Evidence map›Paper›PMID 38148384›Full record

ArticlePharmaceutical research2024

An In Silico Platform to Predict Cardiotoxicity Risk of Anti-tumor Drug Combination with hiPSC-CMs Based In Vitro Study.

Lan Sang, Zhengying Zhou, Shizheng Luo, Yicui Zhang, Hongjie Qian, Ying Zhou, Hua He, Kun Hao

Abstract read
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Article in Pharmaceutical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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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

9 citing papers in PubMed.

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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.

Lan Sang *State Key Laboratory of Natural Medicines, Jiangsu Province Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.
Zhengying Zhou *Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.
Shizheng LuoCenter of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.
Yicui ZhangState Key Laboratory of Natural Medicines, Jiangsu Province Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.
Hongjie QianSchool of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China.
Ying ZhouDepartment of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, China.
Hua HeCenter of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China. huahe_cpupk@cpu.edu.cn.
Kun HaoState Key Laboratory of Natural Medicines, Jiangsu Province Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China. haokun@cpu.edu.cn.

Funding

111 Incubation Project BC2018024Major Discipline Academic and Technical Leaders Training Program of Jiangxi Province 20212BCJ23025National Natural Science Foundation of China 81773826National Natural Science Foundation of China 81973391
6 · The paper itself

Abstract

objectiveAntineoplastic agent-induced systolic dysfunction is a major reason for interruption of anticancer treatment. Although targeted anticancer agents infrequently cause systolic dysfunction, their combinations with chemotherapies remarkably increase the incidence. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a potent in vitro model to assess cardiovascular safety. However, quantitatively predicting the reduction of ejection fraction based on hiPSC-CMs is challenging due to the absence of the body's regulatory response to cardiomyocyte injury.

methodsHere, we developed and validated an in vitro-in vivo translational platform to assess the reduction of ejection fraction induced by antineoplastic drugs based on hiPSC-CMs. The translational platform integrates drug exposure, drug-cardiomyocyte interaction, and systemic response. The drug-cardiomyocyte interaction was implemented as a mechanism-based toxicodynamic (TD) model, which was then integrated into a quantitative system pharmacology-physiological-based pharmacokinetics (QSP-PBPK) model to form a complete translational platform. The platform was validated by comparing the model-predicted and clinically observed incidence of doxorubicin and trastuzumab-induced systolic dysfunction.

resultsA total of 33,418 virtual patients were incorporated to receive doxorubicin and trastuzumab alone or in combination. For doxorubicin, the QSP-PBPK-TD model successfully captured the overall trend of systolic dysfunction incidences against the cumulative doses. For trastuzumab, the predicted incidence interval was 0.31-2.7% for single-agent treatment and 0.15-10% for trastuzumab-doxorubicin sequential treatment, covering the observations in clinical reports (0.50-1.0% and 1.5-8.3%, respectively).

conclusionsIn conclusion, the in vitro-in vivo translational platform is capable of predicting systolic dysfunction incidence almost merely depend on hiPSC-CMs, which could facilitate optimizing the treatment protocol of antineoplastic agents.

Indexed as

Antineoplastic AgentsInduced Pluripotent Stem CellsCardiotoxicityCells, CulturedDoxorubicinDrug CombinationsHumansMyocytes, CardiacTrastuzumabAntineoplastic AgentsDoxorubicinDrug CombinationsTrastuzumabcancer therapycardiac toxicityin vitro to in vivo translationpluripotent stem cellsquantitative systems pharmacology

Identifiers

PMID38148384
PMCPMC10879352

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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.