ReviewClinical and translational science2026
MIDD Evidence to Support Drug Regulatory Decisions in China.
Review in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The paper systematically reviews the technical guidelines for Model-Informed Drug Development (MIDD) issued by China's Center for Drug Evaluation (CDE), analyzing typical application cases of innovative drugs approved both in China and internationally to evaluate MIDD's critical role in supporting drug development and regulatory decision-making. As of December 2025, CDE has released seven specific guidelines focused on quantitative pharmacology models, covering the entire drug development lifecycle, including dose exploration and optimization, pediatric extrapolation, rare disease drug development, and exposure-response (E-R) relationship research. MIDD have been successfully applied across multiple domains in innovative drug development, optimizing dosing regimens through E-R analysis for dose selection; constructing comprehensive evidence chains via modeling and simulation for pediatric and rare disease drug development; supporting dosage rationality through population PK andPBPK models for dose adjustments in special populations; and characterizing complex in vivo processes in advanced therapeutic products through mechanistic models. While MIDD enhances R&D efficiency and reduces clinical trial burdens, the field in China currently faces three major challenges: data quality, prospective design, and validation standards. It is necessary to strengthen data collection, model validation, and full lifecycle management to promote the paradigm shift from "model-assisted" to "model-driven" drug development, thereby accelerating the global market entry of Chinese innovative drugs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.