The U.S. biomedical “innovation ecosystem”—encompassing the universe of stakeholders and activities directed toward understanding disease areas and developing novel treatments for them—is in a period of stress. As noted in the September release of a report by the President’s Council of Advisors on Science and Technology (PCAST), significant scientific advances over the last 25 years have moved us toward a better understanding of the biologic underpinnings of some of the most debilitating diseases that affect the U.S. population. While novel treatment options for many of these disease areas have been developed over this time period, recent history has demonstrated that advances in basic research have not consistently translated into substantial progress in the production of novel treatments and cures. The rate at which new biomedical products are entering the market has remained relatively constant over the last few decades, while the cost and time associated with the development of new products appears to have steadily increased. Seeing the advances in novel treatments that have been made during this time may lead many to believe that increased funding for early stage research and development can relieve the stress on the innovation ecosystem. In today’s economy, however, this notion may well prove unachievable as additional public funds are unlikely to be available and private investment is constricted. These trends point toward the need for novel strategies to improve productivity in biomedical innovation and efficiently move medical products from scientific discovery to clinical practice.
Consequently, it is more important than ever to identify ways that current levels of investment could have greater impact rather than simply increasing the level of spending. In other words, we need to be able to do more with less. While capital is needed for basic research and translation of bench-top findings to clinical science, we must create efficiencies in the development process and generate more robust, meaningful clinical evidence on the developing targets in order to make research and development investments go further and continue attracting greater investment. This is especially true for investments needed to support smaller startup companies, which often struggle to raise funds needed to move promising initial results from Phase 2 clinical trials into the larger and more expensive Phase 3 trials despite promising results. Identifying such hurdles and smartly deploying available resources to overcome them could result in increased efficiency of clinical development. It is important to note that pursuing efficiencies should not be taken to mean that the evidentiary or safety standards for moving a product to market ought to be lessened or changed; rather, efficiency in clinical development will help address challenges by allowing us to learn how products perform in a faster, less expensive manner.
In order to harness data and resources efficiently, it will be important for industry to continue exploring pre-competitive collaborations to better understand the nature of diseases and how to treat them. Ultimately, such arrangements provide greater benefit to those involved than any potential loss of competitive advantage associated with collaborating. By forming creative partnerships in which multiple competing companies come together to share data and explore tough questions, industry can not only make better use of the basic science tools at their collective disposal but also better integrate patient outcomes and post-market evidence into a more concerted industry-wide assessment of where innovative products are needed. In this way, data from across the drug discovery, development, and use spectrum can be fully utilized. A primary example of companies coming together in the pre-competitive space is the recently announced TransCelerate BioPharma, a group effort between 10 leading pharmaceutical companies to accelerate drug development and improve clinical trials.
Improvements in the research and clinical development of innovative medical products can also be supported by a learning health care system that is able to generate and harness more and better evidence to inform health care decision making post product approval. Given the current economic environment, it will be important for stakeholders to continue their work in establishing such a system and augmenting the impact that they can have on improving the biomedical landscape. With a true learning health care system, one that leverages the billions of pieces of information from the totality of electronic health care data generated during routine care (e.g., administrative claims, electronic health records, patient-reported data), we will benefit from a strong data environment that supports more efficient outcomes research, benefit/risk assessment, and health care decision-making. This would allow continual learning from patients’ experiences as they encounter the health care system to understand what treatments work best and for whom. A better understanding of what medical interventions can have substantial impact on improving quality of care and patient outcomes, including those of most importance to patients themselves, could then bring increased clarity to the ecosystem on what approaches are most promising and what areas are most in need of further innovation.
Finally, addressing the challenges to improving biomedical innovation must include a push to recognize and strengthen the aspects of translational and regulatory sciences that make them unique and indispensable in the product development process. Understanding the evidentiary requirements of each field will be paramount, especially as new methodologies, clinical trial designs, and types of evidence continue to force these fields to be nimble and rigorous in their analytics while maintaining a commitment to patient safety. It will be especially important for the fields of translational and regulatory science to engage academia and industry to recruit and train new generations of scientists capable of advancing their respective disciplines. In short, strengthening the ways in which basic, translational, and regulatory sciences inform and bolster one another will be key to ensuring a robust and efficient product pipeline.
For more information on these issues, including discussion by senior thought leaders from across the biomedical innovation ecosystem, please visit the Brookings event pages for “New Policy Directions for Biomedical Innovation ” and the “Annual State of Biomedical Innovation Conference.” There you will find archived webcasts, background documents, and further reading.
A Brookings report using NSSO data has shown that 15 per cent of Indians now have some form of health insurance compared to 1 per cent in 2004. Also, while nearly 62 per cent in Andhra Pradesh are covered, less than 5 per cent of people in UP have health insurance.