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Record W2267471943 · doi:10.18433/j3x61s

Prodrugs of Antiinfective Agents: A Review

2016· review· en· W2267471943 on OpenAlexvenueno aff
Mona Piplani, Avtar Chand Rana, Prabodh Chander Sharma

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2016
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
FundersIndian Council of Medical Research
KeywordsProdrugBiopharmaceuticalPharmacologyDrugMedicinePharmacokineticsBiologyBiotechnology

Abstract

fetched live from OpenAlex

Prodrugs are the pharmacologically inactive derivatives of active drugs typically intended to optimize the exposure of active drug at target site, through manipulation of its physicochemical, biopharmaceutical or pharmacokinetic properties. This approach has a number of advantages over conventional drug administration. Antiinfective agents are associated with number of limitations, responsible for their reduced bioavailability. Various antiinfective prodrugs have been synthesized with reduced side effects and improved pharmacological properties. The present paper illustrates different vistas of prodrug approach of antiinfective agents describing brief classification, synthetic approaches, pharmacological aspects and recent patents. It is a very productive area of research and its prologue in human therapy has given triumphant outcomes in improving the clinical and therapeutic effectiveness of drugs.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.184
GPT teacher head0.518
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2016
Admission routes1
Has abstractyes

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