Article
Chemistry, Analytical
Gang Wu, Chuanfei Yu, Wenbo Wang, Jialiang Du, Zhihao Fu, Gangling Xu, Meng Li, Lan Wang
Summary: Imaged capillary isoelectric focusing (icIEF) and ion exchange chromatography (IEX) are routinely used for charge variant analysis of therapeutic monoclonal antibodies (mAbs). In this study, icIEF-MS and strong cation exchange (SCX)-MS were compared, and it was found that icIEF-MS outperformed SCX-MS in terms of sensitivity, carryover effect, protein identification, and separation resolution.
ANALYTICAL CHEMISTRY
(2023)
Review
Cell Biology
Mathilde Coulet, Oliver Kepp, Guido Kroemer, Stephane Basmaciogullari
Summary: Biotherapeutics, especially monoclonal antibodies, have become powerful tools for the treatment of various diseases. The pharmaceutical industry has made great progress in developing bioproduction processes, but understanding cellular responses to environmental changes is crucial for improving productivity. Metabolomics offers a promising approach to unlock the full potential of cellular production.
Article
Energy & Fuels
Chao Zhong, Kai Zhang, Xiaoming Xue, Ji Qi, Liming Zhang, Chuanjin Yao, Yongfei Yang, Jian Wang, Jun Yao, Weidong Zhang
Summary: This research introduces a novel approach combining multiple surrogate models that imitate the landscape of the initial production optimization problem and an advanced multitasking optimization method to achieve optimal solutions within a limited time frame.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Rafael D. de Oliveira, Galo A. C. Le Roux, Radhakrishnan Mahadevan
Summary: Dynamic flux balance analysis (dFBA) models are widely used in systems biology for various applications. This approach involves dynamic mass balance equations to describe the concentration of metabolites and an optimization model to calculate the internal flux distribution of the cell. In this study, a nonlinear programming formulation is applied, where the ODE system is discretized using orthogonal collocation technique and the optimization problem is replaced by its first-order optimality conditions. An adaptive mesh scheme is also used to efficiently handle changes in the constraints. This formulation ensures differentiability and can be solved by large-scale solvers with automatic differentiation packages, providing results equivalent to state-of-the-art methods and outperforming them in dynamic optimization problems.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Obstetrics & Gynecology
Joe Eid, Mahmoud Abdelwahab, Hayley Williams, Joy Lehman, Carlos Malvestutto, Mark B. Landon, Maged M. Costantine, Kara M. Rood
Summary: Treatment with monoclonal antibodies can reduce the risk of hospitalization for pregnant individuals with mild or moderate COVID-19, especially those who are unvaccinated.
OBSTETRICS AND GYNECOLOGY
(2022)
Review
Energy & Fuels
Adarsh Kumar Arya
Summary: Pipelines are considered the most cost-effective and safe method for natural gas transportation, but require significant investment. This paper addresses the lack of review papers in pipeline optimization and provides a detailed overview of 14 optimization parameters and 6 optimization techniques. The findings aim to enhance understanding and implementation of optimization in the pipeline industry.
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY
(2022)
Review
Immunology
Susanna Esposito, Bahaa Abu-Raya, Paolo Bonanni, Fabianne Cahn-Sellem, Katie L. Flanagan, Federico Martinon Torres, Asuncion Mejias, Simon Nadel, Marco A. P. Safadi, Arne Simon
Summary: Routine childhood vaccinations are vital for protecting children from serious diseases, and active vaccinations in infants are highly effective. However, some important viral pathogens, such as RSV, do not yet have approved vaccines. The introduction of anti-viral monoclonal antibodies, like nirsevimab, into pediatric vaccine schedules could potentially offer additional protection for infants against RSV.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Cristian Pablos, Alejandro Merino, Luis Felipe Acebes, Jose Luis Pitarch, Lorenz T. Biegler
Summary: Industrial processes can reduce costs and enhance grid stability by working with cogeneration utilities and utilizing Demand Response programs. Utilizing a dynamic-integrated optimization approach can better address this issue and improve efficiency.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Review
Chemistry, Medicinal
Hassan A. Alhazmi, Mohammed Albratty
Summary: Monoclonal antibodies (mAbs) are a rapidly expanding class of biopharmaceuticals that have a wide range of applications in disease detection and treatment. Various analytical techniques, including chromatographic, electrophoretic, spectroscopic, and electrochemical methods, are used for the characterization and quality control of mAbs.
Article
Computer Science, Interdisciplinary Applications
Juan J. Romero, Eleanor W. Jenkins, Scott M. Husson
Summary: This work discusses the use of surrogate functions and a new optimization framework to create an efficient and robust computational framework for process design. The model process is the capture chromatography unit operation for monoclonal antibody purification. Surrogate functions are implemented to reduce computational time, resulting in accurate results with a 93% decrease in processing time. A new optimization framework is also developed to reduce the number of simulations needed for solving the optimization problem, and its performance is compared with individual optimization algorithms using MATLAB built-in tools for problems with different variables.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Review
Immunology
Romy Mosch, Henk-Jan Guchelaar
Summary: This review discusses ADA formation of mAbs and its clinical impact, as well as proposes the use of HLA haplotypes as biomarkers to predict patients' susceptibility to ADA formation.
FRONTIERS IN IMMUNOLOGY
(2022)
Review
Immunology
Waller-Pulido Alejandra, Jimenez-Perez Miriam Irene, Gonzalez-Sanchez Fabio Antonio, Rojo-Gutierrez Rocio Patricia, Torres-Anguiano Elizabeth, Aleman-Aguilar Juan Pablo, Garcia-Varela Rebeca
Summary: Monoclonal antibodies (mAbs) have been widely used in immunotherapies against various diseases and have potential in immunization. They play a key role in recognizing and targeting specific antigens. Different types of mAbs are discussed, and common techniques such as hybridomas or phage display are used for their production. Specialized downstream processes are employed to achieve desired yield, isolation, and product quality. Novel perspectives in these protocols can lead to improved high-scale production of mAbs.
INTERNATIONAL IMMUNOPHARMACOLOGY
(2023)
Review
Microbiology
Mary Garvey
Summary: This passage introduces the importance of biologics in medical research and the definition of biologics. It also describes in detail the application and advantages of eukaryotic expression systems in the production of biologics.
Editorial Material
Pharmacology & Pharmacy
B. Gorovits, A. Hays, D. Jani, C. Jones, C. King, A. Lundequist, J. Mora, M. Partridge, D. Pathania, S. S. Ramaswamy, D. Rutwij, H. Shen, G. Starling
Summary: EURL ECVAM recommends discontinuing the use of animals for the development of antibodies, emphasizing that EU countries should adhere to Directive 2010/63/EU and not authorize animal immunization without legitimate scientific justification. AAPS acknowledges progress in reducing animal use in drug discovery but suggests more data and discussion within the scientific community are needed before implementing non-animal derived antibodies.
Article
Mathematics
Sandra A. Obiri, Bernard T. Agyeman, Sarupa Debnath, Siyu Liu, Jinfeng Liu
Summary: This paper provides guidelines for sensor selection in the upstream production process of mAbs and applies a variable selection technique to improve estimation accuracy. The proposed approach is demonstrated through different case studies and evaluated using RMSE as the evaluation criterion.
Article
Thermodynamics
Patrick Burkardt, Tamara Ottenwaelder, Andrea Koenig, Joern Viell, Alexander Mitsos, Christian Wouters, Wolfgang Marquardt, Stefan Pischinger, Manuel Dahmen
Summary: This paper proposes a method for computer-aided design of tailor-made fuels and combines it with experimental research and model-based evaluation to create a multi-component biofuel for highly boosted spark-ignition engines. The designed fuel shows superior combustion performance and lower production costs compared to conventional fuels.
INTERNATIONAL JOURNAL OF ENGINE RESEARCH
(2023)
Article
Engineering, Multidisciplinary
Ludger Leenders, Doerthe Franzisca Hagedorn, Hatim Djelassi, Andre Bardow, Alexander Mitsos
Summary: Energy-intensive production sites are often supplied with energy by on-site energy systems. However, the scheduling of production and energy systems often have misaligned objectives, leading to suboptimal schedules. To address this, the scheduling problem of the production system can be formulated as a bilevel problem and an algorithm is proposed to solve it.
OPTIMIZATION AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Jannik Burre, Dominik Bongartz, Alexander Mitsos
Summary: Superstructure optimization is a computationally demanding task used to select the optimal structure. In chemical engineering, it is important to consider different process alternatives to minimize specific objective functions. Traditional approaches have limitations, so it is suggested to consider problem formulations that introduce additional nonconvexities while reducing the number of optimization variables for problems containing nonconvex functions.
OPTIMIZATION AND ENGINEERING
(2023)
Article
Engineering, Chemical
Jan G. G. Rittig, Martin Ritzert, Artur M. M. Schweidtmann, Stefanie Winkler, Jana M. M. Weber, Philipp Morsch, Karl Alexander Heufer, Martin Grohe, Alexander Mitsos, Manuel Dahmen
Summary: Fuels with high-knock resistance are crucial for efficient and low emission spark-ignition engines. Computer-aided molecular design (CAMD) supported by graph machine learning (graph-ML) can identify molecules with desired autoignition properties. A modular graph-ML CAMD framework is proposed, integrating generative graph-ML models, graph neural networks, and optimization to design molecules in a continuous molecular space.
Article
Engineering, Chemical
Thomas Nevolianis, Nadja Wolter, Luise F. Kaven, Lukas Krep, Can Huang, Adel Mhamdi, Alexander Mitsos, Andrij Pich, Kai Leonhard
Summary: In this study, we propose a bottom-up approach to model the synthesis of N-vinylcaprolactam-based microgels functionalized with glycidyl methacrylate. We estimate the parameter values for unknown reaction rates using a hybrid approach based on quantum chemical calculations and experimental data. Our approach achieves a coefficient of determination of 0.97 for the enthalpy transfer rate over time during microgel synthesis. This study demonstrates that quantum chemistry methods and physical experiments can be integrated into models for a better understanding and designing of pVCL/GMA microgel synthesis processes.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Engineering, Chemical
Ke Chen, Mingzhao Liu, Jianghang Gu, Adel Mhamdi, Sven Gross, Yi Heng
Summary: In this study, a hybrid parallel strategy is proposed to improve the computational efficiency of liquid-gas mass transfer processes. The strategy combines high-throughput computing at the top level and high-performance unit simulations with different interface capture strategies at the bottom level. The effectiveness of the strategy is demonstrated by investigating CO2 absorption in methanol with varying concentrations of Al2O3 nanoparticles. The results show that the DNS model matches the experimental data better with high computational accuracy and efficiency.
CHEMICAL ENGINEERING SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Jan G. Rittig, Karim Ben Hicham, Artur M. Schweidtmann, Manuel Dahmen, Alexander Mitsos
Summary: Ionic liquids (ILs) are important solvents for sustainable processes, and predicting activity coefficients (ACs) of solutes in ILs is necessary. Recent advancements in matrix completion methods (MCMs), transformers, and graph neural networks (GNNs) have shown high accuracy in predicting ACs of binary mixtures. In this study, a GNN is presented to predict temperature-dependent infinite dilution ACs of solutes in ILs, achieving similar performance to a state-of-the-art MCM and enabling predictions for IL-containing solutions.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Moritz J. Begall, Artur M. Schweidtmann, Adel Mhamdi, Alexander Mitsos
Summary: Computational Fluid Dynamics (CFD) is used to optimize the geometry of complex milli-scale reactors by coupling with the multi-objective Bayesian Optimization algorithm TSEMO. The framework automatically executes CFD simulations to minimize stagnating flow areas and maximize mixing performance. It can find Pareto-optimal reactor variations and be adapted for other devices and objectives.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai Leonhard, Alexander Mitsos
Summary: Graph neural networks (GNNs) are used in chemical engineering to learn physico-chemical properties based on molecular graphs. The pooling function in GNNs is important for combining atom feature vectors into molecular fingerprints. Unsuitable pooling functions can lead to unphysical GNNs that have poor generalization. This study compares and selects meaningful GNN pooling methods based on physical knowledge about the learned properties, and demonstrates the impact of physical pooling functions on molecular properties.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Engineering, Chemical
Mohammad El Wajeh, Adel Mhamdi, Alexander Mitsos
Summary: This study presents a modular and rigorous dynamic model for biodiesel and glycerol production, along with two different control structures. The model is implemented in Modelica open-source and the importance of developing dynamic models for advanced control and estimation techniques is highlighted. The control structure based on an information-rich configuration shows satisfactory control performance, emphasizing the importance of dynamic models for advanced control and estimation techniques.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Computer Science, Software Engineering
Susanne Sass, Angelos Tsoukalas, Ian H. H. Bell, Dominik Bongartz, Jaromil Najman, Alexander Mitsos
Summary: This paper focuses on deterministic global optimization (DGO) for nonconvex parameter estimation problems. The branch-and-bound algorithm is accelerated by using reduced data sets for constructing valid bounds. The results indicate that both solution candidate regions and regions with low quality fits can be identified based on the reduced data sets, and the average CPU time per branch-and-bound iteration typically decreases when using reduced data sets.
OPTIMIZATION METHODS & SOFTWARE
(2023)
Review
Computer Science, Interdisciplinary Applications
Simone Mucci, Alexander Mitsos, Dominik Bongartz
Summary: Hydrogen produced from renewable electricity can be used to synthesize valuable chemical products, contributing to the decarbonization of the chemical industry. Polymer Electrolyte Membrane Water Electrolyzers (PEM-WEs) show promise for coupling with fluctuating power inputs, but the flexibility of downstream synthesis processes under time-variable hydrogen flow rates is unclear. This review focuses on the potential for flexible operation of hydrogen production, carbon capture, nitrogen production, and the synthesis of various chemicals, and discusses opportunities for heat and mass integration.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Sonja H. M. Germscheid, Fritz T. C. Roeben, Han Sun, Andre Bardow, Alexander Mitsos, Manuel Dahmen
Summary: Combining the demand response of industrial processes on electricity spot markets with real-time electricity market participation can reduce operational costs. Risk-averse market participation allows for savings, but may face financial risks; risk-neutral participation allows for greater savings, but may involve higher risks on weekends. Moreover, load-shifting capabilities depend on the modeling of on/off decisions, and sequential scheduling can achieve participation in both markets while balancing multiple factors.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Energy & Fuels
Simone Mucci, Alexander Mitsos, Dominik Bongartz
Summary: The synthesis of methanol from captured carbon dioxide and green hydrogen could be a promising replacement for the current fossil-based production. The study found that storage, especially hydrogen storage, is particularly beneficial when the electricity price is high and highly fluctuating, and in the future, batteries could play a bigger role.
JOURNAL OF ENERGY STORAGE
(2023)