Natalie LaFranzo, PhD - Vice President, Market Development
You should end your oncology drug development program today.
This may seem like a radical idea, especially after the billions of dollars that have been invested in the thousands of therapies in clinical trials today. But, hear me out.
What if we flipped the script, and in lieu of investing more into new therapies, took the tools we have today and used them to match therapies to patients, instead of patients to therapies? It seems subtle, but it’s important. Today, we have at our disposal an infinite number of oncology drugs and drug combinations - from chemotherapy and radiation, to more powerful targeted therapies, cancer vaccines, and immunotherapy drugs. Yet, when a patient arrives at the clinic and is diagnosed with cancer, they are still sequentially tested for single-analyte biomarkers that qualify or disqualify them for a specific therapy or clinical trial. This process is time-consuming, expensive, and often leaves the patient and clinician disappointed when treatment after treatment is unsuccessful (which we’ve discussed previously). However, this is still our approach today, likely based off the infrastructure that was built over the last 30 years and is designed to pump drugs into the market, rather than thinking critically about what is needed in a new era of precision medicine.
So, instead of adding another 500, 1000, or 2500 new drugs or drug combinations to the market, I propose we invest this energy and effort into characterization tools, specifically molecular diagnostics. But, let me be clear. The same lessons we’ve learned from drug development should be applied in this arena as well. First, let’s not go on a wild goose chase. While the industry seems to be chasing “big data”, we’re better off in the sweet spot where we can characterize disease in a clinically-relevant manner. This doesn’t mean using single-analytes; rather, let’s take a highly rational, multidimensional approach. This relies on tools developed using technologies such as next-generation sequencing and machine-learning to identify, validate, and deploy powerful biomarkers. Historically, simple single-analyte tests have been distributed, while high complexity tests have been centralized. The days of one laboratory and one machine running all samples for a clinical trial to ensure consistent results are over. We have to develop reagents and software tools that can be leveraged on sequencers across the world, with straightforward validation and control materials. Specifically, just as therapies are distributed across the world to the patients who need them most, the future requires robust, distributed high complexity testing to meet the needs of all those involved (including clinicians, payers, regulatory agencies, and most importantly, patients).
In many disease areas, testing has become not only multianalyte but also comprehensive, thus allowing a consolidation of testing and a more global view of what is happening in the patient. This move argues for testing first, and treatment consideration second. This sounds so obvious and most would assume this is how the industry is positioned today, but if that was the case would diagnostics really be referred to as “companion diagnostics”? In order for precision medicine to become a reality, we need to start thinking of drugs as companion therapies. We’ll take our most sophisticated, reliable technologies and collect valuable information about a patient’s molecular profile BEFORE we consider which treatments to pursue. This is really the goal of precision medicine - letting the patient and the biology inform treatment decisions. But, it has been unclear when we might arrive at a time when this is feasible. Today, we’re close...really close. And, companies that don’t start shifting their mindset will find themselves unprepared for this next stage in healthcare. And so, I encourage you to end your drug development program(s) today. Instead, let’s focus on moving taking the powerful molecular information we can collect about patients, their tumor or disease, and their response to a therapy, and let’s build a precision medicine approach that has a higher chance of success, more rational design, and better impact on patient outcomes.