Evidence map›Paper›PMID 32405662›Full record

ArticlePharmaceutical research2020

Probing the Molecular-Level Interactions in an Active Pharmaceutical Ingredient (API) - Polymer Dispersion and the Resulting Impact on Drug Product Formulation.

Fengyuan Yang, Yongchao Su, James Small, Chengbin Huang, Gary E Martin, Andrew M Farrington, James DiNunzio, Chad D Brown

Abstract read
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In one paragraph

Article in Pharmaceutical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 35% of its field
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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
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  4. Article
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  7. Influence of PlasdoneAAPS PharmSciTech · 2021
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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

8 authors at 3 institutions in 1 country.

Fengyuan YangMRL, Merck & Co., Inc., West Point, Pennsylvania, USA. fengyuanyang@gmail.com.
Yongchao SuMRL, Merck & Co., Inc., West Point, Pennsylvania, USA.
James SmallMRL, Merck & Co., Inc., West Point, Pennsylvania, USA.
Chengbin HuangMRL, Merck & Co., Inc., West Point, Pennsylvania, USA.
Gary E MartinMRL, Merck & Co., Inc., Rahway, New Jersey, USA.
Andrew M FarringtonMRL, Merck & Co., Inc., West Point, Pennsylvania, USA.
James DiNunzioMRL, Merck & Co., Inc., West Point, Pennsylvania, USA.
Chad D BrownMRL, Merck & Co., Inc., West Point, Pennsylvania, USA.
United States Military Academy · USMerck & Co., Inc., Rahway, NJ, USA (United States) · USUniversity of Wisconsin–Madison · US

Funding

Merck Sharp and Dohme Not applicable
6 · The paper itself

Abstract

purposeAn investigation of underlying mechanisms of API-polymer interaction patterns has the potential to provide valuable insights for selecting appropriate formulations with superior physical stability and processability. MATERIALS AND

methodsIn this study, copovidone was used as a polymeric carrier for several model compounds including clotrimazole, nifedipine, and posaconazole. The varied chemical structures conferred the ability for the model compounds to form distinct interactions with copovidone. Rheology and nuclear magnetic resonance (NMR) were combined to investigate the molecular pattern and relative strength of active pharmaceutical ingredient (API)-polymer interactions. In addition, the impact of the interactions on formulation processability via hot melt extrusion (HME) and physical stability were evaluated.

resultsThe rheological response of an API-polymer system was found to be highly sensitive to API-polymer interaction, depending both on API chemistry and API-polymer miscibility. In the systems studied, dispersed API induced a stronger plasticizer effect on the polymer matrix compared to crystalline/aggregated API. Correspondingly, the processing torque via HME showed a proportional relationship with the maximum complex viscosity of the API-polymer system. In order to quantitatively evaluate the relative strength of the API-polymer interaction, homogeneously dispersed API-polymer amorphous samples were prepared by HME at an elevated temperature. DSC, XRD, and rheology were employed to confirm the amorphous integrity and homogeneity of the resultant extrudates. Subsequently, the homogeneously dispersed API-polymer amorphous dispersions were interrogated by rheology and NMR to provide a qualitative and quantitative assessment of the nature of the API-polymer interaction, both macroscopically and microscopically. Rheological master curves of frequency sweeps of the extrudates exhibited a strong dependence on the API chemistry and revealed a rank ordering of the relative strength of API-copovidone interactions, in the order of posaconazole > nifedipine > clotrimazole. NMR data provided the means to precisely map the API-polymer interaction pattern and identify the specific sites of interaction from a molecular perspective. Finally, the impact of API-polymer interactions on the physical stability of the resultant extrudates was studied.

conclusionQualitative and quantitative evaluation of the relative strength of the API-polymer interaction was successfully accomplished by utilizing combined rheology and NMR. Graphical Abstract.

Indexed as

ClotrimazoleDrug CarriersDrug CompoundingDrug LiberationElasticityHot Melt Extrusion TechnologyHot TemperatureMagnetic Resonance SpectroscopyMolecular ConformationNifedipinePyrrolidinesRheologyStructure-Activity RelationshipTriazolesVinyl CompoundsViscosityClotrimazoleDrug CarriersNifedipinepoly(vinylpyrrolidone-co-vinyl-acetate)posaconazolePyrrolidinesTriazolesVinyl CompoundsAPI-polymer interaction and hot melt extrusion (HME)NMRrheology

Identifiers

PMID32405662
OpenAlexW3024736162

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.