Cutting costs could be the key to curing cancer

Cutting costs could be the key to curing cancer
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The first question often asked when learning someone has cancer is, “What kind of cancer is it?” In the era of immunotherapy, our view of cancer is changing. Today, the patient’s immune system is as important as the type of cancer when treating the tumor.

We no longer treat patients using a one-size-fits-all approach that subjects them to physically and financially debilitating treatments that may not work. Modern clinicians attempt to optimize the treatment for the patient using tumor-based biomarkers.

This approach is called precision medicine (PM). Even when a PM approach is used, there can be failures. When a PM approach is not used, the result is often expensive, lengthy and unsuccessful large-scale clinical trials. Modern drug developers must do better.


Consider the different outcomes of two checkpoint inhibitor trials using Merck’s Keytruda and Bristol-Myers Squibb’s Opdivo for patients with advanced non-small cell lung cancer. Merck used a PM, biomarker directed development strategy for Keytruda: Only patients with a predefined level of the PD-L1 biomarker were allowed into the trial. Bristol-Myers Squibb tested a broader, unselected population in its trial of Opdivo. Merck’s trial succeeded; Bristol-Myers Squibb’s failed. Merck’s PM approach to select patients may have made the difference.

The recent failure of Incyte’s Phase III trial of epacadostat combined with pembrolizumab (Keytruda) for people newly diagnosed with melanoma has raised some doubt about the future of combination immunotherapies.

That is the wrong conclusion to take from that study. I believe immunotherapy as part of combination therapy is the future of cancer therapy, but the industry cannot afford these high-profile failures. What can we learn from these failed trials and how do we apply these lessons for future success?

PM remains part of the solution, but it must catch up with our understanding of cancer therapeutics. Before PM, we had little insight into why a medication worked or failed. We now have greater understanding of how a specific patient, and their tumor, will react to a certain medications. Ideally, we use biomarkers to select the best therapy for a patient.

Traditional PM uses genetic and molecular cues to better characterize the patient’s disease to refine and define therapeutic decisions. But times have changed.

In the immunotherapy era, the biomarker signature extends beyond the tumor signature to the patient. Patient immunological biomarkers, that are independent of the tumor, can be measured and may provide important clues on how to treat the patient.

An example of traditional PM is the use of tumor biomarkers in deciding how to treat a woman with breast cancer. HER2 is a tumor-based biomarker. A woman diagnosed with HER2-positive breast cancer will receive a different treatment from a woman with HER2-negative breast cancer. PM based on HER2 status is a proven strategy that benefits patients.  Still, not all HER2-positive breast cancer patients respond to the targeted therapy. There must be more going on.

I propose that tumor biomarker profiling is not enough. I believe part of the problem may be the failure to use patient-based biomarkers, many of which are patient derived immunologic biomarkers.

Developers need to focus on an array of tumor-specific and patient-specific biomarkers, regardless of the cancer, to be successful. The smart use of tumor-derived and patient-derived biomarkers should better match therapies to patients. Let’s call this precision medicine 2.0 (PM 2.0). PM 2.0 should give greater insight into how an individual patient will respond to treatments and allow clinicians to match and combine traditional therapies with modern immunotherapies for the best possible outcome.

Developers must adjust our approach to designing clinical trials to take advantage of this new world. PM 2.0, a multiparameter biomarker directed approach, should allow for smaller clinical trials that enroll patients most likely to benefit from a specific treatment.

Increasing the precision of patient selection will avoid the high cost and disheartening failures caused by faulty, untargeted, non-precise trial design. In my opinion, by the time a drug reaches Phase III, trial design, not the drug design, is often the cause for the failed trial. Big companies may be able to afford such failures. Small companies, no matter how promising the therapies, cannot.

While any failure is disappointing for the companies, scientists and clinicians involved in the long march from bed-to-bedside, the real loser is the patient waiting for that medical breakthrough that may make a difference in their life. When a good drug fails because the trial design failed to take advantage of all of the scientific insight available, it is a tragedy for patients and their families.

Raymond J. Tesi M.D. is the CEO of INmune Bio, an immunotherapy drug development company based in La Jolla, California.