Our Research

The Insigneo Institute for in silico Medicine supports the development of patient centred healthcare systems in order to provide clinicians with the tools to interpret medical data in new ways. These new technologies support the work of clinicians, giving them a broader and deeper insight into the underlying physiological problems of an individual patient.

The developed technologies are based on mechanistic or phenomenological models, which can accurately predict the evolution of a condition or the effect of an intervention. Such an informed patient centred healthcare approach will drastically improve the prevention, diagnosis, treatment and monitoring of many diseases. In addition to modeller experts, the Insigneo Institute for in silico Medicine has adopted an integrative approach by including experimentalists within the Institute to be able to generate knowledge from either in vitro biological processes or from patient measurements (such as clinical imaging, wearable sensors, medical informatics) so that the data can either inform the models and be used as input data or validation tools.

The unique collaboration between academics from the University of Sheffield and clinicians and clinical researchers from the Sheffield Teaching Hospitals NHS Foundation Trust, provides an exceptional mix of insights and resources which further the advancement of in silico research here in Sheffield, with a vision to provide better healthcare for the future. Clinical translation is at the heart of Insigneo’s vision and the collaboration between clinicians and researchers enables us to achieve this goal.


The Insigneo Institute for in silico Medicine is a collaborative initiative between the University of Sheffield and Sheffield Teaching Hospitals NHS Foundation Trust.

The Institute coordinates 140 academics and clinicians from a multiplicity of disciplines who collaborate to improve health outcomes by developing subject-specific computer models able to predict ‘biomarkers’ – measures of physiology that can support a clinical decision – which are difficult or impossible to obtain directly. These advanced computer simulations can then be used directly in clinical practice to improve diagnosis and optimise treatment, offering a path to a more personalised medicine.

Insigneo includes academics from the University’s faculties of engineering, medicine and science who use the speed and accuracy of digital modelling to bring substantial benefits to both medical care and clinical trials. The Institute is at the forefront of clinical translation – ensuring that developments in the laboratory benefit patients as quickly as possible. In the future, such detailed digital models of the structure of organs and the mechanisms of diseases could be used to help diagnose conditions, understand the impact of surgical interventions and even run digital drug trials.

With the world population approaching 10 billion, in silico medicine technologies will enable a predictive, personalised, preventive and participative medicine, essential to ensuring the long-term sustainability of universal healthcare systems, and widening essential healthcare facilities to all of humanity.


Key Achievements

The Digital Patient: People are increasingly used to the idea of an avatar – a digital version of themselves – in games, on websites and in forums. Insigneo is introducing this concept to medicine to create the ‘Digital Patient’ – an individualised model of each patient, generated from their data, which can be used to identify personalised treatment options. The Digital Patient can provide risk estimates and to show how alternative lifestyles or treatments could affect a person’s health in the future. These Digital Patient technologies are primarily used by medical professionals as decision support systems in clinical settings; for example: our VirtuHeart™ technology replaces an invasive examination to identify the optimal treatment for patients with narrowing cornonary arteries; our CT2S™ technology makes it possible to predict with precision the force required for a patient’s bone to fracture – information that identifies patients at risk of injury from osteoporosis, and in need of protective treatment.

In silico Clinical Trials: To test the safety and efficacy of new biomedical products, the medical industry still primarily relies on experiments using animals, and on long, risky, very expensive clinical trials, where a new product is tested on human subjects. These methods are not completely reliable, but increase enormously the cost of innovation and the time-to-market. This makes it very difficult to develop new products for rare diseases, or for paediatric applications, where the potential for economic return hardly justifies the investment involved. Additionally, for ethical reasons, there is a growing unease around the use of animals in medical research. In silico medicine technologies can be used in combination with laboratory techniques to reduce the number of animals involved in these experiments, to refine the designs to eliminate suffering, and actually to replace animal experimentation in those cases where there is solid evidence that in silico models are equally good – or better – at predicting safety and efficacy in humans. We also use in silico technologies to “augment” human clinical trials, again with the goals of reduction, refinement, and partial replacement. Our DigiMouse™ technology can reduce by 60% the number of animals required to test bone-strengthening drugs; our in silico technologies are being used in clinical trials on Juvenile Idiopathic Arthiritis treatments; and our methods are being applied to the causal determination of bone fractures in cases of suspected child abuse.

Personal Health Forecasting: This class of technologies is only just emerging, but it represents the future of healthcare. The concept involves the use of the deluge of data provided by mobile health technologies and wearable sensors in the real-time updating of subject-specific models, to raise warnings when the subject’s circumstances are moving towards a potentially dangerous state, and to advise the subject on how best to adjust their daily life to manage chronic conditions such as diabetes, hypertension or arthrosis. The MoveMore™ ‘App’ is already capable of remotely monitoring the daily activity levels of very large numbers of subjects in this way.


The future of Diagnosis and Treatment

In silico methods of diagnosis and treatment are revolutionary because they offer a way to understand the processes and interactions within the body as a whole – rather than in many, disparate parts. It is now possible to create sophisticated, personalised computer models that can closely replicate the physiology and anatomy of individual patients. These models can be used to predict the outcomes of alternative treatments, and optimise the selection of drugs and devices for each patient. The opportunities for this technology to improve the diagnosis, treatment, and outcomes for people with complex conditions – including Parkinson’s disease, cancer and heart disease – are limitless. The University of Sheffield and its global partners are at the forefront of these society-changing developments.

To meet the needs of this accelerating trend, from September 2017 Insigneo will offer a new Masters Degree in Computational Medicine, designed to train the new specialists in in silico medicine who will go on to be employed by biomedical companies, regulatory agencies, developers of software for healthcare, research hospitals, and the newly-emerging in silico medical services industry. This training mechanism will link naturally to Insigneo’s PhD programme on in silico medicine, and we expect that entry to this Masters programme will be intensely competitive.


We will continue to update these pages with the latest developments, so please check back or sign up to the Insigneo newsletter to read about the latest developments here at the Institute.