Collaborative Research

Bringing people, data and ideas together to push the boundaries of science, with audit and reproducibility as standard

Scientific discovery and reproducibility are the cornerstones of modern biomedical research. Ensuring that results can be verified allows new research to build on existing knowledge, enabling rapid advances in our understanding of human disease and its treatments.

With collaborative, multidisciplinary research around large, complex datasets from multiple locations, organisations, sources and disciplines increasingly becoming the norm, the ability to deliver reproducible high-quality results brings challenges around data linkage, sharing, knowledge management, the merging of ontologies, and more.

Derive, publish and share reproducible results

AnalytiXagility offers research teams a proactive, end to end approach to making complex datasets more accessible, intelligible and reproducible in a risk-free experimentation environment rich in collaborative and analytic tools.

“The collaborative analytics platform should be a huge benefit for research…” Nick McNally, Chief Operating Officer, NIHR University College London Hospitals Biomedical Research Centre

Taking all the weight of data audit and security from upload to publication, AnalytiXagility allows teams to focus on the project at hand, freeing up valuable time, and improving communication and productivity between remote groups and individuals throughout the analytic process.

The ability to track and audit all data and analytic activity, along auto-publication of analysis into research journal ready formats, makes AnalytiXagility unrivalled in its ability to promote collaborative research and makes rapid evidence-based, reproducible research a reality.

Once research objectives are complete, AnalytiXagility can also be structured to commercialise the operational delivery of research findings.

The platform of choice of collaborative, multidisciplinary research teams

AnalytiXagility is already recognised for its ability to share and publish data in a responsible manner, including the ability to archive data, documentation and code at specific points in time, and support the delivery of verifiable, evidence-based research outcomes. The platform is currently included in programmes funded by Innovate UK, SBRI, MRC, IMI, Scottish Funding Council and Horizon 2020 across multiple disease types including cystic fibrosis, multiple sclerosis, hypertension, diabetes, traumatic brain injury and cancer.

Modern NeuroICU units managing patients with traumatic brain injuries (TBI) have sophisticated bedside monitoring equipment, which means large volumes of high-frequency patient data is constantly being generated. Currently, summaries of patient data such as blood pressure and intracranial pressure are displayed on monitoring devices to aid clinical decision-making, but the analysis of the raw high-frequency data isn’t summarised and presented. This previously unseen clinical information has the potential to revolutionise the treatment of TBI patients.

AnalytiXagility services are currently being used to securely store and analyse high-frequency anonymised data collected through bedside monitoring systems from patients in the neurointensive care unit at the Queen Elizabeth University Hospital Glasgow for the CHART-ADAPT project. An app will be built to deliver results that clinicians will use at the bedside to select clinical analysis algorithms which will inform the best course of care for the patient. The project is funded by Innovate UK and is a collaboration with the University of Glasgow, NHS Greater Glasgow and Clyde’s Department of Clinical Physics and Bioengineering and Philips Healthcare.

AnalytiXagility services are currently supporting the build and validation of a single NHS platform that enables implementation of stratified medicine in multiple sclerosis (MS). The FutureMS programme studies relapsing-onset multiple sclerosis at the genetic level to help researchers predict severity in individual patients, with the goal of enabling suitable therapies to be prescribed.

Secure, private AnalytiXagility project workspaces combine routine capture and integration of clinical, laboratory, imaging, and prescription data with automated analytics and subsequent provision of clinical stratification support tools via a point of care clinical dashboard.

In addition, a multiple sclerosis biomarker discovery project that aims to develop predictive models (clinical and genomic) of personalised disease activity at diagnosis is also leveraging AnalytiXagility – including the development of an app service to capture quality of life data.

AnalytiXagility is in use by major research organisations in order to facilitate the linking and releasing data to research groups for secondary use. Using inbuilt SQL and R functionality, linked data sets have been transformed into defined XML output formats, with AnalytiXagility’s workspaces then used to support the delivery of the output datasets for specified purposes.

As an example, AnalytiXagility collated clinical data extracts (CSV/XML) from multiple source systems, anonymised the data to an approved specification and made the data available for profiling, analysis, linkage and validation by distributed research groups at the NIHR University College London Hospitals Biomedical Research Centre.

Email to discuss your collaborative research project