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Pharmaceutical biotechnology. --- Pharmaceutical technology. --- Pharmaceutical laboratory techniques --- Pharmaceutical laboratory technology --- Technology, Pharmaceutical --- Technology --- Biopharmaceutical technology --- Drugs --- Biotechnology --- Pharmaceutical technology

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Biopharmaceutical and pharmaceutical manufacturing are strongly influenced by the process analytical technology initiative (PAT) and quality by design (QbD) methodologies, which are designed to enhance the understanding of more integrated processes. The major aim of this effort can be summarized as developing a mechanistic understanding of a wide range of process steps, including the development of technologies to perform online measurements and real-time control and optimization. Furthermore, minimization of the number of empirical experiments and the model-assisted exploration of the process design space are targeted. Even if tremendous progress has been achieved so far, there is still work to be carried out in order to realize the full potential of the process systems engineering toolbox. Within this reprint, an overview of cutting-edge developments of process systems engineering for biopharmaceutical and pharmaceutical manufacturing processes is given, including model-based process design, Digital Twins, computer-aided process understanding, process development and optimization, and monitoring and control of bioprocesses. The biopharmaceutical processes addressed focus on the manufacturing of biopharmaceuticals, mainly by Chinese hamster ovary (CHO) cells, as well as adeno-associated virus production and generation of cell spheroids for cell therapies.

Technology: general issues --- History of engineering & technology --- clonal cell population --- phenotypic diversity --- inoculum train --- uncertainty-based --- cell culture model --- biopharmaceutical manufacturing --- Escherichia coli --- hybrid modeling --- machine learning --- model-assisted DoE --- quality by design --- upstream bioprocessing --- surface plasmon resonance (SPR) --- bioprocess --- monitoring --- biosensor --- quality by design (QbD) --- process analytical technology (PAT) --- biotherapeutics production --- vaccines production --- CHO DP-12 --- computational fluid dynamics --- bioreactor characterization --- hydrodynamic gradients --- process development --- critical shear stress --- Kolmogorov length scale --- operational space --- sensors --- cell culture --- spectroscopy --- PAT --- smart biomanufacturing --- soft-sensor --- Adeno-associated virus --- transfection --- PEI --- continuous --- gene therapy --- microcarriers --- bioreactor --- transient expression --- spheroid strength --- β-cells --- diabetes --- shear stress-guided production --- hydrodynamic stress --- Gaussian processes --- Bayes optimization --- Pareto optimization --- multi-objective --- seed train --- Chinese hamster ovary cells --- cryopreservation --- monoclonal antibodies --- N−1 perfusion --- process intensification --- upstream processing --- clonal cell population --- phenotypic diversity --- inoculum train --- uncertainty-based --- cell culture model --- biopharmaceutical manufacturing --- Escherichia coli --- hybrid modeling --- machine learning --- model-assisted DoE --- quality by design --- upstream bioprocessing --- surface plasmon resonance (SPR) --- bioprocess --- monitoring --- biosensor --- quality by design (QbD) --- process analytical technology (PAT) --- biotherapeutics production --- vaccines production --- CHO DP-12 --- computational fluid dynamics --- bioreactor characterization --- hydrodynamic gradients --- process development --- critical shear stress --- Kolmogorov length scale --- operational space --- sensors --- cell culture --- spectroscopy --- PAT --- smart biomanufacturing --- soft-sensor --- Adeno-associated virus --- transfection --- PEI --- continuous --- gene therapy --- microcarriers --- bioreactor --- transient expression --- spheroid strength --- β-cells --- diabetes --- shear stress-guided production --- hydrodynamic stress --- Gaussian processes --- Bayes optimization --- Pareto optimization --- multi-objective --- seed train --- Chinese hamster ovary cells --- cryopreservation --- monoclonal antibodies --- N−1 perfusion --- process intensification --- upstream processing

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Biopharmaceutical and pharmaceutical manufacturing are strongly influenced by the process analytical technology initiative (PAT) and quality by design (QbD) methodologies, which are designed to enhance the understanding of more integrated processes. The major aim of this effort can be summarized as developing a mechanistic understanding of a wide range of process steps, including the development of technologies to perform online measurements and real-time control and optimization. Furthermore, minimization of the number of empirical experiments and the model-assisted exploration of the process design space are targeted. Even if tremendous progress has been achieved so far, there is still work to be carried out in order to realize the full potential of the process systems engineering toolbox. Within this reprint, an overview of cutting-edge developments of process systems engineering for biopharmaceutical and pharmaceutical manufacturing processes is given, including model-based process design, Digital Twins, computer-aided process understanding, process development and optimization, and monitoring and control of bioprocesses. The biopharmaceutical processes addressed focus on the manufacturing of biopharmaceuticals, mainly by Chinese hamster ovary (CHO) cells, as well as adeno-associated virus production and generation of cell spheroids for cell therapies.

Technology: general issues --- History of engineering & technology --- clonal cell population --- phenotypic diversity --- inoculum train --- uncertainty-based --- cell culture model --- biopharmaceutical manufacturing --- Escherichia coli --- hybrid modeling --- machine learning --- model-assisted DoE --- quality by design --- upstream bioprocessing --- surface plasmon resonance (SPR) --- bioprocess --- monitoring --- biosensor --- quality by design (QbD) --- process analytical technology (PAT) --- biotherapeutics production --- vaccines production --- CHO DP-12 --- computational fluid dynamics --- bioreactor characterization --- hydrodynamic gradients --- process development --- critical shear stress --- Kolmogorov length scale --- operational space --- sensors --- cell culture --- spectroscopy --- PAT --- smart biomanufacturing --- soft-sensor --- Adeno-associated virus --- transfection --- PEI --- continuous --- gene therapy --- microcarriers --- bioreactor --- transient expression --- spheroid strength --- β-cells --- diabetes --- shear stress-guided production --- hydrodynamic stress --- Gaussian processes --- Bayes optimization --- Pareto optimization --- multi-objective --- seed train --- Chinese hamster ovary cells --- cryopreservation --- monoclonal antibodies --- N−1 perfusion --- process intensification --- upstream processing --- n/a

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This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems.

Technology: general issues --- History of engineering & technology --- manufacturing process --- additive manufacturing --- IoT --- computer systems and networks --- 3D printing --- digital twin --- Industry 4.0 --- pharmaceutical manufacturing --- biopharmaceutical manufacturing --- process modeling --- mixed-integer linear programming --- bin-packing problem --- material requirements planning --- agri-supply chain management --- variable production rate --- optimal resources --- imperfect production --- eco-efficient production --- closed-loop scheduling --- scheduling stability --- optimal control and scheduling --- fouling --- heat exchanger networks --- continuous manufacturing --- bioprocessing --- process systems engineering --- single-use technology --- AGV—Automated Guided Vehicles --- DES—Discrete Event Simulation --- FMS—Flexible Manufacturing Systems --- OEE—Overall Equipment Efficiency --- WCLcWorld Class Logistic --- abrasive water jet --- cutting --- surface quality --- quality prediction --- 3D simulation modeling and analysis --- model implementation --- bottleneck analysis --- production costs --- resource conservation --- smart manufacturing --- edge computing --- machine learning --- blockchain --- Industrial Internet of Things --- inventory management --- supply chain --- multi-echelon --- stochastic programming --- reinforcement learning --- digitalisation --- model-based --- computational engineering --- process simulation --- LNG terminal --- operational optimization --- BOG compressor --- MINLP --- enterprise process architecture --- new technologies integration --- process intelligence --- real-time monitoring --- fault detection --- predictive process adjustment --- vacuum gripper --- sensor data --- Tri-X Intelligence --- cyber-physical systems --- human-cyber systems --- intelligent systems --- intelligent manufacturing --- multi-parametric programming --- explicit MPC --- enterprise-wide optimisation --- set-point tracking --- algebraic geometry --- continuous pharmaceutical manufacturing --- model predictive control --- state estimation --- quality-by-control (QbC) --- glidant effects --- plant-model mismatch --- regional logistics --- low-carbon economy --- cloud model --- comprehensive evaluation --- Beijing-Tianjin-Hebei region --- pharmaceutical manufacture --- uncertainty --- operational flexibility --- operational envelopes --- modeling --- n/a --- AGV-Automated Guided Vehicles --- DES-Discrete Event Simulation --- FMS-Flexible Manufacturing Systems --- OEE-Overall Equipment Efficiency

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This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems.

Technology: general issues --- History of engineering & technology --- manufacturing process --- additive manufacturing --- IoT --- computer systems and networks --- 3D printing --- digital twin --- Industry 4.0 --- pharmaceutical manufacturing --- biopharmaceutical manufacturing --- process modeling --- mixed-integer linear programming --- bin-packing problem --- material requirements planning --- agri-supply chain management --- variable production rate --- optimal resources --- imperfect production --- eco-efficient production --- closed-loop scheduling --- scheduling stability --- optimal control and scheduling --- fouling --- heat exchanger networks --- continuous manufacturing --- bioprocessing --- process systems engineering --- single-use technology --- AGV-Automated Guided Vehicles --- DES-Discrete Event Simulation --- FMS-Flexible Manufacturing Systems --- OEE-Overall Equipment Efficiency --- WCLcWorld Class Logistic --- abrasive water jet --- cutting --- surface quality --- quality prediction --- 3D simulation modeling and analysis --- model implementation --- bottleneck analysis --- production costs --- resource conservation --- smart manufacturing --- edge computing --- machine learning --- blockchain --- Industrial Internet of Things --- inventory management --- supply chain --- multi-echelon --- stochastic programming --- reinforcement learning --- digitalisation --- model-based --- computational engineering --- process simulation --- LNG terminal --- operational optimization --- BOG compressor --- MINLP --- enterprise process architecture --- new technologies integration --- process intelligence --- real-time monitoring --- fault detection --- predictive process adjustment --- vacuum gripper --- sensor data --- Tri-X Intelligence --- cyber-physical systems --- human-cyber systems --- intelligent systems --- intelligent manufacturing --- multi-parametric programming --- explicit MPC --- enterprise-wide optimisation --- set-point tracking --- algebraic geometry --- continuous pharmaceutical manufacturing --- model predictive control --- state estimation --- quality-by-control (QbC) --- glidant effects --- plant-model mismatch --- regional logistics --- low-carbon economy --- cloud model --- comprehensive evaluation --- Beijing-Tianjin-Hebei region --- pharmaceutical manufacture --- uncertainty --- operational flexibility --- operational envelopes --- modeling --- manufacturing process --- additive manufacturing --- IoT --- computer systems and networks --- 3D printing --- digital twin --- Industry 4.0 --- pharmaceutical manufacturing --- biopharmaceutical manufacturing --- process modeling --- mixed-integer linear programming --- bin-packing problem --- material requirements planning --- agri-supply chain management --- variable production rate --- optimal resources --- imperfect production --- eco-efficient production --- closed-loop scheduling --- scheduling stability --- optimal control and scheduling --- fouling --- heat exchanger networks --- continuous manufacturing --- bioprocessing --- process systems engineering --- single-use technology --- AGV-Automated Guided Vehicles --- DES-Discrete Event Simulation --- FMS-Flexible Manufacturing Systems --- OEE-Overall Equipment Efficiency --- WCLcWorld Class Logistic --- abrasive water jet --- cutting --- surface quality --- quality prediction --- 3D simulation modeling and analysis --- model implementation --- bottleneck analysis --- production costs --- resource conservation --- smart manufacturing --- edge computing --- machine learning --- blockchain --- Industrial Internet of Things --- inventory management --- supply chain --- multi-echelon --- stochastic programming --- reinforcement learning --- digitalisation --- model-based --- computational engineering --- process simulation --- LNG terminal --- operational optimization --- BOG compressor --- MINLP --- enterprise process architecture --- new technologies integration --- process intelligence --- real-time monitoring --- fault detection --- predictive process adjustment --- vacuum gripper --- sensor data --- Tri-X Intelligence --- cyber-physical systems --- human-cyber systems --- intelligent systems --- intelligent manufacturing --- multi-parametric programming --- explicit MPC --- enterprise-wide optimisation --- set-point tracking --- algebraic geometry --- continuous pharmaceutical manufacturing --- model predictive control --- state estimation --- quality-by-control (QbC) --- glidant effects --- plant-model mismatch --- regional logistics --- low-carbon economy --- cloud model --- comprehensive evaluation --- Beijing-Tianjin-Hebei region --- pharmaceutical manufacture --- uncertainty --- operational flexibility --- operational envelopes --- modeling