2023 TheNextGenerationofEvidencebase
- (Subbiah, 2023) ⇒ Vivek Subbiah. (2023). “The Next Generation of Evidence-based Medicine.” In: Nature Medicine. https://doi.org/10.1038/s41591-022-02160-z
Subject Headings: Modern Clinical Research.
Notes
- Topics:
- Advancements in wearable technologies and data science
- Transforming evidence-based medicine.
- Future of clinical trials and evidence-based medicine
- Limitations and inefficiencies of the clinical trial landscape
- COVID-19 pandemic and its impact on clinical trials.
- Cross-disciplinary approaches in medicine
- Machine learning and deep neural networks in clinical research.
- Improving electronic health records and workflow
- Need for fundamental transformation in clinical trials
- Preventive, personalized, pragmatic, and patient-participatory medicine.
- Keywords:
- Wearable technologies
- Evidence-based medicine
- Clinical trials
- COVID-19 pandemic
- Clinical research
Cited By
Quotes
Abstract
Recently, advances in wearable technologies, data science and machine learning have begun to transform evidence-based medicine, offering a tantalizing glimpse into a future of next-generation ‘deep’ medicine. Despite stunning advances in basic science and technology, clinical translations in major areas of medicine are lagging. While the COVID-19 pandemic exposed inherent systemic limitations of the clinical trial landscape, it also spurred some positive changes, including new trial designs and a shift toward a more patient-centric and intuitive evidence-generation system. In this Perspective, I share my heuristic vision of the future of clinical trials and evidence-based medicine.
Main
The last 30 years have witnessed breathtaking, unparalleled advancements in scientific research—from a better understanding of the pathophysiology of basic disease processes and unraveling the cellular machinery at atomic resolution to developing therapies that alter the course and outcome of diseases in all areas of medicine. Moreover, exponential gains in genomics, immunology, proteomics, metabolomics, gut microbiomes, epigenetics and virology in parallel with big data science, computational biology and artificial intelligence (AI) have propelled these advances. In addition, the dawn of CRISPR–Cas9 technologies has opened a tantalizing array of opportunities in personalized medicine.
...
Conclusion
The success of future clinical trials requires a fundamental transformation in how trials are designed, conducted, monitored, adapted, reported and regulated to generate the best evidence. The status quo model is unsustainable. Instead, preventive, personalized, pragmatic and patient-participatory medicine is needed, and paradigm shifts are required to get there via sustainable growth. Silos need to be broken. Standards of care and clinical trials are currently viewed in different realms; however, the overarching goal of both is to improve health outcomes. The COVID-19 pandemic created an opportunity to observe how routine clinical care and clinical trials can work synergistically to generate evidence86. Pragmatic platform trials such as the RECOVERY trial should be a model and guide for trial efficiency and real-time impact.
Current paradigms must be continuously challenged by emerging technology and by all stakeholders (the new generations of scientists, physicians, the pharma industry, regulatory authorities and, most importantly, patients). Disruptive innovation should lead to every clinical site being a research site, with all necessary quality checks and research as part of the standard of care. The healthcare system should be integrated into an intuitive RWE-generation system, with clinical research and clinical care going hand in hand. Beyond an ad hoc creative flash of genius (necessitated by a pandemic), sustained momentum will be needed to leverage the knowledge gained from programs such as ‘Operation Warp Speed’ (initiated by the US government to accelerate COVID-19 vaccine development). My personal view is that every major disease needs a ‘Moonshot’ program and every rare disease should have an ‘Operation Warp Speed’—both with clearly identified, sustainable goals to improve population health and address equity, diversity and global access to therapies. Methodological advances and future AI-based analyses of all data will provide deep evidence to realize the goal of personalized medicine— that is, to offer the right treatment to the right patient at the right time.
References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023 TheNextGenerationofEvidencebase | Vivek Subbiah | The Next Generation of Evidence-based Medicine | 2023 |