research, has exposed weaknesses in current clinical trial practices and driven improvements in trial design.
The Data Deluge: Research’s New Challenge
Despite unprecedented advances in clinical research, translating these findings into clinical practise lags significantly across most research areas. Drug development is costly, often unsuccessful, and creates substantial financial and societal burdens. Chronic disease data is often fragmented across isolated systems (data silos), hindering efficient clinical trials and generation of high-quality evidence. Multidisciplinary collaboration is essential to overcome this. Randomized controlled trials (RCTs), while valuable, are often impractical due to time and cost and constraints in generating evidence. Their limited sample sizes also restrict generalizability, leaving many clinical questions unanswered. Ethical considerations and consent processes can lengthen RCTs. Clear definitions of prognostic/ predictive biomarkers and endpoints are crucial for faster drug development. Staffing shortages also pose a challenge to these trials.
Transforming Clinical Trials
To improve population health, innovative research strategies are essential for boosting patient engagement and generating high quality evidence that facilitates the rapid translation of diagnostic and treatments from research to clinical practise. Future clinical trials will leverage AI, machine learning, and deep learning to enhance drug discovery, image interpretation, electronic health record data management, and trial workflows. These trials will also incorporate advancements in immunology, precision medicine and related fields. Master protocols, including sub-studies like umbrella, basket, platform, and master observational trials, are advancing clinical trial design. Future trials will likely be more decentralized, virtual, and rely on digital endpoints for realistic, globally harmonized, standardized real-world patient experience tracking and remote monitoring. Increased collaboration among academic institutions, patients, sponsors (pharmaceutical, government and cooperative groups), regulatory bodies, and CROs can improve the research landscape. Improved trial accessibility and patient participation can be achieved through navigation services and site-agnostic matching. Accelerated drug development can be facilitated by priority reviews, orphan, fast-track, and breakthrough designations. Transportation analyses can enhance the validity of trial results. Individualized N-of-1 genomic trials may improve rare disease assessment. Integrating “digital twins” – patient-specific medical analogs combining mechanistic information and medical history data – has the potential to further enhance these trials. Trial designs can incorporate external or synthetic control arms mirroring those of a randomized controlled trial (RCTs). Increased pediatric RCTs aided by AI (as a compliment to, not replacement for, human intelligence), can improve our understanding of rare diseases. Conclusion In conclusion, successful clinical trials require transforming their design, execution, assessment, and documentation. This involves optimizing the use of digital and AI-driven data and technologies to better connect trials with real-world experiences. Future clinical research development will be challenged by the need to effectively leverage multidimensional and real-world evidence. This requires successfully retrieving, integrating and analyzing large datasets and information derived from advanced scientific techniques. Increased global funding partnerships and use of social media and online platforms can raise awareness and community engagement. Improving public health and addressing diversity, equity, and global access to therapeutics requires breaking down silos, embracing digitilization and decentralization, and advancing personalized, pragmatic, preventive, and precision medicine.
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