Evidence map›Paper›PMID 38820153›Full record

ReviewScience advances2024

Clinical translation of antibody drug conjugate dosing in solid tumors from preclinical mouse data.

Baron Rubahamya, Shujun Dong, Greg M Thurber

Abstract readReview
In one paragraph

Review in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Review
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  4. Preclinical Activity of the B7-H3-Targeting Antibody-Drug Conjugate Vobramitamab Duocarmazine in Pediatric Solid Tumors.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
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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

3 authors.

Baron RubahamyaDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0002-9116-0848
Shujun DongDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Greg M ThurberDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0001-7570-2080

Funding

Maximizing Antibody Drug Conjugate Efficacy through Multiple Mechanisms of ActionR35GM128819 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Greg Thurber · 2018 to 2026
$2.8M
NIGMS NIH HHS R35 GM128819
6 · The paper itself

Abstract

Antibody drug conjugates (ADCs) have made impressive strides in the clinic in recent years with 11 Food and Drug Administration approvals, including 6 for the treatment of patients with solid tumors. Despite this success, the development of new agents remains challenging with a high failure rate in the clinic. Here, we show that current approved ADCs for the treatment of patients with solid tumors can all show substantial efficacy in some mouse models when administered at a similar weight-based [milligrams per kilogram (mg/kg)] dosing in mice that is tolerated in the clinic. Mechanistically, equivalent mg/kg dosing results in a similar drug concentration in the tumor and a similar tissue penetration into the tumor due to the unique delivery features of ADCs. Combined with computational approaches, which can account for the complex distribution within the tumor microenvironment, these scaling concepts may aid in the evaluation of new agents and help design therapeutics with maximum clinical efficacy.

Indexed as

ImmunoconjugatesNeoplasmsAnimalsAntineoplastic AgentsCell Line, TumorDisease Models, AnimalDrug Evaluation, PreclinicalHumansMiceTranslational Research, BiomedicalTumor MicroenvironmentXenograft Model Antitumor AssaysAntineoplastic AgentsImmunoconjugates

Identifiers

PMID38820153
PMCPMC11141632

What OpenQuestion holds

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Registered trials

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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.