Non-adherence to medicines for long-term conditions is a complex and prevalent phenomenon, with significant clinical and economic consequences for patients and health providers worldwide. Simple effective solutions have eluded researchers over many decades. A mixed methods randomised controlled trial was conducted to test the effectiveness of a pharmacist-led intervention to improve adherence, in the context of mail-order pharmacy. 677 patients prescribed at least one oral medication for type 2 diabetes and/or lipid regulation were recruited from a UK pharmacy, and randomised (340 interventions, 337 controls). The intervention was patient-centred, comprising spoken information and advice by phone, and written information by post, delivered by a pharmacist. All elements of the intervention were tailored to the individuals' needs. The primary outcome was self-reported adherence to medication at six-month follow up. Secondary outcomes included prescription refill adherence, lipid and glycaemic control, and patient satisfaction. Patients who received the intervention had 54% increased odds of being adherent (defined as ≥90% of medication taken in the past 7 days), compared to the control group (OR 1.54, 95%CI 1.11-2.15, p=0.01). Analyses of dispensing data also showed that the odds of being classified as adherent (≥90%) were 60% greater for the intervention group compared to the control group (OR 1.60, 95%CI 1.14-2.24, p < 0.01). For patients who provided a blood sample at six-month follow up, 67% vs 31% (16 interventions, 5 controls, p=0.06) and 65% vs 55% (64 interventions, 38 controls, p=0.24) achieved guideline targets for glycaemic and lipid control, respectively. Satisfaction with the Medicines Advice Service was high, with 91.8% (n=245) agreeing that they were satisfied overall. Intervention, led by a pharmacist and tailored to the individuals' needs, can significantly improve medication adherence in patients with long-term conditions. The findings provide further support for the enhanced role of pharmacists in supporting and advising patients, and improving outcomes.

The quality of initial professional pharmacy education (IPPE) is receiving growing attention in the development of modern health policy. This is due to the gradually extended role of pharmacists, a global shortage of pharmacy workforce and their skill-mix imbalances, all of which require improvements to respond to the expanding and ever-changing population health needs. To achieve enhanced and equitable quality worldwide, evidence that can be used as a global basis for identifying gaps and challenges to assist strengthening IPPE is demanded. The purpose of this research was to generate evidence to construct the first global map of the attributes of quality IPPE for assisting the improvement of IPPE across nations. The research questions what are the differences and commonalities in the current IPPE practices worldwide, and if there are globally shared attributes for high quality IPPE, which can support further development of professional roles. A mixed-methods approach was implemented to investigate personal and institutional factors in a global context. To seek students’ factors in the quality IPPE, a global online survey on students’ learning processes and experiences was conducted, resulting in 4,105 student responses from 78 countries. To investigate teaching and institutional attributes of IPPE, an attached email global survey on IPPE institutions and programmes and a curriculum content analysis were conducted, which compared country-level institutional information from 110 countries and territories as well as contrasting in-depth curricula content data from 16 countries. The combined findings provide measures of current IPPE practices across nations. This includes differences in approaches to learning between regions and nations; pharmacy model to foster the adoption of deep approach to learning; global variation regarding capacity, provision, and regulations; and variation in curricula content when contrasting science and practice components. The thesis provides evidence for a policy review of IPPE to assist with enhancing global quality.

Despite the existence of vaccinations, diagnostic tools and treatments, tuberculosis (TB) prevalence is increasing because of the circulation of people and misuse of antibiotics, giving rise to growing numbers of drug resistant strains of Mycobacterium tuberculosis. There is therefore a pressing need to look for new strategies against TB, in the hope of finding new drugs with novel mechanisms of anti-tubercular action or ways to potentiate the activity of already existing drugs and reduce treatment duration. This thesis explores the employment of peptides in anti-tuberculosis therapy. The project was initiated by the identification of a novel therapeutic target in M. tuberculosis: murein peptide ligase (Mpl, Rv3712), an enzyme involved in the bacterial peptidoglycan recycling process. The aim is to synthesise its putative natural substrates (peptidoglycan peptide fragments) to characterise its activity and synthesise sequence analogues. These analogues were tested on the whole-cell and will be evaluated for inhibitory activity on the recombinant Mpl enzyme and eventually could be used in combination with existing or new drugs to see whether they increase anti-tubercular potency and thus combat resistance. Attainment of the putative substrate required the synthesis of mDAP, an unusual amino acid unique to peptidoglycan. Its synthesis was successfully completed and it was incorporated in the tripeptide Mpl putative substrate. Solid-phase synthesis has been used successfully and proved effective for rapid synthesis of multiple short peptide analogues in parallel. In addition it was used to synthesise anti-tuberculosis lasso peptides, lariatins A and B, lassomycin and analogues, to evaluate the structural requirements for biological activity. The method for the heterologous expression and purification of recombinant Mpl from M. tuberculosis has been confirmed as successful, and the enzyme is available for future target-based evaluation using the synthesised mDAP-containing tripeptide and eventually for other mDAP-containing PG fragments and analogues.

This thesis applies inorganic chemistry to develop new nanoparticulate vaccine adjuvants, entities added to a vaccine to inculcate robust immunity. The Introduction sets out the background to this work, and the Experimental Methods chapter reviews the techniques applied. Chapter 3 then reports the preparation of AlO(OH) using a continuous hydrothermal synthetic pathway – with sub-100 °C temperatures and atmospheric pressure – to produce nanoscale particles. A variety of experimental parameters was explored, and some degree of particle engineering could be achieved albeit over a narrow range of sizes and shapes. There was some evidence of particle size influencing the response of macrophages to the samples. Chapter 4 and Chapter 5 aim to engineer the size and shape of hydroxyapatite and zinc oxide nanoparticles, respectively, through different continuous hydrothermal processes. Several different morphologies (spheres, and mixtures of spheres/rods/platelets) could be produced. The morphology and particle size appear to affect cytokine production in vitro. Chapter 6 explores layered double hydroxides (LDHs) as inorganic adjuvants. A series of materials were prepared and characterised, and the effect of changing the LDH chemical composition on adjuvanticity determined. It was found that the size of the guest anion influences the immune response. Further, computational models were developed to aid the in silico prediction of immunogenicity, with calculated energy values being a suitable proxy for the zeta potential. The related hydroxy double salt (HDS) materials are investigated as adjuvants in Chapter 7. A series of materials was prepared and their chemical composition found to markedly effect the immune response in vitro. Computational models were sought with the same in silico aim as the LDH materials, however with limited success owing to a lack of detailed structural knowledge in the literature. Finally, overarching conclusions and suggestions for the future outlook of this area of research are given in Chapter 8.

Inkjet printing is a technology that is witnessing many applications across numerous areas of research. This technology is adopted here to address some challenges in medicine and pharmaceutical science. A thermal inkjet (HP 5940) was modified and used for this work; the robustness of the modified printer was confirmed afterwards. With printing of bacteria as a theme in this thesis, an initial assessment of the effect of ink jetting on the viability of bacterial cells was conducted and the damage was found to be negligible. An analytical application of ink jetting in antimicrobial susceptibility testing was conducted. A model was developed whereby varying antibiotic concentrations were printed onto agar-coated glass slides; a fixed bacterial population was then printed onto the varying antibiotic concentrations. The concentration of printed antibiotic exhibiting no bacterial growth after incubation was then computed based on an initial cartridge characterisation using HPLC. Minimum inhibitory concentrations obtained for antibiotics tested, using the designed model, when compared with standard broth microdilution technique were within an acceptable range, i.e., one doubling dilution apart. The inkjet printing technology was also applied in formulating probiotics. Probiotics for site-specific delivery into the lower small intestines or colon were formulated by printing the probiotic strain (Lactobacillus acidophilus LA 5) onto edible starch paper and encapsulating organisms in PhloralÒ pre-coated capsules to protect organisms from the harshness of stomach fluids. The encapsulated formulation exhibited over 40% recovery at sites of interest with 78.3% of the administered strain adhering to intestinal cells. The formulation was able to eliminate completely a population of E. coli when co-incubated. The potential of ink jetting in formulating probiotic oro-dispersible films (ODFs) was also explored. ODFs containing Streptococcus salivarius and xylitol were prepared and the benefits in managing dental caries were assessed. The probiotic ODFs reduced Streptococcus mutans numbers by 2.86 log cycles.

Lentiviral vectors are increasingly used as delivery methods in gene therapy clinical trials due to their high efficiency transducing cells and stability of transgene expression. The development of packaging and producer cell lines for the production of lentiviral vectors has always been a labour-intensive and lengthy process. Sequential introduction of vector components, adaptability to suspension cultures, autotransduction and genetic, transcriptional or cell line growth instability are some of the limitations that cause significant drops in productivity. Improved transcription of self-inactivating vectors leading to high titers has been attempted in different ways with the intent to find a high stable producer clone. In this project, we studied the use of lentiviral vectors as a tool to target and identify high-transcribing loci in the genome of our host cells for lentiviral packaging cell line development. Third generation lentiviral vectors carrying eGFP under the control of an endogenous clinically-tested promoter (short EF1α) were produced, containing a variable DNA sequence tag (barcode) in their long terminal repeat (LTR). The aim of the barcode is to uniquely tag, identify and track a particular clone within the heterologous expressing population. Human embryonic kidney cell lines (HEK-293) were transduced with a barcoded lentiviral library at a low multiplicity of infection. We demonstrated that integration site analysis and next-generation sequencing of lentiviral barcoded vector junctions by ligation-mediated PCR (LM-PCR) coupled with RNA-Seq allows for quantification of the relative abundance of each barcode variant in each specific genomic position. Expression cassettes containing lentiviral vector components were then site-specifically integrated into these genomes sites using the CRISPR-Cas9 technology. The barcoding lentiviral system allows for rapid and high-resolution high-throughput screening of gene expression in a large number of genomic positions naturally targeted for optimal vector expression but also of lower expressing sites in order to meet lentiviral cytotoxicity and stoichiometric constraints.

Leukaemia is a blood/bone marrow cancer caused by malignant immature hematopoietic precursors, and quickly becomes a systematic malignancy. The most severe type of leukaemia that has the highest number of lethal outcomes is Acute Myeloid Leukaemia (AML) where malignant cells escape host immune surveillance by inactivating cytotoxic lymphoid cells. We discovered a fundamental biochemical mechanism in AML cells, which includes ligand dependent (probably FLRT3) activation of ectopically expressed latrophilin 1 and possible other G-protein coupled receptors, leading to upregulated translation and secretion of the immune receptor Tim-3 and its ligand galectin-9. This process involved protein kinase C and the mammalian target of rapamycin (mTOR). Tim-3 was observed to participate in galectin-9 secretion, and was also released in a free soluble form. Galectin-9 impaired the anti-cancer activities of cytotoxic lymphoid cells including natural killer (NK) cells and soluble Tim-3 prevented the secretion of interleukin-2 (IL-2), which was required for the activation of cytotoxic lymphoid cells. These results were validated in ex vivo experiments, using primary samples from AML patients. This fundamental pathway provides reliable targets for both highly specific diagnosis and immune therapy of AML. Furthermore, we demonstrated that the Tim-3/galectin-9 autocrine loop has intracellular functions and promotes cell growth and proliferation by directly upregulating translational pathway controlled by mTOR.

Pseudotyped viruses (PVs) provide a safe, flexible platform for fundamental virological studies and antibody screening assays. Generation of influenza PVs involves co-transfection of producer cells with plasmids encoding the necessary viral components. The pseudotype virus neutralisation assay (PVNA) is a sensitive technique to measure protective antibody responses which cause neutralisation of virus particles. Many traditional methodologies, e.g. Haemagglutination Inhibition (HI) and Single Radial Haemolysis (SRH), detect only surface glycoprotein binding antibodies whereas the PVNA quantifies infectivity-neutralising responses. Haemagglutinin (HA) and neuraminidase (NA) are the two major surface glycoproteins embedded within the membrane of an influenza virion. HA is responsible for virion attachment and entry into a host cell and NA is essential for viral egress and thus spread of infection. Two enzymes crucial for the infectivity of influenza viruses are; HA-cleaving cellular proteases and the NA itself. Optimisation of both enzymes in PV production is necessary to increase the titre of PVs. Producing high titre PVs is important as this permits minimal quantities to be used in PVNAs, and repeat experiments can be carried out using the same batch of virus, minimising intra-study variability. Optimising PVs and employing them in a novel situation, such as an equine influenza vaccine efficacy trial, has been carried out with promising results. We have demonstrated that data obtained from the PVNA correlates well with the traditional SRH assay and consequently there is the potential for more widespread adoption in research and commercial settings. Furthermore, PVs have been manipulated to assess how single amino acid changes with equine influenza virus can affect the neutralisation efficacy of sera generated by vaccination. Novel PVs, such as those derived from canine and phocine (seal) influenza strains have also been produced and provide a new platform for sero-surveillance of these viruses particularly in the case of wild or feral animals, due to issues with obtaining samples from wild animals during acute infection. Overall, PVs have been demonstrated as useful and readily-manipulated tools for studying antibody responses against equine, canine and phocine influenza viruses.

The influenza virus still causes hundreds of thousands of deaths globally, on top of morbidity and associated economic burden. We are currently at the height of efforts surrounding the development and employment of 'universal' vaccines against this virus, with clinical trials commencing on the most promising candidates. Despite this, the influenza virus poses more of a threat to human life than it ever has previously, with multiple subtypes of pandemic potential circulating around the globe. The key to current efforts lies in the priming of the immune system towards generating long lasting defences against conserved epitopes and conferring heterosubtypic immunity against the surface glycoprotein haemagglutinin. While vaccine strategies have expanded rapidly over recent years with the advent of 'headless' constructs as well as those derived from consensus, mosaic or chimeric sequences, the serological techniques to test how effective these vaccines are, have advanced less rapidly. Classical serological assays have been shown to be ineffective at detecting the antibodies which modern 'universal' vaccines strife to elicit, replaced by ELISA based approaches combined with mouse models measuring in vivo protection. In this thesis, an alternative method for the detection of heterosubtypic antibodies is used in depth across multiple platforms. Influenza pseudotypes have been employed using chimeric haemagglutinin constructs in a comprehensive project aimed at dissecting head and stalk directed antibodies present in human serum. Characterised broadly neutralising monoclonal antibodies have been tested on panels of influenza pseudotypes including divergent bat influenza viruses which hitherto have not been encountered in humans. A further aspect of influenza immunity has been covered in the detection of anti neuraminidase antibodies which have an important role to play in influenza heterosubtypic immunity. Finally, influenza pseudotypes bearing the glycoproteins from the less studied influenza B virus have been assayed in a large scale project aimed at correlating pseudotype assays with classical approaches.

The ability to predict human pharmacokinetics in early stages of drug development is of paramount importance to prevent late stage attrition as well as in managing toxicity. This thesis explores the machine learning modelling of one of the main pharmacokinetics parameters that determines the therapeutic success of a drug - volume of distribution. In order to do so, a variety of physiological phenomena with known mechanisms of impact on drug distribution were considered as input features during the modelling of volume of distribution namely, Solute Carriers-mediated uptake and ATP-binding Cassette-mediated efflux, drug-induced phospholipidosis and plasma protein binding. These were paired with molecular descriptors to provide both chemical and biological information to the building of the predictive models. Since biological data used as input is limited, prior to modelling volume of distribution, the various types of physiological descriptors were also modelled. Here, a focus was placed on harnessing the information contained in correlations within the two transporter families, which was done by using multi-label classification. The application of such approach to transporter data is very recent and its use to model Solute Carriers data, for example, is reported here for the first time. On both transporter families, there was evidence that accounting for correlations between transporters offers useful information that is not portrayed by molecular descriptors. This effort also allowed uncovering new potential links between members of the Solute Carriers family, which are not obvious from a purely physiological standpoint. The models created for the different physiological parameters were then used to predict these parameters and fill in the gaps in the available experimental data, and the resulting merging of experimental and predicted data was used to model volume of distribution. This exercise improved the accuracy of volume of distribution models, and the generated models incorporated a wide variety of the different physiological descriptors supplied along with molecular features. The use of most of these physiological descriptors in the modelling of distribution is unprecedented, which is one of the main novelty points of this thesis. Additionally, as a parallel complementary work, a new method to characterize the predictive reliability of machine learning classification model was proposed, and an in depth analysis of mispredictions, their trends and causes was carried out, using one of the transporter models as example. This is an important complement to the main body of work in this thesis, as predictive performance is necessarily tied to prediction reliability.