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Record W4412136497 · doi:10.1021/acscentsci.5c00576

Carbamate Prodrugs Restrict <i>In Vivo</i> Metabolism and Improve the Pharmacokinetics of Isoniazid

2025· article· en· W4412136497 on OpenAlexaff
Jishnu Sankar, Manish Kumar Bajpai, Anjali Chauhan, Ravi Maddheshiya, Nidhi Sharma, Aditya Sharma, Yashwant Kumar, Dinesh Mahajan

Bibliographic record

VenueACS Central Science · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsDiscovery Centre
FundersDepartment of Science and Technology, Ministry of Science and Technology, IndiaBiotechnology Industry Research Assistance CouncilTranslational Health Science and Technology InstituteDepartment of Biotechnology, Ministry of Science and Technology, India
KeywordsProdrugPharmacokineticsIn vivoCarbamatePharmacologyIsoniazidChemistryMedicineVirologyBiochemistryBiologyPathologyBiotechnologyTuberculosis

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Isoniazid (INH), an important first-line drug in tuberculosis (TB) treatment, faces significant challenges primarily due to hepatotoxicity and peripheral neuropathy as major side effects. These adverse effects often lead to poor patient compliance and treatment dropouts. The INH’s in vivo metabolism is responsible for these adverse effects. INH’s reactive terminal −NH 2 group is involved in its undesired in vivo metabolic transformations. To address this, we designed and synthesized carbamate-based prodrugs of INH by masking the −NH 2 group to reduce its metabolic activity. Herein, we report our efforts to develop such prodrugs and their impact on in vivo metabolism and the pharmacokinetic profile of free INH. The ex vivo stability, bioconversion, and in vivo pharmacokinetic profile with detailed metabolite analysis of these prodrugs were determined in mice. The lead prodrug 1d demonstrated enhanced systemic exposure of free INH (1.5-fold, AUC ≈ 3948 ng·h/mL), reduced formation of undesired metabolites, and prolonged half-life (1.3-fold, t 1/2 ≈ 0.88 h) compared to naive INH. This prodrug approach represents a promising strategy for safer and more effective TB therapy, with the potential for less frequent dosing and improved patient compliance.

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)0.001
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 score0.041
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.381
Teacher spread0.343 · 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 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
Published2025
Admission routes1
Has abstractyes

Explore more

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