Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic.

Drug regulators around the world make decisions about drug approvability based on qualitative benefit–risk analysis. In this work, a quantitative benefit–risk analysis approach captures regulatory decision‐making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression‐free survival (PFS), and objective response rate (ORR) which are different than benefit–risk analysis based on overall survival (OS). Twenty‐three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit–risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit–risk framework.

The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB).

Drug regulators seek to make decisions regarding drug approvals based on analysis of the relevant benefits and risks. In this work, 25 US Food and Drug Administration (FDA) decisions on melanoma drugs were identified and analyzed based on clinical trial results published between 1999 and 2017. In each case, the benefits and risks of the new drug in each clinical trial relative to a comparator (typically the control arm of the same clinical trial) were quantified. The benefits and risks were analyzed using a common scale to allow for direct comparison. A sensitivity analysis was conducted using vemurafenib to explore the magnitude of uncertainty in the quantitative assessments. The associated FDA decision outcomes of the new drugs were consistent with the benefits and risks quantified in this work.Drug regulatory agencies base drug approval decisions on the benefits and risks of a drug (see representative quotations in Table S1). Benefit-risk assessment approaches 1,2 are valuable in providing a clear set of expectations and also have the potential to support the accessibility of safe and effective medicines to patients over the product lifecycle as new information becomes available. [3][4][5] As part of the Prescription Drug User Fee Act and the US Food and Drug Administration's (FDA) Safety and Innovation Act, the FDA committed to structuring their assessments of new drug applications and biological license applications as benefit-risk assessments. In prior work, a framework for such assessments was proposed 6 and used for analysis of FDA decision-making in new drug applications and biological license applications for the disease areas of non-small cell lung cancer (NSCLC) 7 and multiple myeloma. 8 In this work, that same approach is applied to the disease area of melanoma of the skin. In prior work on NSCLC 7 overall survival (OS) was used as the measure of benefit. In the prior work on multiple myeloma, 8 because FDA drug decisions were based primarily on other, non-OS metrics, 9 progression-free survival (PFS) was used as the common measure of benefit. In the present work, similar to prior work on NSCLC, 7 OS was used as the common measure of benefit.There were an estimated 1,169,351 people living with melanoma of the skin in the United States in 2014. 10 An estimated 91,270 new cases of and 9, 320 deaths related to melanoma of the skin were projected to occur in the United States in 2018. 11 Melanoma of the skin represented an estimated 5.2% of all new cases of cancer in the United States in 2017.Among patients newly diagnosed with melanoma, 84% are in the local (confined to the primary site) stage of the disease, 9% are in the regional (spread to regional lymph nodes) stage, 4% are in the distant metastatic stage, and the stage of 3% is unknown. The prognosis for melanoma patients varies by the stage of the disease at diagnosis. The 5-year relative survival of patients in the local, regional, and distant stages is 98.5%, 62.9%, and 19.9%, respectively. 10 With the advent of small molecule-targeted therapies...

Drug regulators such as the US Food and Drug Administration (FDA) make decisions about drug approvals based on benefit–risk analysis. In this work, a quantitative benefit–risk analysis approach captures regulatory decision making about new drugs to treat renal cell carcinoma (RCC). Fifteen FDA decisions on RCC drugs based on clinical trials whose results were published from 2005 to 2018 were identified and analyzed. The benefits and risks of the new drug in each clinical trial were quantified relative to comparators (typically the control arm of the same clinical trial) to estimate whether the benefit–risk was positive or negative. A sensitivity analysis was demonstrated using pazopanib to explore the magnitude of uncertainty. FDA approval decision outcomes for the clinical trials assessed were consistent and logical using this benefit–risk framework.