Review of advanced physical and data-driven models for dynamic bioprocess simulation: Case study of algae-bacteria consortium wastewater treatment.

Microorganism production and remediation processes are of critical importance to the next generation of sustainable industries. Undertaking mathematical treatment of dynamic biosystems operating at any spatial or temporal scale is essential to guarantee their performance and safety. However, constructing physical models remains a challenge due to the extreme complexity of process biological mechanisms.

Optimal Piecewise Linear Regression Algorithm for QSAR Modelling.

Quantitative Structure-Activity Relationship (QSAR) models have been successfully applied to lead optimisation, virtual screening and other areas of drug discovery over the years. Recent studies, however, have focused on the development of models that are predictive but often not interpretable. In this article, we propose the application of a piecewise linear regression algorithm, OPLRAreg, to develop both predictive and interpretable QSAR models.

An integrated platform for intuitive mathematical programming modeling using LaTeX.

This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling.

Repulsion-dispersion parameters for the modelling of organic molecular crystals containing N, O, S and Cl.

In lattice energy models that combine ab initio and empirical components, it is important to ensure consistency between these components so that meaningful quantitative results are obtained. A method for deriving parameters of atom-atom repulsion dispersion potentials for crystals, tailored to different ab initio models, is presented. It is based on minimization of the sum of squared deviations between experimental and calculated structures and energies.

Exploring the intrinsic behaviour of multisite phosphorylation systems as part of signalling pathways.

Multisite phosphorylation is a basic way of chemically encoding substrate function and a recurring feature of cell signalling pathways. A number of studies have explored information processing characteristics of multisite phosphorylation, through studies of the intrinsic kinetics. Many of these studies focus on the module in isolation.

The Increasingly Human and Profitable Monoclonal Antibody Market.

The monoclonal antibody (mAb) market has changed rapidly in the past 5 years: it has doubled in size, becoming dominated by fully human molecules, launched bispecific molecules, and faced competition from biosimilars. We summarize the market in terms of therapeutic applications, type and structure of mAbs, dominant companies, manufacturing locations, and emerging markets.

Integration of environmental aspects in modelling and optimisation of water supply chains.

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales.

Optimal model-based control of non-viral siRNA delivery.

Further quantitative understanding of the biological effects and mechanisms involved in cellular and intracellular delivery of nucleic acid materials is required to produce clinical applications of gene therapy. Several modeling approaches have been used in this field; however, a comprehensive approach that integrates all the key pharmacological issues into a holistic framework that is applicable for in vivo conditions is still lacking. This contribution presents a pharmacokinetic/pharmacodynamic model-based control study of non-viral siRNA delivery describing the dynamics of the delivery process and takes into account the main multi-objective optimization issues such as efficacy and toxicity, as well as the effect of uncertainty in cell doubling time.

A Nexus Approach for Sustainable Urban Energy-Water-Waste Systems Planning and Operation.

Energy, water, and waste systems analyzed at a nexus level are important to move toward more sustainable cities. In this paper, the "resilience.io" platform is developed and applied to emphasize on waste-to-energy pathways, along with the water and energy sectors, aiming to develop waste treatment capacity and energy recovery with the lowest economic and environmental cost.

Mild hypothermic culture conditions affect residual host cell protein composition post-Protein A chromatography.

Host cell proteins (HCPs) are endogenous impurities, and their proteolytic and binding properties can compromise the integrity, and, hence, the stability and efficacy of recombinant therapeutic proteins such as monoclonal antibodies (mAbs). Nonetheless, purification of mAbs currently presents a challenge because they often co-elute with certain HCP species during the capture step of protein A affinity chromatography. A Quality-by-Design (QbD) strategy to overcome this challenge involves identifying residual HCPs and tracing their source to the harvested cell culture fluid (HCCF) and the corresponding cell culture operating parameters.

Stochastic optimization of broadband reflecting photonic structures.

Photonic crystals (PCs) are built to control the propagation of light within their structure. These can be used for an assortment of applications where custom designed devices are of interest. Among them, one-dimensional PCs can be produced to achieve the reflection of specific and broad wavelength ranges.

Arbitrarily tight BB underestimators of general non-linear functions over sub-optimal domains.

In this paper we explore the construction of arbitrarily tight BB relaxations of general non-linear non-convex functions. We illustrate the theoretical challenges of building such relaxations by deriving conditions under which it is possible for an BB underestimator to provide exact bounds. We subsequently propose a methodology to build BB underestimators which may be arbitrarily tight (i.

Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production.

Biodiesel produced from microalgae has been extensively studied due to its potentially outstanding advantages over traditional transportation fuels. In order to facilitate its industrialization and improve the process profitability, it is vital to construct highly accurate models capable of predicting the complex behavior of the investigated biosystem for process optimization and control, which forms the current research goal. Three original contributions are described in this paper.

Modelling compartmentalization towards elucidation and engineering of spatial organization in biochemical pathways.

Compartmentalization is a fundamental ingredient, central to the functioning of biological systems at multiple levels. At the cellular level, compartmentalization is a key aspect of the functioning of biochemical pathways and an important element used in evolution. It is also being exploited in multiple contexts in synthetic biology.

Exploring cellular behavior under transient gene expression and its impact on mAb productivity and Fc-glycosylation.

Transient gene expression (TGE) is a methodology employed in bioprocessing for the fast provision of recombinant protein material. Mild hypothermia is often introduced to overcome the low yield typically achieved with TGE and improve specific protein productivity. It is therefore of interest to examine the impact of mild hypothermic temperatures on both the yield and quality of transiently expressed proteins and the relationship to changes in cellular processes and metabolism.

Osmotic behaviour of human mesenchymal stem cells: Implications for cryopreservation.

Aimed at providing a contribution to the optimization of cryopreservation processes, the present work focuses on the osmotic behavior of human mesenchymal stem cells (hMSCs). Once isolated from the umbilical cord blood (UCB) of three different donors, hMSCs were characterized in terms of size distribution and their osmotic properties suitably evaluated through the exposure to hypertonic and isotonic aqueous solutions at three different temperatures. More specifically, inactive cell volume and cell permeability to water and di-methyl sulfoxide (DMSO) were measured, being cell size determined using impedance measurements under both equilibrium and dynamic conditions.

Cascading effect in bioprocessing-The impact of mild hypothermia on CHO cell behavior and host cell protein composition.

A major challenge in downstream purification of monoclonal antibodies (mAb) is the removal of host cell proteins (HCPs). Previous studies have shown that cell culture conditions significantly impact the HCP content at harvest. However, it is currently unclear how process conditions affect physiological changes in the host cell population, and how these changes, in turn, cascade down to change the HCP profile.

Semi-empirical modeling of microalgae photosynthesis in different acclimation states - Application to N. gaditana.

The development of mathematical models capable of accurate predictions of the photosynthetic productivity of microalgae under variable light conditions is paramount to the development of large-scale production systems. The process of photoacclimation is particularly important in outdoor cultivation systems, whereby seasonal variation of the light irradiance can greatly influence microalgae growth. This paper presents a dynamic model that captures the effect of photoacclimation on the photosynthetic production.

Overproduction of L-tryptophan via simultaneous feed of glucose and anthranilic acid from recombinant Escherichia coli W3110: Kinetic modeling and process scale-up.

L-tryptophan is an essential amino acid widely used in food and pharmaceutical industries. However, its production via Escherichia coli fermentation suffers severely from both low glucose conversion efficiency and acetic acid inhibition, and to date effective process control methods have rarely been explored to facilitate its industrial scale production. To resolve these challenges, in the current research an engineered strain of E.

An efficient model construction strategy to simulate microalgal lutein photo-production dynamic process.

Lutein is a high-value bioproduct synthesized by microalga Desmodesmus sp. It has great potential for the food, cosmetics, and pharmaceutical industries. However, in order to enhance its productivity and to fulfil its ever-increasing global market demand, it is vital to construct accurate models capable of simulating the entire behavior of the complicated dynamics of the underlying biosystem.

Multi-criteria manufacturability indices for ranking high-concentration monoclonal antibody formulations.

The need for high-concentration formulations for subcutaneous delivery of therapeutic monoclonal antibodies (mAbs) can present manufacturability challenges for the final ultrafiltration/diafiltration (UF/DF) step. Viscosity levels and the propensity to aggregate are key considerations for high-concentration formulations. This work presents novel frameworks for deriving a set of manufacturability indices related to viscosity and thermostability to rank high-concentration mAb formulation conditions in terms of their ease of manufacture.

Advanced model-based control strategies for the intensification of upstream and downstream processing in mAb production.

Current industrial trends encourage the development of sustainable, environmentally friendly processes with minimal energy and material consumption. In particular, the increasing market demand in biopharmaceutical industry and the tight regulations in product quality necessitate efficient operating procedures that guarantee products of high purity. In this direction, process intensification via continuous operation paves the way for the development of novel, eco-friendly processes, characterized by higher productivity and lower production costs.

Optimization-based framework for resin selection strategies in biopharmaceutical purification process development.

This work addresses rapid resin selection for integrated chromatographic separations when conducted as part of a high-throughput screening exercise during the early stages of purification process development. An optimization-based decision support framework is proposed to process the data generated from microscale experiments to identify the best resins to maximize key performance metrics for a biopharmaceutical manufacturing process, such as yield and purity. A multiobjective mixed integer nonlinear programming model is developed and solved using the ε-constraint method.

Chebyshev model arithmetic for factorable functions.

This article presents an arithmetic for the computation of Chebyshev models for factorable functions and an analysis of their convergence properties. Similar to Taylor models, Chebyshev models consist of a pair of a multivariate polynomial approximating the factorable function and an interval remainder term bounding the actual gap with this polynomial approximant. Propagation rules and local convergence bounds are established for the addition, multiplication and composition operations with Chebyshev models.

Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. I. Adaptive local approximate models.

The global search stage of crystal structure prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in the CrystalPredictor II [Habgood et al. (2015).