SynthesisThe AAPS journal2021
A Systematic Review of the Efforts and Hindrances of Modeling and Simulation of CAR T-cell Therapy.
Synthesis in The AAPS journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Applying State-of-the-Art Survival Extrapolation Techniques to the Evaluation of CAR-T Therapies: Evidence from a Systematic Literature Review.Advances in therapy · 2021Pooled it
- Review
- Foundational Principles for the Quantitative Translation of T-Cell Therapeutics for Hematologic Malignancies and Immunology.Clinical pharmacology and therapeutics · 2026Review
- Microgravity-cultured glioblastoma organoids integrated with microfluidic chip for CAR-γδ T evaluation.Communications biology · 2025Article
- Spatiotemporal dynamics of tumor-CAR T-cell interaction following local administration in solid cancers.PLoS computational biology · 2025Article
- Computational modelling of CAR T-cell therapy: from cellular kinetics to patient-level predictions.EBioMedicine · 2025Review
- Multi-physiology modeling of the immune system in the era of precision immunotherapy.Frontiers in immunology · 2025Review
- Making drugs from T cells: The quantitative pharmacology of engineered T cell therapeutics.NPJ systems biology and applications · 2024Article
- A multi-scale semi-mechanistic CK/PD model for CAR T-cell therapy.Frontiers in systems biology · 2024Article
- Current advances in experimental and computational approaches to enhance CAR T cell manufacturing protocols and improve clinical efficacy.Frontiers in molecular medicine · 2024Review
- Manufacturing CD20/CD19-targeted iCasp9 regulatable CAR-TSCM cells using a Quantum pBac-based CAR-T engineering system.PloS one · 2024Article
- Modeling Patient-Specific CAR-T Cell Dynamics: Multiphasic Kinetics via Phenotypic Differentiation.Cancers · 2022Article
- Clinical Pharmacology Perspectives for Adoptive Cell Therapies in Oncology.Clinical pharmacology and therapeutics · 2022Review
- A Consideration of Fixed Dosing Versus Body Size-Based Dosing Strategies for Chimeric Antigen Receptor T-Cell Therapies.Clinical pharmacology in drug development · 2022Article
- Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T-cellular therapy development.Clinical and translational science · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chimeric antigen receptor (CAR) T-cell therapy is an immunotherapy that has recently become highly instrumental in the fight against life-threatening diseases. A variety of modeling and computational simulation efforts have addressed different aspects of CAR T-cell therapy, including T-cell activation, T- and malignant cell population dynamics, therapeutic cost-effectiveness strategies, and patient survival. In this article, we present a systematic review of those efforts, including mathematical, statistical, and stochastic models employing a wide range of algorithms, from differential equations to machine learning. To the best of our knowledge, this is the first review of all such models studying CAR T-cell therapy. In this review, we provide a detailed summary of the strengths, limitations, methodology, data used, and data gap in currently published models. This information may help in designing and building better models for enhanced prediction and assessment of the benefit-risk balance associated with novel CAR T-cell therapies, as well as with the data need for building such models.
Indexed as
Identifiers
What Socratic 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 Socratic graph.