How pharmaceutical companies can benefit by using data from secondary sources throughout the drug development cycle
In one of our recent Stanton Chase Boardroom debates, Lieven Annemans, Senior Professor of Health Economics at the Faculty of Medicine at Ghent University in Belgium, examined why there’s a need in healthcare to use real world data and real world evidence. Real world data isn’t collected through conventional randomized controlled trials, but instead from existing secondary sources such as databases of national health services and health insurers, patient and population surveys, patient chart reviews, observational cohort studies, pragmatic clinical trials, and registries. Analyzing this data yields real world evidence about the actual usage, benefits, and risks of a product. Our discussion then looked at the increased interest in the use of real world evidence as part of the continuum of evidence generation for innovative medicines and health technologies.
The Challenge of Proving the Value of a New Treatment
In countries that have universal healthcare such as Belgium and the U.K., healthcare policy has three goals — quality, solidarity, and sustainability. However, these objectives frequently conflict with one another. For example, if a new drug is developed, it can enhance the quality of care in a specific disease area — but if it’s expensive, it’s not sustainable. So, the policy makers determine that the drug must be paid for out of pocket — at the expense of solidarity, because only those who can afford it will receive the new treatment.
Healthcare systems need innovative treatments that address important health needs, offer a benefit to patients, the healthcare system, or both, and are cost-effective and affordable within the healthcare budget. When evaluating a new treatment, its cost and health effect are compared to those of existing methods of care. Subsequently, it can be placed in one of three positions. It can be dominant, meaning that it would save the healthcare system money, for example by avoiding hospitalizations. It can be much more expensive without improving the care, which means it’s not cost-effective. Finally, it can be cost-effective, meaning that it may cost more than the current care but delivers significant health benefits to patients.
To evaluate the cost-effectiveness of a new drug or technology, there needs to be a threshold that depends on the cost of the medicine and the actual improvement to the patient’s quality of life. In some countries, like the U.K., there’s an official threshold of £30,000, but in other countries there isn’t yet an official threshold.
When it comes to approving a new drug or technology, the challenge is the uncertainty regarding its value. Healthcare systems and funding organizations need to know whether or not it provides sufficient health benefits at a reasonable price. Yet without going to market, pharmaceutical companies can’t obtain sufficient data to prove the long-term efficacy and value of an innovative treatment.
Of course, pharmaceutical companies perform clinical trials, get authorization from the European Medicines Agency, and construct predictive models as to the long-term outcomes of the treatment. Yet clinical trials are insufficient: the populations are artificial, the medical management is artificial, the trials are too short, and there’s the question of participation bias — i.e. study participants behave differently than normal because they feel “special.”
The Value of Real World Evidence
To provide a comprehensive overview of the efficacy and cost-effectiveness of a new treatment, real world evidence is needed. In general, pharmaceutical companies focus primarily on data about the drug or technology they’re currently developing. However, it’s important to understand that there’s significant value in the real world evidence about how patients currently progress with their disease. That can be leveraged to examine the value deficit — or in what way current treatments are lacking. That same real world evidence — obtained from secondary sources — can be used to determine how the new treatment can improve patients’ lives and add value. Then when the treatment is approved for use and goes to market, more real world evidence needs to be collected to ascertain whether or not it actually yields the expected results. In short, real world evidence should be utilized throughout all stages of the innovation cycle.
Professor Annemans and his colleagues have developed a new initiative called TRUST – 4RD — a tool for reducing uncertainties in sourcing evidence for specialized treatments for rare diseases. The concept can also be applied to a broader scope. This tool aims to reduce uncertainties by defining and prioritizing evidence gaps and how they will impact the value of a treatment. Based on these findings, pharmaceutical companies must engage in an iterative dialog with payers to agree on study designs that can help reduce the evidence gaps by collecting more data — both experimental data and real world evidence. With this model, data from clinical trials and real world evidence aren’t in competition — instead, they should be used to complement each other.
In practice, reducing uncertainty in this manner will require the pharmaceutical industry and the health care systems or public knowledge assessment bodies to initiate a dialog very early on in the innovation cycle. This will facilitate discussions that result in joint decision making about the value and pricing of new treatments. Based on these decisions, outcome- based contracts can be issued. For example, after a temporary approval of a new treatment, health systems can utilize real world evidence to determine if it is cost-effective and revise the reimbursement accordingly. At the same time, if the treatment doesn’t live up to expectations, the pharmaceutical company will reimburse the healthcare system.
The Benefits of Leveraging Real World Evidence
Utilizing real world evidence in the innovation cycle offers several distinct benefits. It will enable the generation of additional insights before and after the launch of a new drug or health technology. This in turn will help ensure that the industry only invests in the development of new treatments that add value. In addition, it will inform dynamic price setting in relation to the actual value of medicines and health technologies. Finally, it will help optimize the appropriate use of treatments in daily practice.
Obstacles to the Use of Real World Evidence
Thanks to the availability of more data and more powerful analytics, pharmaceutical companies can obtain large amounts of real world data that can help them make more realistic and data-driven decisions. Nevertheless, while real world data is available, there’s still a long way to go to ensure that real world evidence is accurate and comprehensive. Data from “pragmatic trials” is not true real world data. Utilizing registries and observational cohort studies is costly and poses a significant administrative burden. In patient and population surveys, there’s a selection bias — plus, people report what they think they do instead of what they actually do. Reviewing patient charts is extremely resource intensive, while leveraging databases of medical records can reveal data gaps. And last but certainly not least, to gain access to accurate, comprehensive data, countries need unified health systems where a single input updates the data across all relevant modules.
Moreover, it should be clear that low quality or incorrectly analyzed data shouldn’t be used. Additionally, it’s counterproductive to use real world data for the wrong purpose or at the wrong time. In short, the question shouldn’t be, “We have data — what shall we do with it?” Instead, we should ask ourselves, “What data do we need and when do we need it to answer the questions that can’t be answered via a clinical trial?”
About the Author
Tamara Severi is the Global Practice Leader Life Sciences & Healthcare and a Partner of the Stanton Chase Brussels office. With a background in the pharmaceutical industry, Ms. Severi joined Stanton Chase in 2006 and successfully built the firm’s Healthcare practice from the ground up. With more than 11 years of experience in both domestic and international executive search, she has developed significant expertise in the areas of Life Sciences, Manufacturing, and Consumer Products. In addition, she’s an expert member of the international Healthcare Practice Advisory Group. Ms. Severi holds a master’s degree in Molecular Biology from the University of Leuven and a doctoral degree in Medical Sciences from the Internal Medicine department of UZ Gasthuisberg Leuven. In addition, she completed a FWO post-doctoral.