Evidence map›Paper›PMID 42406159›Full record

ReviewJournal of pharmacokinetics and pharmacodynamics2026

Bridging the operational gap in population pharmacokinetic-pharmacodynamic analysis: an international perspective on the 2025 Chinese group standard.

Zheng Jiao, Jun-Jie Ding, Guang-Li Ma, Xuan Zhou, Lu-Jin Li, Kun Wang, Liang Li, Yu-Peng Ren

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of pharmacokinetics and pharmacodynamics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Zheng JiaoPharmacy Department, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, 241 Huai Hai West Road, Shanghai, China. zjiao@sjtu.edu.cn.ORCID http://orcid.org/0000-0001-7999-7162
Jun-Jie DingCentre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-6429-3178
Guang-Li MaDepartment of Clinical Pharmacology, Changchun GeneScience Pharmaceutical Co., Ltd., 88 Hongcao Road, Shanghai, China.ORCID http://orcid.org/0009-0005-7670-1246
Xuan ZhouDepartment of Clinical Pharmacology Modelling & Simulation, GSK, Building 7, 999 Huanke Road, Pudong, Shanghai, China.ORCID http://orcid.org/0000-0001-5750-1728
Lu-Jin LiState Key Laboratory of Integration and Innovation of Classic Formula and Modern Chinese Medicine, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai, China.ORCID http://orcid.org/0000-0003-2923-3206
Kun WangDepartment of Pharmacometrics, Shanghai Qiangshi Information Technology Co., Ltd., 3201 A Sino Life Tower, 707 Zhangyang Road, Pudong, Shanghai, China.ORCID http://orcid.org/0000-0003-2609-6058
Liang LiDepartment of Clinical Pharmacology, Gracell Biopharmaceuticals Inc., Building 3, Guilin Road, Xuhui District, Shanghai, China.ORCID http://orcid.org/0000-0002-4069-783X
Yu-Peng RenDepartment of Clinical Pharmacology and Pharmacometrics, Johnson & Johnson Innovative Medicine, Building A, Xinyan Mansion, 65 Guiqing Road, Xuhui District, Shanghai, China.ORCID http://orcid.org/0009-0000-6812-3742

Funding

National Natural Science Foundation of China 82073933
6 · The paper itself

Abstract

Population pharmacokinetic/pharmacodynamic (PPK/PD) modeling is a key component of model-informed drug development and model-informed precision dosing. Regulatory agencies in the United States, Europe, Japan, and China, together with the recently adopted ICH M15 guideline, have established high-level principles for the conduct, evaluation, and reporting of population modeling analyses. However, many practical implementation details are intentionally left to sponsors, investigators, and analysts. Although this flexibility accommodates diverse objectives, data structures, therapeutic areas, and decision contexts, it may also contribute to inter-analyst variability and limit the reproducibility, transparency, and consistency of PPK/PD practice. This review discusses the 2025 Chinese Pharmacological Society group standard for PPK/PD analysis from an international and implementation-oriented perspective. The standard describes a stepwise analytical lifecycle comprising pre-analysis preparation, base model development, final model establishment, model application, and reporting, with model evaluation embedded iteratively throughout the process. It also formalizes operational elements often implicit or under-specified in existing guidance, including a prospective Population Modeling Analysis Plan, distinction between exploratory and confirmatory analyses, prioritization of decision-relevant parameters, staged verification checkpoints, a five-element risk-management cycle, and ethical considerations related to data governance and equitable model application. We position the Chinese group standard as an analyst-level operational reference that complements, rather than replaces or duplicates, the decision-level assessment framework provided by ICH M15. Although developed within the Chinese regulatory and professional context, the structured workflow described in the standard may provide a practical reference for organizations seeking to improve the reproducibility, transparency, and consistency of PPK/PD analyses internationally.

Indexed as

Drug DevelopmentModels, BiologicalPharmacokineticsChinaHumansReproducibility of ResultsModel-informed drug developmentModel-informed precision dosingPharmacometricsPopulation pharmacodynamicsPopulation pharmacokineticsRegulatory scienceStandard operating procedure

Identifiers

PMID42406159

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.