A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets.

database disintegration time quality by design response surface method tablet tensile strength

Journal

Pharmaceutics
ISSN: 1999-4923
Titre abrégé: Pharmaceutics
Pays: Switzerland
ID NLM: 101534003

Informations de publication

Date de publication:
28 Jun 2020
Historique:
received: 02 05 2020
revised: 05 06 2020
accepted: 27 06 2020
entrez: 2 7 2020
pubmed: 2 7 2020
medline: 2 7 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 32605318
pii: pharmaceutics12070601
doi: 10.3390/pharmaceutics12070601
pmc: PMC7408303
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : JSPS KAKENHI
ID : 20K06986

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Auteurs

Yoshihiro Hayashi (Y)

Formulation Development Department, Development and Planning Division, Nichi-Iko Pharmaceutical Co., Ltd.; 205-1, Shimoumezawa Namerikawa-shi, Toyama 936-0857, Japan.
Laboratory of Pharmaceutical Technology, Graduate School of Medicine and Pharmaceutical Science for Research, University of Toyama; 2630 Sugitani, Toyama-shi, Toyama 930-0194, Japan.

Kaede Shirotori (K)

Laboratory of Pharmaceutical Technology, Graduate School of Medicine and Pharmaceutical Science for Research, University of Toyama; 2630 Sugitani, Toyama-shi, Toyama 930-0194, Japan.

Atsushi Kosugi (A)

Formulation Development Department, Development and Planning Division, Nichi-Iko Pharmaceutical Co., Ltd.; 205-1, Shimoumezawa Namerikawa-shi, Toyama 936-0857, Japan.

Shungo Kumada (S)

Formulation Development Department, Development and Planning Division, Nichi-Iko Pharmaceutical Co., Ltd.; 205-1, Shimoumezawa Namerikawa-shi, Toyama 936-0857, Japan.

Kok Hoong Leong (KH)

Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Malaya, 50603 Kuala Lumpur, Malaysia.

Kotaro Okada (K)

Laboratory of Pharmaceutical Technology, Graduate School of Medicine and Pharmaceutical Science for Research, University of Toyama; 2630 Sugitani, Toyama-shi, Toyama 930-0194, Japan.

Yoshinori Onuki (Y)

Laboratory of Pharmaceutical Technology, Graduate School of Medicine and Pharmaceutical Science for Research, University of Toyama; 2630 Sugitani, Toyama-shi, Toyama 930-0194, Japan.

Classifications MeSH