A recent AAPS webinar reports on the broad uses of biomarkers in drug development.
By Mark Crawford
Shashi Amur, Ph.D., senior scientific advisor for the Food and Drug Administration (FDA), presented a recent webinar entitled,
Role of Biomarkers in Supporting Personalized Medicine Efforts. The presentation describes different categories of biomarkers identified by the FDA-NIH Biomarker Working Group and discusses the role of biomarkers in drug development, with an emphasis on personalized medicine.
Individualizing Care
Drug development continues to move in the direction of personalized medicine, also known as precision medicine—where ideally the most effective therapy or treatment is determined by the genetic makeup of the patient. As defined by FDA-NIH, the ultimate goal of personalized medicine is to “tailor medical treatment to the individual characteristics, needs, and preferences of a patient during all stages of care, including prevention, diagnosis, treatment, and follow-up.” This involves identifying the physiologic/genetic strengths and weaknesses in a patient that, when addressed, can optimize the effectiveness of drug therapy for the patient.
Biomarkers are essential for the development of personalized or precision medicine. Biomarkers can be used in drug development (for example, patient selection) or in clinical practice, such as determining what devices or drugs are the best fit for patients, depending on the presence or absence of certain biomarkers.
Biomarkers
Biomarkers can be used in basic, translational, and clinical research and in clinical settings to facilitate medical product development and inform patient care decisions. A biomarker is a defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions.
“Biomarkers even have applications in food safety, environmental science, veterinary medicine, and other fields,” writes FDA. “The scientific and medical communities, patients, providers, patient advocacy organizations, industry, and regulators all play important roles in the development and application of biomarkers.”1
In the spring of 2015, the FDA-NIH Joint Leadership Council undertook the harmonization of terms used in translational science and medical product development, with a focus on terms related to the study endpoints and biomarkers. The end result—BEST: Biomarkers, EndpointS, and Other Tools—was published in 2016 and is a glossary of terminology and uses of biomarkers and endpoints in basic biomedical research, medical product development, and clinical care.
Biomarker Integration into Drug Development
Biomarkers are used in drug development to help define mechanisms of action, drug target selection, stratification, patient selection, enrichment, dose selection, safety assessment, efficacy assessment, molecular pathways leading to disease, and preclinical safety assessment.
Biomarkers are useful for enrichment in clinical trials and identifying the “right” patients to enroll in clinical trials. Studies have shown that biomarkers are key contributors to drug development success—for example, a study of 1,079 oncology drugs (1998–2013) by Biotechnology Innovation Organization showed that success rates for drugs developed with a biomarker was 24 percent, compared to just 6 percent for compounds developed without biomarkers, a four-fold increase.
Below are three key categories of biomarkers:
- Diagnostic biomarkers (to identify individuals with a disease or condition of interest or to define a subset of the disease)
- Prognostic biomarkers (indicate the likelihood of a clinical event, disease recurrence, or progression)
- Predictive biomarkers (to identify individuals who are likely to experience a favorable or unfavorable effect from a specific intervention or exposure)
Diagnostic Biomarkers
Diagnostic biomarkers are used to determine whether a patient has a particular medical condition for which treatment may be indicated, or whether an individual should be enrolled in a clinical trial studying a particular disease. Many diseases have subtypes with markedly different prognoses or responses to a specific treatment. Recently, subtypes of organ-specific cancers have been defined using tumor biomarkers, instead of histology—for example, breast cancer disease subtypes based on hormone-receptor subtypes (treatment responses higher in tumors that had these receptors). In another example, non-small-cell lung cancer subtypes have been identified based on specific molecular aberrations in ALK, EGFR, ROS-1 or BRAF.
Prognostic Biomarkers
Prognostic biomarkers are used to identify likelihood of a clinical event, disease recurrence, or progression in patients who have the disease or medical condition of interest. They are measured at a defined baseline, which may include a background treatment. For example, autosomal dominant polycystic kidney disease (ADPKD) is a hereditary disease marked by the development and growth of cysts over time, which causes increased kidney size. Total kidney volume has been qualified a prognostic factor for selecting patients with ADPKD, who are at high risk for progressive decline in renal function, for inclusion in interventional clinical trials.
Predictive Biomarkers
Predictive biomarkers are used to identify individuals who are more likely than similar individuals without the biomarker to experience a favorable or unfavorable effect from exposure to a medical product or an environmental agent. Establishing that a biomarker is predictive for an intervention’s effect generally requires a comparison of the intervention to a control treatment in individuals with and without the biomarker, usually in randomized trials. For example, certain cystic fibrosis transmembrane conductance regulator mutations can be used to select patients who are more likely to respond to ivacaftor in clinical trials evaluating treatment for cystic fibrosis. Another example is the human leukocyte antigen allele (HLA)–B*5701 genotype, which can be used to evaluate human immunodeficiency virus.
Predictive biomarkers can also be utilized to identify optimal/tolerated dose of drugs and to avoid adverse drug reactions in individuals. For example, tetrabenazine, a vesicular monoamine transporter 2 inhibitor, is indicated for the treatment of chorea associated with Huntington disease.
Patients who require doses of tetrabenazine greater than 50 mg per day should be first tested and genotyped to determine if they are poor metabolizers (PMs) or extensive metabolizers (EMs) by their ability to express the drug metabolizing enzyme, CYP2D6. This can affect dosage. The maximum daily dose for PMs is 50 mg with a maximum single dose of 25 mg; the maximum daily dose in EMs and intermediate metabolizers is 100 mg, with a maximum single dose of 37.5 mg.
Summary
Biomarkers can be used as drug development tools and can be incorporated into drug development through the drug approval process, scientific community consensus followed by regulatory acceptance, and biomarker qualification.
The BEST glossary provides terminologies relevant to biomarkers and describes seven categories of biomarkers, including diagnostic, prognostic, and predictive biomarkers, which contribute significantly to the development of personalized medicine. In particular, prognostic and predictive biomarkers can be used as enrichment factors in clinical trials to select the “right” patients for study. This approach helps reduce the number of individuals needed for clinical trials, increases clinical trial success rates, and reduces drug-development costs.
References
- S. Food and Drug Administration. The BEST Resource: Harmonizing Biomarker Terminology. Published June 2016. Accessed April 24, 2019.
Mark Crawford is a science and technology freelance writer based in Corrales, N.M.