Implementation Of Quality By Design Research Articles

Quality by Design Framework Applied to GMMA Purification

In recent years, Generalized Modules for Membrane Antigens (GMMA) have received increased attention as an innovative vaccine platform against bacterial pathogens, particularly attractive for low- and middle-income countries because of manufacturing simplicity. The assessment of critical quality attributes (CQAs), product-process interactions, identification of appropriate in process analytical methods, and process modeling is part of a robust quality by design (QbD) framework to support further development and control of manufacturing processes. QbD implementation in the context of the GMMA platform will ensure robust manufacturing of batches with desired characteristics, facilitating technical transfer to local manufacturers, regulatory approval, and commercialization of vaccines based on this technology. Here, we summarize the methodology suggested, applied to a first step of GMMA manufacturing process.Graphical

Overview: flexible and versatile approach of quality by design & process analytical technology in industries

Quality by Design (QbD) is crucial to the creation of contemporary in pharmaceuticals, microbiology, biotechnology, product management etc. In order to build proactive, scientific, and risk-based processes and products, QbD helps and supports both the industry and the FDA. Instead of waiting until the final quality check of the finished product, it is founded on the idea of establishing quality from the very beginning of the process. A successful plan that lowers batch failures and recalls is finally provided by an efficient QbD approach, which offers insights and crucial upstream information throughout the development process. The purpose of this review is to provide an overview of the implementation of Quality by Design (QbD), its tools, elements, and techniques, the relevancy with various guidelines, and the use in present-day pharmaceutical. The IQ Consortium provides information on the current situation of process analytical technology (PAT) as it relates to the creation of active pharmaceutical ingredients (API) in branded pharmaceutical firms. The article gives concrete examples of why and how the pharmaceutical industry uses PAT tools in API development by using an API process pipeline. PAT can reduce personnel risks involved with sampling dangerous compounds for in-process testing and increase R&D efficiency. Although not all chemical processes or stages are easily suited to applying the features of the PAT toolbox, PAT permits accurate and speedy (real or near time) evaluations of processes that might involve compounds that are highly dangerous, transitory, or heterogeneous when necessary. The major regulatory agencies and the biotech sector have worked hard to assist the application of the ideas of Quality by Design (QbD) and Process Analytical Technology (PAT) over the past ten years, with varying degrees of success. Despite the fact that just one biotech therapy has received approval under the QbD paradigm thus far, the tools and methods associated with these two ideas are deeply ingrained in the work procedures of the majority of international pharmaceutical firms. This overview is mainly focused on the QbD and PAT's development in the first place. Second, give an overview of QbD and PAT implementation and point out any places where more contributions are possible.

Quality by Design in Pharmaceuticals: A Review of its Impact on Regulatory Compliance and Product Quality.

The pharmaceutical industry has embraced the quality-by-design (QbD) approach as a promising development, formulation and manufacturing strategy. QbD provides a systematic and science-based framework for designing and producing high-quality products, with a particular focus on identifying, assessing and controlling risks throughout the development process. This review aims to assess the benefits of implementing QbD in pharmaceutical processes, evaluate its impact on regulatory compliance and explore its potential to enhance drug product quality. The primary objective of this review is to evaluate the influence of QbD on pharmaceutical development and manufacturing processes. It also seeks to examine the regulatory requirements associated with the implementation of QbD and highlight the advantages of this approach in terms of product quality and cost-effectiveness. Additionally, the review aims to explore the potential of QbD in improving the safety and efficacy of drug products. The QbD approach holds tremendous potential to revolutionize the pharmaceutical industry by optimizing drug development & manufacturing processes, reducing costs and enhancing product quality and consistency. However, implementing QbD requires a comprehensive understanding of the underlying science, as well as strict adherence to regulatory requirements in drug development and manufacturing. In conclusion, by embracing the QbD approach, the pharmaceutical industry can ensure the production of safe, effective and regulation-compliant products while simultaneously improving process efficiency. This strategic shift toward QbD represents a pivotal step in advancing pharmaceutical research and manufacturing capabilities, ultimately benefiting both the industry and more importantly, patients worldwide.

Current challenges and recent advances on the path towards continuous biomanufacturing.

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

Pitfalls and Opportunities in the Execution of Quality by Design in Analytical Sciences

Abstract: Quality by Design (QbD) is a systematic approach integrated with quality risk management. It uses different design approaches followed by statistical analysis to yield a quality product. Now, the pharmaceutical industries are intrested in the application of QbD principles to analytical methods and term it as Analytical QbD (AQbD), which does not essentially mean less analytical testing; to a particular extent, it means the right analysis at the right time, supported by science and risk evaluation which ensures that the analytical method can be improved throughout its life cycle. However, for that, the analyst must have sound knowledge of Analytical Target Profile (ATP), method performance characteristics, risk assessment, choice of Design of Experiment (DoE), optimization of Method Operable Design Region (MODR). Some papers have cited the importance, regulatory flexibility, theoretical aspects, and statistical analysis of AQbD, but only a few discuss the core issue of gradual implementation of QbD in analytical sciences. For seamless transition, researchers need clarification on AQbD terminologies, acceptable methods, criteria to embrace critical quality attributes (CQAs), and standards to judge the adequacy of controls. This paper summarizes the challenges and solutions for the implementation of AQbD.

Quality by Design Assisted Optimization and Risk Assessment of Black Cohosh Loaded Ethosomal Gel for Menopause: Investigating Different Formulation and Process Variables

Black cohosh (Cimicifuga racemosa) (CR) is a popular herb and is medically lauded for ameliorating myriad symptoms associated with menopause. However, its pharmaceutical limitations and non-availability of a patient-compliant drug delivery approach have precluded its prevalent use. Henceforth, the current research premise is aimed at developing an ethosomal gel incorporating triterpene enriched fraction (TEF) obtained from CR and evaluating its effectiveness through the transdermal application. TEF-loaded ethosomes were formulated using solvent injection, optimized and characterised. The optimized ethosomes were then dispersed into a polymeric gel base to form ethosomal gel which was further compared with the conventional gel by in-vitro and ex-vivo experiments. Here, the quality by design (QbD) approach was exploited for the optimization and development of ethosomal gel. The elements of QbD comprising initial risk assessment, design of experimentation (DoE), and model validation for the development of formulation have all been described in detail. The optimized ethosomes (F03) showed a nanometric size range, negative zeta potential and good entrapment. The in vitro release profile of gel revealed a burst release pattern following the Korsmeyer Peppas model having Fickian diffusion. The transdermal flux of ethosomal gel was observed to be more than that of conventional gel. Texture analysis and rheological characterization of the gel, revealed good strength showing shear thinning and pseudoplastic behaviour. The confocal microscope investigation revealed the deeper skin permeation of ethosomal gel than conventional gel. This result was further strengthened by DSC, IR and histological assessment of the animal skin (Wistar rat), treated with the optimized formulation. Conclusively, the implementation of QbD in the formulation resulted in a better understanding of the process and the product. It aids in the reduction of product variability and defects, hence improving product development efficiencies. Additionally, the ethosomal gel was found to be a more effective and successful carrier for TEF than the conventional gel through the transdermal route. Moreover, this demands an appropriate animal study, which is underway, for a stronger outcome.

Quality by design based development of nanostructured lipid carrier: a risk based approach

The aim of this review is to discuss the development of nanostructured lipid carrier (NLC) by the application of quality by design (QbD). QbD started with the evolution of the quality concept and slow adaptation of quality guidelines, which has now become a regulatory requirement. In this review, brief history and elements of QbD including risk assessment (RA) have been discussed followed by the design of experiments (DoEs) that acts as a tool to analyze the input whose variation can optimize the output with the desired goal. NLC is a versatile delivery system as researchers widely use it to administer therapeutics with different physicochemical properties. The surface of NLC can be modified, making it a suitable delivery system with targeting potential for therapeutics. Implementation of QbD provides a high-quality robust formulation that can consistently meet the patient’s requirement throughout its life cycle without compromising the safety and effectiveness of the drug and delivery system. This review discusses QbD concepts followed by the systematic development of NLC by the application of DoE. Process analytical technology (PAT) and six sigma concepts have also been included which can benefit in the development of optimized NLC.

Quality by Design (QbD) concept Review in Pharmaceuticals

Quality by Design (QbD) refers to a holistic approach towards drug development. Quality by design is a vital part of the modern approach to pharmaceutical quality. The purpose of this practice school topic is to discuss the pharmaceutical Quality by Design (QbD) and illustrate how it can be used to ensure pharmaceutical quality. The QbD is a systemic approach to pharmaceutical development. It means designing and developing formulations and manufacturing processes to ensure predefined product quality. Some of the QbD elements include: Defining Quality target product profile, identifying critical quality attributes, link the drug excipients attributes, establishing design space, control strategy, critical process parameters and product life cycle management. Using QbD, pharmaceutical quality is assured by understanding and controlling formulation and manufacturing variables. A new approach to drug development could increase efficiencies, provide regulatory support and flexibility, and offer important business benefits throughout the product’s life cycle. This PS topic explores the processes used in developing a market formulation and required supportive data, particularly in light of the industry’s current movement toward submissions based on QbD. The work also facilitates the adoption and implementation of QbD. Principles in the development of pharmaceutical industries. Successful implementation of QbD concepts requires cooperation across a multitude of company teams, from R&D to manufacturing to quality control and regulatory affairs. This is necessary to ensure that QbD concepts are incorporated not only when the first activities are initiated around a product’s design but also during the design of the process used to make the product and other activities associated with a product’s life cycle. The application of the concept of quality by design (QbD) presented in this paper aligns with the principles of ICH Q8, Q9 and Q10 guidelines.

QbD Approach: A Framework for Integrating Quality into Pharmaceutical Products

Introduction: The traditional development processes use a quality by testing (QbT) approach that needs continuous testing to determine quality. Such processes are fixed, averse to change, and focus only on process reproducibility. This approach does not allow variation in material and process controls. In order to overcome the shortcomings of the traditional process, regulatory bodies have issued guidelines for the industries to improve the understanding of the process and the quality of the product. It aims to shift from traditional process QbT to a scientific approach quality by design (QbD) to assure product quality in the pharmaceutical industry.
 Methodology: Articles related to QbD published in many search engines such as Scopus, Google Scholar, and PubMed were reviewed.
 Review Findings: In order to ensure the quality of pharmaceutical products, regulatory bodies have emphasized on the implementation of QbD. For this, various guidelines have been published from time to time. The Indian pharmaceutical industry has started to apply the principles of QbD. Implementation of QbD develops a detailed understanding of the manufacturing process. The design space is achieved by QbD within which the expected quality is achieved even with changes in process parameters.
 Conclusion: In short, the QbD approach is a great tool for assuring pharmaceutical product quality and better understanding of the manufacturing process. Therefore, it is imperative to have a successful implementation of the QbD approach.

Harnessing the potential of machine learning for advancing “Quality by Design” in biomanufacturing

ABSTRACT Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (CQAs). To identify CPPs and their interdependencies with product yield and CQAs, design of experiments, and multivariate statistical approaches are typically used in industry. Although these models can predict the effect of CPPs on product yield, there is room to improve CQA prediction performance by capturing the complex relationships in high-dimensional data. In this regard, machine learning (ML) approaches offer immense potential in handling non-linear datasets and thus are able to identify new CPPs that could effectively predict the CQAs. ML techniques can also be synergized with mechanistic models as a ‘hybrid ML’ or ‘white box ML’ to identify how CPPs affect the product yield and quality mechanistically, thus enabling rational design and control of the bioprocess. In this review, we describe the role of statistical modeling in Quality by Design (QbD) for biomanufacturing, and provide a generic outline on how relevant ML can be used to meaningfully analyze bioprocessing datasets. We then offer our perspectives on how relevant use of ML can accelerate the implementation of systematic QbD within the biopharma 4.0 paradigm.

Recommendations for Effective and Defendable Implementation of Quality by Design

Quality by Design (QbD) is a systematic, holistic, and proactive approach to development that begins with predefined objectives and emphasizes product and process understanding and process control based on sound science and quality risk management. In the past decade, an increasing number of pharmaceutical companies have been practicing QbD, enabling the successful development and scale-up of active pharmaceutical ingredient processes. QbD implementation is more complicated than desired in part because of the nonprescriptive nature of the QbD guidelines, which requires interpretation for the appropriate application of QbD, including regional regulations. In this paper, on the basis of observations made during two decades of QbD training and project support as well as frequently asked questions, certain practical recommendations are made regarding effective use of three QbD methods: risk analysis, statistical Design of Experiments, and scale-up investigations. Although QbD is still evolving, because of its business and technical benefits, including the definition of effective control strategies and the development of robust processes, the pharmaceutical industry is embracing the use of QbD elements while maintaining realistic expectations for the evaluation of QbD success.

Application of tools and techniques of quality by design in pharmaceutical process

PurposeThe purpose of this article is to demonstrate the application of the tools and techniques of Quality by Design (QbD) approach in an Indian pharmaceutical drug product manufacturing company and to understand the challenges, managerial implications and lessons learned while implementing this initiative.Design/methodology/approachThis work adopts the Action Research methodology for impurity reduction in a drug product manufacturing company in India by using the tools and techniques of QbD approach. Various QbD tools like Design of experiments, process capability evaluation and control charts were effectively utilized for the study.FindingsAs a part of QbD implementation in the organization, a specific drug product was identified and the impurity level in the product was studied. Significant variables impacting the impurity were identified and the optimum levels for the significant variables were identified through design of experiments. The solutions were implemented and the impurity levels were reduced significantly.Research limitations/implicationsEven though the article is based on a single case study related to tools and techniques of QbD in a single organization in India, the identified problem is a generic product quality related issue for any pharmaceutical drug product manufacturing company. Hence the findings of this research are applicable to pharmaceutical drug manufacturing industry in general.Originality/valueThis article illustrates the systematic usage of various tools and techniques of QbD methodology in a pharmaceutical drug product manufacturing company. The usage of Design of Experiments for process optimization and application of other tools and techniques are ready references for the practitioners and novice users in the field.

Implementation of Quality by Design (QbD) Principles in Regulatory Dossiers of Medicinal Products in the European Union (EU) Between 2014 and 2019

BackgroundQuality by Design (QbD) is a systematic risk-based approach to development, with predefined characteristics and quality risk management throughout the life cycle of a product. International Conference on Harmonization (ICH) guidelines Q8–Q11 give guidance on QbD applications with ICH Q8 (R2)—approved in 2009—describing the principles of QbD in detail. Since its adoption over 10 years ago, more information about QbD usage for the development of medicinal products is expected to be written in regulatory dossiers by companies.MethodsThe present study set out to evaluate the implementation of QbD principles and elements in all EU approved marketing applications (MA) (n = 494), based on information available in the European Public Assessment Reports (EPARs), for a period of six years (2014–2019), starting 5 years after QbD adoption.ResultsOf the 494 MAs, 271 were submitted with a full dossier (article 8(3)). According to EMA (38%), out of the 271 full dossier submissions, only 104 were developed using full QbD. This figure did not increase during this period. Interestingly, between 2014 and 2019, several MAs were not developed via full QbD implementation but used one or more QbD elements during development, including design space. In addition, a higher percentage of small molecule products were developed with QbD as opposed to biotechnology-derived products (78% vs. 22%, respectively).ConclusionOverall, QbD during development of medicinal products is still not commonly described in dossiers. However, more companies started mentioning QbD elements, thus making it a promising step toward QbD as the standard for development in the future.

Electrospinning/electrospraying coatings for metal microneedles: A design of experiments (DOE) and quality by design (QbD) approach

The research presented here shows QbD implementation for the optimisation of the key process parameters in electrohydrodynamic atomisation (EHDA). Here, the electrosprayed nanoparticles and electrospun fibers consisting of a polymeric matrix and dye. Eight formulations were assessed consisting of 5% w/v of polycaprolactone (PCL) in dichloromethane (DCM) and 5% w/v polyvinylpyrrolidone (PVP) in ethanol. A full factorial DOE was used to assess the various parameters (applied voltage, deposition distance, flow rate). Further particle and fiber analysis using Scanning Electron Microscopy (SEM), Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA), Fourier Transform Infrared Spectroscopy (FTIR), particle/fiber size distribution. In addition to this in vitro release studied were carried out using fluorescein and Rhodamine B as model dyes and in vitro permeation studies were applied. The results show a significant difference in the morphology of resultant structures as well as a more rapid release profile for the PVP particles and fibers in comparison to the sustained release profiles found with PCL. In vitro drug release studies showed 100% drug release after 7 days for PCL particles and showed 100% drug release within 120 min for PVP particles. The release kinetics and the permeation study showed that the MN successfully pierced the membrane and the electrospun MN coating released a large amount of the loaded drug within 6 h. This study has demonstrated the capability of these robust MNs to encapsulate a diverse range drugs within a polymeric matrix giving rise to the potential of developed personalised medical devices.

Development and optimization of beer containing malted and non-malted substitutes using quality by design (QbD) approach

Quality by Design (QbD) approach has been widely used in the pharmaceutical field, but its application in the development of food products is recent. The objective of this work was to apply QbD in the development of Ale-type beer, with up to 45% of barley malt substitutes, with alcohol content of 5.50 ± 0.55% v/v and a good sensory evaluation. A simplex-centroid mixture design was used, in which five cereals were tested: maize, oat malt, rice, rye malt, and sorghum. In the screening design, rice, maize, and oat malt were selected. The optimization design allowed the definition of the design space to meet critical quality attributes. The standard (100% barley malt) and optimized (55% barley malt, 42% oat malt, and 3% maize) formulations had similar physicochemical, fermentative, and sensory parameters. The implementation of QbD helps improve quality and reduce quality deviations. • Implementation of QbD promotes innovation in the creation of new food products. • A simplex-centroid mixture design was used during screening and optimization steps. • Design space region allowed to achieve physicochemical and sensory requirements. • Optimized beer was obtained using 55% barley malt, 42% oat malt and 3% maize.

Modeling of hydrophobic interaction chromatography for the separation of antibody-drug conjugates and its application towards quality by design

Antibody-drug conjugates (ADCs) are hybrid molecules based on monoclonal antibodies (mAbs) with covalently attached cytotoxic small-molecule drugs. Due to their potential for targeted cancer therapy, they form part of the diversifying pipeline of various biopharmaceutical companies, in addition to currently seven commercial ADCs. With other new modalities, ADCs contribute to the increasing complexity of biopharmaceutical development in times of growing costs and competition. Another challenge is the implementation of quality by design (QbD), which receives a lot of attention. In order to answer these challenges, mechanistic models are gaining interest as tools for enhanced process understanding and efficient process development. The drug-to-antibody ratio (DAR) is a critical quality attribute (CQA) of ADCs. After the conjugation reaction, the DAR can still be adjusted by including a hydrophobic interaction chromatography (HIC) step. In this work, we developed a mechanistic model for the preparative separation of cysteine-engineered mAbs with different degrees of conjugation with a non-toxic surrogate drug. The model was successfully validated for varying load compositions with linear and optimized step gradient runs, applying conditions differing from the calibration runs. In two in silico studies, we then present scenarios for how the model can be applied profitably to ensure a more robust achievement of the target DAR and for the efficient characterization of the design space. For this, we also used the model in a linkage study with a kinetic reaction model developed by us previously. The combination of the two models effectively widens system boundaries over two adjacent process steps. We believe this work has great potential to help advance the incorporation of digital tools based on mechanistic models in ADC process development by illustrating their capabilities for efficient process development and increased robustness. Mechanistic models can support the implementation of QbD and eventually might be the basis for digital process twins able to represent multiple unit operations.

Roadmap for Quality by Design Implementation for Dietary Supplements.

Recently, there is a growing interest in quality by design (QbD) in the dietary supplements industry. Effective QbD implementation necessitates a comprehensive understanding of multiple factors such as; the relationship between the critical qualities attributes (CQAs) and the scientific properties of the dietary supplement, the relationship between the manufacturing process, CQAs and the variability in raw materials. There are still two critical challenging concerns to be addressed in the implementation of QbD for herbal drugs. First, the quality variation of botanical raw materials and second, the difficulty in defining the satisfactory ranges of CQAs. In order to tackle these challenges, this review provides a snapshot of the numerous techniques that can be used in the identification and characterization of the botanical raw materials, therefore, will help in the successful QbD implementation for botanicals and dietary supplements. In order to implement this approach and to be considered in the current dietary supplement regulations, fruitful discussions and collaborations between academia, industry and regulatory agencies are required.

Multiparametric quality by design-fuzzy model applied in the development of a biomedical measuring system

This work presents the adaptation of the Quality by Design (QbD) approach for application in the quality assurance of a biomedical measuring system under development. First attempts in applying QbD to biomedical technologies indicated a significantly higher number of parameters than its traditional application in the pharmaceutical industry. These preliminary studies did not fulfill the QbD stage of Design Space (DS) configuration for biomedical devices, an essential step to identifying the proper operating ranges of parameters and guaranteeing quality features. Therefore, it persisted the challenge of configuring DS for health devices, overcoming dependences in the interaction of multiple process parameters and critical attributes. The present work develops a hybrid QbD-Fuzzy approach for multiparametric DS configuration. The proposed method was applied in the development phase of a low-cost and high-sensitive magnetic measuring system for locating metallic foreign bodies in patients, employing sensors based on the Giant Magnetoimpedance effect. The results provided the acceptable operating ranges of the multiple process parameters to ensure the biomedical equipment's suitability. The proposed strategy contributes to the QbD implementation in biomedical technologies and, therefore, promotes the reliability of diagnostic and therapeutic results in the clinical environment.

Quality by Design: Concept to Applications

Quality by Design (QbD) is associated with a modern, systematic, scientific and novel approach which is concerned with pre-distinct objectives that not only focus on product, process understanding but also lead to process control. It predominantly signifies the design and product improvement and the manufacturing process in order to fulfill the predefined manufactured goods or final products quality characteristics. It is quite essential to identify the desired and required product performance report, such as Target Product Profile, typical Quality Target Product Profile (QTPP) and Critical Quality Attributes (CQA). This review highlighted the concepts of QbD design space, for critical material attributes (CMAs) as well as the critical process parameters that can totally affect the CQAs within which the process shall be unaffected thus, consistently manufacturing the required product. Risk assessment tools and design of experiments are its prime components. This paper outlines the basic knowledge of QbD, the key elements; steps as well as various tools for QbD implementation in pharmaceutics field are presented briefly. In addition to this, quite a lot of applications of QbD in numerous pharmaceutical related unit operations are discussed and summarized. This article provides a complete data as well as the roadmap for universal implementation and application of QbD for pharmaceutical products.

A Novel Framework to Aid the Development of Design Space across Multi-Unit Operation Pharmaceutical Processes-A Case Study of Panax Notoginseng Saponins Immediate Release Tablet.

The fundamental principle of Quality by Design (QbD) is that the product quality should be designed into the process through an upstream approach, rather than be tested in the downstream. The keystone of QbD is process modeling, and thus, to develop a process control strategy based on the development of design space. Multivariate statistical analysis is a very useful tool to support the implementation of QbD in pharmaceutical process development and manufacturing. Nowadays, pharmaceutical process modeling is mainly focused on one-unit operations and system modeling for the development of design space across multi-unit operations is still limited. In this study, a general procedure that gives a holistic view for understanding and controlling the process settings for the entire manufacturing process was investigated. The proposed framework was tested on the Panax Notoginseng Saponins immediate release tablet (PNS IRT) production process. The critical variables and the critical units acting on the process were identified according to the importance of explaining the variability in the multi-block partial least squares path model. This improved understanding of the process by illustrating how the properties of the raw materials, the process parameters in the wet granulation and the compaction and the intermediate properties affect the tablet properties. Furthermore, the design space was developed to compensate for the variability source from the upstream. The results demonstrated that the proposed framework was an important tool to gain understanding and control the multi-unit operation process.