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Record W4311139822 · doi:10.1016/j.iotech.2022.100303

191P Preliminary biomarker and safety results of SQZ-PBMC-HPV at RP2D in monotherapy and combination with checkpoint inhibitors in HLA A*02+ patients with recurrent, locally advanced, or metastatic HPV16+ solid tumors

2022· article· en· W4311139822 on OpenAlexaff
Antonio Jimeno, N.R. Miselis, J.C. Park, J. Jennings, N. Dhani, U. Holtick, W.T. Iams, K. Rodabaugh, N. Nair, M. Kornacker, S.M. Loughhead, H. Bernstein, R. Zwirtes, Ruqian Ji, M. Warren, Aiman Al Sharei

Bibliographic record

VenueImmuno-Oncology Technology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineInternal medicineOncologyPharmacodynamicsImmunotherapyPeripheral blood mononuclear cellCancerAntigenImmunologyPharmacokinetics

Abstract

fetched live from OpenAlex

Cancer vaccines strive to produce robust, antigen-targeted, T cell-mediated anti-tumor responses, but have struggled to induce tumor regression in patients. The Cell Squeeze® system achieves efficient antigen presentation by delivering target antigens directly into the cytosol of a patient’s PBMCs. SQZ-PBMC-HPV is an autologous cell vaccine that presents epitopes of HPV16 viral oncoproteins on HLA-A*02 to induce CD8 T cell activation. Monotherapy data showed tumor inflammation markers that may indicate correlation with clinical response motivating expansion of the monotherapy and combination with immune checkpoint inhibitors (ICIs).

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.275
Teacher spread0.268 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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