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Record W4409627890 · doi:10.1158/1538-7445.am2025-4203

Abstract 4203: Discovery and development of a potent and highly selective ATR inhibitor IMP9064

2025· article· en· W4409627890 on OpenAlexaff
Sui Xiong Cai, Ning Ma, Xiaozhu Wang, Yangzhen Jiang, Mingchuan Guo, Ruiyu Zhou, Mu Chen, Ye Tian

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsImpact
Fundersnot available
KeywordsPharmacologyMedicine

Abstract

fetched live from OpenAlex

Abstract The ataxia telangiectasia and RAD3-related (ATR) kinase is a crucial component of the DNA damage response (DDR) and functions in conjunction with ataxia telangiectasia mutated (ATM). Loss or functional deficiency of ATM may lead to increased reliance on ATR signaling pathways. Preclinical and clinical studies have indicated a potential synthetic lethality between ATR inhibition and ATM deficiency. We have identified a novel, potent, and highly selective ATR inhibitor IMP9064. Herein we present its discovery and IND enabling in vitro and in vivo studies. IMP9064 is highly activity inhibiting ATR, and is highly selective among kinases. IMP9064 also shows potent cytotoxicity to a wide range of cancer cell lines. In addition, IMP9064 has a desirable PK profile in preclinical species. IMP9064 has demonstrated anti-tumor efficacy in human colorectal cancer CDX animal models with good dose-response tumor growth inhibition and tolerability. The results of in vitro and in vivo studies suggest that used alone or in combination with PARP inhibitor, WEE1 inhibitor, PKMYT1 inhibitor or HER2 ADC, IMP9064 has good anti-tumor activity and synergistic effect. IMP9064 has entered a phase 1/2 study to evaluate the safety and efficacy either as monotherapy or in combination with PARP inhibitor Senaparib in patients with advanced solid tumors (ClinicalTrials.gov Identifier: NCT05269316). The recommended phase 2 dose (RP2D) has been determined and IMP9064 is currently in expansion studies for selected tumors. Citation Format: Sui Xiong Cai, Ning Ma, Xiaozhu Wang, Yangzhen Jiang, Mingchuan Guo, Ruiyu Zhou, Mu Chen, Ye Edward Tian. Discovery and development of a potent and highly selective ATR inhibitor IMP9064 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4203.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.348
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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