
Dr Carina Dunlop
Academic and research departments
Department of Mathematics, Centre for Mathematical and Computational Biology.Biography
My research focuses on the mathematical modelling of biological systems. I joined the University of Surrey as a Lecturer in Mathematics in January 2012. Prior to this I spent four years at Heidelberg University as a postdoctoral fellow, and three and a half years as a postdoctoral researcher at Oxford University. I completed my doctoral research in fluid dynamics in 2004 at the University of Oxford, where I read mathematics as an undergraduate.
Areas of specialism
University roles and responsibilities
- Admissions Tutor
Affiliations and memberships
Research
Research interests
I am interested in using mathematical and computational approaches to solve a broad range of problems in developmental biology, tissue morphogenesis and cancer modelling. A particular research focus is on the cell as a physical object, incorporating an understanding of the role of mechanical forces into models of biological processes. I draw on a diverse range of concepts in pursuing this research ranging from population modelling to the theories of fluid dynamics and elasticity theory. Currently ongoing projects include work on tissue self-organization, mechanical regulation of growth and cellular contractility.
Current students:
PhD - Kieran Boniface, Oct. 2019 - present, Mathematical models for tissue growth and development with applications to organoids and tissue eningeering
PhD - Josephine Solowiej-Wedderburn, Oct. 2017 - present, Mechanical models of cell-substrate interactions
PhD- Adam Nasim, Jan. 2018 - present, Mathematical modelling of pharmacological approaches to cancer treatment (collaboration with Dr James Yates, AstraZeneca)
MMath - Robert Dymott, Importance of interstitial fluid flow in tumour growth
Former students
Euan Littlejohns, PhD, University of Surrey (2014 -18), Continuum Elasticity Models for Tissue Growth and Mechanotransduction
Philip Murray, DPhil, University of Oxford (2004-8): From discrete to continuum models of tumour growth, co-supervisors: Prof. P. K. Maini and Dr M.J. Tindall. now Lecturer, Division of Mathematics, University of Dundee
Matthew Johnston, DPhil,University of Oxford (2004-8): Mathematical modelling of cell population dynamics in the colonic crypt, co-supervisors: Prof. P.K. Maini and Prof. S.J. Chapman
Research projects
Supervision
Postgraduate research supervision
Kieran Boniface, PhD, Oct. 2019 - present, Mathematical models for tissue growth and development with applications to organoids and tissue eningeering
Josephine Solowiej-Wedderburn, PhD, Oct. 2017 - present, Mechanical models of cell-substrate interactions
Adam Nasim, PhD, Jan. 2018 - present, Mathematical modelling of pharmacological approaches to cancer treatment (collaboration with Dr James Yates, AstraZeneca)
My teaching
I am lecturing this year on
MATM040 - Mathematical Biology and Physiology
MAT2050 - Inviscid Fluid Dynamics
My publications
Publications
A 2‐day meeting was held by members of the UK Quantitative Systems Pharmacology Network (http://www.qsp‐uk.net/) in November 2018 on the topic of Translational Challenges in Oncology. Participants from a wide range of backgrounds were invited to discuss current and emerging modeling applications in nonclinical and clinical drug development, and to identify areas for improvement. This resulting perspective explores opportunities for impactful quantitative pharmacology approaches. Four key themes arose from the presentations and discussions that were held, leading to the following recommendations:
• Evaluate the predictivity and reproducibility of animal cancer models through precompetitive collaboration.
• Apply mechanism of action (MoA) based mechanistic models derived from nonclinical data to clinical trial data.
• Apply MoA reflective models across trial data sets to more robustly quantify the natural history of disease and response to differing interventions.
• Quantify more robustly the dose and concentration dependence of adverse events through mathematical modelling techniques and modified trial design.
A two-day meeting was held by members of the UK Quantitative Systems Pharmacology Network (http://www.qsp-uk.net/) in November 2018 on the topic of Translational Challenges in Oncology. Participants from a wide range of backgrounds were invited to discuss current and emerging modelling applications in non-clinical and clinical drug development, and to identify areas for improvement. This resulting perspective explores opportunities for impactful quantitative pharmacology approaches. Four key themes arose from the presentations and discussions that were held, leading to the following recommendations:
- Evaluate the predictivity and reproducibility of animal cancer models through pre-competitive collaboration
- Apply mechanism of action (MoA) based mechanistic model derived from nonclinical data to clinical trial data
- Apply MoA reflective models across trial data sets to more robustly quantify the natural history of disease and response to differing interventions
- Quantify more robustly the dose and concentration dependence of adverse events through mathematical modelling techniques and modified trial design