Beyond the hype, where might simulation and digital twin technology deliver value for pharma?

There is considerable excitement about the potential for simulation and digital twin technology to drive the personalised health agenda through better diagnosis of disease, faster and cheaper clinical trials and better training and engagement with physicians. Overcoming the considerable technical, ethical and regulatory challenges will not, however, be easy, and so how can pharma benefit now and how should it prepare for the future?

To help you sift market potential from scientific ambition we interviewed, in The Future of Personalised Medicine: The Role of Simulation and Digital Twins, knowledgeable experts to give you a clear perspective of what is reality now and future development pathways this rapidly emerging field could take.

Experts explore simulation and digital twin technology

• Which disease areas will specifically benefit from simulation and digital twins in terms of diagnosis?
• How can pharma leverage the diagnostic opportunities offered by simulation and digital twins?
• How will simulation and digital twins of human body functions lead to more accurate and efficient clinical development?
• How will simulation and digital twins influence the personalisation of treatments?
• What patient data and medical records will be of value to pharma in developing simulations and digital twins and what are the data security and privacy implications of accessing such data?
• How can pharma work with technology and software companies to develop effective simulation and digital twin solutions?

What are simulation and digital twins?

The concepts of simulation and digital twins refer to the creation of a digital replica of a physical asset. Various technological principles and advancements, including 3D simulation, 4G/5G, big data, cloud computing and artificial intelligence, are brought together to create a digital equivalent (a simulation or a digital twin) to the virtual world of a physical entity. While simulation and digital twins are interrelated concepts in computer engineering, they are distinct from each other. Essentially, simulation relates to knowing what could happen, while digital twins relate to what is happening in real-time as well as what could happen.

What our experts say…

"The use of simulation and digital twins in clinical trial and testing brings financial benefits to pharma in that it can speed up development of a drug or device, resulting in cost savings. To take an example from the medical device field, Medtronic received approval for their MRI-compatible pacemaker through a combination of animal data and simulation results from a well-established in silico model. This enabled the company to demonstrate the device's efficacy and safety without having to test on real patients in a full clinical trial, which would have taken two more years. As a result, thousands of patients were able to receive the device earlier whilst Medtronic generated additional revenue from not having to spend money on clinical trials."
Liesbet Geris

""Simulation and digital twins simply makes personalisation possible. To a certain extent, treatment is already personalised by your own doctor in that he knows you quite well so he will have some idea of what kind of treatment you need. However, he might not know all the details of your current situation and offer treatment that is quite generic. In contrast, in terms of simulation and digital twins, I can see healthcare wearables being used to feed detailed information about your body into a digital twin or personal digital avatar of yourself. Your digital twin can then be used to test different treatments and see how they affect it. Moreover, simulation and digital twins can be used to tailor specific doses for different patients. This is important because you cannot give the same dose for an adult who weighs 200 pounds to a very thin lady who only weighs 50 kilograms or less."
Thierry Marchal

Case Studies

• EPFL's Blue Brain Project: Understanding the role of neurons in brain disease
• The use of digital evidence to gain approval: the case of Medtronic's MRI pacemaker
• Facilitating personalised therapies: The case of Empa's digital skin twin
• The FDA's big push on computational regulatory science
• The VPH Institute: developing a roadmap for the digital patient
• The Living Heart Project: Collaboration for the advancement of cardiovascular research
• Medtronic's MiniMed® 670G system: one step closer to a fully automated artificial pancreas system

What to expect

• A detailed report which explores the emerging fields of simulation and digital twin technology and the transformational impact they could have on personalised medicine through improved diagnosis, clinical trials, physician engagement
• An examination of 8 key issues which pharma and technology developers need to understand and respond to
• 15 targeted questions put to experts
• Their perceptive responses that provided 28 insights supported by 45 directly quoted comments

Expert contributors

Contributors to this report were carefully selected and screened against the following criteria:

• A pharma professional or consultant in the field of simulation, digital twins, digital modelling of disease, artificial intelligence or computer engineering.
• Have between five to 20 years' experience in fields relating to artificial intelligence for personalised medicine.
• Responsibility for simulation or modelling of disease, treatment pathways or patient response.
• Direct experience of precision medicine strategies and exploring digital modelling and simulation of human cells, tissues or organs, either as part of a committee or as the lead decision-maker, in the last 12 months.

Contributors to the report:

• Geoff Chase is a Distinguished Professor at the University of Canterbury and an Adjunct Professor of Medicine at the University of Otago, both in New Zealand. In these positions, he leads research in clinical applications of bioengineering in intensive care and diabetes. Before starting his career in academia, Chase had a wide range of engineering experience spanning a period of over 10 years. Today, his research work is in model-based therapeutics, which combines engineering, clinical medicine and physiology, with a primary clinical focus on intensive and acute care medicine. With several awards, recognitions and patents to his name, Chase is a specialist in control systems, physiological systems dynamics and dynamic and systems modelling.
• Liesbet Geris is a professor in Biomechanics and Computational Tissue Engineering at the University of Liège and KU Leuven in Belgium. Her research focuses on the multi-scale and multi-physics modelling of biological processes. Together with her team and their clinical collaborators, she uses these models to investigate the aetiology of non-healing fractures, design in silico potential cell-based treatment strategies and optimise manufacturing processes of these tissue engineering constructs. Geris is also the scientific coordinator of a musculoskeletal tissue engineering platform with over 50 researchers and the current executive director of the Virtual Physiological Human Institute, where she advocates the use of in silico modelling in healthcare through liaising with the clinical community, the European Commission and Parliament, regulatory agencies (EMA, FDA) and various other stakeholders.
• Thierry Marchal is the Global Industry Director of Healthcare at ANSYS, a computer software company that develops engineering simulation software for various industries. In this position, which he has held for almost 13 years, Marchal heads Computer Aided Engineering (CAE) for the emerging healthcare, construction and consumer products industries. This involves helping them to adopt and deploy engineering simulation for accelerating their product development process. He is also a founding member and current secretary general of Avicenna Alliance, an association of academia and healthcare organisations that intend to make in silico medicine a standard practice in healthcare.
• Lorena Puica is the founder and CEO of iamYiam Limited and the president of iamYiam Foundation. The multiple award-winning iamYiam platform is a science-backed and AI-powered preventive and personalised health platform that empowers people to personally take charge of their health with the help of Syd, their personal, daily and lifelong AI partner. Puica is also a guest lecturer at the University of Oxford and Cornell University, as well as a speaker on several international platforms. She was named by Deep Knowledge Analytics as one of the Top 30 women in AI for drug discovery and advanced healthcare. Her specialities include AI, strategy, business development and health and wellness.