Funding
Self-funded
Project code
MPB10021026
Start dates
October, February and April
Application deadline
Applications accepted all year round
Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.
The PhD will be based in the School of Medicine, Pharmacy and Biomedical Sciences and will be supervised by Dr Gavin Fullstone.
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The work on this project will involve:
- Personalised prediction of anti-cancer drug (and drug combinations) responses in cancer patients
- Computational modelling of cancer drug (BH3-mimetics) clearance, toxicity and efficacy using quantitative systems pharmacology and the open systems pharmacology suite
- In vitro cell culture models and quantitative experimental approaches
- Integration of clinical trial and patient data into models including high throughput proteomics
Cancer is one of the major public health challenges of the 21st century, accounting for nearly 1 in 6 deaths worldwide (World Health Organisation). Development of cancer is normally held in check by the regulated cell death pathway apoptosis, disruption of which is one of the hallmarks of cancer. Hence, re-sensitising cancer cells to apoptosis using chemotherapeutic drugs or state-of-the-art precision therapeutics is a key strategy in cancer treatment. BH3-mimetics are precision therapeutics that trigger apoptosis by inhibition of key anti-apoptotic regulatory proteins, BCL2, BCLXL and MCL1 (1). Of these, Venetoclax is routinely used to treat various forms of leukaemia, whilst other BH3-mimetics are under various stages of clinical evaluation.
In this project, you will employ an approach called quantitative systems pharmacology (QSP) to predict how cancer patients will respond to specified doses and combinations of different BH3-mimetics. QSP is a method that integrates our understanding of drug uptake, clearance and action into detailed holistic computational models for predicting complex dose-toxicology/dose-efficacy relationships and is playing a growing role in drug development and clinical trial design (2). To create, evaluate and refine QSP models of BH3-mimetic-induced apoptosis in cancer treatment, you will employ multidisciplinary approaches including lab-based experimental work in cancer cells, computational simulation and integration of patient data. You will then employ these models to perform in silico clinical trials to predict optimal BH3-mimetic treatment programmes for cancer patient cohorts, balancing dose-limiting intolerabilities with onsite anti-cancer efficacy.
1. Diepstraten, S. T. et al. The manipulation of apoptosis for cancer therapy using BH3-mimetic drugs. Nat Rev Cancer 22, 45–64 (2022).
2. Azer, K. et al. History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications. Front Physiol Volume 12-2021, (2021).
Fees and funding
Visit the research subject area page for fees and funding information for this project.
Funding availability: Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK (UK and EU students only – eligibility criteria apply).
Bench fees
Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.
Entry Requirements
You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject (molecular biology, biomedical sciences, systems biology, pharmacology or related area). In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
A key criterion for selection is enthusiasm for engaging with the multidisciplinary approach (wet lab-based and computational-based research) used in the project to tackle critical questions in cancer treatment. Wet lab experience is highly desired. Whilst knowledge of coding is not required (all models will be implemented in well-documented software with graphical user interfaces), some experience would be advantageous for automating simulation and data analysis steps.
How to apply
We’d encourage you to contact Dr Gavin Fullstone (gavin.fullstone@port.ac.uk) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, please follow the 'Apply now' link on the Pharmacy, Pharmacology and Biomedical Sciences PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
When applying please quote project code:MPB10021026