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Record W4407932301 · doi:10.1021/acs.oprd.4c00528

Development of a Scalable Manufacturing Process for AB-343 Drug Substance: A Potential Candidate for the Treatment of Coronavirus Infections

2025· article· en· W4407932301 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

VenueOrganic Process Research & Development · 2025
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsArbutus Biopharma (Canada)
Fundersnot available
KeywordsDrugCoronavirus disease 2019 (COVID-19)CoronavirusProcess developmentDrug developmentSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Drug candidateVirologyManufacturing process2019-20 coronavirus outbreakMedicinePharmacologyNanotechnologyBiochemical engineeringMaterials scienceProcess engineeringEngineeringInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

A scalable process for manufacturing of the anticoronavirus clinical candidate AB-343 has been developed. The lactam-containing subunit of the molecule was prepared using a novel synthetic route involving a nitro-Michael reaction and a rhodium-catalyzed nitro group hydrogenation followed by in situ translactamization sequence as a key transformation. The drug substance was assembled via sequential amide coupling and deprotection reactions, followed by a final dehydration of a primary amide to the corresponding nitrile using T3P. AB-343 drug substance was successfully manufactured on a multikilogram scale using this route, which was suitable for supporting IND-enabling studies and Phase I clinical development.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.060
GPT teacher head0.409
Teacher spread0.349 · 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