The influence of HPMC viscosity as FRC parameter on the release of low soluble drug from hydrophylic matrix tablets

The importance of functionality-related characteristics (FRC) of hydroxypropyl methylcellulose (HPMC) described in the pharmacopeia monograph can be evaluated only for selected formulation or technological process. The aim of our work was to investigate the influence of apparent viscosity as one of the FRC for two batches of the same HPMC grade on the release properties of diclofenac sodium from HPMC matrix tablets. Our results show that two batches of HPMC differ in viscosity significantly and as a consequence, the significant differences were observed in the release profiles as well. HPMC-B sample has higher viscosity and therefore higher average molecular weight, thus the erosion and drug release were slower compared to HPMC-A sample with lower apparent viscosity. It can be concluded that batch-to-batch viscosity variation of the same HPMC grade can lead to the different release profiles; therefore the specification limits of some FRC should be postulated during the development of each individual formulation. However, the viscosity interval as FRC can not be generalized, because it is different for different tablet compositions.     

吲达帕胺缓释片的研制及释药机理考察

目的：研制吲达帕胺缓释片，并考察其释药机理。方法：以HPMC为骨架材料，以微晶纤维素、乳糖和可压性淀粉调节释放度，对吲达帕胺缓释片的影响因素进行了考察，并采用正交试验设计筛选处方。结果：吲达帕胺缓释片的组成为：HPMC K4M 37．5mg，HPMC K15M7．5mg，乳糖45．0mg，可压性淀粉37．5mg，微晶纤维素21．0mg，硬脂酸镁1．5mg，药物的释放符合零级动力学方程，释放机制为骨架溶蚀机制；释药速率受介质pH值的影响，几乎不受压片压力的影响。结论：研制的吲达帕胺缓释片体外释放符合国外同类产品的释药特性。     

盐酸曲美他嗪缓释片的研制及其体外释药特性考察

目的:研制盐酸曲美他嗪(TMZ)缓释片,并考察其体外药物释放特性。方法:以羟丙基甲基纤维素(HPMC)为主要骨架材料,采用湿法制粒压片法,制备TMZ缓释片;以释放度为评价指标,采用正交试验设计对处方进行优化;根据药物不同时间释放度,拟合释放度方程,确定释药特性。结果:TMZ缓释片的处方组成为:HPMC 90 mg,羧甲基纤维素钠30 mg,微晶纤维素60 mg,10%聚乙烯吡咯烷酮-乙醇溶液(w/v)适量,硬脂酸镁2 mg;12 h释放度为(98.1±1.8)%,体外释放曲线符合一级动力学方程(r=0.994 2);压片力对药物释放有一定影响。结论:研制的TMZ缓释片制备工艺简单,重现性好,释药特性达到缓释要求。     

A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation

Quality by design (QbD) is an essential part of the modern approach to pharmaceutical quality. This study was conducted in the framework of a QbD project involving ramipril tablets. Preliminary work included identification of the critical quality attributes (CQAs) and critical process parameters (CPPs) based on the quality target product profiles (QTPPs) using the historical data and risk assessment method failure mode and effect analysis (FMEA). Compendial and in-house specifications were selected as QTPPs for ramipril tablets. CPPs that affected the product and process were used to establish an experimental design. The results thus obtained can be used to facilitate definition of the design space using tools such as design of experiments (DoE), the response surface method (RSM) and artificial neural networks (ANNs). The project was aimed at discovering hidden knowledge associated with the manufacture of ramipril tablets using a range of artificial intelligence-based software, with the intention of establishing a multi-dimensional design space that ensures consistent product quality. At the end of the study, a design space was developed based on the study data and specifications, and a new formulation was optimized. On the basis of this formulation, a new laboratory batch formulation was prepared and tested. It was confirmed that the explored formulation was within the design space.     

Effect of multivariate process instability on principal component analysis: A case study

With the rising use of principal component analysis/partial least squares (PCA/PLS) in the process analytical technology (PAT) initiative of the pharmaceutical industry, it seems appropriate to view that approach from a statistical process control (SPC) perspective. The purpose of this study was to demonstrate the effect of process instability (ie, state of statistical out-of-control) on use of PCA/PLS. The demonstrated differences in results should encourage PCA/PLS users to incorporate SPC as an active part of their process analytical control (PAC) toolkit to check for stability prior to drawing conclusions based on PCA/PLS analysis.     

A new technique for spectrophotometric determination of pseudoephedrine and guaifenesin in syrup and synthetic mixture

The accuracy in predicting different chemometric methods was compared when applied on ordinary UV spectra and first order derivative spectra. Principal component regression (PCR) and partial least squares with one dependent variable (PLS1) and two dependent variables (PLS2) were applied on spectral data of pharmaceutical formula containing pseudoephedrine (PDP) and guaifenesin (GFN). The ability to derivative in resolved overlapping spectra chloropheniramine maleate was evaluated when multivariate methods are adopted for analysis of two component mixtures without using any chemical pretreatment. The chemometrics models were tested on an external validation dataset and finally applied to the analysis of pharmaceuticals. Significant advantages were found in analysis of the real samples when the calibration models from derivative spectra were used. It should also be mentioned that the proposed method is a simple and rapid way requiring no preliminary separation steps and can be used easily for the analysis of these compounds, especially in quality control laboratories.     

A quality by design (QbD) case study on liposomes containing hydrophilic API: II. Screening of critical variables, and establishment of design space at laboratory scale

Two statistical designs were used in this case study as part of an investigation into the feasibility and the advantages of applying QbD concepts to liposome-based complex parenteral controlled release systems containing a hydrophilic active pharmaceutical ingredient (API). The anti-viral drug Tenofovir was used as a model compound. First design (Plackett-Burman) was used to screen eight high-risk variables obtained from risk analysis and assess their impact on liposome characteristics (drug encapsulation efficiency, particle size, and physical stability). It was discovered that out of eight high-risk variables only lipid and drug concentration had significant effects on the drug encapsulation efficiency. This allowed the use of a central composite design (CCD) (with more predictive capability) to fully elucidate the relationship between lipid concentration, drug concentration and encapsulation efficiency. On comparing the CCD model generated response surface with additional data points, the accuracy and robustness of the model was confirmed. Using this developed model, the design space for Tenofovir liposomes preparation has been established in a laboratory setting, within which the preparation variability is minimized. With regard to sample storage stability, it was shown that at 4 °C the prepared Tenofovir liposomes, dispersed in aqueous phase, achieved stability for at least 2 years. These principles can be applied to liposomes containing other hydrophilic APIs, and can provide time and cost saving to industrial formulation scientists, and result in a more robust liposome preparation process.     

Sensor Network Robustness Using Model-Based Data Reconciliation for Continuous Tablet Manufacturing

Advances in continuous manufacturing in the pharmaceutical industry necessitate reliable process monitoring systems that are capable of handling measurement errors inherent in all sensor technologies and detecting measurement outliers to ensure operational reliability. The purpose of this work was to demonstrate data reconciliation (DR) and gross error detection methods as real-time process management tools to accomplish robust process monitoring. DR mitigates the effects of random measurement errors, while gross error detection identifies nonrandom sensor malfunctions. DR is an established methodology in other industries (i.e., oil and gas) and was recently investigated for use in drug product continuous manufacturing. This work demonstrates the development and implementation of model-based steady-state data reconciliation on 2 different end-to-end continuous tableting lines: direct compression and dry granulation. These tableting lines involve different equipment and sensor configurations, with sensor network redundancy achieved using equipment-embedded sensors and in-line process analytical technology tools for the critical process parameters and critical quality attributes. The nonlinearity of the process poses additional challenges to solve the steady-state data reconciliation optimization problem in real time. At-line and off-line measurements were used to validate the framework results.     

Evaluation of Cytochrome P450 Selectivity for Hydralazine as an Aldehyde Oxidase Inhibitor for Reaction Phenotyping

Hydralazine has been reported as a selective mechanism-based inactivator of aldehyde oxidase (AO) and it is widely used in the pharmaceutical industry for reaction phenotyping to estimate fraction metabolized by AO and to identify AO substrates. In this study, however, hydralazine was found to inhibit CYP1A2, 2B6, 2D6, and 3A in human suspension hepatocytes under reaction phenotyping assay conditions, at concentrations that chemically knocked out most of the AO activities (≥50 μM). Furthermore, hydralazine is a time-dependent inhibitor of CYP1A2. Based on these findings, precautions need to be taken when using hydralazine as an AO inhibitor for in vitro studies because fraction metabolized by AO is likely to be overestimated and the likelihood of false positives in identifying AO substrates increases.     

Industrial application of QbD and NIR chemometric models in quality improvement of immediate release tablets

Quality by Design (QbD) and chemometric models are different sides of the same coin. While QbD models utilize experimentally designed settings for optimization of some quality attributes, these settings can also be utilized for chemometric prediction of the same attributes. We aimed to synchronize optimization of comparative dissolution results of carvedilol immediate release tablets with chemometric prediction of dissolution profile and content uniformity of the product. As an industrial application, selection of variables for optimization was done by performing risk assessment utilizing the archived product records at the pharmaceutical site. Experimental tablets were produced with 20 different settings with the variables being contents of sucrose, sodium starch glycolate, lactose monohydrate, and avicel Ph 101. Contents of the excipients were modelled with F1 dissimilarity factor and F2 similarity factor in HCL, acetate, and USP dissolution media to determine the design space. We initiatively utilized Partial Least Square based Structural Equation Modelling (PLS-SEM) to explore how the excipients and their NIR records explained dissolution of the product. Finally, the optimized formula was utilized with varied content of carvedilol for chemometric prediction of the content uniformity.     

The Application of Modeling and Prediction to the Formation and Stability of Amorphous Solid Dispersions

Amorphous solid dispersion (ASD) formulation development is frequently difficult owing to the inherent physical instability of the amorphous form, and limited understanding of the physical and chemical interactions that translate to initial dispersion formation and long-term physical stability. Formulation development for ASDs has been historically accomplished through trial and error or experience with extant systems; however, rational selection of appropriate excipients is preferred to reduce time to market and decrease costs associated with development. Current efforts to develop thermodynamic and computational models attempt to rationally direct formulation and show promise. This review compiles and evaluates important methods used to predict ASD formation and physical stability. Recent literature in which these methods are applied is also reviewed, and limitations of each method are discussed.     

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories.This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.     

A metabonomic approach for mechanistic exploration of pre-clinical toxicology

Metabonomics involves the application of advanced analytical tools to profile the diverse metabolic complement of a given biofluid or tissue. Subsequent statistical modelling of the complex multivariate spectral profiles enables discrimination between phenotypes of interest and identifies panels of discriminatory metabolites that represent candidate biomarkers. This review article presents an overview of recent developments in the field of metabonomics with a focus on application to pre-clinical toxicology studies. Recent research investigations carried out as part of the international COMET 2 consortium project on the hepatotoxic action of the aminosugar, galactosamine (galN) are presented. The application of advanced, high-field NMR spectroscopy is demonstrated, together with complementary application of a targeted mass spectrometry platform coupled with ultra-performance liquid chromatography. Much novel mechanistic information has been gleaned on both the mechanism of galN hepatotoxicity in multiple biofluids and tissues, and on the protection afforded by co-administration of glycine and uridine. The simultaneous identification of both the metabolic fate of galN and its associated endogenous consequences in spectral profiles is demonstrated. Furthermore, metabonomic assessment of inter-animal variability in response to galN presents enhanced mechanistic insight on variable response phentoypes and is relevant to understanding wider aspects of individual variability in drug response. This exemplar highlights the analytical and statistical tools commonly applied in metabonomic studies and notably, the approach is applicable to the study of any toxin/drug or intervention of interest. The metabonomic approach holds considerable promise and potential to significantly advance our understanding of the mechanistic bases for adverse drug reactions.     

Pharmaceutical applications of vibrational chemical imaging and chemometrics: a review

The emergence of chemical imaging (CI) has gifted spectroscopy an additional dimension. Chemical imaging systems complement chemical identification by acquiring spatially located spectra that enable visualization of chemical compound distributions. Such techniques are highly relevant to pharmaceutics in that the distribution of excipients and active pharmaceutical ingredient informs not only a product's behavior during manufacture but also its physical attributes (dissolution properties, stability, etc.). The rapid image acquisition made possible by the emergence of focal plane array detectors, combined with publication of the Food and Drug Administration guidelines for process analytical technology in 2001, has heightened interest in the pharmaceutical applications of CI, notably as a tool for enhancing drug quality and understanding process. Papers on the pharmaceutical applications of CI have been appearing in steadily increasing numbers since 2000. The aim of the present paper is to give an overview of infrared, near-infrared and Raman imaging in pharmaceutics. Sections 2 and 3 deal with the theory, device set-ups, mode of acquisition and processing techniques used to extract information of interest. Section 4 addresses the pharmaceutical applications.