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

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....

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Autores principales: Hayashi, Yoshihiro, Shirotori, Kaede, Kosugi, Atsushi, Kumada, Shungo, Leong, Kok Hoong, Okada, Kotaro, Onuki, Yoshinori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408303/
https://www.ncbi.nlm.nih.gov/pubmed/32605318
http://dx.doi.org/10.3390/pharmaceutics12070601
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author Hayashi, Yoshihiro
Shirotori, Kaede
Kosugi, Atsushi
Kumada, Shungo
Leong, Kok Hoong
Okada, Kotaro
Onuki, Yoshinori
author_facet Hayashi, Yoshihiro
Shirotori, Kaede
Kosugi, Atsushi
Kumada, Shungo
Leong, Kok Hoong
Okada, Kotaro
Onuki, Yoshinori
author_sort Hayashi, Yoshihiro
collection PubMed
description 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.
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spelling pubmed-74083032020-08-13 A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets Hayashi, Yoshihiro Shirotori, Kaede Kosugi, Atsushi Kumada, Shungo Leong, Kok Hoong Okada, Kotaro Onuki, Yoshinori Pharmaceutics Article 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. MDPI 2020-06-28 /pmc/articles/PMC7408303/ /pubmed/32605318 http://dx.doi.org/10.3390/pharmaceutics12070601 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hayashi, Yoshihiro
Shirotori, Kaede
Kosugi, Atsushi
Kumada, Shungo
Leong, Kok Hoong
Okada, Kotaro
Onuki, Yoshinori
A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets
title A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets
title_full A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets
title_fullStr A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets
title_full_unstemmed A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets
title_short A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets
title_sort precise prediction method for the properties of api-containing tablets based on data from placebo tablets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408303/
https://www.ncbi.nlm.nih.gov/pubmed/32605318
http://dx.doi.org/10.3390/pharmaceutics12070601
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