A multi-dimensional comparative study of 505(b)(2) NDAs approved by FDA and Class 2 NDAs approved by NMPA from 2017 to 2023: Uncovering trends, characteristics, and regulation of modified new drugs
Bibliographic record
Abstract
Modified new drugs are pivotal in advancing innovative therapies through repurposing existing therapeutic agents. The regulatory framework, including the pertinent regulations and policies, plays a crucial role in shaping the development and evolution of these drugs. This retrospective study systematically compared the regulatory approvals of modified new drugs via the 505(b)(2) new drug application (NDA) pathway in the United States (US) and Class 2 NDA pathway in China from 2017 to 2023, which focused on distinctions in registration classifications, availability, therapeutic indications, dosage forms, modifications, clinical advantages and clinical study designs. The findings indicate that the US has more detailed and comprehensive classification systems, as well as a higher number of approvals (417 vs. 99). Moreover, the modified new drugs approved in China still exhibit significant gaps in indication distribution, dosage forms, and modifications compared to those in the US. Notably, a greater proportion of confirmatory clinical studies were conducted for Class 2 NDAs (81.4 %) than 505(b)(2) NDAs (41.0 %), with a significant difference in the use of active controls (48.6 % in China vs. 26.4 % in the US, P = 0.002). Additionally, the combination of emerging technologies in modified new drugs presents both technical and regulatory challenges for authorities. It raises worthwhile questions about how regulators will evaluate medical products developed with entirely new technologies. Therefore, it is recommended that Chinese regulators refine registration classifications, reassess the positioning of modified new drugs, and expand the definition of clinical advantage within the policy and regulatory framework. These measures are essential for addressing unmet medical needs and fostering a conducive ecosystem for the advancement of modified new drugs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".