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Record W4214879148 · doi:10.5267/j.ccl.2021.12.001

An unexpected aerobic oxidation of α-amino boronic acid part of Borteomib, leading to (thermal) decomposition of this very expensive anti-cancer API

2022· article· en· W4214879148 on OpenAlexvenueno aff
Abolghasem Beheshti, Meghdad Payab, Vahid Seyyed-Ali-Karbasi, Seyyed Amir Siadati

Bibliographic record

VenueCurrent Chemistry Letters · 2022
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryBoronic acidInert gasSolventAldehydeDecompositionMoleculeBortezomibThermal decompositionCombinatorial chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

This project was started when an unknown peak was being detected in the organic volatile impurity (OVI) analysis (using the head-space vapor sampling procedure) of bortezomib (BZB) active pharmaceutical ingredient (API), in pharmaceutical companies. During the OVI analysis of the API of BZB, a huge-area peak with an unknown source appeared in the chromatograms of the gas chromatography with flame ionization detector (GC-FID). The data prepared by GC-MAS revealed that the considered huge peak was 3-methylbutanal (3MBut). But, investigating the synthesis procedures showed that during all the synthesis steps, 3MBut or any other solvent containing this impurity was not being applied. Thus, we had concluded that there is a possibility for emergence of this aldehyde from bortezomib itself. To find out which part of bortezomib might turn into 3MBut, we began to investigate all its molecular structure, and hypothesized that the α-amino-boronic acid part of the molecule turned into 3MBut. The experimental analysis and theoretical quantum chemical calculations confirmed that the α-amino-boronic acid center of bortezomib molecule undergoes a rare and unexpected aerobic oxidation by O2 molecule, even in catalyst and solvent-free conditions. The result of this project not only might make clear the passive source of the 3MBut peak of the OVI of bortezomib, but also, it would suggest to store this API in an inert oxygen-free atmosphere to improve the long-term and accelerated (thermal) stability of this very expensive anti-cancer drug.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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.

Study designBench or experimental
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

Citations3
Published2022
Admission routes1
Has abstractyes

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