Optimisation of chromatography for downstream protein processing

Downstream bioprocessing and especially chromatographic steps, commonly used for the purification of multicomponent systems, are significant cost drivers in the production of therapeutic proteins. Lately, there has been an increased interest in the development of systematic methods where operating conditions are defined and chromatographic trains are selected. Several models have been developed previously, where chromatographic trains were selected under the assumption of 100% recovery of the desired product. Removing this assumption gives the opportunity not only to select chromatographic trains but also determine the timeline in which the product is selected. Initially, a mixed integer non-linear (MINLP) programming mathematical model was developed to tackle that problem and was tested using three illustrative examples. Later on, this model was linearised by applying piecewise linear approximation techniques and computational efficiency was improved. Next, an alternative MILP model was developed by discretising the recovery levels of the product and computational efficiency improved even by 100-fold. Finally, the equilibrium dispersive model was used in a simple 4-protein mixture and the MINLP model was validated. This research represents a significant step towards efficient downstream process operation and synthesi

Method for solving generalized convex nonsmooth mixed-integer nonlinear programming problems

In this paper, we generalize the extended supporting hyperplane algorithm for a convex continuously differentiable mixed-integer nonlinear programming problem to solve a wider class of nonsmooth problems. The generalization is made by using the subgradients of the Clarke subdifferential instead of gradients. Consequently, all the functions in the problems are assumed to be locally Lipschitz continuous. The algorithm is shown to converge to a global minimum of an MINLP problem if the objective function is convex and the constraint functions are f degrees-pseudoconvex. With some additional assumptions, the constraint functions may be f degrees-quasiconvex

Using projected cutting planes in the extended cutting plane method

In this paper we show that simple projections can improve the algorithmic performance of cutting plane-based optimization methods. Projected cutting planes can, for example, be used as alternatives to standard cutting planes or supporting hyperplanes in the extended cutting plane (ECP) method. In the paper we analyse the properties of such an algorithm and prove that it will converge to a global optimum for smooth and nonsmooth convex mixed integer nonlinear programming problems. Additionally, we show that we are able to solve two old but very difficult facility layout problems (FLP), with previously unknown optimal solutions, to verified global optimum by using projected cutting planes in the algorithm. These solution results are also given in the paper

Computational modelling of separation processes for green continuous pharmaceutical manufacturing

The pharmaceutical industry has traditionally implemented batch manufacturing for the production of a wide range of products due to its mature technological development and ability for recall of products where necessary. However, several demonstrations of Continuous Pharmaceutical Manufacturing (CPM) in the past two decades have drawn significant attention from academia, industry and regulatory bodies due to its potential for smaller equipment, enhanced efficiencies, access to difficult or hazardous process conditions with greater ease and safety and reduced costs and waste. While continuous processing is not new in other manufacturing sectors, its application to pharmaceutical production has only drawn significant attention in recent years due to the numerous demonstrations of continuous flow syntheses of complex molecules and functional groups inherent of Active Pharmaceutical Ingredients (APIs), which is the foundation of any end-to-end CPM plant. The literature to date has predominantly focussed on design and optimisation of flow synthesis routes; however, the development of efficient continuous separation processes is a major bottleneck to CPM and are often challenging and materially intensive unit operations. The design of effective continuous separation processes for societally important APIs amenable to continuous production is essential for CPM success. Mathematical modelling is a viable and useful tool in the elucidation of promising designs prior to pilot plant studies that can allow rapid screening of multiple candidate configurations and can circumvent expensive and laborious experimental campaigns. Moreover, they allow optimisation of process design configurations to maximise their operational and economic benefits. This PhD thesis aims to elucidate cost-optimal upstream CPM plant and continuous separation process designs for a range of APIs. Steady-state process models for upstream CPM plants for different APIs are constructed, using published data for reaction rate law elucidation and kinetic parameter estimation, activity coefficient and group contribution models for non-ideal multicomponent mixture phase equilibria prediction and pharmaceutical process costing methodologies. The constructed models are then used for process simulation, design and optimisation of CPM plants, using Nonlinear Programming (NLP) for individual case-based process optimisation and Mixed Integer Nonlinear Programming (MINLP) for CPM process synthesis to optimality. The systematic frameworks and methods used in this work can be expanded to other APIs amenable to CPM with similar processes. This work highlights the immense value in systematic and rigorous model-based simulation and optimisation campaigns for CPM process development

Systematic methods for solvent design : towards better reactive processes

The focus of this thesis is the development of novel methodologies for systematic identification of optimal solvents for chemical reactions. Two aspects are considered: the integrated solvent and process design using a mixed solvent, and the design of an optimal solvent using ab initio methods that do not rely on experimental data. A methodology is developed for the integrated design of a CO2-expanded solvent in a reaction process. Posing as objective function the cost of the process, for a defined production rate, an optimisation problem is formulated, with decision variables that include the organic co-solvent, the composition and the mass of the mixed solvent. Emphasis is placed on the prediction of the reaction rate, for which the solvatochromic equation combined with a preferential solvation model are used, and on solid-vapour-liquid phase equilibrium, for which the group-contribution volume translated Peng-Robinson equation of state is used. The proposed methodology is applied to the Diels-Alder reaction of anthracene and 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD), and three CO2-expanded solvents are considered (acetone, acetonitrile and methanol). Acetonitrile and acetone are found to offer good performance over a range of CO2 concentrations. The importance of taking into account multiple process performance indicators, when designing gas-expanded liquids, is highlighted. As a further step toward systematic solvent design approaches that are not limited by the availability of experimental data and consider a large number of candidate solvents, an ab initio methodology is developed for the design of optimal solvents for reactions. The developed method combines quantum mechanical calculations with a computer-aided molecular design formulation. In order to limit the number of QM calculations but also retain accuracy and ensure convergence, the Kriging approach is used. Kriging is a response surface approach, which has recently attracted a lot of attention because it is an exact extrapolator with a statistical interpretation which makes it stand out from other methods. The proposed approach is used successfully to identify promising solvents for the Menschutkin reaction of phenacyl bromide and pyridine and the Cope elimination of methylamine oxide. The use of Kriging as the surrogate model is found to lead to improved solvents when compared to the simpler solvatochromic equation used in previous work.Open Acces

Optimisation Methodologies for the Design and Planning of Water Systems

This thesis addresses current topics of design and planning of water systems from water treatment units to a country-wide resources management schemes. The methodologies proposed are presented as models and solution approaches using mathematical programming, and mixed integer linear (MILP) and non-linear (MINLP) programming techniques. In Part I of the thesis, a synthesis problem for water treatment processes using superstructure optimisation is studied. An MINLP model is developed for the minimisation of water production cost considering physicochemical properties of water and operating conditions of candidate technologies. Next, new alternative path options are introduced to the superstructure. The resulting MINLP model is then partially linearised (plMINLP) and also presented as a mixed integer linear fractional programming (MILFP) model in order to improve the convergence of the optimisation model. Various linearisation and approximation techniques are developed. As a solution procedure to the fractional model, a variation of the Dinkelbach's algorithm is proposed. The models are tested on theoretical examples with industrial data. In Part II, an optimisation approach formulated as a spatially-explicit multi-period MILP model is proposed for the design of planning of water resources at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, trading schemes among regions and pricing, and water availability under climate change. The objective is to meet water demand while minimising the total cost associated with developing and operating the water supply chain. Additionally, a fair trade-o between the total cost and reliability of the supply chain is incorporated in the model. The solution method is applied based on game theory using the concept of Nash equilibrium. The methodology is implemented on a case study based on Australian water management systems

Adsorptive reactor technology for VOC abatement.

Imperial Users onl