Ensuring Drug Safety Through Biomarker-Based Epidemiology

The pharmaceutical industry values the sizing of populations by indication, age, sex, country, comorbidity, severity, subtype, or genetic profile. Such estimations aid in the production of calculations for sales forecasting, treatment potential, and reimbursement eligibility. The extent to which a pharmaceutical therapy works, and how it performs within safe and effective dosages, depends on the accuracy of the disease diagnosis and on the soundness of the trial methods. With a focus on drug safety using examples from the industry and from Decision Resources, we explore the use of biomarkers in epidemiology and the use of epidemiology in drug development.

Questions Answered

• The September 2010 ruling by the FDA focusing on safety signals is but one example of how regulators are increasing their scrutiny of and demand for drug safety. How can pharmaceutical companies be more proactive about how they monitor and assess drug safety? How can predictive biomarkers facilitate this research?
• Population-based studies provide the best-available data for estimating patient populations for bottom-up pharmaceutical market forecasting. Is it feasible to collect biomarker data through population-based epidemiology studies that feed patient forecasting?
• Epidemiological estimates published by Decision Resources for select indications have incorporated biomarker data into their methodologies. How has the use of biomarkers refined the epidemiology projections for breast cancer, for example?

Scope

• Strategies relying on biomarker and epidemiological data: drug safety, meeting regulatory standards, risk mitigation, postmarketing surveillance, pharmacogenomics, and drug labels.
• Example of biomarker-based epidemiology: Prevalence and incidence of breast cancer.
• Legislation and regulatory rulings: FDAAA; REMS; September 28, 2010, ruling on reporting of safety signals; good pharmacoepidemiology practices (GPP).
• Clinical trials and databases reviewed: STABILITY; SOLID-TIMI 52; Surveillance, Epidemiology and End Results (SEER).
• Expert commentary: Decision Resources epidemiologist Alison Isherwood, Ph.D., makes a strong case for using biomarker data to estimate the number of prevalent cases in breast cancer.

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