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Record W2404804404

The importance of characterizing the crystal form of the drug substance during drug development.

2003· article· en· W2404804404 on OpenAlexaff
Sophie‐Dorothée Clas

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug Solubulity and Delivery Systems
Canadian institutionsMerck Canada Inc. (Canada)
Fundersnot available
KeywordsDrugBioavailabilityDrug developmentSubstance usePharmacologyBiochemical engineeringChemistryMedicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

The existence of a new physical form of a drug substance with a bioavailability significantly different from that of the original form can have serious effects on the therapeutic levels of the dosage form. The goal of any dosage form is to ensure reproducible safe exposure during preclinical and clinical studies, and ultimately for the marketed product. This review discusses the different physical forms of a drug substance, including amorphous forms, polymorphs, hydrates and salts, and the importance of characterizing the form of the drug substance during development. A definition of the different forms is provided, and enantiotropism, monotropism and polyamorphicity are discussed. This article provides examples of cases in which changes in the physical form resulted in changes in stability and/or bioavailability of the product. The review also discusses some of the methods used to quantify the physical form of a drug substance in a product.

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)0.004
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.060
GPT teacher head0.306
Teacher spread0.245 · 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
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

Citations19
Published2003
Admission routes1
Has abstractyes

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