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Precision healthcare seeks to deploy therapies that are sensitive to the particular genetic, lifestyle and environmental circumstances of each patient. Understanding how best to use these numerous features about each patient is a true mathematical challenge.

The EPSRC Centre for Mathematics of Precision Healthcare brings together Imperial’s mathematicians, engineers and computer scientists with medical scientists and clinicians to address such issues across different areas in healthcare.

Our launch will feature the following speakers: 

Professor Beth Simone Noveck, Director, GovLab  

The Jerry Hultin Global Network Professor at New York University’s Tandon School of Engineering and the Florence Rogatz Visiting Clinical Professor of Law at Yale Law School, Beth Noveck is  Director of The GovLab and its MacArthur Research Network on Opening Governance. Beth served in the White House as the first United States Deputy Chief Technology Officer and director of the White House Open Government Initiative (2009-2011). UK Prime Minister David Cameron appointed her senior advisor for Open Government,  Her most recent book is Smart Citizens, Smarter State: The Technologies of Expertise and the Future of Governing.


Precision Healthcare and Public Health Policy

In this view from the United States, Professor Beth Noveck looks at the innovative options available today to analyze newly emerging data that might help us to predict, prevent and treat disease, and gain insight into the biological, environmental, and behavioral factors that drive these diseases. In her talk, Beth will discuss some of the paradigmatic ways in which data is being put to use to improve health and health care, with a special focus on the White House Precision Medicine Initiative and the projects it supports, and on how precision medicine and the application of big data is transforming how government makes health policy and delivers services. She will argue that for precision healthcare to succeed, it has to be open, patient-driven and participatory. Hence the integration of open government policies including open data, open science, citizen science and human-centered design are as crucial to the goals of greater health and wellness as the technologies and algorithms at the heart of precision medicine.

Professor Paul Matthews, Edmond and Lily Safra Chair and Head of Brain Sciences, Imperial College London

Professor Paul Matthews brings together a wide range of clinical, academic and industry experience. Prior to his current role he was the founding Director of two internationally leading research brings together a wide range of academic and industry experience imaging centres, the University of Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB) and, later, of GlaxoSmithKline’s Clinical Imaging Centre (now a public “spin out” as Imanova, Ltd). From 2005 – 2014 he was Vice President at GlaxoSmithKline Medicines Discovery and Development.


Data Science for Precision Medicine

Advances in medicine continue, but while more medical needs are being met, new questions arise.  What is the prognosis of a disease if untreated?  Who should be treated?  Which is the best treatment?  When should it be started?  Initiation of treatments for chronic diseases often is more effective if started early.  Which risk factors define an “actionable profile” of the person who will benefit.  All medicines come with a risk of adverse events, as well as benefit.  What level of risk, symptoms or signs should drive treatment decisions and how confident can the doctor be? Precision medicine is founded on making precise diagnoses- defining the most meaningful clusters of symptoms, signs and other clinical data for defining a patient’s disease and their expected prognosis accurately and providing an evidence-based framework for predicting treatment response. Precision medicine then addresses the challenge of managing these treatments to best balance benefit and risk for the individual patient. All of these steps involve the development of predictive models involving the integration of clinical and biological data with an understanding of the impact of disease on the lives of individual patients.  The healthcare community now is generating an increasingly large and rich range of data relevant to these questions.  The challenge of transforming this data into the kinds of information needed to help doctors practice precision medicine with better analytics and visualisation tools and “smarter” decision support will be outlined in this talk.

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