The drug market has become very competitive with the development of existing companies and the emergence of new companies. The emergence on the market of so-called generic drugs makes the speed of development of new drugs a prime target. The pharmaceutical industry has until now focused on speeding-up drug development by focusing on the chemistry aspects with very little attention given to potential engineering solutions. When looking at the engineering side of the pharmaceutical industry, and more particularly to the design side of equipment like chemical reactors, the pharmaceutical industry has restricted itself to using stirred tank reactors to analyse, develop and produce products. This type of reactor is perceived as flexible and easy to operate for batch operations. Chemical engineering research has opened up the route for new potential reactor designs, which can offer effective solutions to the problems of reaction scale-up. This work aims to develop an automated comparison of different types of chemical reactors in accordance with their ability to scale-up bulk pharmaceutical products. It looks at the engineering side of drug scale-up in order to provide a reliable and fast evaluation procedure for the selection of a reactor which facilitates reaction scale-up. In this piece of research, indicators of success in the scale-up and assessment of quality of process design is centred around yields (or selectivity), capital expenditures and costs and regulatory compliance. Due to the complexity of the reactions i.e. the number of components or the number of steps involved in the synthesis of a compound, side reactions occur undermining the production of a targeted compound. This problem can be solved in some cases by changing the chemistry of the synthesis of the product. This procedure tends to be very time consuming as each possible route has to be first developed at bench scale. Then each promising route is scaled-up over increasing sizes of stirred tank reactor. The different engineering factors involved within the reaction are commonly neglected, so is the possibility of using different types of reactor. In this study, the level of selectivity achieved, i.e. how much product is generated for the amount of reactant used, is simulated by mathematical models. Selectivity is then used to evaluate profit generated or cost (capital or running) endorsed and reflect on the efficiency of the process design. Regulatory compliance is also looked at through the impact that parameter uncertainty can have on the process design. The influence of mixing on product selectivity is shown in this work as being critical. A comparison of the mixing efficiency of various types of reactors is studied through the influence of mixing on selectivity. Mass transfer is also of prime importance in organic synthesis with the emergence of catalysts. This aspect has also been given particular attention in this work, and various types of reactor have been evaluated against their potential to scale-up a mass transfer sensitive reaction. The comparison of the different types of chemical reactor is carried out through the use of an optimisation procedure. The optimisation is done over the different variables which represent inherent characteristics of each reactor type e.g. energy dissipation rate, mass transfer achievable in a reactor. Uncertainty analysis is also used through the Fourier Amplitude Sensitivity Test (FAST), a global sensitivity analysis method, to evaluate the impact that parameter uncertainty or parameter tolerance has on the process design. The FAST method is a global sensitivity analysis method which offers the advantage that a limited number of sampling points are necessary to evaluate the parameter sensitivity analysis of a model. The selection is then based on a multi-objective optimisation procedures. This allows us to trade-off uncertainty and annualised costs. The advantages of this methodology are the speed of evaluation, the ease of use as well as the versatility and generic aspect. It permits to evaluate the impact that parameter uncertainty has on each type of reactor as well as the identify the equipment which generate the best profit. The mathematical model is able to incorporate dynamic behaviour with out having to resort to the level of detail required for computational fluid dynamics (CFD) and have been implemented in gPROMS.

The high-throughput technologies of combinatorial chemistry and high-throughput screening have caused an explosion in the amount of data that pharmaceutical companies have available to them in the early stages of drug discovery. These large datasets are frequently analysed with machine learning tools and techniques. In this work, kernel-based machine learning algorithms are assessed and developed for virtual screening purposes using a wide range of molecular representations, and recommendations for improving the accuracy or the activity models are made.

The high-throughput technologies of combinatorial chemistry and high-throughput screening have caused an explosion in the amount of data that pharmaceutical companies have available to them in the early stages of drug discovery. These large datasets are frequently analysed with machine learning tools and techniques. In this work, kernel-based machine learning algorithms are assessed and developed for virtual screening purposes using a wide range of molecular representations, and recommendations for improving the accuracy or the activity models are made.

Ultrasound irradiation of a protein or polymer solution at the air:water interface can be used to form hollow microspheres containing an air bubble. By introducing a layer of oil and sonicating the oil:water interface, microspheres containing an oil droplet are formed. The microspheres are stabilised by disulfide crosslinking, have diameters of between 1-20 mm and have a number of applications; gas filled protein microspheres are used as ultrasound contrast agents and oil filled microspheres are being developed for delivery of lipophilic drugs. This project extends the scope of sonochemically produced microspheres to include water-in-oil emulsion filled microspheres, which facilitate encapsulation of hydrophilic species, and polymer microspheres that release their contents in response to an external stimulus. Successful encapsulation of a water in oil emulsion phase is demonstrated using confocal microscopy. Release studies are reported for a number of hydrophilic species (in vitro) including 5,6-carboxyfluorescein, 5-fluorouracil and sodium chloride. Release can be triggered by sonochemical disruption of the microsphere shells or cleavage of the disulfide cross links. Thiol-ene coupling reactions initiated by ultrasound irradiation are reported. In water, ultrasound initiation of thiol-ene reactions with electron rich alkenes results in rates of reaction which compare favourably with conventional thermal initiation. Thiol-ene crosslinking is proposed as an alternative to disulfide crosslinking to stabilise sonochemically produced microspheres. Temperature responsive microspheres are produced via the sonochemical method using a block copolymer of N-isopropylacrylamide and thiolated methacrylic acid, P(MASH-b-NIPAm). The block co-polymer is synthesised using reversible addition-fragmentation transfer (RAFT) polymerisation and has a lower critical solution temperature (LCST) of 37 ºC. The microspheres formed from this block copolymer can be seen to rupture, releasing their internal oil phase, when heated above 37 ºC. These findings provide a basis from which to develop sonochemically produced polymer microspheres for responsive delivery of both hydrophilic and lipophilic species.

In the past forty years advancements in fluorescence-based methods including imaging (e.g. confocal and multi-photon) and quantitative spectroscopies (e.g. Fluorescence Correlation Spectroscopy) have been applied to systems ranging from solutions to in vivo models: such methods possess the ability to monitor fluorescence intensity fluctuations and offer the potential to unravel biophysical and biochemical phenomena. A major disadvantage associated with these methods is their ever-increasing cost resulting in the development of image analysis tools that offer the potential to exploit hidden information contained in confocal images.The hypothesis pertaining to this thesis is that image analysis tools developed in recent years exemplified by Raster Image Correlation Spectroscopy (RICS), Spatial Intensity Distribution Analysis (SpIDA) and Fluorescence Intensity Gaussian Mixture Model Analysis (FIGMMA) will provide a new insight into current pharmaceutical problems. The application of these methods to the quantification of protein aggregation, monomer/dimer equilibria, p-glycoprotein efflux activity and transcytosis are presented in this thesis.Protein aggregation poses a major challenge to the biotechnology industry which currently lacks analytical capabilities to profile broad particle size ranges. An in-house RICS (ManICS) software was validated against Dynamic Light Scattering and Fluorescence Correlation Spectroscopy (FCS) to determine Bovine Serum Albumin (BSA) aggregate population distributions under accelerated stability conditions. Initial stages implicated in the growth of aggregates are vital to the mechanistic assessment of protein aggregation. Hence, real-time in situ examination of monomer loss and aggregation of BSA was performed at 50 °C to enable continuous assessment with imaging and subsequent SpIDA analysis. Results obtained from this study suggested reversible fluctuation between monomers and dimers for up to four hours.To correlate membrane receptor and transporter expression with activity and enable the comparison of expression in multiple cell lines, population densities of p-glycoprotein transporters and transferrin receptors were determined using SpIDA in samples subjected to immunofluorescence labelling.The Calcein retention assay is a routine approach to determining multidrug resistance associated with p-glcoprotein efflux and the traditional plate reader approach omits microscopic aspects of p-glycoprotein Calcein-AM uptake and efflux. Confocal microscopy and data obtained from image analyses supported the subcellular and intercellular assessment of Calcein accumulation in MDR1-transfected and control cell lines as a function of time and verapamil concentration. Finally, live cell imaging of transferrin vesicular transport and Cell TraceTM Calcein red-orange AM internalisation in combination with traditional Transwell® assays were assessed to compare their transcellular transport and intracellular concentrations in multiple cell lines. Images obtained enabled visualisation of internalisation and following analysis using SpIDA, RICS and FIGMMA the number of intracellular vesicles and dynamic parameters of Cell TraceTM Calcein red-orange diffusion and intracellular concentration were determined.In conclusion, image analysis tools were applied to providing new parametric insights into a number of pharmaceutically-relevant processes and in some instances this is the first example of such studies. Despite current phenomenal advances in image acquisition capabilities, there remains a broad scope for the validation of image analysis tools and their application to a multitude of areas of interest to pharmaceutical and biomolecular research.