| Title |
Polymorphic Transformation of Indomethacin during Hot Melt Extrusion Granulation: Process and Dissolution Control
|
|---|---|
| Published in |
Pharmaceutical Research, May 2018
|
| DOI | 10.1007/s11095-017-2325-x |
| Pubmed ID | |
| Authors |
Ting Xu, Kajalajit Nahar, Rutesh Dave, Simon Bates, Kenneth Morris |
| Abstract |
To study and elucidate the effect of the intensity and duration of processing stresses on the possible solid-state changes during a hot melt extrusion granulation process. Blends of α-indomethacin and PEG 3350 (w/w 4:1) were granulated using various screw sizes/designs on the melt extruder under different temperature regimes. Differential Scanning Calorimetry and X-ray Powder Diffraction were employed for characterization. The dissolution behavior of the pure polymorphs and the resulting granules was determined using in-situ fiber optic UV testing system. An XRPD quantitation method using Excel full pattern fitting was developed to determine the concentration of each constituent (amorphous, α and γ indomethacin and PEG) in samples collected from each functioning zone and in granules. Analysis of in-process samples and granules revealed that higher temperature (≥130°C) and shear stress accelerated the process induced phase transitions from amorphous and/or the α form to γ indomethacin during heating stage. However, rapid cooling resulted in an increased percentage of the α form allowing isolation of the meta-stable form. By determining the conditions that either prevent or facilitate process induced transformations of IMC polymorphs during melt granulation, a design space was developed to control the polymorph present in the resulting granules. This represents the conditions necessary to balance the thermodynamic relationships between the polymorphs of the IMC system and the kinetics of the possible transformations as a function of the processing stresses. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 17% |
| Student > Master | 4 | 14% |
| Researcher | 3 | 10% |
| Student > Doctoral Student | 2 | 7% |
| Student > Bachelor | 2 | 7% |
| Other | 5 | 17% |
| Unknown | 8 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 10 | 34% |
| Chemistry | 2 | 7% |
| Nursing and Health Professions | 1 | 3% |
| Materials Science | 1 | 3% |
| Engineering | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 14 | 48% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 May 2018.
All research outputs
#15,508,366
of 23,047,237 outputs
Outputs from Pharmaceutical Research
#2,246
of 2,870 outputs
Outputs of similar age
#207,691
of 326,024 outputs
Outputs of similar age from Pharmaceutical Research
#16
of 32 outputs
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