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Updated: Dec 15, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Predicting Regulatory Product Approvals Using a Proposed Quantitative Version of FDA's Benefit-Risk Framework to
Stephen Sun1, Suzanne Heske2, Melanie Mercadel2
1Syneos Health, 1030 Sync Street, Morrisville, NC, 27560, USA. stephen.sun@syneoshealth.com.
Background:
Approval of regulated medical products in the USA is based upon a rigorous review of the benefits and risks as performed by the US Food and Drug Administration (FDA) staff of scientists and is summarized in a descriptive and qualitative format called the FDA's Benefit-Risk Framework (BRF). This present method highlights the key factors in regulatory decision-making, but does not clearly define the reason for its final approval.
Method:
This study proposes a quantitative version of FDA's BRF to calculate a Net-Benefit Score and a Benefit-Risk Ratio as a method to define a single-value summary of the tradeoffs between benefits and risks and allow comparisons among other products. In this retrospective review of five years of new molecular entities and new biologic (N = 185 products) regulatory decision-making, this proposed scoring system codifies and quantitates the information about a product's benefits, risks, and risk management information in a format that may predict why regulated medical products are approved in the USA.
Results:
Simple calculation of codified benefits, risks, and risk mitigations with numerical limits is proposed to provide a repeatable process and transparency for documenting the net-benefit of regulatory product approval.
Conclusion:
Use of a strict process of collecting, codifying, and analyzing public information to determine a Net-Benefit score and a Benefit-Risk Ratio is possible to anticipate regulatory product approval.
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