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Click here to search FindAPhD.com for PhD studentship opportunitiesModelling of tumour size, new lesions and other markers as longitudinal end points in oncology studies
Dr K Ogungbenro, Prof Leon Aarons
No more applications being accepted
Funded PhD Project (European/UK Students Only)
About the Project
The aim of this project is to develop an integrated framework of efficacy and toxicity in oncology based on mechanistic models of tumour size, new lesions and other markers. Change in tumour size is an informative patient-level continuous end point that can be assessed in phase 1b or II studies and coupled with tumour growth inhibition (TGI) and survival models, can enhance the understanding gained from these studies compared with the traditional approach of estimating objective response rate and progression free survival. TGI models have been used to analyse longitudinal tumour size data in clinical studies. These models explicitly incorporate drug exposure over time to drive drug effect on tumour size. Drug exposure could refer to either drug dose or an integrated measure of drug exposure, such as area under the curve in exposure-response models or pharmacokinetic profile in full pharmacokinetic/pharmacodynamic models. These drug-specific models allow estimation of efficacy parameters and can be used to perform dose (schedule)-response simulations of tumour shrinkage and to assess dose response in overall survival or other clinical end point of interest, using drug-independent models. TGI models that incorporate both drug-and disease-specific parameters (e.g. tumour growth rate) may also be of value to scale antitumor effect from early (Phase II) to late (Phase III) clinical studies.
A framework for drug-disease modelling in oncology has been proposed for quantitative prediction of survival benefit using patient risk factors and tumour size data. This approach has also been extended to incorporate drug exposure and change in tumour size at end of a cycle to predict overall survival. This research will evaluate and extend the integrated modelling framework to different tumour types that used similar designs.
During the project the student will develop quantitative modelling skills that will involve the use of computational software packages such as MATLAB, R, NONMEM and MONOLIX. The student will be based at the Centre for Applied Pharmacokinetic Research in Manchester which is an internationally recognised, academic-led centre of excellence for research and training in the area of mechanistic in vitro characterisation of drug metabolism, transporters, PBPK and PK-PD modelling. The student will interact with researchers and be exposed to interdisciplinary projects ongoing at the Centre for Drug and Disease Modelling and Simulation and NorthWest Centre for Advanced Drug Delivery (NoWCADD), both placed in School of Health Sciences
A framework for drug-disease modelling in oncology has been proposed for quantitative prediction of survival benefit using patient risk factors and tumour size data. This approach has also been extended to incorporate drug exposure and change in tumour size at end of a cycle to predict overall survival. This research will evaluate and extend the integrated modelling framework to different tumour types that used similar designs.
During the project the student will develop quantitative modelling skills that will involve the use of computational software packages such as MATLAB, R, NONMEM and MONOLIX. The student will be based at the Centre for Applied Pharmacokinetic Research in Manchester which is an internationally recognised, academic-led centre of excellence for research and training in the area of mechanistic in vitro characterisation of drug metabolism, transporters, PBPK and PK-PD modelling. The student will interact with researchers and be exposed to interdisciplinary projects ongoing at the Centre for Drug and Disease Modelling and Simulation and NorthWest Centre for Advanced Drug Delivery (NoWCADD), both placed in School of Health Sciences
Funding Notes
This 3-year full-time funded PhD covers UK/EU tuition fees and an annual tax-free stipend. Start date September 2017. On the online application form select PhD Pharmacy and Pharmaceutical Sciences. Full details on how to apply can be found on our website: https://www.bmh.manchester.ac.uk/study/research/apply/.
Applicants are expected to hold or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in pharmacy, pharmacology, mathematics, statistics, or a related discipline. A strong mathematical background or a Masters degree in relevant subject is desirable. Previous experience of data analysis and mathematical/computational modelling would be an advantage.
Applicants are expected to hold or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in pharmacy, pharmacology, mathematics, statistics, or a related discipline. A strong mathematical background or a Masters degree in relevant subject is desirable. Previous experience of data analysis and mathematical/computational modelling would be an advantage.
References
1. Claret L, Girard P, Hoff PM, Van Cutsem E, Zuideveld KP, Jorga K, Fagerberg J, Bruno R. Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. J. Clin. Oncol. J Clin Oncol (2009) 27(25):4103-4108
2. Tham LS, Wang L, Soo RA, Lee SC, Lee HS, Yong WP, Goh BC, Holford NH. A pharmacodynamic model for the time course of tumor shrinkage by gemcitabine + carboplatin in non-small cell lung cancer patients. Clin Cancer Res (2008) 14(13):4213-4218
3. Wang Y, Sung C, Dartois C, Ramchandani R, Booth BP, Rock E, Gobburu J. Elucidation of relationship between tumor size and survival in non-small cell lung cancer patients can aid early decision making in clinical drug development. Clin Pharmacol Ther (2009) 86(2):167-174
4. Bruno R, Claret L. On the use of change in tumor size to predict survival in clinical oncology studies: toward a new paradigm to design and evaluate phase II studies. Clin Pharmacol Ther (2009) 86(2):136-138
5. Zecchin C, Gueorguieva I, Enas NH, Friberg LE. Models for change in tumour size, appearance of new lesions and survival probability in patients with advanced epithelial ovarian cancer. Br J Clin Pharmacol (2016) 82: 717–727
2. Tham LS, Wang L, Soo RA, Lee SC, Lee HS, Yong WP, Goh BC, Holford NH. A pharmacodynamic model for the time course of tumor shrinkage by gemcitabine + carboplatin in non-small cell lung cancer patients. Clin Cancer Res (2008) 14(13):4213-4218
3. Wang Y, Sung C, Dartois C, Ramchandani R, Booth BP, Rock E, Gobburu J. Elucidation of relationship between tumor size and survival in non-small cell lung cancer patients can aid early decision making in clinical drug development. Clin Pharmacol Ther (2009) 86(2):167-174
4. Bruno R, Claret L. On the use of change in tumor size to predict survival in clinical oncology studies: toward a new paradigm to design and evaluate phase II studies. Clin Pharmacol Ther (2009) 86(2):136-138
5. Zecchin C, Gueorguieva I, Enas NH, Friberg LE. Models for change in tumour size, appearance of new lesions and survival probability in patients with advanced epithelial ovarian cancer. Br J Clin Pharmacol (2016) 82: 717–727
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