Evidence map›Paper›PMID 41332775›Full record

ArticlebioRxiv : the preprint server for biology2025

Rethinking the seven-day treatment-free interval in T-cell engager therapy using agent-based modeling.

Nina Obertopp, Matthew Froid, Shari Pilon-Thomas, David Basanta

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Nina ObertoppCancer Biology Ph.D. Program, University of South Florida, Tampa, Florida, USA.ORCID 0009-0006-5100-1590
Matthew FroidCancer Biology Ph.D. Program, University of South Florida, Tampa, Florida, USA.ORCID 0009-0001-1231-7297
Shari Pilon-ThomasDepartment of Immunology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.ORCID 0000-0001-7785-3034
David BasantaDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.ORCID 0000-0002-8527-0776

Funding

Predict radiation-induced shifts in patient-specific tumor immune ecosystem composition to harness immunological consequences of radiotherapyU01CA244100 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ENDERLING, HEIKO, PILON-THOMAS, SHARI · 2020 to 2025
$2.6M
NCI NIH HHS U01 CA244100
6 · The paper itself

Abstract

Background: The CD3/CD19 bispecific T cell engager (TCE) blinatumomab has shown efficacy in relapsed/refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL), but response rates are often limited by T cell exhaustion. Recent preclinical studies suggest that incorporating treatment-free intervals (TFIs) into dosing schedules may enhance therapeutic outcomes. Methods: To systematically evaluate alternative TFI strategies, we developed an agent-based model (ABM) of tumor-T cell interactions under various blinatumomab dosing regimens. The model was calibrated using published Results: Our ABM recapitulates experimental observations showing that a 7-day TFI improved T cell function over continuous dosing during the initial 28-day treatment period. However, when simulations were extended to a full 42-day cycle to mimic clinical regimen, this advantage was lost. In contrast, shorter TFIs consistently outperformed both 7-day and continuous schedules, leading to superior tumor control at all timepoints. A translationally oriented Monday-through-Friday (MO_FR) regimen also achieved comparable benefits. Conclusions: Our results indicate that the empirically tested 7-day TFI schedule may not be optimal. TFI with shorter intervals as well as translationally relevant schedules such as MO_FR, may offer greater therapeutic benefit. This work demonstrates the value of ABM in preclinical immunotherapy design and supports model-guided refinement of TCE dosing strategies prior to clinical translation. Future work will focus on validating these predictions in more complex

Identifiers

PMID41332775
PMCPMC12667981

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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.