Hayashi, Yoshihiro and Shirotori, Kaede and Kosugi, Atsushi and Kumada, Shungo and Leong, Kok Hoong and Okada, Kotaro and Onuki, Yoshinori (2020) A precise prediction method for the properties of API-containing tablets based on data from placebo tablets. Pharmaceutics, 12 (7). ISSN 1999-4923, DOI https://doi.org/10.3390/pharmaceutics12070601.
Full text not available from this repository.Abstract
We previously reported a novel method for the precise prediction of tablet properties (e.g., tensile strength (TS)) using a small number of experimental data. The key technique of this method is to compensate for the lack of experimental data by using data of placebo tablets collected in a database. This study provides further technical knowledge to discuss the usefulness of this prediction method. Placebo tablets consisting of microcrystalline cellulose, lactose, and cornstarch were prepared using the design of an experimental method, and their TS and disintegration time (DT) were measured. The response surfaces representing the relationship between the formulation and the tablet properties were then created. This study investigated tablets containing four different active pharmaceutical ingredients (APIs) with a drug load ranging from 20-60%. Overall, the TS of API-containing tablets could be precisely predicted by this method, while the prediction accuracy of the DT was much lower than that of the TS. These results suggested that the mode of action of APIs on the DT was more complicated than that on the TS. Our prediction method could be valuable for the development of tablet formulations.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Tablet; Response surface method; Quality by design; Tensile strength; Disintegration time; Database |
| Subjects: | Q Science > Q Science (General) R Medicine R Medicine > RS Pharmacy and materia medica |
| Divisions: | Faculty of Pharmacy Faculty of Pharmacy > Department of Pharmaceutical Chemistry |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 01 Dec 2023 01:00 |
| Last Modified: | 01 Dec 2023 01:01 |
| URI: | http://eprints.um.edu.my/id/eprint/36576 |
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