Physiologically Based Pharmacokinetic Absorption Model for Pexidartinib to Evaluate the Impact of Meal Contents and Intake Timing on Drug Exposure.

Pexidartinib is a systemic treatment for patients with tenosynovial giant cell tumor not amenable to surgery. Oral absorption of pexidartinib is affected by food; administration with a high-fat meal (HFM) or low-fat meal (LFM) increases absorption by approximately 100% and approximately 60%, respectively, compared with the fasted state. Pexidartinib is currently dosed 250 mg orally twice daily with an LFM (approximately 11-14 g of total fat). We developed a physiologically based pharmacokinetic model to determine the impact on drug exposure of dose timing with respect to meals, meal type, and caloric content. A 15%-16% increase in plasma exposure was predicted when consuming an HFM 1 hour after dosing with an LFM, but almost no effect on pharmacokinetics was predicted when an HFM was consumed 3 hours or more before or after pexidartinib dosing with an LFM. Exposure was not significantly affected when pexidartinib was taken with a 500-kcal LFM over the range of fat (approximately 11-14 g of total fat; 20%-25% calories from fat) for an LFM. These findings on timing of pexidartinib dose with respect to meals should be considered by patients and physicians to reduce the potential for side effects.

Greedy design space construction based on regression and latent space extraction for pharmaceutical development.

Implementation of the design space (DS) is a scientific concept for ensuring quality to be submitted as a part of the regulatory filing of a drug product for approval to market. An empirical approach is constructing the DS based on the regression model whose inputs are process parameters and material attributes over the different unit operations, i.e., a high-dimensional statistical model. While the high-dimensional model assures quality and process flexibility through a comprehensive process understanding, it has difficulty visualizing the feasible range of input parameters, i.e., DS. Therefore, this study proposes a greedy approach to constructing the extensive and flexible low-dimensional DS based on the high-dimensional statistical model and the observed internal representations that satisfies both comprehensive process understanding and the DS visualization capability. Introducing the observed correlation structure enabled the dimensionality reduction of the DS. The non-critical controllable parameters were fixed to the target values in visualizing the low-dimensional DS as a function of critical parameters. The expected variation of non-critical non-controllable parameters was considered the source of variation in prediction. The case study demonstrated the proposed approach's usefulness for developing the pharmaceutical manufacturing process.

Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation.

Soft sensors are powerful tools for the implementation of process analytical technology (PAT). They are categorized into white-box (first-principle), black-box (statistical), and gray-box models. Gray-box models integrate white-box and black-box models to address each drawback, i.e., prediction accuracy and intuitiveness. Although they have been applied to various industrial processes, their applicability to water content monitoring in fluidized bed granulation has not been reported. In this study, we evaluated three types of gray-box models, i.e., parallel, serial, and combined gray-box models, in terms of prediction accuracy using real operating data on a commercial scale with two formulations. The gray-box models were constructed by integrating the heat and mass balance model (white-box model) and locally weighted partial least squares regression (LW-PLSR) model (black-box model). LW-PLSR was utilized to cope with collinearity and nonlinearity. In the serial gray-box models, LW-PLSR models adjusted the fitting parameters of the white-box model depending on the process parameters for each query. In the parallel gray-box or combined gray-box models, LW-PLSR models compensated for the output error of the white-box or serial gray-box models, respectively. The results demonstrated that all three types of gray-box models improved the prediction accuracy of the white-box models regardless of the formulation. Besides, we proposed the assessment method based on Hotelling's T2 and Q residual for gray-box models using LW-PLSR, which contributes decision support to select gray-box or white-box model. The accurate and descriptive gray-box models are expected to enhance process understanding and precise quality control in fluidized bed granulation.

Prediction Performance and Economic Efficiency of Soft Sensors for in-Line Water Content Monitoring in Fluidized Bed Granulation: PP-Based Model vs. NIRS-Based Model.

Soft sensors play a crucial role as process analytical technology (PAT) tools. They are classified into physical models, statistical models, and their hybrid models. In general, statistical models are better estimators than physical models. In this study, two types of standard statistical models using process parameters (PPs) and near-infrared spectroscopy (NIRS) were investigated in terms of prediction accuracy and development cost. Locally weighted partial least squares regression (LW-PLSR), a type of nonlinear regression method, was utilized. Development cost was defined as the cost of goods required to construct an accurate model of commercial-scale equipment. Eleven granulation lots consisting of three laboratory-scale, two pilot-scale, and six commercial-scale lots were prepared. Three commercial-scale granulation lots were selected as a validation dataset, and the remaining eight granulation lots were utilized as calibration datasets. The results demonstrated that the PP-based and NIRS-based LW-PLSR models achieved high prediction accuracy without using the commercial-scale data in the calibration dataset. This practical case study clarified that the construction of accurate LW-PLSR models requires the calibration samples with the following two features: 1) located near the validation samples on the subspace spanned by principal components (PCs), and 2) having a wide range of variations in PC scores. In addition, it was confirmed that the reduction in cost and mass fraction of active pharmaceutical ingredient (API) made the PP-based models more cost-effective than the NIRS-based models. The present work supports to build accurate models efficiently and save the development cost of PAT.

Scale-Free Soft Sensor for Monitoring of Water Content in Fluid Bed Granulation Process.

In-line monitoring of granule water content during fluid bed granulation is important to control drug product qualities. In this study, a practical scale-free soft sensor to predict water content was proposed to cope with the manufacturing scale changes in drug product development. The proposed method exploits two key ideas to construct a scale-free soft sensor. First, to accommodate the changes in the manufacturing scale, the process parameters (PPs) that are critical to water content at different manufacturing scales were selected as input variables. Second, to construct an accurate statistical model, locally weighted partial least squares regression (LW-PLSR), which can cope with collinearity and nonlinearity, was utilized. The soft sensor was developed using both laboratory (approx. 4 kg) data and pilot (approx. 25 kg) scale data, and the prediction accuracy in the commercial (approx. 100 kg) scale was evaluated based on the assumption that the process was scaled-up from the pilot scale to the commercial scale. The developed soft sensor exhibited a high prediction accuracy, which was equivalent to the commonly used near-infrared (NIR) spectra-based method. The proposed method requires only standard instruments; therefore, it is expected to be a cost-effective alternative to the NIR spectra-based method.

Influence of particle size and blender size on blending performance of bi-component granular mixing: A DEM and experimental study.

The effect of particle size enlargement and blender geometry down-scaling on the blend uniformity (BU) was evaluated by Discrete Element Method (DEM) to predict the blending performance of a binary granular mixture. Three 10 kg blending experiments differentiated by the physical properties specifically particle size were performed as reference for DEM simulations. The segregation behavior observed during the diffusion blending was common for all blends, while the sample BU, i.e., standard deviation of active ingredient content % was different among the three blends reflecting segregation due to the particle size differences between the components. Quantitative prediction of the sample BU probability density distribution in reality based on the DEM simulation results was successfully demonstrated. The average root mean square error normalized by the mean of the mean sample BU in the blends was 0.228. Beside the ratio of blender container to particle size, total number of particles in the blender and the number of particles in a sample were confirmed critical for the blending performance. These in-silico experiments through DEM simulations would help in setting a design space with respect to the particle size and in a broader sense with respect to the physical properties in general.

Selection of a round convex tablet shape that mitigates the risk of chipping and capping based on systematic evaluation by utilizing multivariate analysis.

Selecting a tablet shape that minimizes the risk of chipping and capping during manufacture is important in pharmaceutical industry. Here, the selection was performed based on systematic evaluation for the first time. Abrasion and stress relaxation time were utilized as indices of the occurrences of chipping and capping, respectively. Partial least square regression models that used tablet shape parameters to estimate the tablet's abrasion and stress relaxation time were utilized to develop response surface plots of the effect of the tablet shapes on the occurrence of chipping and capping systematically, and to identify an optimum tablet shape that is expected to have a low occurrence of chipping and capping. A verification study using commercial scale facilities proved that the optimum tablet shape had a lower occurrence of chipping and capping compared to suboptimum examples as speculated by their abrasion and stress relaxation time. The observed mathematical relationship between the tablet shapes and the occurrence of chipping and capping were consistent with the previous studies based on the comparison of limited number of tablet shapes using different formulations. Consequently, it is expected to be applicable to other formulations beyond the evaluated formulation in the present study.

Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate analysis of prior data.

Designing efficient, robust process parameters in drug product manufacturing is important to assure a drug's critical quality attributes. In this research, an efficient, novel procedure for a coating process parameter setting was developed, which establishes a prediction model for setting suitable input process parameters by utilizing prior manufacturing knowledge for partial least squares regression (PLSR). In the proposed procedure, target values or ranges of the output parameters are first determined, including tablet moisture content, spray mist condition, and mechanical stress on tablets. Following the preparation of predictive models relating input process parameters to corresponding output parameters, optimal input process parameters are determined using these models so that the output parameters hold within the target ranges. In predicting the exhaust air temperature output parameter, which reflects the tablets' moisture content, PLSR was employed based on prior measured data (such as batch records of other products rather than design of experiments), leading to minimal new experiments. The PLSR model was revealed to be more accurate at predicting the exhaust air temperature than a conventional semi-empirical thermodynamic model. A commercial scale verification demonstrated that the proposed process parameter setting procedure enabled assurance of the quality of tablet appearance without any trial-and-error experiments.

Yellow coloration phenomena of incorporated indomethacin into folded sheet mesoporous materials.

Solid-state (13)C nuclear magnetic resonance (NMR) spectroscopy that included relaxation time measurement was utilized to evaluate the yellow coloration of evaporated samples (EVPs) of indomethacin (IMC) with commercially available folded sheet mesoporous materials (TMPS). Colorimetric analysis by visible light reflection spectroscopy clarified the color differences in each sample: deep yellow-colored melt-quenched amorphous IMC, a slightly yellow-colored EVP of TMPS-1.5 (pore size: 1.8nm), and a yellow-colored EVP of TMPS-7 (pore size: 7.3nm). The color of EVPs changed from yellow to white after washing with ethanol, indicating the reversible coloration without a chemical reaction. Powder X-ray diffractometry and differential scanning calorimetry demonstrated that the EVPs of TMPS-7 entrapped greater amounts of amorphous IMC into the mesopore than TMPS-1.5. The amount of amorphous IMC in the mesopores could affect the strength of yellow coloration. Solid-state (13)C NMR spectroscopy that included spin-lattice relaxation time (T(1)) measurement revealed that the mobility of the aromatic rings of amorphous IMC in TMPS mesopores was higher than that in melt-quenched amorphous IMC. The difference in color between amorphous IMC in TMPS mesopores and melt-quenched amorphous IMC can be explained by their distinct intramolecular π-conjugation systems.

[Peripheral venous stenoses of hemodialysis shunts: improved long-term patency rates with stent placement].

PURPOSE: The purpose of this study was to evaluate the effectiveness of endovascular stents placed in the peripheral veins of hemodialysis shunts. MATERIALS AND METHODS: 156 endovascular stents were placed in the peripheral veins of 155 hemodialysis shunts with 220 stenoses. Among these, 106 stenoses of 93 hemodialysis shunts had been treated by percutaneous transluminal angioplasty (PTA) before stent placement. RESULTS: The initial success rate was 97.7%. Primary radiologic patency rates of the stents at 6 months, 1 year, and 2 years were 69.8%, 49.1%, and 45.8%, respectively. Secondary radiologic patency rates at 1 year, 2 years, and 3 years were 94.0%, 91.8%, and 88.0%, respectively. Primary clinical patency rates at 6 months, 1 year, and 2 years were 64.4%, 43.4%, and 27.3%; while secondary clinical patency rates at 1 year, 2 years, and 3 years were 93.5%, 86.5%, and 73.4%, respectively. Radiologic and clinical primary patency rates of 106 stenoses and 93 hemodialysis shunts were significantly higher than those of PTA that had been performed before stents were placed. CONCLUSION: Stent placement for stenoses of the peripheral veins of hemodialysis shunts recurring in three months and treated by PTA alone can improve long-term patency.

High incidence of reflux esophagitis observed by routine endoscopic examination after gastric pull-up esophagectomy.

A gastric tube has been widely used for reconstruction of the esophagus after esophagectomy for esophageal cancer. Reflux esophagitis after esophagectomy is frequently observed. Therefore we retrospectively investigated the risk factors for reflux esophagitis after gastric pull-up esophagectomy in 74 outpatients with thoracic esophageal cancer. Reflux esophagitis was diagnosed endoscopically. Esophagitis was classified according to the Los Angeles classification. Reflux symptoms, medications, and the surgical procedure were reviewed. The relation between reflux symptoms and reflux esophagitis and the influence of the anastomotic site were evaluated. Reflux esophagitis was observed in 53 patients. Severe esophagitis (grade C or D) was found in 75.6% of these patients. Although all patients with esophagitis took antacid agents, histamine receptor-2 blocker was effective in only 35% of them. The correlation between reflux symptoms and reflux esophagitis was not significant. Reflux esophagitis was present in 56.4% of patients with neck anastomosis and in 88.6% of patients with intrathoracic anastomosis ( p = 0.0039). We concluded that routine endoscopic examination is necessary after gastric pull-up esophagectomy because reflux esophagitis is not diagnosed based on reflux symptoms. When a gastric tube is used for reconstruction after esophagectomy, neck anastomosis is recommended to lower the risk of reflux esophagitis.