Evidence map›Paper›PMID 38743253›Full record

ArticleCancer chemotherapy and pharmacology2024

Non-linear IV pharmacokinetics of the ATR inhibitor berzosertib (M6620) in mice.

Joshua J Deppas, Brian F Kiesel, Jianxia Guo, Robert A Parise, D Andy Clump, David Z D'Argenio, Christopher J Bakkenist, Jan H Beumer

Abstract read
In one paragraph

Article in Cancer chemotherapy and pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

8 authors.

Joshua J DeppasCancer Therapeutics Program, UPMC Hillman Cancer Center, University of Pittsburgh, Room G27e 5117 Centre Ave, Pittsburgh, PA, 15213, USA.
Brian F KieselCancer Therapeutics Program, UPMC Hillman Cancer Center, University of Pittsburgh, Room G27e 5117 Centre Ave, Pittsburgh, PA, 15213, USA.
Jianxia GuoCancer Therapeutics Program, UPMC Hillman Cancer Center, University of Pittsburgh, Room G27e 5117 Centre Ave, Pittsburgh, PA, 15213, USA.
Robert A PariseCancer Therapeutics Program, UPMC Hillman Cancer Center, University of Pittsburgh, Room G27e 5117 Centre Ave, Pittsburgh, PA, 15213, USA.
D Andy ClumpDepartment of Radiation Oncology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
David Z D'ArgenioDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
Christopher J BakkenistDepartment of Radiation Oncology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Jan H BeumerCancer Therapeutics Program, UPMC Hillman Cancer Center, University of Pittsburgh, Room G27e 5117 Centre Ave, Pittsburgh, PA, 15213, USA. beumerj@gmail.com.

Funding

VECTOR CORE FACILITYP30CA047904 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JOHN C. BYRD · 1988 to 2026
$158.0M
NRSA Training CoreTL1TR001858 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI RADOMSKI, THOMAS, RUBIO, DORIS M · 2016 to 2025
$11.1M
The Impact of ATR Kinase Inhibitors on CD8+ T Cell Expansion and Memory DevelopmentR01CA266172 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHRISTOPHER J. BAKKENIST · 2022 to 2026
$2.3M
Cancer Pharmacokinetics Research SpecialistR50CA211241 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PARISE, ROBERT · 2016 to 2025
$1.8M
NCATS NIH HHS TL1 TR001858NCI NIH HHS P30 CA047904NCI NIH HHS R01 CA266172NCI NIH HHS R50 CA211241NIH HHS P30CA047904NIH HHS R01CA266172NIH HHS R50CA211241NIH HHS TL1TR001858
6 · The paper itself

Abstract

backgroundThe Ataxia Telangiectasia and Rad3-related (ATR) protein complex is an apical initiator of DNA damage response pathways. Several ATR inhibitors (ATRi) are in clinical development including berzosertib (formerly M6620, VX-970). Although clinical studies have examined plasma pharmacokinetics (PK) in humans, little is known regarding dose/exposure relationships and tissue distribution. To understand these concepts, we extensively characterized the PK of berzosertib in mouse plasma and tissues.

methodsA highly sensitive LC-MS/MS method was utilized to quantitate berzosertib in plasma and tissues. Dose proportionality was assessed in female BALB/c mice following single IV doses (2, 6, 20 or 60 mg/kg). A more extensive PK study was conducted in tumor-bearing mice following a single IV dose of 20 mg/kg to evaluate distribution to tissues. PK parameters were calculated by non-compartmental analysis (NCA). A compartmental model was developed to describe the PK behavior of berzosertib. Plasma protein binding was determined in vitro.

resultsIncreased doses of berzosertib were associated with less than proportional increases in early plasma concentrations and greater than proportional increase in tissue exposure, attributable to saturation of plasma protein binding. Berzosertib extensively distributed into bone marrow, tumor, thymus, and lymph nodes, however; brain and spinal cord exposure was less than plasma.

conclusionThe nonlinear PK of berzosertib displayed here can be attributed to saturation of plasma protein binding and occurred at concentrations close to those observed in clinical trials. Our results will help to understand preclinical pharmacodynamic and toxicity data and to inform optimal dosing and deployment of berzosertib.

Indexed as

Ataxia Telangiectasia Mutated ProteinsDose-Response Relationship, DrugMice, Inbred BALB CAdministration, IntravenousAnimalsFemaleHumansIsoxazolesMiceNonlinear DynamicsPyrazinesPyrazolesTandem Mass SpectrometryTissue DistributionAtaxia Telangiectasia Mutated ProteinsAtr protein, mouseberzosertibIsoxazolesPyrazinesPyrazolesATR inhibitorBerzosertibPharmacokineticsPreclinicalProtein bindingTissue distribution

Identifiers

PMID38743253
PMCPMC11390321

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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.