Data reconciliation in the Quality-by-Design (QbD) implementation of pharmaceutical continuous tablet manufacturing

Su, Qing; Bommireddy, Yasasvi; Shah, Yash; Ganesh, Sudarshan; Moreno, Mariana; Liu, Jianfeng; Yazdanpanah, Nima; O’Connor, Thomas; Reklaitis, Gintaras V.; Nagy, Zoltán K.

doi:10.1016/j.ijpharm.2019.04.003

Cited by 35 publications

(14 citation statements)

References 46 publications

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“…The QTPP may include dosage form, intended use in the clinical, delivery system, route of administration, the strength of dosage form, container and closure system, factors affecting pharmacokinetics (dissolution), quality criteria of drug product like stability, purity and drug release [4] . Identification of QTPP is followed by the identification of factors which may instigate the QTPP and to further analyze those which do so perilously [5] . These factors are the Critical Quality Attributes (CQAs) of product which eminently depends on the Critical Material Attributes (CMAs) of excipient used in product development along with Critical Process Parameters (CPPs) during manufacturing [6] .…”

Section: Computationalmentioning

confidence: 99%

Scalable Design and Development of Modified Release Hydrochlorothiazide Formulation Employing Quality by Design Approach

Singhai¹,

Sharma²,

Paliwal³

et al. 2022

IJPS

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Singhai et al.: Quality by Design based Scalable Formulation Development of HydrochlorothiazideMyocardial infarction, generally known as 'heart attack' occurs predominantly during the early morning hours and a cause of millions of death worldwide. Hydrochlorothiazide is the recommended drug for the prevention of heart disease, but the commercial market lacks its long action (>4 h) formulation. The endeavor of the present research was to develop a quality product profile of hydrochlorothiazide modified release tablets (~14 h release) by applying computational quality by design approach. Three independent factors were identified by qualitative and quantitative risk assessment. Selected dependent variables were cumulative percent of dissolved hydrochlorothiazide in 2, 5, 8 and 12 h. Graphical tools like half normal, normal and Pareto charts were used to manage model selection. The graphical relationship among the critical, independent variables was represented using contour plot and three-dimensional surface plot. Design space was identified by plotting overlay plot using three factors, two-level full factorial design. Outstanding correlation was observed between predicted and actual values. Similarity factor (F2) of reproducible trials was 78 and 79, and content uniformity was 100.9 % and 100.4 %. Average weight, hardness, thickness, diameter and friability were within acceptable limits. Quality by design approach, along with quality risk management tool furnished an efficient and effective paradigm to structure quality modified release tablets of hydrochlorothiazide.

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Section: Computationalmentioning

confidence: 99%

Scalable Design and Development of Modified Release Hydrochlorothiazide Formulation Employing Quality by Design Approach

Singhai¹,

Sharma²,

Paliwal³

et al. 2022

IJPS

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“…Therefore, models for glidant effects in die filling and compression processes will be used to monitor and control the porosity and tensile strength of tablets. Specifically, these mechanistic models capture the effects of glidant concentration and mixing conditions [61,62].…”

Section: Tablet Press Modelmentioning

confidence: 99%

“…The elastic recovery model is not sensitive to the glidant mixing conditions [61,62], and it is governed by:…”

Section: Tablet Press Modelmentioning

confidence: 99%

“…In this case the four-by-five non-square level-e control system is comprised of controlled variables consisting of the tablet weight, pre-compression force, production rate, and tensile strength and manipulated variables consisting of the dosing position, pre-compression thickness, main compression thickness, turret speed, and glidant concentration. It is assumed that measurements for the tablet weight, pre-compression force, main compression force, and production rate are all available every second [61]. In this simulation, it should be noted that the main compression force was not a directly controlled variable with specified set points.…”

Section: Tablet Press Modelmentioning

confidence: 99%

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Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press

et al. 2021

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The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects.

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“…QTPP can be defined as "A prospective summary of the quality characteristics of a drug product that ideally will be achieved to ensure the desired quality, taking into account safety and efficacy of the drug" 12 . The second step involves the identification of factors which may influence QTPP 13 . These are called critical quality attributes of the product (CQAs).…”

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confidence: 99%

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2019

IJPSR

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Selecting the best possible design is an uphill task considering a lot of criteria which must be scrutinized while choosing any design out of many alternative design options available. The experimental design is often compared and selected based on alphabetical design optimality criteria, like A, D, G or V. Each of them attempts to summarize any one important characteristic of the selected design. G-optimality criteria favor those experimental designs which are having the smallest maximum prediction variance over the entire region of interest. It does not consider the distribution of the magnitude of the prediction variance throughout the region. Graphical methods like variance dispersion graph and the fraction of design space plots can be used to overcome this drawback. These graphical methods are explored extensively for comparing the quality of prediction throughout the design space. It serves as a useful tool to assess the prediction performance of the design and making a comparison between experimental designs. The fraction of the design space plot provides a comprehensive picture of the predictive quality of experimental design through the entire region of interest. Single curve provides detailed information of scaled prediction variance for an assumed model and specific design region for the selected design. Here Fraction of design space plots is adapted to evaluate designs for optimization of modified release tablets of hydrochlorothiazide to get desired in-vitro dissolution profile. Three response surface methodology designs are compared by applying this plot including Central Composite Circumscribed and Face centered design along with Box-Behnken design using Design expert software for modeling.

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Data reconciliation in the Quality-by-Design (QbD) implementation of pharmaceutical continuous tablet manufacturing

Cited by 35 publications

References 46 publications

Scalable Design and Development of Modified Release Hydrochlorothiazide Formulation Employing Quality by Design Approach

Scalable Design and Development of Modified Release Hydrochlorothiazide Formulation Employing Quality by Design Approach

Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press

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