Dissolution Efficiency and Design Space for an Oral Pharmaceutical Product in Tablet Form

Computational quality-by-design strategy to validate high-performance liquid chromatography method for the estimation of meloxicam in bulk dosage forms and milk samples

Bovine clinical mastitis has significant repercussions for farmers across the globe. Meloxicam, a COX-2 inhibitor, attenuates mastitis symptoms and is also approved for veterinary use. An RP-HPLC (Reverse Phase-High Performance Liquid Chromatography) method development and validation is essential in the pharmaceutical industry to assess API (Active Pharmaceutical Ingredient) quantity present in the pharmaceutical dosage forms. RP-HPLC method of meloxicam was developed and optimized with the aid of QbD (Quality by Design) using Box-Behnken design (BBD). The pH of the aqueous mobile phase, acetonitrile (ACN) percentage, and column temperature were chosen as influence variables, and retention time (RT) and tailing factor (Tf) were selected as response variables. The optimum experimental conditions were selected as pH ~ 3 of the aqueous mobile phase, 65% v/v ACN, and 30˚C as column temperature. The drug was eluted at 6.02 min RT with 1.18 as Tf. The method was subjected to validation for accuracy, linearity, precision, range, sensitivity, and robustness and was found to comply with ICH Q2 (R1) guidelines. The in vitro bioequivalent studies were performed in hydrochloric acid, pH ~ 1.2; acetate buffer, pH ~ 4.5; and phosphate buffer, pH ~ 6.8 for two veterinary brands of meloxicam tablets, and their release profiles were compared by mathematical models. Both the brands, brand 1 and 2 exhibited significant (Unpaired t-test, P < 0.05) differences in dissolution efficiency (DE) and mean dissolution time (MDT) except DE at pH 1.2. However, brands 1 and 2 showed similarity (f2 > 50) in terms of release of meloxicam except at pH 6.8 (f2 = 47.01). The in vitro release of meloxicam followed Peppas kinetics except for brand 2 at pH 6.8, where it followed the Higuchi model. Moreover, the recovery of meloxicam extracted with ACN in the milk sample was estimated to be 99.67 ± 0.58% significantly (Unpaired t-test, P < 0.05) higher than 90.34 ± 6.77% extracted with methanol. In conclusion, the optimized and validated RP-HPLC method of meloxicam may further be used for the analysis of drug content in pharmaceutical dosage forms in addition to biological fluids.

Maraviroc Oral Disintegration Tablet: Analytical Design of Experiments (DoE) for Assessment and Comparison of In-Vitro Dissolution Profiles

Background:

The bioavailability of a drug in a solid oral dose depends on its release from the drug product and its balance in dissolution. Compared with a reference drug, the newly developed formulation needs to establish bioequivalence by comparing the dissolution profile.

Objective:

To compare dissolution profiles of a newly developed maraviroc oral disintegration tablet and the reference Axentri® tablet. The current research was designed to establish and validate an integral analytical consistency by Quality by Design (QbD) approach to quantify maraviroc from dissolution samples using the RP-HPLC method.

Methods:

Maraviroc was formulated into an orally disintegrating tablet using a direct compression technique at different concentrations of sodium starch glycolate as super disintegrants and talc and magnesium stearate as glidants. The dissolution test in 0.1N HCl was performed according to standard procedures to predict bioequivalence. The results of dissolution tests were analyzed using the QbD Box Behnken Design multivariate RP-HPLC method.

Results:

The optimized formulation (F2) was selected as it showed 90% drug release in 5 min and a disintegration time of 22 sec with dissolution profiles to the marketed reference to meet the FDA requirements of f2 similarity factor statistics. The integrated analytical QbD method was statistically analyzed by ANOVA, counter-plot, and 3D response surface plots, which demonstrated that the model is statistically significant. The developed method was validated as per ICH guidelines Q2 (R1).

Conclusion :

In conclusion, maraviroc oral disintegrating tablets have been well prepared, and superior statement consistency is established by the implementation of the QbD analytical method for orally disintegrating tablet excellence and adoption.

Development and Validation of a Discriminatory Dissolution Model for an Immediately Release Dosage Form by DOE and Statistical Approaches

A discriminatory dissolution model was built through DOE with multivariate analysis of variance (MANOVA) and multiple linear regression (MLR) modeling to assess dissolution operational space for a highly water soluble immediate-release solid dosage drug product. The dissolution was utilized in the following five aspects: (1) understand the impact of individual variables and their interactions on dissolution performance through effect analysis; (2) explain the lack of discriminatory power of the initial dissolution condition used in early phase development by prediction profiler; (3) predict discriminatory dissolution operational space to differentiate photo degraded drug products from control with contour profiler analysis; (4) validate by the external experimental data acquired with the initial nondiscriminatory dissolution condition and the predicted discriminatory dissolution condition, followed by model independent statistical analysis (e.g., f2); and (5) establish correlation of the discriminatory dissolution with disintegration. The selected discriminatory dissolution method was validated by demonstrating accuracy, precision and linearity, specificity, repeatability, intermediate precision, stability, filter verification, and robustness.

Studying effect of glyceryl palmitostearate amount, manufacturing method and stability on polymorphic transformation and dissolution of rifaximin tablets

Rifaximin (RFX) exhibit polymorphism and commercial formulation contains the α form. The polymorphic transformation of the RFX in the drug product have significant effect on the clinical outcome. The focus of present work was to understand effect of formulation component and manufacturing method, and exposure to stability condition on polymorphic stability and dissolution of RFX tablets. The RFX tablets containing 2.5, 5 and 10% glyceryl palmitostearate (GPS) were manufactured by direct-compression and wet-granulation followed by compression. Ethanol was used as a granulating solvent. The tablets were packed in pharmacy vials and exposed to 40 °C/75% RH for four weeks. The tablets were characterized for polymorphic form by X-ray powder diffraction (XRPD) and Fourier infrared spectroscopy (FTIR), assay and dissolution. Before exposure to stability condition, dissolution ranged from 78.0 ± 2.3 to 81.9 ± 3.5%, and 72.7 ± 2.0 and 75.9 ± 5.8% in directly compressed and ethanol-granulated formulations, respectively. GPS amount of 10% caused a decrease in dissolution albeit insignificant (p > 0.05). The polymorphic forms of RFX were α and γ in directly compressed and ethanol-granulated formulations, respectively. There was a decrease in dissolution rate and extent after exposure to 40 °C/75% RH in directly compressed formulations. On the other hand, only dissolution rate was affected in ethanol-granulated formulations. The dissolution ranged from 52.8 ± 2.0 to 70.0 ± 3.0% in directly compressed formulations after four weeks exposure to 40 °C/75% RH exposure. A decrease in dissolution was linked to polymorphic transformation of the drug and GPS in the formulations after exposure to stability condition. XRPD and FTIR data indicated α to β transformation in directly compressed formulations while no polymorphic change was observed in ethanol-granulated formulations. In conclusion, this study clearly showed effect of formulation and manufacturing variables, and stability exposure on the polymorphic stability and dissolution of RFX, which may have clinical ramification.

A Novel Framework to Aid the Development of Design Space across Multi-Unit Operation Pharmaceutical Processes-A Case Study of Panax Notoginseng Saponins Immediate Release Tablet

The fundamental principle of Quality by Design (QbD) is that the product quality should be designed into the process through an upstream approach, rather than be tested in the downstream. The keystone of QbD is process modeling, and thus, to develop a process control strategy based on the development of design space. Multivariate statistical analysis is a very useful tool to support the implementation of QbD in pharmaceutical process development and manufacturing. Nowadays, pharmaceutical process modeling is mainly focused on one-unit operations and system modeling for the development of design space across multi-unit operations is still limited. In this study, a general procedure that gives a holistic view for understanding and controlling the process settings for the entire manufacturing process was investigated. The proposed framework was tested on the Panax Notoginseng Saponins immediate release tablet (PNS IRT) production process. The critical variables and the critical units acting on the process were identified according to the importance of explaining the variability in the multi-block partial least squares path model. This improved understanding of the process by illustrating how the properties of the raw materials, the process parameters in the wet granulation and the compaction and the intermediate properties affect the tablet properties. Furthermore, the design space was developed to compensate for the variability source from the upstream. The results demonstrated that the proposed framework was an important tool to gain understanding and control the multi-unit operation process.

An Optimization-Based Framework to Define the Probabilistic Design Space of Pharmaceutical Processes with Model Uncertainty

To increase manufacturing flexibility and system understanding in pharmaceutical development, the FDA launched the quality by design (QbD) initiative. Within QbD, the design space is the multidimensional region (of the input variables and process parameters) where product quality is assured. Given the high cost of extensive experimentation, there is a need for computational methods to estimate the probabilistic design space that considers interactions between critical process parameters and critical quality attributes, as well as model uncertainty. In this paper we propose two algorithms that extend the flexibility test and flexibility index formulations to replace simulation-based analysis and identify the probabilistic design space more efficiently. The effectiveness and computational efficiency of these approaches is shown on a small example and an industrial case study.

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.