Immuno-oncology has become a central focus for medical research firms and organizations across the country, and many are working on the same targets. Over the past five years, interest in immuno-oncology has spiked dramatically due to real changes in survival curves for many cancers and the extraordinary amount of money being made available. While all of this is good news for patients diagnosed with cancer, research and development teams are left wondering what their long-term strategy and their capital allocation should look like to pull ahead of the pack.
One of the biggest focuses of research and development teams is the checkpoint inhibitor. Anti-CTLA4 became the first checkpoint inhibitor to earn approval from the FDA five years ago. Today, at least 16 discrete PD1/PDL1 programs are in clinical testing phases, and the figure increases to 70 when studies in pre-clinical stages are included. More than two dozen CTLA-4 programs are also operating at present, not to mention research on emerging checkpoint interests like TIM3, OX40, and LAG3.
Among the four approved checkpoint inhibitors and two late-stage PD1/PDL1 programs, about 1,000 studies are currently registered with ClinicalTrials.gov, and this number does not include undisclosed investigator-initiated trials. Keytruda, one such approved medication, accounts for about 300 studies alone. This data shows that an incredible amount of resources are being invested in immuno-oncology, and with many organizations examining the same targets, the possibility of redundancy is high.
Competition in Clinical Trials Enrollment and Execution
With so many organizations looking into the same targets, one issue that will arise is the competition surrounding clinical trial enrollment and execution. With 1,000 ongoing clinical trials in the checkpoint space, between 50 and 100 thousand patients are already or will soon be enrolled in a trial. Enrolling patients in cancer trials has always presented challenges, but the recent spike in activity will only complicate matters further. A large bottleneck for access to top cancer centers already exists, and they will not likely run multiple similar clinical trials.
Most PD-1/PD-L1 trials happening today include the new therapy in combination with or without standard of care rather than a conventional regimen. While this approach is great for patients, differentiation becomes much harder for late-entry products. Also, other challenges in clinical trials emerge, such as defining response rates when RECIST tumor size and burden endpoints are no longer valid. Researchers need to create new definitions for immunological response rates and correlate them with predictions of overall survival to make clinical findings more accurate.
The Challenge of Product Efficacy Differentiation
As the space continues to grow, immuno-oncology researchers will also face the problem of production differentiation. Opdivo has beaten Keytruda in the marketplace because of the latter’s requirement of additional testing before prescribing. However, Keytruda has a massive clinical program to better define its use. With these two approved therapies, as well as the recent approval of Tecentriq, how will other PD-L1 drugs differentiate themselves enough to encourage physicians to prescribe them?
Most clinicians seem to think that Keytruda and Opdivo have a largely similar efficacy, but as other drugs enter the arena, will they behave the same? How will combinations and dosing/scheduling affect efficacy, and how researchers prove the differences? Differential activity is hard to predict from preclinical work, and nuanced differences tend to disappear in the reality of disease complexity. With such a hyper-competitive space, organizations need to remain diligent about when to double-down and when to fold because proving that one drug is better than another will require an overwhelming investment of resources, as well as an incredible number of patients.
Differentiation through Pricing of Therapies and Combinations
As drugs continue to enter the market, pricing will become a flash-point issue, especially as combinations emerge as the most effective approach. In this type of treatment plan, stacked pricing models will not likely prove successful.
Payers will not believe that both drugs are necessary and pay for both when the gains of a combination are only modest. For this reason, payers will likely place a lot of pressure on companies for competitive pricing packages. Payers may even strike deals with companies to use a certain drug as a foundational therapy in return for large rebates and discounts. Such behavior has happened in the past and with immuno-oncology’s large price tag, it would not be surprising to see a resurgence of these issues.
The pricing question may break new ground as pharmaceutical companies actually compete on pricing in a class of therapies, which has only rarely happened in the past. Success depends on pricing that takes several factors into account. For example, with survival curves extending longer, cancer patients may be on the therapies for longer periods, which should reduce prices to some extent. Payers will have a large influence on pricing and are likely to remain vigilant so that they are not caught off guard, as they were with recent HCV cures.