Evidence map›Paper›PMID 33884530›Full record

ArticleAAPS PharmSciTech2021

Development and Validation of a Discriminatory Dissolution Model for an Immediately Release Dosage Form by DOE and Statistical Approaches.

Mingkun Fu, Ellen Conroy, Michael Byers, Lakshminarasimhan Pranatharthiharan, Thierry Bilbault

Abstract read
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In one paragraph

Article in AAPS PharmSciTech, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mingkun FuSunovion Pharmaceuticals, 84 Waterford Dr, Marlborough, Massachusetts, 01752, USA. mingkun.fu@sunovion.com.
Ellen ConroySunovion Pharmaceuticals, 84 Waterford Dr, Marlborough, Massachusetts, 01752, USA.
Michael ByersQuality Chemical Laboratories, 3220A Corporate Dr, Wilmington, North Carolina, 28405, USA.
Lakshminarasimhan PranatharthiharanSunovion Pharmaceuticals, 84 Waterford Dr, Marlborough, Massachusetts, 01752, USA.
Thierry BilbaultSunovion Pharmaceuticals, 84 Waterford Dr, Marlborough, Massachusetts, 01752, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A discriminatory dissolution model was built through DOE with multivariate analysis of variance (MANOVA) and multiple linear regression (MLR) modeling to assess dissolution operational space for a highly water soluble immediate-release solid dosage drug product. The dissolution was utilized in the following five aspects: (1) understand the impact of individual variables and their interactions on dissolution performance through effect analysis; (2) explain the lack of discriminatory power of the initial dissolution condition used in early phase development by prediction profiler; (3) predict discriminatory dissolution operational space to differentiate photo degraded drug products from control with contour profiler analysis; (4) validate by the external experimental data acquired with the initial nondiscriminatory dissolution condition and the predicted discriminatory dissolution condition, followed by model independent statistical analysis (e.g., f2); and (5) establish correlation of the discriminatory dissolution with disintegration. The selected discriminatory dissolution method was validated by demonstrating accuracy, precision and linearity, specificity, repeatability, intermediate precision, stability, filter verification, and robustness.

Indexed as

Models, ChemicalTabletsLinear ModelsMultivariate AnalysisReproducibility of ResultsSolubilityWaterTabletsWaterdiscriminatorydissolutionDOEstatistic

Identifiers

PMID33884530

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.