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Abstract CT207: Phase 1 first-in-human study of ABBV-151 as monotherapy or in combination with budigalimab in patients with locally advanced or metastatic solid tumors

2021· article· en· W3174572714 on OpenAlexaff
John D. Powderly, Toshio Shimizu, Patricia LoRusso, Albiruni Abdul Razak, Kathy D. Miller, Arjun Vasant Balar, Jordi Bruix, Loren S. Michel, Martha Blaney, Xiaowen Guan, Susan E. Lacy, Satwant Lally, Stacie Lambert, Rachel S. Leibman, Gregory Vosganian, Talia Golan, Anthony W. Tolcher

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineCommon Terminology Criteria for Adverse EventsTolerabilityOncologyAdverse effectInternal medicineResponse Evaluation Criteria in Solid TumorsClinical trialPhases of clinical research

Abstract

fetched live from OpenAlex

Abstract Background Glycoprotein-A repetitions predominant (GARP) regulates membrane-bound transforming growth factor β1 (TGFβ1), an immunosuppressive cytokine. ABBV-151 is a first-in-class monoclonal antibody (mAb) that binds to the GARP-TGFβ1 complex and blocks TGFβ1 release. Preclinical data demonstrated that targeting both GARP-TGFβ1 and programmed cell death protein 1 (PD-1) improved antitumor effects compared with anti-PD-1 alone. Combining ABBV-151 with the anti-PD-1 mAb budigalimab (ABBV-181) may enable a more effective antitumor immune response by reducing the immunosuppressive effect of TGFβ1. Trial design This is a multicenter phase 1, dose escalation and dose expansion study (NCT03821935) in patients (pts; ≥18 yr, Eastern Cooperative Oncology Group performance status 0-1) with locally advanced or metastatic solid tumors. The primary objective of dose escalation is to determine the recommended phase 2 dose (RP2D) of ABBV-151 as monotherapy or with budigalimab; dose expansion will assess the objective response rate of ABBV-151 ± budigalimab. Secondary/exploratory objectives include assessing preliminary efficacy, safety, tolerability, pharmacokinetics (PK), and evaluating potential pharmacodynamic and predictive biomarkers. Dose escalation of ABBV-151, guided by a Bayesian optimal interval design, will assess dose-limiting toxicities during the first 28-day cycle and will be utilized until the RP2D is defined. ABBV-151 + budigalimab (fixed dose) will start ≥2 dose levels below that proven safe for ABBV-151. Adverse events will be evaluated per National Cancer Institute Common Terminology Criteria v5.0. Response will be assessed using Response Evaluation Criteria In Solid Tumors (RECIST) v1.1 and iRECIST every 8 weeks. PK of ABBV-151 will be characterized. Saturation of GARP-TGFβ1 on platelets and PD-1 on CD4 T cells will be determined. Modulation of cytokines, chemokines, lymphocyte activity, and gene expression will be assessed in blood, while gene signatures and protein markers will be explored in tumor tissues. Baseline tumor characteristics will be retrospectively related to response. Enrollment initiated Mar 2019, with 37 pts enrolled as of May 2020. Citation Format: John Powderly, Toshio Shimizu, Patricia LoRusso, Albiruni Razak, Kathy Miller, Arjun Balar, Jordi Bruix, Loren Michel, Martha Blaney, Xiaowen Guan, Susan Lacy, Satwant Lally, Stacie Lambert, Rachel Leibman, Gregory Vosganian, Talia Golan, Anthony Tolcher. Phase 1 first-in-human study of ABBV-151 as monotherapy or in combination with budigalimab in patients with locally advanced or metastatic solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT207.

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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.064
GPT teacher head0.446
Teacher spread0.382 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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