Retrospective Quality by Design (rQbD) applied to the optimization of orodispersible films

Question-based review for pharmaceutical development: An enhanced quality approach

Over the last years, the pharmaceutical industry has faced real challenges regarding quality assurance. In this context, the establishment of more holistic approaches to the pharmaceutical development has been encouraged. The emergence of the Quality by Design (QbD) paradigm as systematic, scientific and risk-based methodology introduced a new concept of pharmaceutical quality. In essence, QbD can be interpreted as a strategy to maximize time and cost savings. An in-depth understanding of the formulation and manufacturing process is demanded to optimize the safety, efficacy and quality of a drug product at all stages of development. This innovative approach streamlines the pharmaceutical Research and Development (R&D) process, provides greater manufacturing flexibility and reduces regulatory burden. To assist in QbD implementation, International Conference on Harmonisation (ICH), U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA) organized and launched QbD principles in their guidance for industry, identifying key concepts and tools to design and develop a high-quality drug product. Despite the undeniable advantages of the QbD approach, and the widespread information on QbD regulatory expectations, its full implementation in the pharmaceutical field is still limited. The present review aims to establish a crosswise overview on the current application status of QbD within the framework of the ICH guidelines (ICH Q8(R2) - Q14 and ICH Q2(R2)). Moreover, it outlines the way information gathered from the QbD methodology is being harmonized in Marketing Authorization Applications (MAAs) for European market approval. This work also highlights the challenges that hinder the deployment of the QbD strategy as a standard practice.

Design space determination of pharmaceutical processes: Effects of control strategies and uncertainty

The identification of process Design Space (DS) is of high interest in highly regulated industrial sectors, such as pharmaceutical industry, where assurance of manufacturability and product quality is key for process development and decision-making. If the process can be controlled by a set of manipulated variables, the DS can be expanded in comparison to an open-loop scenario, where there are no controls in place. Determining the benefits of control strategies may be challenging, particularly when the available model is complex and computationally expensive - which is typically the case of pharmaceutical manufacturing. In this study, we exploit surrogate-based feasibility analysis to determine whether the process satisfies all process constraints by manipulating the process inputs and reduce the effect of uncertainty. The proposed approach is successfully tested on two simulated pharmaceutical case studies of increasing complexity, i.e., considering (i) a single pharmaceutical unit operation, and (ii) a pharmaceutical manufacturing line comprised of a sequence of connected unit operations. Results demonstrate that different control actions can be effectively exploited to operate the process in a wider range of inputs and mitigate uncertainty.

Methods for Developing a Process Design Space Using Retrospective Data

Prospectively planned designs of experiments (DoEs) offer a valuable approach to preventing collinearity issues that can result in statistical confusion, leading to misinterpretation and reducing the predictability of statistical models. However, it is also possible to develop models using historical data, provided that certain guidelines are followed to enhance and ensure proper statistical modeling. This article presents a methodology for constructing a design space using process data, while avoiding the common pitfalls associated with retrospective data analysis. For this study, data from a real wet granulation process were collected to pragmatically illustrate all the concepts and methods developed in this article.

Interpretable artificial neural networks for retrospective QbD of pharmaceutical tablet manufacturing based on a pilot-scale developmental dataset

As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a growing need to effectively predict the product quality based on manufacturing or in-process data. Although artificial neural networks (ANNs) have emerged as powerful tools in data-rich environments, their implementation in pharmaceutical manufacturing is hindered by their black-box nature. In this work, ANNs were developed and interpreted to demonstrate their applicability to increase process understanding by retrospective analysis of developmental or manufacturing data. The in vitro dissolution and hardness of extended-release, directly compressed tablets were predicted from manufacturing and spectroscopic data of pilot-scale development. The ANNs using material attributes and operational parameters provided better results than using NIR or Raman spectra as predictors. ANNs were interpreted by sensitivity analysis, helping to identify the root cause of the batch-to-batch variability, e.g., the variability in particle size, grade, or substitution of the hydroxypropyl methylcellulose excipient. An ANN-based control strategy was also successfully utilized to mitigate the batch-to-batch variability by flexibly operating the tableting process. The presented methodology can be adapted to arbitrary data-rich manufacturing steps from active substance synthesis to formulation to predict the quality from manufacturing or development data and gain process understanding and consistent product quality.

SEDDS Basic Design and Recent Formulation Advancement: A Concurrent Review

In the present scenario, lipid-based novel drug delivery systems are the area of interest for the formulation scientist in order to improve the bioavailability of poorly water-soluble drugs. A selfemulsifying drug delivery system (SEDDS) upon contact with the gastrointestinal fluid, forms an o/w emulsion. SEDDS has gained popularity as a potential platform for improving the bioavailability of the lipophilic drug by overcoming several challenges. The various advantages like improved solubility, bypassing lymphatic transport, and improvement in bioavailability are associated with SMEDDS or SNEDDS. The extent of the formation of stable SEDDS depends on a specific combination of surfactant, co-surfactant, and oil. The present review highlighted the different aspects of formulation design along with optimization and characterization of SEDDS formulation. It also gives a brief description of the various aspects of the excipients used in SEDDS formulation. This review also includes the conflict between types of SEDDS based on droplet size. There is an extensive review of various research regarding different solidification techniques used for SEDDS in the last three years.

Development and Evaluation of Cannabidiol Orodispersible Tablets Using a 23-Factorial Design

Orodispersible tablets (ODTs) are pharmaceutical formulations used to obtain fast therapeutic effects, usually recommended for geriatric and pediatric patients due to their improved compliance, bioavailability, ease of administration, and good palatability. This study aimed to develop ODTs with cannabidiol (CBD) phytocannabinoid extracted from Cannabis sativa used in the treatment of Lennox–Gastaut and Dravet syndromes. The tablets were obtained using an eccentric tableting machine and 9 mm punches. To develop CBD ODTs, the following parameters were varied: the Poloxamer 407 concentration (0 and 10%), the type of co-processed excipient (Prosolv^® ODT G2—PODTG2 and Prosolv^® EasyTab sp—PETsp), and the type of superdisintegrant (Croscarmellose—CCS, and Soy Polysaccharides—Emcosoy^®—EMCS), resulting in eleven formulations (O1–O11). The following dependent parameters were evaluated: friability, disintegration time, crushing strength, and the CBD dissolution at 1, 3, 5, 10, 15, and 30 min. The dependent parameters were verified according to European Pharmacopoeia (Ph. Eur.) requirements. All the tablets obtained were in accordance with quality requirements in terms of friability (less than 1%), and disintegration time (less than 180 s). The crushing strength was between 19 N and 80 N. Regarding the dissolution test, only four formulations exhibited an amount of CBD released higher than 80% at 30 min. Taking into consideration the results obtained and using the Modde 13.1 software, an optimal formulation was developed (O12), which respected the quality criteria chosen (friability 0.23%, crushing strength of 37 N, a disintegration time of 27 s, and the target amount of CBD released in 30 min of 99.3 ± 6%).

Using a material database and data fusion method to accelerate the process model development of high shear wet granulation

High shear wet granulation (HSWG) has been wildly used in manufacturing of oral solid dosage (OSD) forms, and process modeling is vital to understanding and controlling this complex process. In this paper, data fusion and multivariate modeling technique were applied to develop a formulation-process-quality model for HSWG process. The HSWG experimental data from both literature and the authors' laboratory were fused into a single and formatted representation. A material database and material matching method were used to compensate the incomplete physical characterization of literature formulation materials, and dimensionless parameters were utilized to reconstruct process variables at different granulator scales. The exploratory study on input materials properties by principal component analysis (PCA) revealed that the formulation data collected from different articles generated a formulation library which was full of diversity. In prediction of the median granule size, the partial least squares (PLS) regression models derived from literature data only and a combination of literature data and laboratory data were compared. The results demonstrated that incorporating a small number of laboratory data into the multivariate calibration model could help significantly reduce the prediction error, especially at low level of liquid to solid ratio. The proposed data fusion methodology was beneficial to scientific development of HSWG formulation and process, with potential advantages of saving both experimental time and cost.

Robustness Optimization of an Existing Tablet Coating Process Applying Retrospective Knowledge (rQbD) and Validation

The objective of these studies is to verify and validate the improvement in the inter-tablet coating uniformity for an industrially commercialized coated tablet, without involving changes in the approved registration dossier. Using the CPP (critical process parameters) determined from previous retrospective statistical analysis, the recommended working ranges are identified. Retrospective analysis showed that the design of experiments (DoE) provided an improved process variable configuration. Therefore, it is decided to study two critical parameters: Product temperature and drum speed, with an additional 2² experimental design. The quality results of the samples analyzed show that the aesthetic defects of the batches made with the new working ranges have been reduced. These results have also been corroborated with the 42 industrial batches manufactured with the new ranges. With the optimized parameters, tablets have been coated and the suitability of the model determined. The results demonstrated the overall reliability and effectiveness of the proposed Quality by Design approach and provides a useful tool to help optimize the industrial coating process. This study confirms that it is possible to optimize and validate the manufacturing process of an existing commercial product by means of a DoE with retrospective data. Therefore, no variation in the dossier is required.

Quality by Design (QbD) Assisted Fabrication of Fast Dissolving Buccal Film for Clonidine Hydrochloride: Exploring the Quality Attributes

The present work endeavors fabrication of fast dissolving buccal film of clonidine hydrochloride by employing quality by design (QbD) based approach. The total nine formulations were prepared according to formulation by design helped by JMP software 13.2.1. The patient oriented quality target product profiles were earmarked and on that basis critical quality attributes were identified. Preliminary screening studies along with initial risk assessment eased the selection of film-forming polymer (HPMC E 15) and plasticizer (PEG 400) as CMAs for formulation of films. A 32 full factorial plan was utilized for assurance of impact, i.e., HPMC E15 (X1) and PEG 400 (X2), as independent variables (factors) on thickness (mm) (Y1), disintegration time (s) (Y2), folding endurance (Y3), and tensile strength (kg) (Y4). Furthermore, prediction profiler assists in predicting composition of best formulation encompassing desired targeted response. The optimized formulation (F6) showed fast drug dissolution (>90%) within 8 min, and solid state characterization by DSC, XRD revealed excellent film characteristics. In a nutshell, the fast dissolving buccal film for clonidine hydrochloride was successfully developed assisted by QbD approach with markedly improved biopharmaceutical performance as well as patient compliance.