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Record W2332917350 · doi:10.1021/mp500711c

Evolution of Supersaturation of Amorphous Pharmaceuticals: Nonlinear Rate of Supersaturation Generation Regulated by Matrix Diffusion

2015· article· en· W2332917350 on OpenAlexafffund
Dajun Sun, Ping I. Lee

Bibliographic record

VenueMolecular Pharmaceutics · 2015
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug Solubulity and Delivery Systems
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsSupersaturationSolubilityDissolutionAmorphous solidCrystallizationDiffusionChemistryThermodynamicsPrecipitationChemical engineeringChemical physicsCrystallographyPhysical chemistryOrganic chemistryMeteorology

Abstract

fetched live from OpenAlex

The importance of rate of supersaturation generation on the kinetic solubility profiles of amorphous systems has recently been shown by us; however, the previous focus was limited to constant rates of supersaturation generation. The objective of the current study is to further examine the effect of nonlinear rate profiles of supersaturation generation in amorphous systems, including (1) instantaneous or infinite rate (i.e., initial degree of supersaturation), (2) first-order rate (e.g., from dissolution of amorphous drug particles), and (3) matrix diffusion regulated rate (e.g., drug release from amorphous solid dispersions (ASDs) based on cross-linked poly(2-hydroxyethyl methacrylate) (PHEMA) hydrogels), on the kinetic solubility profiles of a model poorly soluble drug indomethacin (IND) under nonsink dissolution conditions. The previously established mechanistic model taking into consideration both the crystal growth and ripening processes was extended to predict the evolution of supersaturation resulting from nonlinear rates of supersaturation generation. Our results confirm that excessively high initial supersaturation or a rapid supersaturation generation leads to a surge in maximum supersaturation followed by a rapid decrease in drug concentration owing to supersaturation-induced precipitation; however, an exceedingly low degree of supersaturation or a slow rate of supersaturation generation does not sufficiently raise the supersaturation level, which results in a lower but broader maximum kinetic solubility profile. Our experimental data suggest that an optimal area-under-the-curve of the kinetic solubility profiles exists at an intermediate initial supersaturation level for the amorphous systems studied here, which agrees well with the predicted trend. Our model predictions also support our experimental findings that IND ASD in cross-linked PHEMA exhibits a unique kinetic solubility profile because the resulting supersaturation level is governed by a matrix diffusion regulated mechanism opposite to that resulted from a high level of initial supersaturation or a rapid dissolution of amorphous solids. This more gradual drug release from IND-PHEMA ASD leads to a more gradual buildup of a sustained supersaturation even without the presence of any dissolved polymer to inhibit the drug precipitation, which avoids the rapid surge of supersaturation above a critical value as normally associated with high initial degrees of supersaturation or rapid dissolution of amorphous IND solids and thus avoids the onset of fast uncontrolled precipitation. This characteristic feature makes cross-linked insoluble PHEMA an attractive carrier for amorphous pharmaceuticals.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.409
Teacher spread0.307 · 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 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

Citations52
Published2015
Admission routes2
Has abstractyes

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