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Do You Have the Data to Benefit from a Post-Keytruda Approval Market?

Genomic Testing Is Necessary to Identify the Right Patients for Treatment. In late May, the oncology market was riveted by the FDA’s approval of Keytruda (pembrolizumab) for adult and pediatric patients with any solid tumor with a specific biomarker referred to as microsatellite instability-high (MSI-H) or mismatch-repair deficient (dMMR)1. Following that announcement, Loxo Pharmaceuticals became the media darling of the American Society of Clinical Oncology meeting, after sharing its preliminary results for larotrectinib (LOXO-101), a candidate for cancers with a different biomarker, TRK or NTRK fusions2. But for all the publicity and speculation about pharmaceutical companies expanding their R&D for “tumor-agnostic” drugs, the in vitro diagnostics (IVD) industry could be the real winner.

This point is supported by the title of an article in MIT Technology Review by Emily Mullin, “Promising New Cancer Drugs Won’t Go Far Unless Everyone Gets Genetic Testing”3. The article underscores the substantial barriers that remain for precision medicine, while simultaneously highlighting the tremendous opportunity for the IVD industry. To make targeted therapies work, genomic testing is necessary to identify the right patients for treatment. In patients without the “right” mutation, a targeted drug may be no better than a placebo, or worse yet, could lead to negative outcomes for patients due to serious side effects.

here are two main barriers to widespread adoption of genetic testing: Insurers refusing to pay for testing, which leaves patients shouldering the cost (or deciding not to have testing at all), and operational issues that keep doctors from being able to order the tests in a timely, efficient manner. The former issue is one the IVD industry has the potential to quickly change.

A variety of factors influence a payer’s coverage decision for diagnostic tests. These include existing clinical guidelines for the test, FDA approval status, competitors’ coverage determinations, and technical evidence assessments. For example, the CDC’s Evaluation of Genomic Applications in Practice and Prevention (EGAPP) working group, active from 2004-2014, used a framework that included analytical validity, clinical validity, and clinical utility4. Health technology assessments (HTAs), performed in-house or through third-party organizations, form the basis of evidence for coverage policy decisions. Understanding how they are performed and what data are desired is essential for IVD developers5. At the very least, HTAs will look for evidence supporting the analytical validity and clinical validity of a test.

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