The Transformation to Value-based, Personalized Healthcare—Implications for Translational and Clinical Research

Brett J Davis, Jonathan Sheldon
iHealth Connections, 2011;1(1):24–7
pdf icon Please loginor registerfor a pdf version ejournal view ejournal

Abstract

The current paradigms for healthcare provision and pharmaceutical R&D are being challenged by several macroeconomic trends that will drive a convergence of healthcare and life sciences ecosystems. The paradigm shift will transform translational research and put health sciences firmly on the road toward delivering personalized healthcare. Intelligent use of longitudinal healthcare data, and the potential of next-generation gene sequencing as a unifying platform that accelerates drug discoveries and ushers in the biomarker era, will push personalized healthcare forward. Many of the advances have been enabled by the growing power of healthcare information technology. However, although many of the current systems are good at executing and automating the transactional tasks they were designed to perform, they are often siloed and proprietary and lack the facility to integrate, analyze, and visualize data as a whole, across populations and at the individual level. The new healthcare delivery paradigm will require an unprecedented collaborative environment that provides data for an integrated view. This will need an investment in context-specific analytics platforms that leverage the valuable data to support translational research.
Acknowledgment: Editorial assistance was provided by Touch Briefings.
Support: The publication of this article was funded by Oracle Health Sciences.
Disclosure The authors have no conflicts of interest to declare.
Correspondence: brett.davis@oracle.com
Convergence in Healthcare and Life Sciences

Several macroeconomic trends are challenging the current paradigms for healthcare provision and pharmaceutical research and development (R&D). As a result, the traditional axioms will be transformed as healthcare and life sciences ecosystems intersect to deliver a framework for healthcare based on ‘value’ associated with outcomes for individual patients. The factors influencing this era of change include:

• unprecedented pressures on the life sciences industry;
• an evolving regulatory compliance landscape;
• the increased focus on safety and pharmacovigilance;
• the shift towards value-based reimbursement in healthcare;
• inefficiency in healthcare delivery systems;
• the need for healthcare providers to compete on cost and quality; and
• the increasing adoption of healthcare information technology (IT).

The Pressures on Life Sciences

In the life sciences sector, despite increasing financial investment in pharmaceutical R&D, innovation has reached a plateau. The number of new drugs from R&D pipelines has declined since the high of 2004,1 leading many to conclude that the ‘easy’ targets have been discovered. Furthermore, the impact of the patent cliff on the industry has also highlighted the fragility of the blockbuster model, which the industry has recognized as being unsustainable.2 At the turn of the millennium, the initial mapping of the human genome led to a flood of new science and optimism for accelerated progress in drug discovery. However, a decade later the reality is that, although there have been remarkable advances in our understanding of many diseases, the relevance and complexity of disease-associated targets bring significant challenges in drug discovery as well as the regulatory schemes overseeing the industry. Nevertheless, the real need to improve innovation and R&D productivity is driving a fundamental change in medical research that will see a convergence in healthcare and life sciences. By leveraging novel molecular tools and unlocking longitudinal healthcare data from a ‘real world’ setting to generate understanding about what works in a specific population, the transformation of R&D paradigms will have lasting implications for translational and clinical research. This convergence is particularly acute when viewed through the lens of healthcare data where, increasingly, the biopharmaceutical industry needs access to long-term, observational patient data not only for facilitating translational research and clinical development but also for supporting comparative effectiveness studies, safety studies, and pharmacovigilance.

References:
  1. New Drug Review: 2009 Update, FDA/CMS Summit December 2009. Available at: www.fda.gov/downloads/AboutFDA/CentersOffices/CDER/UCM192786.pdf (accessed March 18, 2011).
  2. Pfizer chief says growth is imminent, March 31 2010. Available at: www.nytimes.com/2010/04/01/business/01pfizer.html (accessed March 18, 2011).
  3. Vioxx (rofecoxib) questions and answers. Available at: www.fda.gov/Drugs/DrugSafety/PostmarketDrugSafetyInformationforPatientsandProviders/ucm106290.htm (accessed March 18, 2011).
  4. Spear BB, Heath-Chiozzi M, Huff J, Clinical application of pharmacogenetics, Trends Mol Med, 2001;7(5):201–4.
  5. The Personalized Medicine Coalition, The case for personalized medicine, 2009. Available at: www.personalizedmedicinecoalition.org/sites/default/files/TheCaseforPersonalizedMedicine_5_5_09.pdf (accessed March 18, 2011).
  6. Pirmohamed M, James S, Meakin S, et al., Adverse drug reactions as cause of admission to hospital: prospective analysis of 18,820 patients, BMJ, 2004;329(7456):15–9.
  7. Institute of Medicine, Learning Healthcare System Concepts v2008. Available at: www.iom.edu/~/media/Files/Activity%20Files/Quality/VSRT/Learning%20Healthcare%20System%20Concepts%20v2008.pdf (accessed March 18, 2011).