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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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to analyse complex datasets, extract meaningful insights, and guide the optimisation of drug molecules. Collaborate with internal groups, including the Centre for Additive Manufacturing (CfAM) to design and
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to analyse complex datasets, extract meaningful insights, and guide the optimisation of drug molecules. Collaborate with internal groups, including the Centre for Additive Manufacturing (CfAM) to design and
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, coronaviruses, influenza, pneumonia, RSV) as well as pollution, tobacco, pollen, weather, drugs, foods and stinging insects. The long-term plan for the Driver Programme is to extend the data science capabilities
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The project aims to develop a publicly accessible in silico database that identifies and catalogues bacterial genes capable of altering the effectiveness of chemotherapy drugs in colorectal cancer
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Drug-resistant fungal infections—caused by species like Candida auris, Cryptococcus neoformans, and Aspergillus fumigatus—pose a growing threat in healthcare, with mortality rates exceeding 50% in
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. The within-host model will be linked to: a clinical trial simulation, an essential tool in drug development, to inform the clinical trial design of novel treatments, an individual-based transmission model
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supported by the Cell-Scale Biomechanics Lab , and is part of the lab’s recent technology-development projects, aimed at improving the accuracy of drug efficacy screening for chemotherapy. A recent press
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, showing potential to treat various cancers. The aim of this project is to use a multidisciplinary approach involving (bio)chemistry, computer aided drug design, cell biology and genetics to develop more
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healthcare diagnostics and drug development. The candidate will design fibres having controlled cells spacing, by using the principle of viscoelasticity-induced ordering in straight microchannels (https