The document summarizes a two-day workshop on data-driven system medicine held in Cardiff, Wales. Over 15 speakers from academia, healthcare, and industry discussed applications of artificial intelligence and machine learning to medicine. Talks covered using AI for clinical trials recruitment, disease modeling, precision medicine, and more. The workshop aimed to grow the community applying computational methods to personalized healthcare.

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AI Solutions for Medicine & Healthcare in Wales
Sefat Salama1
& Barbara Szomolay
We are living in an era of fast-evolving technological innovation which impacts every aspect of our lives. In
medicine and healthcare, it is imperative to have advanced informatics infrastructure to facilitate the process
of collating, storing, sharing, integrating and analysing the huge amounts of patient data.
Medicine constantly generates massive amounts of data which exceed the human capacity to process and
utilise. Machine learning (ML) is a technology that can use this data to build algorithms that allow computer-
based systems to generate models for meaningful understanding and potential clinical use.
On June 11th
and 12th
, DELL EMC and Atos (having jointly established Wales’ first Supercomputing Centre of
Excellence) and Partners hosted the Data-driven System Medicine workshop at the Cardiff University Brain
Research Imaging Centre (CUBRIC). Partners included Supercomputing Wales, Advanced Research
Computing @ Cardiff, Systems Immunity Research Institute, Cardiff Institute of Tissue Engineering and
Research and British Society of Immunology South Wales Group. This was organised by Derek Rattansey and
Richard Chapman from DELL Technologies in collaboration with Barbara Szomolay - a lecturer from the
Systems Immunity Research Institute and Tom Connor - a consultant bioinformatician at the Pathogen
Genomics Unit of Public Health Wales. The day-and-a-half-long workshop consisted of a series of talks
delivered by speakers of wide-ranging backgrounds and expertise to a multi-disciplinary group of individuals
from academia, IT and the pharmaceutical industry. All fifteen speakers recognised ML applications and
computational methods in systems medicine as an essential platform towards personalised medicine.
Delegates were also invited to showcase their research projects in this field via posters displayed in the
workshop venue.
Talks on day one of the workshop highlighted the advances and applications of artificial intelligence (AI)
technologies and systems modelling in medicine and healthcare in Wales.
In his opening speech, Roger Whitaker - Cardiff University professor of collective intelligence and academic
director of supercomputing Wales - talked about the prospect of supercomputing-enabled scientific research
in Wales and the importance of the Supercomputing Wales programme which provides Wales with excellent
research facilities for simulation and AI.
In the first talk entitled ‘Health Sciences and a Healthier Wales’ Dr Rob Orford - Chief Scientific Adviser for
Health for the Welsh Government - detailed the Welsh government’s vision for Health and Social Care as
described in the long-term plan for health and social care ‘A Healthier Wales’, published in 2018. He pointed
out that the Welsh Government is keen to adopt a ‘whole system approach to health and social care’, which
is focussed on improving health and wellbeing, preventing illness, driving quality and more accessible health
and social care services, and on improving value and supporting the workforce. Dr Orford highlighted the
different policies directing the transition to precision medicine - through modernisation of diagnostic
services e.g. pathology, imaging, genomics and application of advanced therapeutic medicinal products. Dr
Orford emphasised that in response to rapid change in genetic and genomic technologies, the Welsh
government set out, in 2017, ‘The Genomics for Precision Medicine Strategy’, a plan aiming to ‘create a
sustainable, internationally competitive environment for genetics and genomics to improve health and
healthcare provision for the people of Wales’. He highlighted different assets available in Wales to drive
technology and innovation, such as Health Technology Wales (HTW) (http://www.healthtechnology.wales/),

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a national body working to deliver a strategic, national approach to the identification, appraisal and adoption
of new technologies into health and care services and the Life Sciences Hub (https://lshubwales.com/).
Phil Webb, Associate Director at Velindre NHS University Trust, highlighted that data is a collection of
numbers, image pixels or voxels, sound waves, heat, light, entropic energy, even language and that training
data for AI and ML is becoming easier. He discussed real applications that Velindre is doing in Wales,
including the world’s first real world assistant trained in oncology called Realtime information Technology
Towards activation (RiTTa). RiTTa is an AI chatbot for patient communication built in collaboration with IBM
Watson. This virtual assistant is designed to provide relevant information any time and place. However, she
is effectively a supervised AI and is only as good as her training. Therefore, it is necessary to set up
transparent algorithms and inform patients of the risks.
Richard Rawcliffe - Vice President and General Manager of Dell Technologies, UK Public Sector - asserted
that Dell ‘provide the most comprehensive portfolio of technology solutions – from the point of care to the
data centre to the cloud’. These technological solutions steer innovation in the healthcare and life sciences
sector particularly in issues related to drug interaction, cancer detection, illness prediction, drug discovery,
gene mutation, and sanitation. Rawcliffe explained that research across various disciplines in universities
and research institutions throughout the country is supported by Supercomputing Wales which provides
access to state-of-the-art computing facilities. The Wales Gene Park at Cardiff University, for example,
utilises these facilities to improve and advance its cutting-edge research, aiming to better understand
diagnosis and treatment of a wide range of diseases. In the area of precision medicine, Rawcliffe shed light
on some examples of Dell technologies case studies. Cambridge University, for example, operates a
biomedical cloud for real-time analysis for predictive medicine with Dell EMC HPC. Also, ever since its
partnership in 2011 with the Translational Genomics Research Institute (TGen), Dell ‘tripled its Genomic
Analysis Platform’s computational capacity and quadrupled its storage speed and capacity.
Irena Spasic, professor at the Cardiff University School of Computer Science, co-director of the Data
Innovation Research Institute and co-lead of the UK Healthcare Text Analytics Network (HealTex), explained
how Natural Language Processing (NLP) systems can be used to identify patients eligible for clinical trials
from narrative medical records. Clinical trials are an important step in discovering new treatments and are
designed to generate data on safety and efficacy. Nevertheless, 86% of trials fails to recruit the required
number of patients and 30% is the average dropout rate. Text mining is an effective and rapid approach to
search electronic health records to identify patients for trials using binary classification against certain
eligibility criteria. She also pointed out that developing a general-purpose universal NLP algorithm is
impossible since an algorithm can outperform another only if it is highly specialised to the structure of the
specific problem under consideration (No free lunch theorem). Since 85% of actionable information is buried
within the text, NLP can unlock this evidence from text.
Simon Elwood-Thompson - Chief Technology Officer of the Secure Anonymised Information Linkage (SAIL)
databank - delivered a very interesting talk entitled ‘UK Secure e-Research Platform (UKSeRP) - all data’s the
same but different’. The SAIL databank has been operating for >12 years and so far over 32 billion medical
records have been banked. It is now powered by UKSeRP, a publicly funded research cloud designed to
support the use of secondary data. It was developed by the Health Informatics Group at Swansea University
and it allows the research community to store, access, share, analyse and link to data safely and
anonymously for research purposes. UKSeRP has now users on 4 continents and is being used by UK Biobank,
UK Multiple Sclerosis Register, Dementias Platform UK, Welsh government, Cloud Infrastructure for
Microbial Genomics (CLIMB), Administrative Data Research Network (ADRN) and several other
organisations.

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Martyn Guest – professor and technical director at Supercomputing Wales – delivered a captivating talk
entitled ‘Delivering Infrastructure and Support for Research Computing’. Guest took the audience in a
journey into the lifetime of the supercomputer Hawk – their latest High-Performance Computing (HPC)
cluster, which offers a major enhancement in resource. He spoke about the procurement, installation and
operational deployment of the computing service (Hawk). He continued demonstrating the project
expansion and the growing percentage of user community and demands on the service. He stressed that the
mission of Supercomputing Wales is to provide high performance computing services and facilities for
researchers who are in need of extra computing power to solve intricate problems.
Talks on day two highlighted the importance of electronic healthcare and clinical records as an excellent
source to use reflective data to learn about medicine and to improve health care and the role of machine
learning to provide answers to several patient related questions.
Benedict Seddon – professor at the Institute of Immunity and Transplantation of University College London,
showed how mathematical modelling can describe the kinetics of constitutive renewal and de novo influx of
the murine CD4 T cell memory compartments. In a previous work with Andrew Yates (professor at Columbia
University), it was shown that CD4 T cell memory subsets are kinetically heterogeneous and that slow- and
fast-dividing subpopulations can explain the surprisingly high rates of influx of new cells necessary for the
maintenance of memory compartments. In a subsequent work they showed that environment (such as
cleanliness of animal facilities equipment) and microbiome exposure can influence establishment of memory
but that chronic turnover of CD4 T cell subsets appears insensitive to such stimuli.
Venkatesh Pilla Reddy - Associate Principal Scientist, Modelling and Simulation, DMPK, Oncology R&D,
AstraZeneca, UK spoke about the importance of pharmacokinetics/pharmacodynamics (PK/PD) modelling
for targeting brain tumours and the Positron-Emission Tomography (PET) imaging technology. He and his
research team are currently working on ‘a preclinical PK/PD model based on a mouse glioblastoma survival
model for AZD1390, a novel, brain-penetrant ATM kinase inhibitor’. Their aim is to develop a translational
PK/PD-efficacy model for AZD1390 that would enable them to evaluate the extent/duration of inhibition of
target engagement required to get optimal efficacy in GBM patients. He explained that there is a huge variety
of metabolic/distribution features of brain tumours that can be imaged using PET imaging technology and
helps in optimizing effective dose and regimen of a drug.
Piotr Orlowski - head of Computer Vision and Analysis at GSK, a British multinational pharmaceutical
company - is presently involved in applying quantitative science in medicine by modelling physiological
responses under disease conditions such as stroke and multiple sclerosis. Orlowski said with imaging we
encounter three problems: “How do you acquire an image, how is the biology inside, how do you prepare
the sample that we are looking at”. To resolve these issues, GSK have approached a national physics lab.
Orlowski and his team at GSK are working on an imaging project using magnetic resonance imaging (MRI) to
develop new technology for quantifying pH levels in the brain in order to simulate chemical changes in stroke
patients.
In his talk about ‘Data driven mechanistic modelling for targeting cancer and immune mediated
inflammatory disease’, Mark Coles - professor at Kennedy Institute of Rheumatology at Oxford University -
explained how he and his research groups at Oxford Kennedy Institute of Rheumatology ‘use interdisciplinary
approaches from single molecule imaging to multi-scale computational modelling to identify novel methods
to therapeutically target immune mediated inflammatory disease (IMID)’. He empathised that ‘combining
experimentation with data analysis and modelling can provide a platform to understand both IMID and
cancer mechanism of action and provide a unique tool to de-risking therapeutic development’. Coles said,
“without mechanism data has a limited value”. He added that the challenge for them is therapy discovery

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and development. He demonstrated how biologists think of things by using the same principle used by the
Wright Brothers to design their aeroplane and eventually get it to fly.
Ceire Costelloe - senior lecturer at Department of Primary Care and Public Health at Imperial College London
and director of Global Digital Health Unit (GDHU), delivered a timely talk on ‘Using real world data to drive
precision medicine across the UK healthcare economy’. Costelloe stressed that the driving force of their
research is to ensure best use of routinely available healthcare and clinical data. She and her research team
take the healthcare data they have accessed to produce risk prediction models of different types of diseases
or risk stratification models. They also use traditional epidemiological and statistical approaches as well as
machine learning to build these models. The GDH unit work closely with public health England to reuse these
models to inform interventions and innovation that can then be applied within healthcare system. Costelloe
said the focus of most of their research is on the issue of antimicrobial resistance which is one of the biggest
threats to global health. She stressed that the prevalence of microbial resistant infections is on the increase
in almost every country in the world.
Manasi Nandi, a Senior Lecturer in Integrative Pharmacology at King’s College London, gave an interesting
talk titled ‘Attractor reconstruction for the earlier detection of sepsis: where maths meets medicine’. Nandi’s
talk revolved mainly on early detection of cardiovascular deterioration in syndromes such as sepsis. She
focused on how modern clinical monitoring devices can be used to capture huge amounts of data namely
1,000 data points per second. However the data are underused, extracting single point averages of routine
cardiovascular outputs (systolic, diastolic pressure, ECG intervals). Nandi and her research partner,
University of Surrey mathematician Philip Aston, collaborated to devise a mathematical attractor called
‘Attractor Reconstruction’ which quantifies other morphological and variability changes from the same
waveforms, providing more sensitive information about cardiovascular changes. Dr Nandi said, “attractor
reconstruction has very wide potential application that is above and beyond recognition of patients with
sepsis. Attractor construction has the potential to be extended to predicting a range of health conditions
and could even be used to help understand how effective drugs are, or whether they carry a safety risk.
Christopher Yau - reader at Institute of Cancer and Genomic Sciences at University of Birmingham and Turing
Institute- talked about ‘Machine learning for the molecular determinants of human disease’. Yau and his
research group focus on ‘developing cutting edge computational statistical methods and tools that can be
widely used by specialists and non-specialists alike for research and clinical practice in cancer’. Yau said that
they are currently trying to model disease progression with a particular emphasis on Omics to do that and
the challenges of modelling complex evolving conditions. Yau also provided a look into the mechanism of
deep learning applied to non- predictive applications.
Sascha Ott - reader at Department of Computer Science at University of Warwick - spoke about ‘Single-cell
RNA sequencing in reproductive medicine’. His research team introduced a novel method called JACC (Julia’s
Algorithm for Cell Classification) which makes use of the fact that gene expression profiles are intrinsically
bimodal and can be broadly categorised into 3 different types. This simple idea led to developing JACC’s
algorithm which incorporates a “hierarchical” classification system. JACC’s advantage over standard single
cell sequencing workflows is its ease of use, ability to identify rare cell subpopulations and keeping the user
closer to the true nature of data. He also pointed out that rather than having several different approaches
that are hard to interpret, parsimony principle could be applied in data analysis to standardise the various
computational workflows.
Timothy Bowen – Senior Lecturer in Matrix & Molecular Biology at the Wales Kidney Research Unit (WKRU),
Cardiff University School of Medicine - spoke about ‘Systems approaches to translational nephrology’.
Bowen stressed that chronic kidney disease (CKD) is a huge problem in terms of public health. He added it is
almost as common as heart disease and that 40% of people who get diabetes end up with diabetic kidney

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disease (DKD). He spoke about the WKRU’s work, and asserted that it is the only UK biomedical research unit
that focuses on those affected by kidney disease. He said that the WKRU are currently applying systems
approaches to identify novel biomarkers and means of therapeutic intervention for CKD, DKD and acute
kidney injury, another major clinical problem.
The Data-driven System Medicine workshop at the Cardiff University CUBRIC showcased a multidisciplinary
group of experts and representatives of Academia and IT/Pharmaceutical Industry. They all recognised the
potential that AI, ML and systems modelling can unlock for personalised medicine. The workshop attracted
a large number of attendees from different disciplines and backgrounds in the area of medicine and
healthcare. We hope to further grow this community by setting up a social media platform
https://twitter.com/DatafocusSysMed that will inform the public about novel developments and activities
taking place in the computational and health communities of both Academia and Industry. We look forward
to similar sui generis events in the years coming.
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Sefat Salama, a university teacher, science communicator and journalist, writing mainly about
science, technology and environment related issues. She authored a number of books in Arabic
including her most read and cited book Nanotechnology: Tiny World and Big Future, 2009, The Ethics
and Challenges of the Era of Robots, 2014 (co-author), and Science Fiction and Developing Creativity,
2006 (Co-author). She co-authored a book chapter entitled ‘Role of Emotions in Climate Change
Communication’, 2017 in Handbook of Climate Change Communication: Theory of Climate Change,
Vol. 1- Springer.