I am a PhD research student at Cardiff, studying data analysis and computational modelling of embryo growth rate and other metrics of success in In-Vitro Fertilization. My project is funded by the KESS2 initiative (see research) and is supervised by:
My project is an academia-industry collaboration with the London Womens Clinic(LWC), who cofund the project. At the LWC I am supervised by Andrew Thomson,Fertility Laboratory Manager LWC Wales and Bristol.
In addition to my research, I teach Linear Algebra I and Computing for Mathematics labs.
I also am a subject tutor for the 'Maths and Numeracy' stream of the Cardiff University Step Up Programme, which provides year 12/13 students from backgrounds which are under-represented at university with higher level teaching and application support.
- Mathematical Biology
- Ecological modelling
Linear Algebra 1 Tutorials
Computing for Mathematics Labs
Data analysis and computational modelling of embryo growth rate and other metrics of success in In-Vitro Fertilization
This project is an academia-industry collaboration between Cardiff University and the London Women's Clinic (LWC)
In-Vitro Fertilisation (IVF) is the process where eggs are fertilised with sperm in a lab. Successful fertilisation leads to the formation of embryos, which are then transferrred to the womb of the prospective mother. Since the birth of the first baby by IVF in 1978, IVF has become increasingly popular with over 70,000 IVF babies born a year in the UK alone according to the Human Fertilisation & Embryology Authority (HFEA). Patients can have their embryos vitrified (have water removed) and cryogenically preserved to be thawed later and transferred. There is some evidence that vitrified embryos might increase pregnancy chances, but the data is currently inconclusive.
This project, co-funded by LWC, focuses on improving the success rates for IVF using frozen embryos. There are two main challenges to tackle:
- Selecting the best embryo
- Optimal embryo storage and management.
The first challenge involves data extraction and statistical modelling and the second challenge involves modelling the heat distribution in thawing embryos after their cryopreservation.
Challenge 1: Selecting the best embryo
A key factor for success during In-Vitro Fertilization (IVF) is choosing the best quality embryo to transfer to the patient in order to maximise the chances for a successful pregnancy. Current methods such as time-lapse imaging exist to allow for observation of the embryo as it thaws, but currently this information is not being utilised.
The aim is to develop a sophisticated, user-friendly image segmentation software tool that will accurately extract multiple features of a thawing embryo’s time-lapse images. This tool is not available currently in the IVF field and it will greatly speed up and eventually automate the extraction of multiple embryo features, while eliminating human error. Also, in IVF clinics only single focal frames of embryos are monitored currently; the software tool will extract the full 3D structure of embryos.
Data from hundreds of embryos will be extracted and then processed with a meta-statistical analysis. A variety of different embryo quality metrics suggested in the IVF field will be assessed, to see which metric or combination of metrics correlates with embryo success.
Challenge 2: Modelling the temperature of embryos
The second challenge will focus on modelling the temperature of thawing embryos after they have been cryopreserved.
Whenever embryos are transported, or inspected, it is imperative that their temperature is carefully controlled, to avoid damaging them. The inspection stage is the most critical as the embryo is removed from the storage liquid (liquid nitrogen) for observation and then re-immersed. Although this inspection is the most important stage for temperature control there are currently no protocols on how long it would take the embryo to heat beyond the point of damage.
We will thus develop a computational model for the temperature evolution in a thawing embryo, using a heterogeneous three-dimensional heat transfer model. With the model we will predict the exact time and conditions at which the embryos become damaged for different storage and observation scenarios, paving the way to creating effective handling protocols.
Knowledge Economy Skills Scholarships 2 (KESS 2) is a pan-Wales higher level skills initiative led by Bangor University on behalf of the HE sector in Wales. It is part funded by the Welsh Government’s European Social Fund (ESF).