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Record W2766447985 · doi:10.1002/cpdd.395

Pharmacokinetics of the BCL‐2 Inhibitor Venetoclax in Healthy Chinese Subjects

2017· article· en· W2766447985 on OpenAlexaboutno aff
TT Cheung, Ahmed Hamed Salem, Rajeev Menon, Wijith Munasinghe, Orlando F. Bueno, Suresh Agarwal

Bibliographic record

VenueClinical Pharmacology in Drug Development · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsnot available
FundersGenentechAbbVie
KeywordsVenetoclaxMedicinePharmacokineticsPharmacologyInternal medicineOncologyLeukemia

Abstract

fetched live from OpenAlex

Abstract Venetoclax has been approved in the United States, Europe, Canada, and Australia for appropriate patients with difficult‐to‐treat chronic lymphocytic leukemia (CLL). The objective of this phase 1 study was to evaluate the pharmacokinetics of venetoclax in Chinese subjects to inform the dose selection of venetoclax in a phase 2 study of patients with relapsed/refractory (R/R) CLL in China. Twelve healthy first‐generation Han Chinese subjects received a single 100‐mg dose of venetoclax following a low‐fat breakfast. Pharmacokinetic parameters were estimated using noncompartmental methods. After a single dose of venetoclax in healthy Chinese subjects, the median time to peak concentration was 6 hours (range, 4 to 6 hours), and the mean ± SD C max , AUC inf , and terminal half‐life were 1.0 ± 0.32 μg/mL, 12.6 ± 5.4 μg·h/mL, and 18.4 ± 2.97 hours, respectively. On average, venetoclax C max and AUC inf values were 94% and 66% higher, respectively, in Chinese subjects compared with those observed historically for non‐Asian subjects receiving the same dose. Based on these pharmacokinetic results and the established exposure–response relationship of venetoclax in non‐Asian CLL subjects, a 400‐mg once‐daily dosage regimen was selected for evaluating the venetoclax pharmacokinetics, efficacy, and safety in the venetoclax phase 2 open‐label study in Chinese subjects with R/R CLL.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.456
Teacher spread0.400 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations29
Published2017
Admission routes1
Has abstractyes

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