31 results found
Papathanasiou MM, Kontoravdi C, 2020, Engineering challenges in therapeutic protein product and process design, CURRENT OPINION IN CHEMICAL ENGINEERING, Vol: 27, Pages: 81-88, ISSN: 2211-3398
Papathanasiou MM, Stamatis C, Lakelin M, et al., 2020, Autologous CAR T-cell therapies supply chain: challenges and opportunities?, Cancer Gene Therapy, ISSN: 0929-1903
Chimeric antigen receptor (CAR) T cells are considered a potentially disruptive cancer therapy, showing highly promisingresults. Their recent success and regulatory approval (both in the USA and Europe) are likely to generate a rapidly increasingdemand and a need for the design of robust and scalable manufacturing and distribution models that will ensure timely andcost-effective delivery of the therapy to the patient. However, there are challenging tasks as these therapies are accompaniedby a series of constraints and particularities that need to be taken into consideration in the decision-making process. Here, wepresent an overview of the current state of the art in the CAR T cell market and present novel concepts that can debottleneckkey elements of the current supply chain model and, we believe, help this technology achieve its long-term potential.
Kis Z, Papathanasiou M, CalvoSerrano R, et al., 2019, A model‐based quantification of the impact of new manufacturing technologies on developing country vaccine supply chain performance: A Kenyan case study, Journal of Advanced Manufacturing and Processing, Vol: 1, ISSN: 2637-403X
Papathanasiou MM, Burnak B, Katz J, et al., 2019, Assisting continuous biomanufacturing through advanced control in downstream purification, Computers and Chemical Engineering, Vol: 125, Pages: 232-248, ISSN: 0098-1354
Aiming to significantly improve their processes and secure market share, monoclonal antibody (mAb) manufacturers seek innovative solutions that will yield improved production profiles. In that space, continuous manufacturing has been gaining increasing interest, promising more stable processes with lower operating costs. However, challenges in the operation and control of such processes arise mainly from the lack of appropriate process analytics tools that will provide the required measurements to guarantee product quality. Here we demonstrate a Process Systems Engineering approach for the design a novel control scheme for a semi-continuous purification process. The controllers are designed employing multi-parametric Model Predictive Control (mp-MPC) strategies and the successfully manage to: (a) follow the system periodicity, (b) respond to measured disturbances and (c) result in satisfactory yield and product purity. The proposed strategy is also compared to experimentally optimized profiles, yielding a satisfactory agreement.
Papathanasiou MM, Burnak B, Katz J, et al., 2019, Control of a dual mode separation process via multi-parametric Model Predictive Control, 12th International-Federation-of-Automatic-Control (IFAC) Symposium on Dynamics and Control of Process Systems including Biosystems (DYCOPS), Publisher: ELSEVIER SCIENCE BV, Pages: 988-993, ISSN: 2405-8963
Papathanasiou MM, Burnak B, Katz J, et al., 2019, CONTROL OF SMALL-SCALE CHROMATOGRAPHIC SYSTEMS UNDER DISTURBANCES, Editors: Munoz, Laird, Realff, Publisher: ELSEVIER SCIENCE BV, Pages: 269-274
Wang X, Kong Q, Papathanasiou MM, et al., 2018, Precision healthcare supply chain design through multi-objective stochastic programming, Computer Aided Chemical Engineering, Pages: 2137-2142
© 2018 Elsevier B.V. Following the FDA's historic approval of the first cell-based, autologous, cancer therapy in 2017, there has been an increasing growth in the personalized cell therapy market. Both the personalized character as well as the sensitive nature of these therapies, has increased the complexity of their supply chain design and optimisation. In this work, we have addressed key issues in the cyclic supply chain for simultaneous design of the supply chain and the manufacturing plan. A comprehensive optimisation based methodology through both deterministic and stochastic programming is presented and applied to study the Chimeric Antigen Receptor (CAR) T cell therapies. Multiple objectives including maximisation of the overall net present value (NPV) and minimisation of the average response time of all patients are evaluated, while accounting the uncertainties in patients’ demand distribution. Results indicate that the total benefits from the optimized supply chain management are significant compared with the current global market.
Papathanasiou MM, Onel M, Nascu I, et al., 2018, Computational tools in the assistance of personalized healthcare, Computer Aided Chemical Engineering, Pages: 139-206, ISBN: 9780444639646
© 2018 Elsevier B.V. Process Systems Engineering has been many years in the forefront, advancing the standards in healthcare and beyond. Gradually, integrated methods that utilize both experimental and/or clinical data, as well as in silico tools are becoming popular among the medical community. In silico tools have already demonstrated their great potential in various sectors, assisting the industry to produce experiments of significantly reduced cost that allow thorough investigation of the system at hand. Similarly, in biomedical systems, the advancement of the current state of the art through the development of intelligent computational tools can lead to personalized healthcare protocols. The first part of this chapter serves as a brief review of the computational tools commonly used in healthcare, such as big data analytics and dynamic mathematical models. The challenges characterizing biomedical systems, such as data availability and patient variability, are also discussed here. We present the advantages and limitations of the various methods and we suggest a generic framework for the design and testing of advanced in silico platforms. The PARametric Optimization and Control (PAROC) framework presented here is based on the design of high-fidelity, dynamic, mathematical models that are then validated using experimental and/or clinical data. Such models provide the basis for the execution of optimization and control studies for the design of patient-specific treatment protocols. The final part of the chapter is dedicated to the application of PAROC to three different biomedical examples, namely: (i) acute myeloid leukemia, (ii) the anesthesia process, and (iii) diabetes mellitus. The challenges of each case are discussed and the application of the relevant PAROC steps is demonstrated.
Papathanasiou MM, Steinebach F, Morbidelli M, et al., 2017, Intelligent, model-based control towards the intensification of downstream processes, COMPUTERS & CHEMICAL ENGINEERING, Vol: 105, Pages: 173-184, ISSN: 0098-1354
Papathanasiou MM, Quiroga-Campano AL, Steinebach F, et al., 2017, Advanced Model-Based Control Strategies for the Intensification of Upstream and Downstream Processing in mAb Production, BIOTECHNOLOGY PROGRESS, Vol: 33, Pages: 966-988, ISSN: 8756-7938
Oberdieck R, Diangelakis NA, Nascu I, et al., 2016, On multi-parametric programming and its applications in process systems engineering, CHEMICAL ENGINEERING RESEARCH & DESIGN, Vol: 116, Pages: 61-82, ISSN: 0263-8762
Papathanasiou MM, Avraamidou S, Oberdieck R, et al., 2016, Advanced control strategies for the multicolumn countercurrent solvent gradient purification process, AIChE Journal, ISSN: 0001-1541
The multicolumn countercurrent solvent gradient purification process (MCSGP) is a semicontinuous, chromatographic separation process used in the production of monoclonal antibodies) . The process is characterized by high model complexity and periodicity that challenge the development of control strategies, necessary for feasible and efficient operation and essential toward continuous production. A novel approach for the development of control policies for the MCSGP process, which enables efficient continuous process control is presented. Based on a high fidelity model, the recently presented PAROC framework and software platform that allows seamless design and in-silico validation of advanced controllers for complex systems are followed. The controller presented in this work is successfully tested against disturbances and is shown to efficiently capture the process periodic nature.
Papathanasioua MM, Oberdieck R, Mantalaris A, et al., 2016, Computational tools for the advanced control of periodic processes - Application to a chromatographic separation, 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1665-1670, ISSN: 1570-7946
Papathanasiou MM, Quiroga-Campano AL, Oberdieck R, et al., 2016, Development of advanced computational tools for the intensification of monoclonal antibody production, 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1659-1664, ISSN: 1570-7946
Campano AQ, Papathanasiou MM, Pistikopoulos EN, et al., 2016, A Predictive Model for Energy Metabolism and ATP Balance in Mammalian Cells: Towards the Energy-Based Optimization of mAb Production, 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1581-1586, ISSN: 1570-7946
Papathanasiou MM, Oberdieck R, Avraamidou S, et al., 2016, Development of advanced control strategies for periodic systems: An application to chromatographic separation processes, American Control Conference (ACC), Publisher: IEEE, Pages: 4175-4180, ISSN: 0743-1619
Papathanasiou MM, Su M, Oberdieck R, et al., 2016, A centralized/decentralized control approach for periodic systems with application to chromatographic separation processes, 11th IFAC Symposium on Dynamics and Control of Process Systems including Biosystems, Publisher: ELSEVIER SCIENCE BV, Pages: 159-164, ISSN: 2405-8963
Papathanasiou MM, Mantalaris A, Pistikopoulos EN, 2016, Advanced control strategies for a periodic, two-column chromatographic process, IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), Publisher: IEEE, Pages: 387-392, ISSN: 1844-7872
Nascu I, Diangelakis NA, Oberdieck R, et al., 2016, Explicit MPC in real-world applications: the PAROC framework, American Control Conference (ACC), Publisher: IEEE, Pages: 913-918, ISSN: 0743-1619
Pistikopoulos EN, Diangelakis NA, Oberdieck R, et al., 2015, PAROC-An integrated framework and software platform for the optimisation and advanced model-based control of process systems, CHEMICAL ENGINEERING SCIENCE, Vol: 136, Pages: 115-138, ISSN: 0009-2509
Velliou EG, Brito dos Santos SUSANA, Papathanasiou MM, et al., 2015, Towards unravelling the kinetics of an acute myeloid leukaemia model system under oxidative and starvation stress: a comparison between two- and three-dimensional cultures, BIOPROCESS AND BIOSYSTEMS ENGINEERING, Vol: 38, Pages: 1589-1600, ISSN: 1615-7591
Papathanasiou MM, Reineke K, Gogou E, et al., 2015, Impact of high pressure treatment on the available glucose content of various starch types: A case study on wheat, tapioca, potato, corn, waxy corn and resistant starch (RS3), Innovative Food Science & Emerging Technologies, Vol: 30, Pages: 24-30, ISSN: 1466-8564
Oberdieck R, Diangelakis NA, Papathanasiou MM, et al., 2015, Pop-the parametric optimization toolbox, Pages: 70-72
Copyright © American Institute of Chemical Engineers. All rights reserved. Recent years have seen an increased interest in multi-parametric programming (mp-P), in large part due to the ever increasing number of areas where mp-P can be applied such as bilevel programming, reactive scheduling and decentralized control. This in turn has led to significant theoretical advances in fields such as multi-parametric mixedinteger programming, multi-parametric moving horizon estimation and global mp-P . For the solution of the underlying mp-P problems, currently only one solver package is openly available, namely the MPT toolbox . Albeit being very complete and providing a wide array of capabilities, the MPT toolbox is computationally limiting when larger problems are considered. Additionally, as it has its own class and object definitions, software interoperability becomes a challenging process especially during the closed-loop validation of the derived controllers.
Papathanasiou MM, Steinebach F, Stroehlein G, et al., 2015, A control strategy for periodic systems - application to the twin-column MCSGP, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1505-1510, ISSN: 1570-7946
Papathanasiou MM, Campano AQ, Steinebach F, et al., 2015, 424226 Advanced control strategies towards the intensification of monoclonal antibody production, Pages: 429-431
Pistikopoulos EN, Oberdieck R, Diangelakis NA, et al., 2015, Paroc-A unified framework towards the optimal design, operational operation and model-based control of process systems, Pages: 335-337
Copyright © American Institute of Chemical Engineers. All rights reserved. The presence of uncertainty in process systems is one of the key reasons for deviation from set operation policies, resulting in suboptimal or even infeasible operation. As these uncertainties realize themselves on different time scales such as on a control, scheduling or design level, an integrated, comprehensive approach to consider uncertainty is required. Thus, in this contribution we demonstrate PAROC (PARametric Optimization and Control), a novel unified framework for the design, operational optimization and advanced model-based control of process systems, which decomposes this challenging problem into a series of steps, shown in the Figure below [ 1].
Papathanasiou MM, Sun M, Steinebach F, et al., 2015, A centralized/decentralized control approach for the Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) process, Pages: 355-357
Papathanasiou MM, Campano AQ, Steinebach F, et al., 2015, Advanced control strategies towards the intensification of monoclonal antibody production, Pages: 714-716
Process intensification plays a dominant role in the improvement of sustainability and productivity of biopharmaceutical processes. In particular, during the past few years there has been increasing demand on product quality and higher titers in the production of monoclonal antibodies (mAbs) . The latter consists of two main parts: (1) the upstream processing (USP), where the cells are cultured and the therapeutic agent is produced and (2) the downstream processing (DSP) that involves the isolation/purification of the targeted product. Both the upstream and the downstream processing, however, are affected by various parameters related to the design of the bioreactor, the methods chosen for separation/purification as well as the operation mode (e.g. batch or continuous).
Papathanasiou MM, Steinebach F, Diangelakis NA, et al., 2014, On the development of multi-parametric controllers for the twin-column MCSGP, Pages: 620-631
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