Analysis of stabilization mechanisms in β-lactoglobulin-based amorphous solid dispersions by experimental and computational approaches
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Dokumenter
- Fulltext
Forlagets udgivne version, 3,63 MB, PDF-dokument
Our previous work shows that β-lactoglobulin-stabilized amorphous solid dispersion (ASD) loaded with 70 % indomethacin remains stable for more than 12 months. The stability is probably due to hydrogen bond networks spread throughout the ASD, facilitated by the indomethacin which has both hydrogen donors and acceptors. To investigate the stabilization mechanisms further, here we tested five other drug molecules, including two without any hydrogen bond donors. A combination of experimental techniques (differential scanning calorimetry, X-ray power diffraction) and molecular dynamics simulations was used to find the maximum drug loadings for ASDs with furosemide, griseofulvin, ibuprofen, ketoconazole and rifaximin. This approach revealed the underlying stabilization factors and the capacity of computer simulations to predict ASD stability. We searched the ASD models for crystalline patterns, and analyzed diffusivity of the drug molecules and hydrogen bond formation. ASDs loaded with rifaximin and ketoconazole remained stable for at least 12 months, even at 90 % drug loading, whereas stable drug loadings for furosemide, griseofulvin and ibuprofen were at a maximum of 70, 50 and 40 %, respectively. Steric confinement and hydrogen bonding to the proteins were the most important stabilization mechanisms at low drug loadings (≤ 40 %). Inter-drug hydrogen bond networks (including those with induced donors), ionic interactions, and a high Tg of the drug molecule were additional factors stabilizing the ASDs at drug loading greater than 40 %.
| Originalsprog | Engelsk |
|---|---|
| Artikelnummer | 106639 |
| Tidsskrift | European Journal of Pharmaceutical Sciences |
| Vol/bind | 192 |
| Antal sider | 13 |
| ISSN | 0928-0987 |
| DOI | |
| Status | Udgivet - 2024 |
Bibliografisk note
Funding Information:
We thank Arla Foods Ingredients Group P/S for providing the samples of Lacprodan BLG Pharma Grade. X.Z. acknowledges the China Scholarship Council (201908210313) for financial support. This work was supported by the Swedish Research Council (2021-02092). The computations and data handling were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973. The authors acknowledge financial support from NordForsk for the Nordic University Hub project #85352 (Nordic POP, Modelling).
Funding Information:
We thank Arla Foods Ingredients Group P/S for providing the samples of Lacprodan BLG Pharma Grade. X.Z. acknowledges the China Scholarship Council ( 201908210313 ) for financial support. This work was supported by the Swedish Research Council ( 2021-02092 ). The computations and data handling were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973 . The authors acknowledge financial support from NordForsk for the Nordic University Hub project # 85352 (Nordic POP, Modelling).
Publisher Copyright:
© 2023 The Author(s)
Antal downloads er baseret på statistik fra Google Scholar og www.ku.dk
ID: 378755267