The Evolution of Health Research
Bridging the Gap Between Innovation and Scientific Evidence
Introduction
In the last decade, the commercial health industry has seen explosive growth, driven by an increasing demand for alternative, personalized solutions to health. Unfortunately, the scientific rigor behind many of these products has not kept pace with their innovation.
The purpose of this paper is to explore the historical landscape of commercial health research, highlighting its limitations, and proposing a new model that leverages advances in technology and available resources to elevate the quality and credibility of health-based research.
The Landscape of Commercial Health Research
The landscape of commercial health research has evolved significantly over the years in an effort to keep up with advancements in product development, scientific methodologies, and regulatory frameworks. Historically, health research has been predominantly run by academic institutions and contract research organizations (CROs), with a strong focus on traditional research methodologies like randomized controlled trials (RCTs).
Despite their strengths, traditional RCTs have limitations, particularly regarding cost, time, and applicability to real-world settings. The meticulous design and implementation required for these trials often result in high costs and extended timelines, making them less accessible to smaller companies. Moreover, the controlled environments of RCTs may not accurately reflect real-world conditions.
The integration of real-world evidence (RWE) into the health research landscape marks one significant shift. By leveraging data from electronic health records, wearable technology, and patient registries, researchers can gain insights into the effectiveness of interventions across diverse populations and settings.
Current Shortcomings of Traditional Research Methods
Reliance on outdated methodologies limits the ability to fully capture the impact of new health products in a rapidly evolving market.
Lack of Real-World Relevance
Traditional research conducted in controlled environments often does not accurately reflect real-world conditions, limiting generalizability.
High Costs & Time Constraints
RCTs are expensive and time-consuming, often taking years. This is impractical for companies looking to rapidly innovate.
Limited Personalization
Traditional research methods do not account for individual variability in response to health interventions.
Reliance on Self-Reported Data
Many studies rely on subjective self-reported data, which is prone to bias compared to objective biometric collection.
A New Model for Commercial Health Research
At the forefront of addressing these challenges is a need for a real-world, multifaceted, and personalized approach to health research. Continuous monitoring of health and biomarker data allows researchers to incorporate objective, real-world evidence into research models at the participant level.
The adoption of adaptive trial designs and digital health platforms can further streamline the research process. Adaptive trials allow for modifications as data is collected, enabling more efficient resource allocation. Digital health platforms facilitate remote monitoring, expanding access to a broader participant pool.
Conclusion
As the health and wellness market becomes increasingly more saturated, the need for credible, scientifically validated products is more important than ever. The time has come to evolve beyond traditional research methods and embrace a new paradigm that leverages the power of technology to validate innovative health products.
Ready to validate your health solution?
For inquiries or customized research design, please contact our clinical research team.
Contact ResearchReferences
- Singhal, S. and Ungerman, D. (2023) Healthcare’s next chapter: What’s ahead for the US healthcare industry. McKinsey.
- Kroeger, C.M., et al. (2018). Scientific rigor and credibility in the nutrition research landscape. American Journal of Clinical Nutrition.
- Gomis-Pastor, M., et al. (2024). Clinical validation of digital healthcare solutions: State of the art, challenges, and opportunities. Healthcare (Basel).
- IQVIA. (2019). The changing landscape of research and development. IQVIA.
- Sherman, R.E., et al. (2016). Real-world evidence - What is it and what can it tell us? NEJM, 375(23), 2293-2297.
- Dang, A. (2023). Real-world evidence: A primer. Pharmaceutical Medicine, 37(1), 25-36.
- Piwek, L., et al. (2016). The rise of consumer health wearables: Promises and barriers. PLoS Medicine.
- Pallmann, P., et al. (2018). Adaptive designs in clinical trials: Why use them, and how to run and report them. BMC Med 16, 29.