Evidence map›Paper›PMID 33615174›Full record

ArticleACS pharmacology & translational science2021

Quantitative Systems Pharmacology Modeling of PBMC-Humanized Mouse to Facilitate Preclinical Immuno-oncology Drug Development.

Huilin Ma, Minu Pilvankar, Jun Wang, Craig Giragossian, Aleksander S Popel

Open access · greenAbstract read
In one paragraph

Article in ACS pharmacology & translational science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 16% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

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  7. Assessing the performance of QSP models: biology as the driver for validation.Journal of pharmacokinetics and pharmacodynamics · 2024
    Review
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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

5 authors at 2 institutions in 1 country.

Huilin MaDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States.
Minu PilvankarBiotherapeutics Discovery Research, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, Connecticut 06877, United States.
Jun WangBiotherapeutics Discovery Research, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, Connecticut 06877, United States.
Craig GiragossianBiotherapeutics Discovery Research, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, Connecticut 06877, United States.
Aleksander S PopelDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States.
Boehringer Ingelheim (United States) · USJohns Hopkins University · US

Funding

Predictive experiment-based multiscale models of the tumor immune microenvironment and immunotherapy in breast cancerR01CA138264 · NCI · JOHNS HOPKINS UNIVERSITY · PI POPEL, ALEKSANDER S. · 2009 to 2023
$8.1M
Integrating bioinformatics into multiscale models for hepatocellular carcinomaU01CA212007 · NCI · JOHNS HOPKINS UNIVERSITY · PI EWALD, ANDREW JOSEF, FERTIG, ELANA · 2018 to 2022
$3.2M
NCI NIH HHS R01 CA138264NCI NIH HHS U01 CA212007
6 · The paper itself

Abstract

Progress in immunotherapy has resulted in explosively increased new therapeutic interventions and they have shown promising results in the treatment of cancer. Animal testing is performed to provide preliminary efficacy and safety data for drugs under development prior to clinical trials. However, translational challenges remain for preclinical studies such as study design and the relevance of animal models to humans. Hence, only a small fraction of cancer patients showed response. The explosion of drug candidates and therapies makes preclinical assessment of every plausible option impossible, but it can be easily tested using Quantitative System Pharmacology (QSP) models. Here, we developed a QSP model for humanized mice. Tumor growth dynamics, T cell dynamics, cytokine release, immune checkpoint expression, and drug administration were modeled and calibrated using experimental data. Tumor growth inhibition data were used for model validation. Pharmacokinetics of T cell engager (TCE), tumor growth profile, T cell expansion in the blood and infiltration into tumor, T cell dissemination from primary tumor, cytokine release profile, and expression of additional PD-L1 induced by IFN-γ were modeled and calibrated using a variety of experimental data and showed good consistency. Mouse-specific response to T cell engager monotherapy also showed the key features of

Identifiers

PMID33615174
PMCPMC7887858
OpenAlexW3108312356

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.