MétaCan
Menu
Back to cohort
Record W4386531039 · doi:10.4155/bio-2023-0092

Volumetric Absorptive Microsampling Coupled with Hybridization LC–MS/MS for Quantitation of Antisense Oligonucleotides

2023· article· en· W4386531039 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioanalysis · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsAltasciences (Canada)
Fundersnot available
KeywordsOligonucleotideChromatographyChemistryDNABiochemistry

Abstract

fetched live from OpenAlex

Background: Volumetric absorptive microsampling has emerged as a less invasive alternative to venous sampling for small-molecule pharmacokinetic studies, but its application to novel therapeutics such as antisense oligonucleotides (ASOs) is not well-established. Results: A workflow was developed using Mitra microsampling coupled with hybridization LC–MS/MS for accurate determination of fomivirsen, a 21-mer ASO, in human blood. Quantitative recovery was achieved regardless of blood hematocrit level or microsample age by implementing impact-assisted extraction. A thorough method evaluation confirmed sensitivity, linearity, precision/accuracy, matrix effect, metabolite interference and four months of microsample stability. Conclusion: The combined impact-assisted extraction and hybridization LC–MS/MS workflow demonstrated the successful quantitation of fomivirsen, establishing the validity and applicability of the approach for ASO drug candidates.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.172
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.302
Teacher spread0.267 · 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