ReviewCurrent issues in molecular biology2025
The Potential Use of Digital Twin Technology for Advancing CAR-T Cell Therapy.
Review in Current issues in molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- A decade of innovation in healthcare: Automation, bio-printing and digital twin technologies for personalized therapies.International journal of pharmaceutics: X · 2026Review
- Review
- Artificial Intelligence and the Transformation of Cell and Gene Therapy Development.Pharmaceutics · 2026Review
- Process Systems Engineering in Precision Medicine: Opportunities in Autologous CAR-T Therapy.Engineering in life sciences · 2026Review
- Plying potency assays for immunotherapy of solid tumors.Frontiers in immunology · 2026Review
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025Review
- Digital Twins in Personalized Medicine: Bridging Innovation and Clinical Reality.Journal of personalized medicine · 2025Review
- From data-driven cities to data-driven tumors: dynamic digital twins for adaptive oncology.Frontiers in artificial intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CAR-T cell therapy is a personalized immunotherapy that has shown promising results in treating hematologic cancers. However, its therapeutic efficacy in solid cancers is often limited by tumor evasion mechanisms, resistance pathways, and an immunosuppressive tumor microenvironment. These challenges highlight the need for advanced predictive models to better capture the intricate interactions between CAR-T cells and tumors to enhance their potential. Digital Twins represent a transformative approach for optimizing CAR-T cell therapy by providing a virtual representation of the therapy-tumor trajectory using high-dimensional patient data. In this review, we first define Digital Twins and outline the fundamental steps in their development. We then explore the critical parameters required for designing CAR-T-specific Digital Twins. We examine published case studies demonstrating a few applications of Digital Twins in addressing key challenges in CAR-T cell therapy, including their impact on clinical trials and manufacturing processes. Finally, we discuss the limitations associated with integrating Digital Twins into CAR-T therapy. As Digital Twin technology continues to evolve, the potential to enhance CAR-T therapy through precision modeling and real-time adaptation could redefine the landscape of personalized cancer treatment.
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.