Published on: 8th March 2017
Today, Wednesday 8th March, is International Women’s Day, where people around the world recognise and celebrate the social, economic, political and cultural achievements of women. In support, The Farr Institute has put the spotlight its on female researchers, who talk about their experiences in using big data in research.
From representing around 50% of the the Institute’s PhD Students to Deputy Director Prof Jill Pell receiving a recent CBE, women are key leaders across The Farr Institute’s Working Groups.
Dr Catharine Goddard, Network Manager, said: “It is a privilege to work for an Institute in which women are so well represented, both amongst the research scientists and the operations teams, who are so essential to the successful functioning of The Farr Institute. The team science environment within The Farr Institute allows women scientists to thrive and I hope our female leaders at The Farr Institute provide inspiration and mentorship for the next generation of women leaders in health data science.”
Professor Ronan Lyons, Co-Director, said: “There are a number of successful, prominent women working within The Farr Institute who aspiring researchers can look to for inspiration. Their ground breaking research is making an incredible impact in this industry and a positive impact of the health and well-being of the UK. It is an exciting, innovative time for health informatics in the UK and our researchers are proud to be part of the UK’s vision to become a global leader in data driven improvements in public health and patient care.”
To read about Farr Scotland’s all-female Public Engagement team, click here.
Professor Sinead Brophy, Farr CIPHER
Sinead is based at Swansea University, and has expertise in Epidemiology and Public Health.
From I was little I was always interested in why? What happens if you did things differently? I wanted to be a vet or doctor but people who knew me generally said that was not my personality and I would be frustrated by the processes and being in a system and would argue too much. So I guess I was always a researcher at heart, I always liked investigating and understanding things. I started with studying Biotechnology and then went into epidemiology research in Bath in the Hospital for Rheumatic Diseases (one of the largest databases in the world for people with a particular Rheumatic disease called ankylosing spondylitis). I linked X rays, genetic data and other data (such as hospital records) and looked at how to predict who would have severe arthritis and who would have a mild form of the condition. In 2003 I came to Swansea to help to develop research in epidemiology using large databases such as hospital admissions and general practice data.
I have worked over twenty years on research on arthritis, mainly on ankylosing spondylitis. I have also worked in diabetes research and was secretary to the European Diabetes Epidemiology group. I am currently working on research on child health with a real interest in physical activity and well-being and work with schools. I evaluate the ways of improving both health and educational attainment together. I am also very interested in data driven or machine learning approaches to understanding problems. That is looking at patterns in data to understand things instead of always coming with preconceived ideas – for example, looking at patterns of diagnosis and visits to hospital/GP for children given certain medications in order to understand positive and negative effects of medicines prescribed in children. In relation to this I am on the Independent Scientific Advisory Committee for the Medicines and Healthcare products Regulatory Agency research database.
I am currently carrying out research into the health of children at school level and how their health could be improved through in-school activities. For example through activity vouchers which could can improve their fitness and attitudes to being active. We examine fitness, heart health and how social networks change with having the ability to socialise through activity. This is a project that was designed in cooperation with pupils and teachers. We are very proud that we have been able to take ideas that have come from the pupils and teachers and work with them to pilot and test it and now we have brought it to a full randomised trial thanks to funding from the British Heart Foundation. I work with other national centres such as FARR Institute in Scotland and London to research and compare findings into conditions such as autism or heart disease across the UK and examine how policy differences in the different areas might influence health.
What really inspires me is when I feel the findings of research can actually be used to change or improve things. I find it very rewarding to investigate, understand and then hopefully improve the way things are done. The best part is when working with routine data you can see how a small change can have a big effect on a whole population and then to see the ripples or knock on effects when something is changed. Seeing the big picture is fascinating and scary too as it shows how much we are a product of our environment rather than our own personal decisions. For example I feel that my work on arthritis had an impact at a national level in terms of being part of guidelines and recommendations for treatment for patients across the UK. I also feel that my research with schools and children’s well-being can and will have an impact on children’s health across Wales and even the rest of the UK.
Dr Ann John, Farr CIPHER
Ann, based at Swansea University Medical School, has expertise in Psychiatric Epidemiology and Public Health. Her research focus is the mental health of children and young people and the prevention of suicide and self-harm.
I definitely took a convoluted route to big data research. I started off my career as a general practitioner and clinical assistant in psychiatry. It became obvious very quickly that many of my most vulnerable patients had mental health issues and that these pervaded their lives from their physical health to their jobs and relationships. It also became obvious that socio-economic circumstances and education, with the opportunities it offers, had a huge impact on health. The injustice of health inequity, particularly stark in those with mental disorders, inspired me to undertake my Public Health Medicine training. During my training I came to do an academic attachment at the Medical School. I was analysing Welsh Health Survey and Census data on common mental disorders. The SAIL Databank was coming into being and I thought ‘I can replicate this study in SAIL using routine data instead’. I thought it was going to be easy but although it took a couple of years to unpick recording behaviour and other vagaries of routine data, I’m still here. I love being able to take the topic area I’m passionate about and look at it across populations. People with mental health problems often don’t take part in traditional research. Routine data gives everyone a voice in research- albeit a split-file anonymous voice!
I’m both a Member of the Royal College of General Practitioners and the Faculty of Public Health by examination. I lead on suicide prevention for Public health Wales and the Suicide Information Database- Cymru, an electronic case – control study within SAIL. My doctorate was to develop a predictor of needs for services for common mental disorders based on routine data so we could plan resources and services.
While epidemiology is the science of public health and provides the evidence for policy and practice, public health is the translation of that evidence into policy and practice. I think all those years of talking with patients helped me see the individuals in Big Data and turn analyses on hundreds of thousands of people into clear messages that can make a difference. We recently looked at prescribing of psychotropic medication in children and young people and presented our findings to the Children and Young People’s Education Committee. This resulted in a bulletin being sent to all GP’s in Wales and lots of publicity (including Newsround which was one of the few times my children took any notice of my work!). This will all hopefully lead to improved management of young people with mental disorders. SID Cymru data was used in the Child Death Review of probable suicides in Wales 2006-2012 which led to policy changes.
Dr Elizabeth Ford, Farr CIPHER
Elizabeth is based Brighton and Sussex Medical School (BSMS), her areas of expertise include: GP patient records, mental health and epidemiology.
I did my PhD in clinical health psychology, developing aetiological models for the development of PTSD in women following a traumatic birth. While I enjoyed the applied nature of my research, I also thrived on learning to handle data and use new and innovative statistical methods. After my PhD I took up a post as a research statistician in psychiatric epidemiology at Barts Medical School in London. It was a natural jump from there to the “big data” of primary care epidemiology, using routinely collected electronic health records to answer population based health questions.
I completed an undergraduate degree in Psychology and Physiology at the University of Oxford. After my studies I worked for a year a research assistant at UCL and then spent three years living in Paris, working as a medical writer in cancer pharmaceutical research. I loved being involved in medical research and wanted to train properly as a researcher and make my career in it, so I came back to the UK in 2004 to take up an MRC funded PhD at the University of Sussex.
I have worked and trained in range of research disciplines: psychology, psychiatry, epidemiology, primary care, oncology, and clinical trials; so I have a really broad range of research methods to draw on when looking to tackle the next problem. I relish an intellectual challenge and find I can “speak the language” of colleagues from other disciplines, enabling me to forge exciting cross-disciplinary collaborations. In 2016 I was awarded a grant from the Wellcome Trust in collaboration with astrophysicists at Sussex University, to study dementia diagnosis in primary care. We will be bringing data techniques from astronomy, such as Bayesian modelling and probabilistic programming to find a signature for dementia onset in routinely collected general practice data. This may help GPs to identify dementia earlier in the disease course, helping patients maintain a good quality of life. To complement this work, I also supervise a health-psychology PhD student who is investigating how and why GPs record diagnoses of dementia, and why sometimes GPs choose not to pursue a diagnosis where they have recognised dementia symptoms. I also continue to research best practice in postnatal mental health and rheumatoid arthritis in primary care.
Dr Lamiece Hassan, Farr HeRC/Connected Health Cities
Lamiece is based in the Division of Informatics, Imaging and Data Science at The University of Manchester. Her areas of expertise include public engagement, mental health and citizen science.
Since finishing my degree in Psychology, I’ve been working in health services research for over ten years. I first got into using ‘big data’ when I was doing my PhD, looking at what types of medicines were routinely prescribed to treat mental illness in prisons and in the wider community. As part of that work, I also worked with a group of ex-offenders who acted in an advisory capacity. Their insights helped me to understand why certain medicines were prescribed more often in prisons and why others were denied. When a post came up at the Health eResearch Centre (HeRC) combining public engagement and research using health data, I was extremely keen to get involved in the work done there.
At HeRC, I conduct, support and promote research that involves the public as partners, rather than just participants. Practically, this means I work across a range of health informatics projects spanning topics like hay fever, dementia, childhood obesity and chronic kidney disease. I’m also interested in research into public opinion on reusing routinely collected health data. Finding ever more creative ways to involve members of the public to enhance our research and encourage interest in health data science is what gets me out of bed in the morning! I also get a kick out of seeing our research reported in the news. It is exciting because every day is different – my work has taken me to science museums, pubs, music festivals, conferences and schools to talk about our work.
Dr Sabine van der Veer, Farr HeRC
Sabine is based at the Centre for Health Informatics at The University of Manchester. Her research interests include patient-led symptom reporting for chronic disease management, and getting wearable sensor data into clinical practice.
I did my MSc in Health Informatics at the University of Amsterdam (the Netherlands) because I was interested in how people interact with technology and how it can change their lives and health. After that, it took a while before I decided to pursue an academic career. I lived in Spain for a while, studied Spanish Literature, and worked as an IT project manager in a large university hospital. Although these detours have made my career path somewhat long and winding, they have also increased my confidence in that being a researcher is what I really want.
Being a researcher is great because you have the freedom and opportunity to shape your own ideas and make them a reality. It also allows you to take your time to dig into a topic through reading, exploring, writing, discussing. That feeling of truly understanding something is wonderful.
I am currently coordinating a UK-wide health informatics network to expedite kidney research, while also chairing a working group that advises NHS England on introducing patient-reported outcomes as part of routine clinical care for people with kidney disease. My research projects focus on how we can use new information technology, such as wearable devices and smartphones, to improve symptom reporting for people living with a long-term condition. Ultimately, I hope this will help people with a long-term condition to be more involved in their own health care.
Dr Mary Tully, Farr HeRC
Mary is based within the centre for health informatics and Manchester pharmacy school at The University of Manchester, her areas of expertise include: qualitative research, public attitudes to the use of health data.
I can’t say that I ever got into big data research – a better description is probably that I work around big data. For many years I served on research ethics committees and got involved in discussions around the ethics and governance of using big data. This led on to my interest in public attitudes towards the use of big data and consequently public engagement. I work in this area both within The Farr Institute in Manchester and more broadly within Connected Health Cities, where I am director of public engagement. This initiative is a collaboration of key partners and stakeholders working together, learning from each other, to improve care for our citizens living in the north of England by analysing healthcare data.
I am a pharmacist by background and my job is split between the Manchester Pharmacy School (where I teach professional ethics to the undergraduate students and do research to reduce prescribing errors in hospital) and the Centre for Health Informatics. Probably the hardest thing is to avoid ending up with two full time jobs – there are so many interesting things to get involved with, it is hard not to always say yes!
What we are working on at the moment is the citizens’ juries for Connected Health Cities. This work builds on a set of citizens’ juries that we did for The Farr Institute of Manchester, about what informed citizens would choose to do regarding the use of health data for research purposes. We have just completed juries that looked at both healthcare and commercial uses of health data. The findings showed that, over the four days of the juries, people tended to become more supportive of greater sharing of patient data for public benefit. They were more supportive in principle, but support for individual uses depended entirely on how they perceived the public benefit for the specific use under consideration. As a consequence, some citizens became more cautious about information sharing for certain uses and less cautious for other uses. We are planning on using these findings to help shape the public engagement strategy for Connected Health Cities over the next couple of years.
Dr Hannah Lennon, Farr HeRC
Hannah is based at the Health eResearch Centre at The University of Manchester, her areas of expertise include using health data to investigate the association between obesity and obesity-related cancers.
I am mathematician working in Statistics. Using large data sets, electronic health records and clinical trial data, we can look at patterns in body weight/fat and try to learn about its relationship with cancer. I’d previously had little experience of working with data so I was keen for my first post-doctoral project to involve real life data. I wanted to understand it fully, to find out about its messiness and benefits alike.
I completed a maths degree first, which equipped me with a great foundation in terms of programming and analytical skills. My training provided me with a wealth of transferable knowledge to work in informatics. I also completed a PhD in Mathematics, focusing on Computational Statistics, which has been very useful when thinking about the theoretical, abstract side of research.
I’m inspired by the thought of our work providing a better understanding and benefiting people. I’ve always had a passion to work in healthcare to combine my training, education and skills to research cancer.
Obesity is a risk factor for 13 obesity-related cancers. We know each individual is different and the amount of increased cancer risk for some people is different to others. My work looks at clustering together individuals with similar BMI trajectories to give a better understanding of the link between obesity through an adult’s lifetime and cancer.
I am also investigating the association of obesity and survival in cancer patients with two of the common cancers, colorectal and endometrial.
Ms Maxine Mackintosh, Farr London/Denaxas Lab
Maxine is a PhD student based at The Farr Institute and the Dementia Research Centre in Queen’s Square in London where she is investigating the use of electronic health records for early detection of dementia. She is active the wider health innovation scene and a big supporter of women in STEM.
My health economic masters raised all the dysfunctions and inefficiencies existing at the macro level in health systems, but provided by-and-large, policy solutions. I became interested in how else we can address major health challenges in innovative ways, so I began exploring the London health/tech scene. I started by attending a few digital health meetups, and quickly became inspired by some of the amazing innovations coming out of research, startups and corporates in this area, of which many were using nebulous (to me, at that time) Big Data. After listening to “Big Data this”, “Big Data that” for some months I decided I did not want to listen any more but do it. So I started teaching myself basic programming and benefited enormously from the many women/tech/coding initiatives in London (particularly Code First: Girls) to help individuals like myself looking to move into tech. Then when I saw my PhD advertised it came at a perfect moment and a perfect combination of my background and new interests, so I took the chance!
Like most people who are working in Big Data research, which is a melting pot of disciplines, I think I have had a portfolio academic background. My undergraduate was in neuroscience/pharmacology at UCL, but my dislike for lab work and love for science and health meant I moved to do an MSc in health economics and policy at the LSE and LSHTM. During all my universities years, studying hiatus and gaps I’ve always done little internships or non-academic projects. In hindsight rather audacious and naive emails asking for opportunities has opened some amazing doors. I spent a time at Roche in Basel working in technology strategy, L’Oreal’s scientific team, with chemical entrepreneurs in Kenya and at the Royal Society looking at high risk-high impact scientific investments. A random range of jobs, but always with an anchor in academia.
I’ve just started my 2nd year of my PhD so starting to see some early results coming through. Unfortunately they are not what I was hoping for but I’m having a play with different methods and trying to grapple with machine learning approaches. I’m looking at what cognition looks like in routinely collected data so as to investigate whether these data sets can be used for early detection of dementia. What I like about this area is the flexibility and freedom to ask new, different, creative, and at times slightly esoteric questions. We aren’t finding cures for dementia using traditional methods and approaches so using Big Data approaches means we can try slightly left-field approaches.
I think the best part of my research is getting paid to think, read, and answer questions you’re posing yourself. That’s quite a fun life! The lab, my supervisors and the researchers over at Queen’s Square and the Farr are a really friendly group too, which makes the days full of life.
My research has not been fruitful enough to lead to impact yet, but I am always communicating to others what I am doing, be it blogs, Twitter, Pint of Science or other sic-com platforms, because even if you do not have results to show, your approach and ideas might encourage others to think about their own research in a new light.
Myrto Kremyda-Vlachou, Farr London/ICONIC
Myrto is based at UCL, Farr Institute of Health Informatics, her areas of expertise include: bioinformatics and viral genomics.
I was inspired by the rapid technological advances and the research potential of big data to decipher complex biological mechanisms. My aim would be to use this knowledge and answer questions that would benefit the health sector. During my university studies I became interested in bioinformatics and the opportunities to analyse the genetic code of different organisms. I wanted to learn how to use existing tools and create new methods to analyse big data in combining genomic sequences of viruses and hospital laboratory records.
I hold two BSc degrees: a BSc in Sports Science and a First class BSc in Physiology and Pharmacology from Westminster University. Through my final year’s project at Westminster, I became increasingly interested in bioinformatics and programming, and this led to me carrying out a computational project for my Genetics of Human Disease MSc at UCL.
After my MSc I worked as a research assistant for the ICONIC project, being responsible for a substantial part of the bioinformatics analysis and interpretation using the project’s pipeline. The ICONIC project aims to stratify therapy in viral infections, help hospital infection control responses and inform surveillance in community outbreaks.
I am currently undertaking my PhD with title “Use of machine learning techniques to relate viral genotype to clinical phenotype in Hepatitis C virus infection” at the UCL, Farr Institute.
I currently use the set of tools developed in the ICONIC project (a flagship project by the Department of health and the Wellcome Trust) to analyse viral genomic sequences coming from residual hospital laboratory samples from patients infected with Hepatitis C Virus.
I draw inspiration from the need of patients for receiving a better treatment and of clinicians to be able to provide it, through big data analyses. Additionally, I am inspired by the many projects and people around me, who contribute to the technological and scientific advances expected to shape and improve healthcare in the coming years.
One of the most exciting parts of my research is that I get to analyse and understand huge amounts of real patient data using a variety of computational tools and being able to provide information about individual cases.
As a member of the ICONIC project team, my work contributes to the efforts of making genomic services part of everyday healthcare operations interpreting complexity and aiding clinical decision-making.
Professor Jill Pell CBE, Farr Scotland
Professor Jill Pell is Deputy Director for The Farr Institute in Scotland and Director of the Institute of Health and Wellbeing at the University of Glasgow.
I was introduced to Scottish routine data during my doctoral degree. The options were more limited then (it was early 1990’s) but even then it was fantastic to find out that there were data already collected for the whole of Scotland over a number of years so I could explore trends of time and differences in outcomes by region. Since then more data have become available and it is now possible to link data over generations of the same family, link health data with information from other sectors (such as education) and link routine data with research data; so even now decades later I am still finding new, exciting research opportunities.
I have published around a hundred papers using routine data. They cover a wide range of topics: the impact of policies such as the introduction of smokefree legislation; inequalities in health and access to healthcare; early life factors for adult diseases.
We know that the determinants and outcomes of health are wide and spread beyond the healthcare sector. Scotland is a fantastic place to do research with routine data because we can link data from different sectors, at an individual level. We are currently doing a programme of research that links health and education data. We have shown the impact of pregnancy factors on the health and educational outcomes of children (including gestation of delivery, month of conception, whether breach babies or delivered normally or by caesarean section), we have explored the impact of childhood diseases and educational outcomes and we are currently exploring the impact of mother’s taking various medication during pregnancy on the long-term health of their children. The research group includes scientists from a range of different disciplines and backgrounds who bring different perspectives and insights; so we are all learning constantly.
We are fortunate that our research using routine data has impacted in many ways; influencing governmental policies in tobacco control, being included in obstetric clinical guidelines and helping to inform service cardiology services reconfiguration.
Professor Marion Bennie, Farr Scotland
Marion is a Professor at the Strathclyde Institute of Pharmacy and Biomedical Sciences and holds a senior joint appointment with the NHS in Scotland as Chief Pharmacist, Public Health and intelligence, National Services Scotland.
Our health systems now routinely generate data as a by-product of delivering patient care. It is our public duty to ensure we use these data effectively to better understand the treatments we provide (including medicines which are the most frequently used technology in modern healthcare), both their intended and unintended effects to inform future healthcare.
As a practicing pharmacist working in the hospital sector for a significant part of my career I was faced with making prescribing decisions often based on evidence generated from traditional clinical trials which did not reflect my patient caseload. Moving into a Pharmaceutical Public Health role provided the opportunity to shape initially locally and then nationally how we can collate and learn from the use of medicines in routine clinical practice. Through our ability to record link data generated as you move through the health system, we can understand better who may benefit and also who may be harmed from particular medicines given their specific patient characteristics. Big data analysis provides the scale of data needed to identify these variables and help to populate better clinical decision support tools for clinicians and patients. My most recent move into a joint NHS/Academic position brings science and practice hopefully closer together to create new population based knowledge and improved education for our next generation of clinicians in the safe and effective use of medicines.
My research is focused on pharmacoepidemiology studies – ie the study of the use and effects of medicines in large populations – with current studies in cardiovascular, infection, rheumatology and cancer. Our national Scottish data repository includes all community prescribing which can be linked to patient events and clinical outcome and we are using this capability to estimate patient adherence, calculate patient risk and assess patient outcomes. By example, we have quantified both the temporal and cumulative impact of different types of antibiotics on the risk of acquiring a healthcare associated infection and this is now being used to populate a clinical decision support tool for clinicians to estimate this routinely when a patient presents to inform the prescribing, or not , of an antimicrobial. A further study has examined the effect of feeding back data to primary care clinicians on a regular basis for high risk medicine combinations. Over a 12 month period we found a reduction in use of these high risk combinations in practice across 4 NHS Boards. These data approaches coupled with quality improvement programme initiatives are now being adopted nationally and internationally.
The best part of by research is getting the opportunity to work across disciplines, across countries and with patients and the public on a common goal – to support the safe use of medicines and maximize their value in supporting better health for all.
Katie Wilde, Farr Scotland
Katie is Research Applications Manager and Safe Haven Data Management & Technical Lead at the University of Aberdeen.
I joined the University of Aberdeen as a Graduate Trainee back in 2007 following completion of my Masters in Mathematics (Exeter University), at that point I’d never considered working with data or even in IT but the projects that the University working on the time looked interesting and I was keen to know more. Very early on it was clear that the growth of big data would impact my work and I became a lead analyst involved in several large projects working closely with Corri Black. In 2010 I was appointed lead of the team and since then demand for data linkage has increased dramatically. Our team of 10 now help researchers with preparing their data ready for analysis, performing complex extractions as well as building bespoke applications to help collect data.
As Research Applications Manager and Safe Haven Data Management and Technical Lead I’m responsible for running the Research Application Team Service producing bespoke applications, extractions and linkages as well as managing the technical and data management elements of the Grampian Safe Haven which I help to establish in 2012.
I’m also a key member of IT Services so spend a lot of my time advising on data management and security issues both within the University and for other Universities
‘Life’ and all things Swedish (I’m a qualified active Swedish Aerobics Instructor as well teaching one of my classes at the University!) inspires me, there are so many wonders and challenges out there that I’m always challenging myself to go one step better. The world of data linkage is getting more complex as we attempt to use different data sets and all these developments and challenges keep the job interesting and exciting.
The best part of my job is being able to work with Researchers and Colleagues from all different types of background and with such a wide range of research interests and being heavily involved in scoping and designing their projects so they can achieve their aims. I have bizarre set of knowledge of different health conditions and treatments that have been gleamed over the years. But I’ve also had the chance to work with Shopping data (Kantar Dataset) and Administrative data, and even got to travel to Nigeria to set up a database out there.
Jonine Figueroa, Farr Scotland
Jonine is a Chancellor’s Fellow at the Usher Institute of Population Health Sciences and Informatics, University of Edinburgh
I have had a long standing interest in genomics and molecular biology and was inspired to work in big data science research here at the University of Edinburgh due to the increasing advances of high-throughput technologies to interrogate the molecular basis of disease.
I received my Undergraduate and PhD in Molecular Genetics because of a fascination of the molecular origins of cancer and trained as a basic biology researcher. After completing my PhD I wanted to translate my molecular studies for population health sciences. Luckily, I found a special training programme, the Cancer Prevention Post-doctoral Fellowship at the National Cancer Institute (NCI, USA), which trained scientists to perform multidisciplinary research. With coursework in epidemiology and statistics through a Masters in Public Health, I became a molecular epidemiologist and perform large population studies aimed at understanding the molecular underpinnings of breast and bladder cancers.
Numerous genetic and environmental/lifestyle factors have been associated with cancer risk and survival. How this new wealth of information can be translated into cancer prevention, clinical interventions or precision medicine remains a challenge. We are using data on genetics, imaging and electronic medical records to determine how these factors relate to the incidence and mortality of breast and bladder cancers. Through my affiliations with the Usher Institute, CRUK Edinburgh Centre and International Consortia, my research program aims to clarify the interplay of genes and the environment leading to cancer, with the goal of identifying important risk factors that are relevant to susceptible populations to inform public health and precision medicine programs.
My inspiration to become a cancer researcher began from a personal interest in wanting to make a positive impact on people’s lives. I am inspired by the quest for new knowledge and information with a hope that this will translate into actionable information that can help make people healthier.
More recently, I watched my mother go through cancer treatments, including chemotherapy, which is extremely difficult on the body, although effective. This personal experience only made me remember who I’m working for: the public and to try and use data to make individuals and their families lives better.
I find it most inspirational to work with people of different backgrounds and disciplines as they teach me new things and show me a new way to interpret and view data.
Cumulatively, through my over 160 peer-reviewed publications, I have illustrated the value of integrating genetic, environmental and lifestyle factors, and tumour marker data, to gain insights into how breast and bladder cancer develop.
Through my work in bladder cancer (an excellent model to study the interplay of genes and the environment because of the established causal role of smoking and occupational exposures to aromatic amines) I have contributed to the identification and most robust risk estimates for over a dozen genetic susceptibility loci.
Through my work in the Breast Cancer Association (BCAC) with over 60,000 cases and controls, the largest consortium of breast cancer studies worldwide, I have shown the 1p11.2 region to show distinctive associations by molecular subtypes of breast cancer. Further, my work using cross-sectional and prospective studies of benign breast tissues has shown that markers in normal breast tissues can predict subsequent breast cancer risk. Cumulatively, my work is aimed to explain the biologic mechanisms that give rise to cancer and develop better tools for risk assessment or prevention.