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Performance testing and computer simulations have promising applications in Quality by Design approaches. The objectives of these studies were to investigate the performance of the disintegration test using different setups in addition to comparing the performance of the disintegration test with the rupture test using soft gelatin dietary supplements capsules. Classifying common herbs according to the Biopharmaceutical Classification System approach was also investigated using ADMET predictor TM. The final objective was evaluation the predictive power of computer simulations of in vitro dissolution in different media. The studies concluded that the disintegration test is robust only if firm specifications were applied. However, this test has no advantage over the rupture test. In silico methods can be used to classify herbs according to the BCS. Computer simulations of dissolution in vitro can be also a potential tool to estimate the dissolution behavior. These tools facilitate prediction of quality desired in a product. / Pharmaceutical Sciences

Yes / The present study demonstrates the application of decision tree algorithms to the co-crystallization process. Fifty four (54) batches of carbamazepine-salicylic acid co-crystals embedded in poly(ethylene oxide) were manufactured via hot melt extrusion and characterized by powder X-ray diffraction, differnetial scanning calorimetry, and near-infrared spectroscopy. This dataset was then applied in WEKA, which is an open-sourced machine learning software to study the effect of processing temperature, screw speed, screw configuration, and poly(ethylene oxide) concentration on the percentage of co-crystal conversion. The decision trees obtained provided statistically meaningful and easy-to-interpret rules, demonstrating the potential to use the method to make rational decisions during the development of co-crystallization processes. / Commonwealth Scholarship Commission in the UK (ZMCS-2018-783) and Engineering and Physical Sciences Research Council (EPSRC EP/J003360/1 and EP/L027011/1)

<div>Drug solubility is a persistent challenge in pharmaceutical product development. The objective of this research is to develop a formulation/processing strategy by means of a biodendrimeric solid dispersion (BDSD) platform, for increasing the solubility and dissolution rate of poorly water-soluble drugs. The BSDS platform combines a novel type of excipient, referred to as DLB, with a new application of the hot melt extrusion (HME) process.</div><div><br></div><div>Four model compounds – phenytoin (PHT), griseofulvin (GSF), ibuprofen (IBU), and loratadine (LOR) – were used to evaluate the solubilization effect of an octenylsuccinate-modified dendrimer-like biopolymer (OS-DLB). Shake-flask solubility measurements show that OS-DLB exerts significant solubilizing effect when present at less than 0.2% in water. The presence of hydrophobic C₈ chains on OS-DLB creates the type of favorable nonpolar microenvironment necessary for producing a parallel liquid phase equilibrium responsible for the increase in the total amount of drug dissolved in aqueous media. The higher the hydrophobicity of the drug, the higher the observed solubilization effect. Isothermal titration calorimetry studies show that drug solubilization by OS-DLB occurs by means of entropy-driven interactions. These studies also show that the intermolecular interaction between IBU and OS-DLB in solution exhibits very small energy change upon mixing but a stronger effect on entropy. In comparison, the intermolecular interaction between the less hydrophobic GSF and OS-DLB have significant effects on both enthalpy and entropy. Consequently, in terms of solubilization enhancement, it was found that the interaction between IBU and OS-DLB is entropy-driven (more favorable), while in the case of GSF, the interacting molecules are arranged to maximize enthalpic interaction.</div><div><br></div><div>Based on the solubility studies, a formulation/processing approach for enhancing the dissolution rate of the model drugs was developed. The biopolymer serving as both carrier and solubilizing agent, was coprocessed with poloxamer, functioning as a processing aid, using hot melt extrusion (HME) as an enabling technology. The result is a non-amorphous solid dispersion, exhibiting high and long-lasting supersaturation upon dissolution. A 3-factor, 3-level Box-Behnken design was implemented to define the optimal design space for the formulation/extrusion process. The results obtained from multivariate data analysis (partial least squares and principal components analysis) and response surface modeling suggest that drug release performance of IBU BDSDs is strongly influenced by the processing variables, while maximum release of GSF from the BDSDs can be attained through selective combination of functional excipients.<br></div>

Les entreprises pharmaceutiques ont progressivement adopté le concept de Process Analytical Technology (PAT) afin de contrôler et d'assurer en temps réel la qualité des produits pharmaceutiques au cours de leur production. Le PAT et un composant central du concept plus général de Quality-by-Design (QbD) promu par les agence régulatrices et visant à construire la qualité des produits via une approche scientifique et la gestion des risques.Une méthode basée sur la spectroscopie proche infrarouge (PIR) a été développée comme un outil du PAT pour contrôler en ligne la cristallisation d'un principe actif pharmaceutique. Au cours du procédé les teneurs en principe actif et en solvant résiduel doivent être déterminées avec précision afin d'atteindre un point d'ensemencement prédéfini. Une méthodologie basée sur les principes du QbD a guidé le développement et la validation de la méthode tout en assurant l'adéquation avec son utilisation prévue. Des modèles basés sur les moindres carrés partiels ont été construits à l'aide d'outils chimiométriques afin de quantifier les 2 analytes d'intérêt. La méthode a été totalement validée conformément aux requis officiels en utilisant les profils d'exactitude. Un suivi du procédé en temps réel a permis de prouver que la méthode correspond à son usage prévu.L'implémentation de cette méthode comme à l'échelle industrielle au lancement de ce nouveau procédé permettra le contrôle automatique de l'étape de cristallisation dans le but d'assurer un niveau de qualité prédéfini de l'API. D'autres avantages sont attendus incluant la réduction du temps du procédé, la suppression d'un échantillonnage difficile et d'analyses hors ligne fastidieuses. / Pharmaceutical companies are progressively adopting and introducing the Process Analytical Technology (PAT) concept to control and ensure in real-time product quality in development and manufacturing. PAT is a key component of the Quality-by-Design (QbD) framework promoted by the regulatory authorities, aiming the building of product quality based on both a strong scientific background and a quality risk management approach.An analytical method based on near infrared (NIR) spectroscopy was developed as a PAT tool to control on-line an API (active pharmaceutical ingredient) crystallization. During this process the API and residual solvent contents need to be precisely determined to reach a predefined seeding point. An original methodology based on the QbD principles was applied to conduct the development and validation of the NIR method and to ensure that it is fitted for its intended use. Partial least squares (PLS) models were developed and optimized through chemometrics tools in order to quantify the 2 analytes of interest. The method was fully validated according to the official requirements using the accuracy profile approach. Besides, a real-time process monitoring was added to the validation phase to prove and document that the method is fitted for purpose.Implementation of this method as an in-process control at industrial plant from the launch of this new pharmaceutical process will enable automatic control of the crystallization step in order to ensure a predefined quality level of the API. Other valuable benefits are expected such as reduction of the process time, and suppression of a difficult sampling and tedious off-line analyzes.

<p>To apply Industry 4.0 technologies and accelerate the modernization of continuous pharmaceutical manufacturing, digital twin (DT) and advanced process control (APC) strategies are indispensable. The DT serves as a virtual representation that mirrors the behavior of the physical process system, enabling real-time monitoring and predictive capabilities. Consequently, this facilitates the feasibility of real-time release testing (RTRT) and enhances drug product development and manufacturing efficiency by reducing the need for extensive sampling and testing. Moreover, APC strategies are required to address variations in raw material properties and process uncertainties while ensuring that desired critical quality attributes (CQAs) of in-process materials and final products are maintained. When deviations from quality targets are detected, APC must provide optimal real-time corrective actions, offering better control performance than the traditional open loop-control method. The progress in DT and APC is beneficial in shifting from the paradigm of Quality-by-Test (QbT) to that of Quality-by-Design (QbD) and Quality-by-Control (QbC), which emphasize the importance of process knowledge and real-time information to ensure product quality.</p> <p><br></p> <p>This study focuses on four key elements and their applications in a continuous dry granulation tableting process, including feeding, blending, roll compaction, ribbon milling and tableting unit operations. Firstly, the necessity of a digital infrastructure for data collection and integration is emphasized. An ISA-95-based hierarchical automation framework is implemented for continuous pharmaceutical manufacturing, with each level serving specific purposes related to production, sensing, process control, manufacturing operations, and business planning. Secondly, investigation of process analytical technology (PAT) tools for real-time measurements is highlighted as a prerequisite for effective real-time process management. For instance, the measurement of mass flow rate, a critical process parameter (CPP) in continuous manufacturing, was previously limited to loss-in-weight (LIW) feeders. To overcome this limitation, a novel capacitance-based mass flow sensor, the ECVT sensor, has been integrated into the continuous direct compaction process to capture real-time powder flow rates downstream of the LIW feeders. Additionally, the use of near-infrared (NIR)-based sensor for real-time measurement of ribbon solid fraction in dry granulation processes is explored. Proper spectra selection and pre-processing techniques are employed to transform the spectra into useful real-time information. Thirdly, the development of quantitative models that establish a link between CPPs and CQAs is addressed, enabling effective product design and process control. Mechanistic models and hybrid models are employed to describe the continuous direct compaction (DC) and dry granulation (DG) processes. Finally, applying APC strategies becomes feasible with the aid of real-time measurements and model predictions. Real-time optimization techniques are used to combine measurements and model predictions to infer unmeasured states or mitigate the impact of measurement noise. In this work, the moving horizon estimation-based nonlinear model predictive control (MHE-NMPC) framework is utilized. It leverages the capabilities of MHE for parameter updates and state estimation to enable adaptive models using data from the past time window. Simultaneously, NMPC ensures satisfactory setpoint tracking and disturbance rejection by minimizing the error between the model predictions and setpoint in the future time window. The MHE-NMPC framework has been implemented in the tableting process and demonstrated satisfactory control performance even when plant model mismatch exists. In addition, the application of MHE enables the sensor fusion framework, where at-line measurements and online measurements can be integrated if the past time window length is sufficient. The sensor fusion framework proves to be beneficial in extending the at-line measurement application from just validation to real-time decision-making.</p>