Literature DB >> 22878814

Latent structure analysis of the process variables and pharmaceutical responses of an orally disintegrating tablet.

Yoshihiro Hayashi1, Etsuko Oshima, Jin Maeda, Yoshinori Onuki, Yasuko Obata, Kozo Takayama.   

Abstract

A multivariate statistical technique was applied to the design of an orally disintegrating tablet and to clarify the causal correlation among variables of the manufacturing process and pharmaceutical responses. Orally disintegrating tablets (ODTs) composed mainly of mannitol were prepared via the wet-granulation method using crystal transition from the δ to the β form of mannitol. Process parameters (water amounts (X(1)), kneading time (X(2)), compression force (X(3)), and amounts of magnesium stearate (X(4))) were optimized using a nonlinear response surface method (RSM) incorporating a thin plate spline interpolation (RSM-S). The results of a verification study revealed that the experimental responses, such as tensile strength and disintegration time, coincided well with the predictions. A latent structure analysis of the pharmaceutical formulations of the tablet performed using a Bayesian network led to the clear visualization of a causal connection among variables of the manufacturing process and tablet characteristics. The quantity of β-mannitol in the granules (Q(β)) was affected by X(2) and influenced all granule properties. The specific surface area of the granules was affected by X(1) and Q(β) and had an effect on all tablet characteristics. Moreover, the causal relationships among the variables were clarified by inferring conditional probability distributions. These techniques provide a better understanding of the complicated latent structure among variables of the manufacturing process and tablet characteristics.

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Year:  2012        PMID: 22878814     DOI: 10.1248/cpb.c12-00522

Source DB:  PubMed          Journal:  Chem Pharm Bull (Tokyo)        ISSN: 0009-2363            Impact factor:   1.645


  1 in total

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

Authors:  Yoshihiro Hayashi; Kaede Shirotori; Atsushi Kosugi; Shungo Kumada; Kok Hoong Leong; Kotaro Okada; Yoshinori Onuki
Journal:  Pharmaceutics       Date:  2020-06-28       Impact factor: 6.321

  1 in total

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