Analysis of post-marketing requirements for oncology drug conditional approvals in the United States and China

Abstract

Background: Conditional approvals, also known as accelerated approvals, have been introduced by many pharmaceutical regulators around the world, allowing innovative drugs to enter the market earlier on the basis of limited evidence. This research aims to systematically analyze and compare the post-marketing requirements for conditional approvals of oncology drugs in China and the United States. By collecting and categorizing different types of post-marketing requirements, this study seeks to elucidate how these requirements are proposed and discern the underlying logic and patterns.

Methods: This study delved into oncology drug approvals, encompassing FDA accelerated approvals (up to December 31, 2022) and NMPA conditional approvals (from 2017 to December 31, 2022). Leveraging review documents from FDA and NMPA, comprehensive data on product characteristics, all post-marketing commitments and requirements, and especially those related to confirmatory requirements were extracted. The analysis incorporated descriptive statistics, visualizations such as Upset plots, and thorough examination of confirmatory requirement timeframes.

Findings: This study examined 168 FDA accelerated approvals and 41 NMPA conditional approvals for oncology indications. Post-marketing requirements displayed diversity: FDA emphasized confirmatory studies, clinical pharmacology studies, and more, while NMPA predominantly focused on confirmatory studies. Confirmatory requirement timeframes indicated higher FDA-required completion times for new confirmatory trials compared to continued completion of original pivotal trials. In contrast, NMPA's requirement patterns were comparatively singular, with relatively fixed timeframes. FDA's evolving trend showed decreasing timeframes over time, suggesting an increasing demand for timely confirmatory data.

Interpretation: Conditional approvals offer a unique approach to bring potentially life-saving drugs to the market faster, despite limited supporting evidence. Our analysis of oncology drug conditional approvals in the U.S. and China reveals diverse post-marketing requirement patterns. This study provides valuable insights for regulatory decision-making in a dynamic pharmaceutical landscape. Balancing the risks and rewards of conditional approvals is crucial in ensuring both patient safety and timely access to innovative treatments.

Fig. 1

Study flowchart. The flowchart illustrates the inclusion and exclusion criteria applied to FDA accelerated approvals and NMPA conditional approvals analyzed in this study. FDA, Food and Drug Administration (the U.S.); NMPA, National Medical Products Administration (China); NDA, New Drug Application.

Fig. 2

Illustration of post-marketing requirement patterns. This set of Upset plots visually depicts the patterns of PMRs imposed by FDA and NMPA for conditional approvals. Each row in the plot represents a type of requirement, and the connections between solid points in different rows illustrate the combination patterns of different requirement types. Panels a-d correspond to FDA Initial Approval, FDA Expansion of Indication, NMPA Initial Approval, and NMPA Expansion of Indication, respectively.

Fig. 3

Comparison of timeframes for different confirmatory requirements. This figure depicts the specified timeframes for distinct types of confirmatory requirements by the FDA (a) and NMPA (b). The "One-trial" mode indicates the continuation of the original pivotal trial as a confirmatory requirement, while "New confirmatory trial" signifies the initiation of a new confirmatory trial. Each symbol in the figure represents an individual approval. The Mann-Whitney test was employed for intergroup difference analysis.

Fig. 4

Evolution of time periods for FDA accelerated approvals transitioning to regular approvals or withdrawals over time. This figure presents the temporal evolution of the time periods associated with the transition of FDA accelerated approvals to either regular approvals or withdrawals. Each data point represents an individual accelerated approval, with the x-axis indicating the date of accelerated approval and the y-axis representing the duration of the transition period. For those approvals that have not yet undergone transition, the figure illustrates the duration they have been in the accelerated approval state as of the analysis date (December 31, 2023). The trendlines depict the results of simple linear regression analysis.