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Diagnoses can be challenging for physicians. They often have to assess nonspecific patient symptoms, in combination with patient and family medical histories, to determine which of many possible conditions is responsible for the patient’s current ailment. Even after deciding on the diagnosis, physicians may need to make critical decisions regarding which management strategy to use to reduce symptoms and lower risk of disease progression.
Many clinical tests are now available to assist in diagnosis, disease management, and prognosis. But, after decades of medical research, plenty of gaps in the medical diagnosis and treatment landscape still exist. In the future, with continued improvements in medical knowledge, research practices, and technologies, many of these gaps can begin to close.
While a drug might perform extremely well in one patient population, the same drug might be unsuccessful or even detrimental in others. One familiar example of this is the US Food and Drug Administration (FDA)–approved biologics, programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) antibodies. These immunotherapies can significantly improve survival rates in cancer populations,1 although some patients have experienced hyperprogressive disease and have shorter overall survival than controls.2 Investigations suggest that slow-growing tumors might characterize these patients at baseline, but further research will be needed to sufficiently identify this patient population.
With increased concern over severe side effects, the interest in advancing personalized medicine continues to grow. Being able to identify and target patients who will respond well to treatments during clinical testing has the potential to speed clinical trials, improve treatment efficacy, reduce trial costs, and speed patient access to life-saving drugs. Potentially, personalized treatments might even boost consumer confidence in drugs, user compliance, and pharmaceutical industry profits, given a health care reimbursement system that bases payments on patient outcomes.
Identifying biomarkers associated with specific patient responses has thus become an industry focus. The Precision Medicine Initiative and Cancer Moonshot are a few examples of funding mechanisms that were established to promote personalized medicine,3,4 and the FDA is promoting theranostics (diagnostic testing for choosing a targeted therapy) via providing guidelines for the development of companion diagnostics (CDx).
Developing companion diagnostic tests
The FDA defines CDx as tests needed for the effective or safe use of therapeutics.5 The FDA recommends that these tests be developed alongside their companion therapeutics, so both products can be reviewed and considered together, enabling FDA staff to provide better comments regarding product development through clinical testing.
CDx development can be as challenging as developing a therapeutic. Biomarkers initially tested because of their association with pathogenesis might not be helpful for predicting therapy outcomes or might be useful for predicting favorable but not unfavorable outcomes. Disease pathogenesis is usually complex, with multiple defective proteins in multiple biochemical pathways contributing to disease presentation. This complexity makes it challenging to pin down a single biomarker predictive of drug efficacy for a reasonable percentage of the population.
Several preliminary investigations are needed to decide on diagnostic tool parameters, such as biomarkers, cutoffs, and assay design. The FDA recommends determining test parameters as early as possible to reserve trial samples for evaluating the diagnostic test. With clinical trial samples dedicated to refining cutoff values, there can be a need for additional bridging studies to prove the value of the CDx statistically.
Given the challenges surrounding CDx development, extensive coordination between those developing drugs and diagnostics is essential for productive clinical trials. Both teams need to work together to design their products and clinical trials so that the trial data generated can be used to analyze the quality of both products. Not having the diagnostic test approved at the same time as the therapeutic could delay approval of the therapeutic, although the FDA does make exceptions for some drugs deemed greatly needed and adequately safe to serve certain patient populations.
Future of diagnostics
Despite the challenges associated with CDx development, there are now 35 FDA-approved or cleared CDx, nine of which make use of antibodies.6 An array of antibody-based testing platforms are being used to further our understanding of disease pathogenesis, enabling further diagnostic tool development. These technologies provide a means to identify and test biomarkers for their association with favorable and unfavorable patient outcomes treated or not treated with therapeutics.
CDx enable robust patient stratification for drug efficacy subanalyses within specific patient subsets in clinical trials, with subsequent improvement to clinical trial success. Research is facilitating the development of diagnostics and CDx with the ability to improve the diagnosis, management, and prognosis across multiple diseases. With the extensive volume of ongoing clinical trials, there is an industry focus on personalized medicine, and with the growing availability of highly specific and revolutionary immunodiagnostic tests, the age of more personalized therapy is on the horizon.
1) Wang X, Bao Z, Zhang X, et al. Effectiveness and safety of PD-1/PD-L1 inhibitors in the treatment of solid tumors: a systematic review and meta-analysis. Oncotarget. 2017;8(35):59901-59914.
2) Champiat S, Dercle L, Ammari S, et al. Hyperprogressive disease is a new pattern of progression in cancer patients treated by anti-PD-1/PD-L1. Clin Cancer Res. 2017;23(8):1920-1928.
3) National Institutes of Health. Genetics Home Reference. What is the Precision Medicine Initiative? 2018 Oct 30 [2018 Oct 30]. https://ghr.nlm.nih.gov/primer/precisionmedicine/initiative
4) National Institutes of Health, National Cancer Institute. Cancer Moonshot implementation. 2018 Oct 22 [cited 2018 Oct 30]. https://www.cancer.gov/research/key-initiatives/moonshot-cancer-initiative/implementation
5) US Food and Drug Administration. Principles for the codevelopment of an in vitro companion diagnostic device with a therapeutic product. Draft guidance for industry and Food and Drug Administration staff. 2016 Jul 15 [cited 2018 Oct 30]. https://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM510824.pdf
6) US Food and Drug Administration. List of cleared or approved companion diagnostic devices (in vitro and imaging tools). 2018 Oct 24 [cited 2018 Oct 30]. https://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm301431.htm
7) Ray B, Liu W, Fenyö D. Adaptive multiview nonnegative matrix factorization algorithm for integration of multimodal biomedical data. Cancer Inform. 2017;16:1176935117725727.