Publications by authors named "Kensaku Matsunami"

Real-time release testing (RTRt) of tablet dissolution can significantly improve manufacturing efficiency along with the adoption of continuous manufacturing in the pharmaceutical industry. To assure product quality without destructive testing, models for RTRt should be sufficiently reliable and robust. Whereas mechanistic models have merits of broader applicability and interpretability, data-driven models have been common approaches due to computational speed.

View Article and Find Full Text PDF

In continuous powder handling processes, precise and consistent feeding is crucial for ensuring the quality of the final product. The intermixing effect caused by agitators, which alters the powder's bulk density, flow rate, and flow patterns, plays a significant role in this process, yet it is often overlooked. This study combines discrete element method (DEM) modeling and experiments using a commercial-scale feeder to propose a Digital Twin (DT) framework.

View Article and Find Full Text PDF

T-shaped partial least squares regression (T-PLSR) is a valuable machine learning technique for the formulation and manufacturing process development of new drug products. An accurate T-PLSR model requires experimental data with multiple formulations and process conditions. However, it is usually challenging to collect comprehensive experimental data using large-scale manufacturing equipment because of the cost, time, and large consumption of raw materials.

View Article and Find Full Text PDF

In the last few years, twin-screw wet granulation (TSWG) has become one of the key continuous pharmaceutical unit operations. Despite the many studies that have been performed, only little is known about the effect of the starting material properties on the stepwise granule formation along the length of the twin-screw granulator (TSG) barrel. Hence, this study obtained a detailed understanding of the effect of formulation properties (i.

View Article and Find Full Text PDF

This paper presents an application case of model-based design of experiments for the continuous twin-screw wet granulation and fluid-bed drying sequence. The proposed framework consists of three previously developed models. Here, we are testing the applicability of previously published unit operation models in this specific part of the production line to a new active pharmaceutical ingredient.

View Article and Find Full Text PDF

This work presents a granule size prediction approach applicable to diverse formulations containing new active pharmaceutical ingredients (APIs) in continuous twin-screw wet granulation. The approach consists of a surrogate selection method to identify similar materials with new APIs and a T-shaped partial least squares (T-PLS) model for granule size prediction across varying formulations and process conditions. We devised a surrogate material selection method, employing a combination of linear pre-processing and nonlinear classification algorithms, which effectively identified suitable surrogates for new materials.

View Article and Find Full Text PDF
Article Synopsis
  • Twin-screw wet granulation (TSWG) offers a continuous and efficient alternative to traditional granulation methods, but its dependence on raw material properties hasn't been thoroughly studied.
  • This research introduces four partial least squares (PLS) models that predict suitable liquid-to-solid (L/S) ratios and granule characteristics based on the properties of the starting materials.
  • The study finds that properties like solubility and flow rate significantly affect TSWG processability, and the created PLS models assist in optimizing TSWG settings for new active pharmaceutical ingredients (APIs), streamlining the development process.
View Article and Find Full Text PDF

In the pharmaceutical industry, twin-screw wet granulation has become a realistic option for the continuous manufacturing of solid drug products. Towards the efficient design, population balance models (PBMs) have been recognized as a tool to compute granule size distribution and understand physical phenomena. However, the missing link between material properties and the model parameters limits the swift applicability and generalization of new active pharmaceutical ingredients (APIs).

View Article and Find Full Text PDF

In recent years, continuous twin-screw wet granulation (TSWG) is gaining increasing interest from the pharmaceutical industry. Despite the many publications on TSWG, only a limited number of studies focused on granule porosity, which was found to be an important granule property affecting the final tablet quality attributes, e.g.

View Article and Find Full Text PDF

Coronavirus disease 2019 (COVID-19) has spread throughout the world. The prediction of the number of cases has become essential to governments' ability to define policies and take countermeasures in advance. The numbers of cases have been estimated using compartment models of infectious diseases such as the susceptible-infected-removed (SIR) model and its derived models.

View Article and Find Full Text PDF

This paper aims to determine key parameters that affect tablet quality and productivity in continuous tablet manufacturing. Experiments were performed based on design of experiments using a continuous high-shear granulator and ethenzamide as the active pharmaceutical ingredient. To guide a systematic and comprehensive parameter analysis, a parameter framework was defined that comprised five input parameters on raw material properties and process parameters, 11 intermediate parameters on granule properties, and 11 output parameters on tablet quality and productivity.

View Article and Find Full Text PDF

This paper compares batch and continuous technologies in terms of product quality and process performance in pharmaceutical tablet manufacturing using ethenzamide as the active pharmaceutical ingredient. Batch and continuous processes using wet granulation were investigated by performing experiments on the scale of 5 and up to 100 kg/lot, using the same raw materials. Three technologies were tested and compared: (i) batch technology using fluidized bed granulation, (ii) batch technology using high shear granulation, (iii) continuous technology using high shear granulation.

View Article and Find Full Text PDF

A PHP Error was encountered

Severity: Warning

Message: fopen(/var/lib/php/sessions/ci_sessiongfg5fnbnu4ue1trkcb6l06i5vp98b8p3): Failed to open stream: No space left on device

Filename: drivers/Session_files_driver.php

Line Number: 177

Backtrace:

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: session_start(): Failed to read session data: user (path: /var/lib/php/sessions)

Filename: Session/Session.php

Line Number: 137

Backtrace:

File: /var/www/html/index.php
Line: 316
Function: require_once