ArticleJournal for immunotherapy of cancer2025
Mechanistic data-informed multiscale quantitative systems pharmacology modeling framework enables the clinical translation and efficacy assessment of CAR-T therapy in solid tumors.
Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Rethinking Phase I units in the era of immuno-oncology: a three-layer framework.Journal for immunotherapy of cancer · 2026Review
- MIDD Evidence to Support Drug Regulatory Decisions in China.Clinical and translational science · 2026Review
- A Mechanistic Framework Integrating Renal QSP-PK-PD and Machine Learning for Baseline-Informed Stratification of Diuretic Resistance.The AAPS journal · 2026Article
- Article
- Mechanisms of T cell activation: Integrating signaling pathways, experimental models, and therapeutic implications.EXCLI journal · 2026Review
- Anti-CD19 CAR T-cell therapy for autoimmune diseases: from exploratory clinical trials to quantitative pharmacodynamic modeling development.Frontiers in immunology · 2026Review
- Combining mechanistic quantitative systems pharmacology modeling and patient-derived organoid testing in MET-aberrant non-small cell lung cancer for high-throughput combination efficacy analysis and personalized treatment design.Frontiers in pharmacology · 2025Article
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12 authors.
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Abstract
backgroundChimeric antigen receptor (CAR)-T cell therapy represents an innovative and potentially revolutionary modality in cancer treatment. Despite their great success in treating blood cancers, CAR-T therapies exhibit significantly lower effectiveness in treating solid tumors. Moreover, the preclinical-to-clinical translation of CAR-T therapies targeting solid tumors is still a challenging task because of their unique "live cell" nature and the substantial variability in patients' pathophysiology.
methodsWe have developed a multiscale quantitative systems pharmacology (QSP) model to facilitate the clinical translation of CAR-T therapies in solid tumors. Our mechanistic modeling framework integrates the essential biological features that impact CAR-T cell fate and antitumor cytotoxicity, from cell-level CAR-antigen interaction and activation, to in vivo CAR-T biodistribution, proliferation and phenotype transition, and finally to clinical-level patient tumor heterogeneity and response variability. This modeling framework has been calibrated and validated by multimodal experimental data including published preclinical and clinical data of various CAR-T products and original preclinical data of a novel claudin18.2-targeted CAR-T product LB1908.
resultsWe demonstrated the general utility of this framework in facilitating clinical translation and characterizing the paired cellular kinetics-cytotoxicity response of different antigen-targeting solid tumor CAR-T cell therapies. As an example, we generated model-based virtual patients and prospectively simulated the response to claudin18.2-targeted CAR-T therapies under different dosing strategies, including step-fractionated dosing and convenient flat dose-based regimens, to inform future clinical trial implementation.
conclusionsOur translational QSP platform offers an innovative pathway to integrate multiscale knowledge and inform clinical decision-making of novel solid tumor-targeting CAR-T therapies.
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