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Abstract CT176: Pharmacokinetic/pharmacodynamic (PK/PD) relationships of the novel Treg depleter RG6292 in Phase Ia and Ib studies in patients with solid tumors

2023· article· en· W4365512264 on OpenAlexaff
Tamara Tanos, Kevin Smart, Valentina Gambardella, Kristoffer Staal Rohrberg, Michael Ong, Maria E. Rodriguez Ruiz, Jean‐Pascal Machiels, Miguel F. Sanmamed, Josep Tabernero, Anna Spreafico, Daniel J. Renouf, Stephen J. Luen, Rachel Galot, Bernard Doger, Emiliano Calvo, Aung Naing, Samira Curdt, Nicolas Staedler, Mike Flores, Enrique Gómez Alcaide, Chia-Huey Ooi, Michael Hettich, Sebastian Dziadek, Yuying Xie, Gabriel Schnetzler, Theresa Kolben, Linxinyu Xu, Vaios Karanikas, Christophe Boetsch

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsBC Cancer AgencyPrincess Margaret Cancer CentreOttawa Hospital
Fundersnot available
KeywordsPharmacokineticsPharmacodynamicsPopulationMedicineEffectorCmaxAntibodyImmune systemPharmacologyCancer researchImmunology

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION: Activated Tregs in the tumor micro-environment are correlated with poor outcomes, and are considered as key players in tumor immune-escape. So far, Treg depletion has not been successful in patients, either because adequate Treg depletion was not achieved or because Teff cells have either been impacted or depleted as well. RG6292 is the first anti-human CD25 antibody developed to specifically deplete human Tregs while preserving IL-2R STAT5 signaling and Teff activity. It has been optimized for ADCC and selective depletion of cells with high CD25 density (Treg). MATERIALS and METHODS: Adult patients with advanced solid tumors were given RG6292 i.v. Q3W as monotherapy (S1: NCT04158583) or in combination with atezolizumab 1200 mg Q3W (S2: NCT04642365) in a Ph1 dose escalation study. 76 pts have been treated at dose levels ranging from 0.3 mg to 165 mg in S1 and 48 pts at dose levels ranging from 0.3 mg to 160 mg in S2. In both studies a Bayesian logistic regression model with overdose control guided dose escalation was utilized. Data cutoff was May 27, 2022. Pharmacokinetic and pharmacodynamic analyses were undertaken in peripheral blood and tumor tissue. PK/PD modeling applied to Treg and Teff cells helped characterize and identify the optimal therapeutic window to ensure (1) relevant Treg depletion and (2) limited impact on T effector. RESULTS: RG6292 has a linear and time independent PK with no ADA detected. A Population PK-PD modeling approach was applied to Treg and Teff cells in the periphery. To predict the RG6292 effects in the tumor microenvironment (TME), the PK/PD relationships observed and characterized in the periphery for all cell subpopulations were considered the same, a tumor uptake factor of 15% was considered. At steady-state trough, a 70 mg Q3W dose was predicted to lead to 72% of patients with concentration above the Treg (%CD4) EC50 in tumor and 40% of patients with concentration above the Non-Treg (%CD4) EC50 in plasma. RG6292 induced a dose-dependent peripheral and intratumoral Treg depletion in on-treatment biopsies taken 28 days after initiation of treatment. Treatment did not appear to impact the number nor the functionality of intratumoral CD8 T cells nor any evident effect observed on PDL1 expression. In blood, stable levels of all other immune cells were observed after treatment. Moreover, in both studies a marginal increase of IFNg, CXCL10, IL-10, TNF was observed. No consistent gene expression alterations nor immune signatures could be observed when comparing BSL vs OT biopsies in S1. CONCLUSION: RG6292, consistent with its proposed mechanism of action, induces profound and preferential depletion of Treg cells over CD8+CD25+ in the periphery and in the TME at clinically safe doses between 35-70mg. Further development of RG6292 is currently being explored. Citation Format: Tamara Tanos, Kevin Smart, Valentina Gambardella, Kristoffer Rohrberg, Michael Ong, Maria Esperanza Rodriguez Ruiz, Jean-Pascal Machiels, Miguel Fernández Sanmamed, Josep Tabernero, Anna Spreafico, Daniel Renouf, Stephen Luen, Rachel Galot, Bernard Doger, Emiliano Calvo, Aung Naing, Samira Curdt, Nicolas Staedler, Mike Flores, Enrique Gómez Alcaide, Chiahuey Ooi, Michael Hettich, Sebastian Dziadek, Yuying Xie, Gabriel Schnetzler, Theresa Kolben, Linxinyu Xu, Vaios Karanikas, Christophe Boetsch. Pharmacokinetic/pharmacodynamic (PK/PD) relationships of the novel Treg depleter RG6292 in Phase Ia and Ib studies in patients with solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT176.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.215
GPT teacher head0.511
Teacher spread0.296 · 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".

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Citations2
Published2023
Admission routes1
Has abstractyes

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