ArticleThe AAPS journal2020
A Quantitative Systems Pharmacology Model of T Cell Engager Applied to Solid Tumor.
Article in The AAPS journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- Recent applications of quantitative systems pharmacology and machine learning models across diseases.Journal of pharmacokinetics and pharmacodynamics · 2022Pooled it
- An Overview on T-Cell Engagers: The Current Position in Both the Biological and Mathematical Context.Computational and structural biotechnology journal · 2026Review
- Revolutionizing cancer immunotherapy: T cell engagers beyond hematologic malignancies toward solid tumors.Frontiers in immunology · 2026Review
- Clinical Development of T-Cell Bispecific Antibodies: Review, Challenges, and Prospective Solutions in Solid Tumor.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Impacts of Antibody Structure and Mixtures on Receptor Signaling for Antibody-Dependent Cellular Cytotoxicity.The AAPS journal · 2025Article
- Predicting survival in prospective clinical trials using weakly-supervised QSP.NPJ precision oncology · 2025Article
- Whole-Body Physiologically Based Pharmacokinetic Modeling Framework for Tissue Target Engagement of CD3 Bispecific Antibodies.Pharmaceutics · 2025Article
- Quantitative Systems Pharmacology Modeling in Immuno-Oncology: Hypothesis Testing, Dose Optimization, and Efficacy Prediction.Handbook of experimental pharmacology · 2025Review
- Smart CAR-T Nanosymbionts: archetypes and proto-models.Frontiers in immunology · 2025Review
- Future Directions for Quantitative Systems Pharmacology.Handbook of experimental pharmacology · 2025Review
- Identifying biomarkers for treatment of uveal melanoma by T cell engager using a QSP model.NPJ systems biology and applications · 2024Article
- From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling.NPJ digital medicine · 2024Review
- Hyperthermia in Combination with Emerging Targeted and Immunotherapies as a New Approach in Cancer Treatment.Cancers · 2024Review
- Mechanistic PKPD modeling to describe cytokine release associated with CD3 T-cell engager therapies.Frontiers in immunology · 2024Article
- Development of bispecific T cell engagers: harnessing quantitative systems pharmacology.Trends in pharmacological sciences · 2023Review
- Mechanistically modeling peripheral cytokine dynamics following bispecific dosing in solid tumors.CPT: pharmacometrics & systems pharmacology · 2023Article
- A transcriptome-informed QSP model of metastatic triple-negative breast cancer identifies predictive biomarkers for PD-1 inhibition.Science advances · 2023Article
- Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.NPJ precision oncology · 2023Article
- A next generation mathematical model for the in vitro to clinical translation of T-cell engagers.Journal of pharmacokinetics and pharmacodynamics · 2023Article
- Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Cancer immunotherapy has recently drawn remarkable attention as promising results in the clinic have shown its ability to improve the overall survival, and T cells are considered to be one of the primary effectors for cancer immunotherapy. Enhanced and restored T cell tumoricidal activity has shown great potential for killing cancer cells. Bispecific T cell engagers (TCEs) are a growing class of molecules that are designed to bind two different antigens on the surface of T cells and cancer cells to bring them in close proximity and selectively activate effector T cells to kill target cancer cells. New T cell engagers are being investigated for the treatment of solid tumors. The activity of newly developed T cell engagers showed a strong correlation with tumor target antigen expression. However, the correlation between tumor-associated antigen expression and overall response of cancer patients is poorly understood. In this study, we used a well-calibrated quantitative systems pharmacology (QSP) model extended to bispecific T cell engagers to explore their efficacy and identify potential biomarkers. In principle, patient-specific response can be predicted through this model according to each patient's individual characteristics. This extended QSP model has been calibrated with available experimental data and provides predictions of patients' response to TCE treatment.
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What OpenQuestion holds
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.