Kozo Takayama

Modeling of quantitative relationships between physicochemical properties of active pharmaceutical ingredients and tensile strength of tablets using a boosted tree

Abstract Objectives: The aim of this study was to explore the potential of boosted tree (BT) to develop a correlation model between active pharmaceutical ingredient (API) characteristics and a tensile strength (TS) of tablets as critical quality attributes. Methods: First, we evaluated 81 kinds of API characteristics, such as particle size distribution, bulk density, tapped density, Hausner ratio, moisture content, elastic recovery, molecular weight, and partition coefficient. Next, we prepared tablets containing 50% API, 49% microcrystalline cellulose, and 1% magnesium stearate using direct compression at 6, 8, and 10u2009kN, and measured TS. Then, we applied BT to our dataset to develop a correlation model. Finally, the constructed BT model was validated using k-fold cross-validation. Results: Results showed that the BT model achieved high-performance statistics, whereas multiple regression analysis resulted in poor estimations. Sensitivity analysis of the BT model revealed that diameter of powder particles at the 10th percentile of the cumulative percentage size distribution was the most crucial factor for TS. In addition, the influences of moisture content, partition coefficients, and modal diameter were appreciably meaningful factors. Conclusions: This study demonstrates that BT model could provide comprehensive understanding of the latent structure underlying APIs and TS of tablets.

Relationships between response surfaces for tablet characteristics of placebo and API-containing tablets manufactured by direct compression method

In this study, we evaluated the correlation between the response surfaces for the tablet characteristics of placebo and active pharmaceutical ingredient (API)-containing tablets. The quantities of lactose, cornstarch, and microcrystalline cellulose were chosen as the formulation factors. Ten tablet formulations were prepared. The tensile strength (TS) and disintegration time (DT) of tablets were measured as tablet characteristics. The response surfaces for TS and DT were estimated using a nonlinear response surface method incorporating multivariate spline interpolation, and were then compared with those of placebo tablets. A correlation was clearly observed for TS and DT of all APIs, although the value of the response surfaces for TS and DT was highly dependent on the type of API used. Based on this knowledge, the response surfaces for TS and DT of API-containing tablets were predicted from only two and four formulations using regression expression and placebo tablet data, respectively. The results from the evaluation of prediction accuracy showed that this method accurately predicted TS and DT, suggesting that it could construct a reliable response surface for TS and DT with a small number of samples. This technique assists in the effective estimation of the relationships between design variables and pharmaceutical responses during pharmaceutical development.

Nondestructive Monitoring of the Dispersion State of Titanium Dioxide Nanoparticles in Concentrated Suspensions Using Magnetic Resonance Imaging

The purpose of the present study is to demonstrate the applicability of magnetic resonance imaging, especially T2 relaxation time mapping, for nondestructive monitoring of the dispersion state of nanoparticles (NPs) in concentrated suspensions. TiO2 15-nm-diameter NPs, for use in sunscreen lotion products, were examined as a test NP. First, this study investigated whether T2 is sensitive to the NP concentration. In experiments with pulsed nuclear magnetic resonance on TiO2 NP suspensions with different organic solvents (ethanol, acetone, and decamethylcyclopentasiloxane), the T2 of each solvent varied in the suspensions according to the NP concentration. This study also confirmed that T2 mapping was effective for visualizing differences in NP concentration. Subsequently, gravitational sedimentation of the test suspensions was investigated. T2 mapping exhibited better detection sensitivity to sedimentation occurring in concentrated suspensions than visual observation, as it enabled the detection of changes in NP distributions that could not be visible to the naked eye. In addition, measurements of backscattered light enabled the full understanding of the dispersion stability of the TiO2 NPs in each solvent. Finally, the present study evaluated the centrifuge sedimentation of a commercial TiO2 NP suspension. T2 mapping clearly showed the complicated sedimentation behavior induced by the centrifugation treatment. The simulated fluid flow was consistent with the particle distribution in the centrifuged sample; thus, the sedimentation was believed to have developed in accordance with the vorticity generated by the centrifugation.

Strength Simulation of Scored Tablets Based on the Finite Element Method Using an Extreme Vertices Design

The mechanical strain distribution of scored tablets was simulated using the finite element method (FEM). The score was fabricated as a triangular runnel with the pole on the top surface of flat tablets. The effect of diametral compression on the tablet surface strain was evaluated by changing the angle between the scored line and the diametral compression axis. Ten types of granules were prepared according to an extreme vertices design. Youngs modulus and the Poisson ratio for the model powder bed were measured as elastic parameters. The FEM simulation was then applied to the scored tablets represented as a continuous elastic model. Strain distributions in the inner structure of the tablets were simulated after the application of external force. The maximum principal strain (ε1) value was obtained with tablets containing a large amount of corn starch, in all scored line positions. In contrast, the ε1 value of the tablets containing a large amount of microcrystalline cellulose was minimal. The adequacy of the simulation was evaluated by experiments with scored tablets. The results indicated a fairly good agreement between the FEM simulation and experiments. Moreover, it was found that the ε1 value correlated negatively with the value of tablet hardness. These results suggest that the FEM simulation was advantageous for designing scored tablets.

Determining the Influence of Granule Size on Simulation Parameters and Residual Shear Stress Distribution in Tablets by Combining the Finite Element Method into the Design of Experiments

The influence of granule size on simulation parameters and residual shear stress in tablets was determined by combining the finite element method (FEM) into the design of experiments (DoE). Lactose granules were prepared using a wet granulation method with a high-shear mixer and sorted into small and large granules using sieves. To simulate the tableting process using the FEM, parameters simulating each granule were optimized using a DoE and a response surface method (RSM). The compaction behavior of each granule simulated by FEM was in reasonable agreement with the experimental findings. Higher coefficients of friction between powder and die/punch (μ) and lower by internal friction angle (αy) were generated in the case of small granules, respectively. RSM revealed that die wall force was affected by αy. On the other hand, the pressure transmissibility rate of punches value was affected not only by the αy value, but also by μ. The FEM revealed that the residual shear stress was greater for small granules than for large granules. These results suggest that the inner structure of a tablet comprising small granules was less homogeneous than that comprising large granules. To evaluate the contribution of the simulation parameters to residual stress, these parameters were assigned to the fractional factorial design and an ANOVA was applied. The result indicated that μ was the critical factor influencing residual shear stress. This study demonstrates the importance of combining simulation and statistical analysis to gain a deeper understanding of the tableting process.

Optimization of Premix Powders for Tableting Use

Direct compression is a popular choice as it provides the simplest way to prepare the tablet. It can be easily adopted when the active pharmaceutical ingredient (API) is unstable in water or to thermal drying. An optimal formulation of preliminary mixed powders (premix powders) is beneficial if prepared in advance for tableting use. The aim of this study was to find the optimal formulation of the premix powders composed of lactose (LAC), cornstarch (CS), and microcrystalline cellulose (MCC) by using statistical techniques. Based on the Quality by Design concept, a (3,3)-simplex lattice design consisting of three components, LAC, CS, and MCC was employed to prepare the model premix powders. Response surface method incorporating a thin-plate spline interpolation (RSM-S) was applied for estimation of the optimum premix powders for tableting use. The effect of tablet shape identified by the surface curvature on the optimization was investigated. The optimum premix powder was effective when the premix was applied to a small quantity of API, although the function of premix was limited in the case of the formulation of large amount of API. Statistical techniques are valuable to exploit new functions of well-known materials such as LAC, CS, and MCC.

Prediction of Skin Permeation of Flurbiprofen from Neat Ester Oils and Their O/W Emulsions

Although many in silico models were reported to predict the skin permeation of drugs from aqueous solutions, few studies were founded on the in silico estimation models for the skin permeation of drugs from neat oil formulations and o/w emulsions. In the present study, the cumulative amount of a model lipophilic drug, flurbiprofen (FP), that permeated through skin was determined from 12 different kinds of ester oils (Qoil) and an in silico model was developed for predicting the skin permeation of FP from these ester oils. Thus, the obtained Qoil values were well predicted with the FP solubility in the oils (Soil), the amount of FP uptake into the stratum corneum (SCoil) and molecular descriptors of dipolarity/polarizability (π2H) and molecular density. This model suggests that the thermodynamic activities of FP both in the formulations and skin are the key factors for predicting the skin permeation of FP from the ester oils. In addition, a high linear relationship was observed in the double-logarithm plots between the Qoil and the cumulative amount of FP permeated through skin from 20% ester oil in water emulsion (Qemul20%). Furthermore, the skin permeations of FP from 5 and 10% ester oil in water emulsions, Qemul5% and Qemul10%, respectively, were also predicted by the horizontal translation of the y-axis intercept of the liner equation for the relation between the Qoil and Qemul20%. These prediction methods must be helpful for designing topical oily and/or o/w emulsion formulations having suitable and high skin permeation rate of lipophilic drugs.

Prediction of Dissolution Data Integrated in Tablet Database Using Four-Layered Artificial Neural Networks

A large number of dissolution data were measured and integrated into a previously constructed tablet database composed of 14 kinds of compounds as model active pharmaceutical ingredients (APIs) with contents ranging from 10 to 80%. The database has contained physicochemical and powder properties of APIs, together with basic physical attributes of tablets such as the tensile strength and the disintegration time. In order to enhance the value of this database, drug dissolution data are essential to improving key information for designing tablet formulations. A four-layered artificial neural network (4LNN), newly implemented in commercially available software, was employed to predict dissolution data from physicochemical and powder properties of APIs. Our results showed that an excellent model for the prediction of dissolution data was achieved with 4LNN method. The function of 4LNN was appreciably better than that of conventional three-layered model, despite both models adopting the same number of nodes and algorithms for activation functions. Furthermore, linear regression models resulted in poor prediction of dissolution data.

Enhancement of Galantamine HBr Skin Permeation Using Sonophoresis and Limonene-Containing PEGylated Liposomes

This study aimed to investigate the effect of low-frequency sonophoresis (SN) and limonene-containing PEGylated liposomes (PL) on the transdermal delivery of galantamine HBr (GLT). To evaluate the skin penetration mechanism, confocal laser scanning microscopy (CLSM), Fourier transform infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC) were employed. The application of SN led to more GLT penetration into and through the skin than GLT solution alone. The liposomes also improved GLT permeation, and 2% limonene-containing PL (PL-LI2%) exhibited the highest GLT permeation, followed by PL-LI1%, PL-LI0.1%, and PL. The CLSM images of PL-LI2% resulted in the highest fluorescence intensity of fluorescent hydrophilic molecules in the deep skin layer, and the rhodamine PE-labeled liposome membrane was distributed in the intercellular region of the stratum corneum (SC). PL-LI2% induced significant changes in intercellular lipids in the SC, whereas SN had no effect on intercellular lipids of the SC. DSC thermograms showed that the greatest decrease in the lipid transition temperature occurred in PL-LI2%-treated SC. SN might improve drug permeation through an intracellular pathway, while limonene-containing liposomes play an important role in delivering GLT through an intercellular pathway by increasing the fluidity of intercellular lipids in the SC. Moreover, a small vesicle size and high membrane fluidity might enhance the transportation of intact vesicles through the skin.