Establishing the Safe Space via Physiologically Based Biopharmaceutics Modeling. Case Study: Fevipiprant/QAW039.
The AAPS journal
Physiologically based pharmacokinetic and absorption modeling has increasingly been implemented for biopharmaceutics applications to define the safe space for drug product quality attributes such as dissolution. For fevipiprant/QAW039, simulations were performed to assess the impact of in vitro dissolution on the in vivo performance of immediate-release film-coated tablets during development and scaling up to commercial scale. A fevipiprant dissolution safe space was established using observed clinical intravenous and oral PK data from bioequivalent and non-bioequivalent formulations. Quality control dissolution profiles with tablets were used as GastroPlus™ model inputs to estimate the in vivo dissolution in the gastrointestinal tract and to simulate human exposure. The model was used to evaluate the intraluminal performance of the dosage forms and to predict the absorption rate limits for the 450 mg dose. The predictive model performance was demonstrated for various oral dosage forms (150‒500 mg), including the non-bioequivalent batches in fasted healthy adults. To define the safe space at 450 mg, simulations were performed using theoretical dissolution profiles. A specification of Q = 80% dissolved in 60 min or less for an immediate-release oral solid dosage form reflected the boundaries of the safe space. The dissolution profile of the 450 mg commercial scale batch was within a dissolution region where bioequivalence is anticipated, not near an edge of failure for dissolution, providing additional confidence to the proposed acceptance criteria. Thus, the safe space allowed for a wider than 10% dissolution difference for bioequivalent batches, superseding f similarity analyses.
10.1208/s12248-023-00787-5
Regulatory Experience with Continuous Manufacturing and Real Time Release Testing for Dissolution in New Drug Applications.
Journal of pharmaceutical sciences
Regulatory submissions involving the use of continuous manufacturing (CM) and/or real-time release testing for dissolution (RTRT-D) to the United States Food and Drug Administration (FDA) were identified spanning several years. The submissions were for orally administered IR tablets and they were examined from a biopharmaceutics perspective to highlight commonly occurring issues which the FDA's assessment teams identified with the proposed use of CM and/or RTRT-D. The objective of this study is to provide recommendations for best practices that will help advance the field by (i) generating greater opportunities for (drug) Applicants to benefit from the implementation of advanced manufacturing approaches, (ii) improving high quality regulatory submissions involving CM and RTRT-D, and thus (iii) lessening the regulatory review burden. This paper has identified several common deficiencies, such as inadequate strategies for stratified sampling of drug product (DP) units, inappropriate design of experiments (DoE), inability of the proposed RTRT-D model to account for dissolution variability and to predict the entire time course of dissolution, insufficient documentation, and unsuitable in vitro dissolution methods.
10.1016/j.xphs.2023.08.004
Application of artificial neural networks for Process Analytical Technology-based dissolution testing.
Nagy Brigitta,Petra Dulichár,Galata Dorián László,Démuth Balázs,Borbás Enikő,Marosi György,Nagy Zsombor Kristóf,Farkas Attila
International journal of pharmaceutics
This work proposes the application of artificial neural networks (ANN) to non-destructively predict the in vitro dissolution of pharmaceutical tablets from Process Analytical Technology (PAT) data. An extended release tablet formulation was studied, where the dissolution was influenced by the composition of the tablets and the tableting compression force. NIR and Raman spectra of the intact tablets were measured, and the dissolution of the tablets was modeled directly from the spectral data. Partial Least Square (PLS) regression and ANN models were developed for the different spectroscopic measurements individually as well as by combining them together. ANN provided up to 3% lower root mean square error for prediction (RMSEP) than the PLS models, due to its capability of modeling non-linearity between the process parameters and dissolution curves. The ANN model using reflection NIR spectra provided the most accurate predictions with 6.5 and 63 mean f and f values between the computed and measured dissolution curves, respectively. Furthermore, ANN served as a straightforward data fusion method without the need for additional preprocessing steps. The method could significantly advance data processing in the PAT environment, contribute to an enhanced real-time release testing procedure and hence the increased efficacy of dissolution testing.
10.1016/j.ijpharm.2019.118464
Visualising liquid transport through coated pharmaceutical tablets using Terahertz pulsed imaging.
International journal of pharmaceutics
Dissolution of pharmaceutical tablets is a complex process, especially for coated tablets where layered structures form an additional barrier for liquid transport into the porous tablet matrix. A better understanding of the role of the coating structure in the mass transport processes that govern drug release, starting with the wetting of the coating layer by the dissolution medium, can benefit the formulation design and optimisation of the production. For this study, terahertz pulsed imaging was used to investigate how dissolution medium can penetrate coated tablets. In order to focus on the fundamental process, the model system for this proof-of-principle study consisted of tablet cores made from pure microcrystalline cellulose compacted to a defined porosity coated with Opadry II, a PVA-based immediate release coating blend. The coating was applied to a single side of flat-faced tablets using vacuum compression moulding. It was possible to resolve the hydration of the coating layer and the subsequent liquid ingress into the dry tablet core. The analysis revealed a discontinuity in density at the interface between coating and core, where coating polymer could enter the pore space at the immediate surface of the tablet cores during the coating process. This structure affected the liquid transport of the dissolution medium into the core. We found evidence for the formation of a gel layer upon hydration of the coating polymer. The porosity of the tablet core impacted the quality of coating and thus affected its dissolution performance (r = 0.6932 for the effective liquid penetration rate RP and the core porosity). This study established a methodology and can facilitate a more in-depth understanding of the role of coating on tablet dissolution.
10.1016/j.ijpharm.2022.121703
Evaluation of the influence of material properties and process parameters on granule porosity in twin-screw wet granulation.
International journal of pharmaceutics
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. dissolution. In current study, the granule porosity along the length of the twin-screw granulator (TSG) barrel was evaluated. An experimental set-up was used allowing the collection of granules at the different TSG compartments. The effect of active pharmaceutical ingredient (API) properties on granule porosity was evaluated by using six formulations with a fixed composition but containing APIs with different physical-chemical properties. Furthermore, the importance of TSWG process parameters liquid-to-solid (L/S) ratio, mass feed rate and screw speed for the granule porosity was evaluated. Several water-related properties as well as particle size, density and flow properties of the API were found to have an important effect on granule porosity. While the L/S ratio was confirmed to be the dictating TSWG process parameter, granulator screw speed was also found to be an important process variable affecting granule porosity. This study obtained crucial information on the effect of material properties and process parameters on granule porosity (and granule formation) which can be used to accelerate TSWG process and formulation development.
10.1016/j.ijpharm.2023.123010
Development of a New Jelly Coating Technology (Oral Jelly Coating) to Improve Prescribed Medication Adherence.
Biological & pharmaceutical bulletin
Tablets are the most commonly prescribed dosage form for oral drug administration. Historically, improvement of medication adherence of tablets has been facilitated through, for example, the use of smaller tablets, distinctive shaped tablets and sugar-coated tablets. In addition, new formulation technologies such as orally disintegrating tablets (OD tablets), micro tablet-type granules, jellies, and film formulations are making it possible to create more easily ingested dosage forms. We have developed a new oral jelly coating formulation that can be applied to any sized tablet without reducing the size of the formulation. It was found that this new jelly layer formed on the tablet surface improved the tablet's slipperiness with an appropriate amount of water, while ensuring no change in the dissolution profile. In addition, the jelly layer was ensured storage stability over time without affecting the dissolution profile. Although further studies are needed, this coating technology can quickly change the tablet surface to a jelly-like state after the tablet is taken, giving the tablet the same slipperiness as if it were taken in jelly, making it easier to pass through the pharynx, and thus improving medication adherence.
10.1248/bpb.b23-00625
Holistically assessing the quality consistency of compound liquorice tablets from similarities of both all chemical fingerprints and the integrated dissolution curves by systematically quantified fingerprint method.
Talanta
In recent years, traditional analytical methods have failed to meet the widespread use of multi-component Chinese pharmaceutical formulations. To solve this problem, this study proposed a comprehensive analytical strategy using compound liquorice tablets (CLTs) as an example, both in terms of chemical quality and dissolution curve consistency. Firstly, the peak purity of the two wavelengths was checked using dual-wavelength absorbance coefficient ratio spectra (DARS) to avoid the fingerprint bias caused by peak purity. Secondly, liquid-phase dual-wavelength tandem fingerprint (DWTF) of 38 batches of CLTs was established for the first time. The two analytical methods were also evaluated using the systematically quantified fingerprint method (SQFM), and the 38 batches of samples were classified into two grades with good quality consistency. Quantitative analysis of the five markers of CLTs was performed simultaneously using the standard curve method (SCM) and the quantitative analysis of multiple components by single marker (QAMS). The results showed no significant differences between the two analytical methods (p > 0.5). In addition, the in vitro dissolution of CLTs in two media (pure water and pH = 4.5 medium) was determined by the total UV fingerprint dissolution assay. The similarity of the dissolution curves was also analyzed by combining the f factor and the dissolution-systematically quantified fingerprint method (DSQFM). The result showed that most of the samples had f > 50 and P satisfied the range of 70-130%. Finally, a principal component analysis (PCA) model was developed to combine the evaluation parameters of chemical fingerprint and dissolution curves for comprehensive analysis of the samples. In this study, a chromatographic and dissolution-based quality analysis method was proposed, which effectively overcomes the shortcomings of previous analytical methods and provides a scientific analytical method for the quality control of natural drugs.
10.1016/j.talanta.2023.124774
Fast, Spectroscopy-Based Prediction of In Vitro Dissolution Profile of Extended Release Tablets Using Artificial Neural Networks.
Pharmaceutics
The pharmaceutical industry has never seen such a vast development in process analytical methods as in the last decade. The application of near-infrared (NIR) and Raman spectroscopy in monitoring production lines has also become widespread. This work aims to utilize the large amount of information collected by these methods by building an artificial neural network (ANN) model that can predict the dissolution profile of the scanned tablets. An extended release formulation containing drotaverine (DR) as a model drug was developed and tablets were produced with 37 different settings, with the variables being the DR content, the hydroxypropyl methylcellulose (HPMC) content and compression force. NIR and Raman spectra of the tablets were recorded in both the transmission and reflection method. The spectra were used to build a partial least squares prediction model for the DR and HPMC content. The ANN model used these predicted values, along with the measured compression force, as input data. It was found that models based on both NIR and Raman spectra were capable of predicting the dissolution profile of the test tablets within the acceptance limit of the f difference factor. The performance of these ANN models was compared to PLS models using the same data as input, and the prediction of the ANN models was found to be more accurate. The proposed method accomplishes the prediction of the dissolution profile of extended release tablets using either NIR or Raman spectra.
10.3390/pharmaceutics11080400
Clarification of the internal structure and factors of poor dissolution of substandard roxithromycin tablets by near-infrared chemical imaging.
International journal of pharmaceutics
The spread of substandard and falsified medicines has become a global problem, especially in low- and middle-income countries (LMICs). Previously, we found that some tablets containing the same active ingredient had large differences in their dissolution even though their contents were comparable. In this study, we investigated the poor dissolution of roxithromycin tablets using near-infrared chemical imaging (NIR-CI) to visualize the internal tablet structure. Roxithromycin tablets collected in LMICs and the pioneer product Rulid® as a reference were cut to a flat surface for analysis. NIR spectral data were normalized, and a principal component analysis was performed to create a tablet internal structure image. For Rulid®, the differences between the spectra with high and low scores were small, and well-defined aggregation of ingredients was not observed. However, large differences in the scores were found for roxithromycin tablets manufactured in some LMICs, and non-uniformity of ingredient distribution and aggregation were observed. Additionally, some pharmaceutical excipients, such as starch or magnesium stearate, were found in certain aggregates by comparing NIR spectra. The NIR-CI results showed some excipients existed as large aggregates, which indicated that the ingredients were not evenly mixed in the roxithromycin tablet, and this contributed to its poor dissolution.
10.1016/j.ijpharm.2021.120232
Dissolution profiles prediction of sinomenine hydrochloride sustained-release tablets using Raman mapping technique.
International journal of pharmaceutics
The work aims to explore the feasibility of Raman mapping in predicting the dissolution profiles of solid oral dosage form. In this study, N = 36 batches of representative sinomenine hydrochloride sustained-release tablets were prepared, using a D-optimal design, to introduce adequate variability, and the Raman mapping data of each tablet were acquired. The partial least squares regression models were established using three kinds of different modes, named single point mode, average mode and multi-point mode, to predict the dissolution profiles based on Raman mapping data. The percent dissolutions at specific time points and the parameters of an exponential function, which was employed to fit the dissolution profiles, were predicted, and the accuracy and precision of prediction were tested. The results showed that the multi-point mode displayed the best accuracy and precision in the prediction of both the dissolutions at the specific time points and the function parameters. In summary, the established method based on Raman mapping avoids the shortcomings of traditional dissolution testing protocols, such as complex operation, time-consuming and high analysis cost, thus has great potential of application and popularization.
10.1016/j.ijpharm.2022.121743
Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets.
Sun Fei,Xu Bing,Zhang Yi,Dai Shengyun,Yang Chan,Cui Xianglong,Shi Xinyuan,Qiao Yanjiang
Drug design, development and therapy
The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules' properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet.
10.2147/DDDT.S119122
Research progress on the application of spectral imaging technology in pharmaceutical tablet analysis.
International journal of pharmaceutics
Tablet as a traditional dosage form in pharmacy has the advantages of accurate dosage, ideal dissolution and bioavailability, convenient to carry and transport. The most concerned tablet quality attributes include active pharmaceutical ingredient (API) contents and polymorphic forms, components distribution, hardness, density, coating state, dissolution behavior, etc., which greatly affect the bioavailability and consistency of tablet final products. In the pharmaceutical industry, there are usually industry standard methods to analyze the tablet quality attributes. However, these methods are generally time-consuming and laborious, and lack a comprehensive understanding of the properties of tablets, such as spatial information. In recent years, spectral imaging technology makes up for the shortcomings of traditional tablet analysis methods because it provides non-contact and rich information in time and space. As a promising technology to replace the traditional tablet analysis methods, it has attracted more and more attention. The present paper briefly describes a series of spectral imaging techniques and their applications in tablet analysis. Finally, the possible application prospect of this technology and the deficiencies that need to be improved were also prospected.
10.1016/j.ijpharm.2022.122100