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Record W7117296119 · doi:10.1016/j.iotech.2025.101450

251P Final results of the FAK-PD1 phase I/IIA study of FAK (defactinib) and PD-1 (pembrolizumab) inhibition in advanced solid tumours

2025· article· en· W7117296119 on OpenAlexfundno aff
S.N. Symeonides, T.R.J. Evans, D. A. Fennell, V. Coyle, I. Karydis, A. Oswald, L. Sweeting, C. Macbride, J. McQueen, A. Coleman, T. Wynn, K. Boukas, A. Serrels, C.H.H. Ottensmeier

Bibliographic record

VenueImmuno-Oncology Technology · 2025
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsnot available
FundersNIH Clinical CenterUniversity of California, San DiegoGenentechSierra OncologyIpsenServierWeill Cornell Medical CollegeNational Institute for Health and Care ResearchSeagenSidney Kimmel Comprehensive Cancer CenterPfizerModernaNuCanaIncyteBoston PharmaceuticalsCancer Research UKVerastem OncologyAmgenBarbara Ann Karmanos Cancer InstituteBeiGeneLes Laboratories Pierre FabreMoffitt Cancer CenterSanofiExelixisAstellas PharmaEisaiThomas Jefferson UniversityJohns Hopkins UniversityCelgeneInstitut National Du CancerAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsPhase (matter)CancerSolid tumorCytotoxicity

Abstract

fetched live from OpenAlex

Focal Adhesion Kinase (FAK) is a key intracellular mediator of cell contact interactions, involved in tumour migration, invasion & survival, and recruitment of immunosuppressive cells. In vivo, FAK inhibition can remodel the tumour immune microenvironment, synergising with Programmed cell death receptor 1 (PD-1) blockade. This trial combined defactinib (Verastem), a small molecule FAK inhibitor, with pembrolizumab (MSD, pembro), an anti-PD-1 antibody, for immunotherapy-naïve patients with advanced solid tumours.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.386
Teacher spread0.365 · 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 designNon-randomized trial
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

Citations0
Published2025
Admission routes1
Has abstractno

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