By Naveesha Karunanayaka
The idea of a digital twin holds different meanings across many sectors. Within Healthcare, creating a ‘digital twin’ involved curating a genetic profile of an individual which can then be used for medical purposes. This digital ‘self’ of an individual can then be used for drug and therapy testing – with such personalised tests carried out in bulk prior to use on the individual. This approach allows clinicians to determine which drugs and therapies are likely to deliver the best outcome to the individual.
The healthcare system is yet to leverage the advantages of using data analysis systems and AI as a diagnosis and prognosis tool. The use of digital twins will mean more personalised healthcare – rather than treatment based on the ‘average person’ it will be for the ‘actual person’.1
Creating the digital twin involves significant data collection, using sensors, in conjunction with modelling to ‘build a bridge between the physical and digital world’.2 Then, a computer program can run simulations on the individual’s genetic information based on real world data to detect the body’s performance under specific scenarios. This allows the digital twin to detect issues that may otherwise be missed, or before diseases present symptoms – and so has life-saving potential.
This is a relatively new idea that is being explored for applications in the medical sector. However, progress has been fast – for example, the 3D experience firm Dassault Systems have released the world’s first realistic computer model of the human heart called ‘The Living Heart’. This software can turn a 2D image of a heart into a full dimensional model of the individual’s heart.2 Modelling body systems is a great achievement – but to create a digitalised system to detect and solve medical problems, mapping different diseases digitally is essential. Researchers at Linkoping University Hospital completed a study which successfully used high-resolution data from individual patients to create advanced computer models of 13 autoimmune, metabolic, and malignant conditions.3 This indicates that the basis for the digital twin technology can be implemented as it is demonstrated that diseases can be replicated digitally, therefore, can be used for the digital twin. These digital twins can be replicated an unlimited number of times and treated with various drugs to discover the most effective.
Linkoping University is working as part of an EU plan to use digital twins for cancer patients, and this is hoped to be in clinical trials within a few years. This is an indication of how valuable and in-demand digital twin technology will continue to become. This initiative will involve the digital twins being regularly updated and tested for signs of any changes in health.
There are different ethical implications to this technology. On one hand, the use of a digital twin could vastly reduce the need for animal testing during clinical trials. Further, potential side effects of drugs/therapies can be detected early, and severe negative reactions to treatments can be avoided by prior testing on the digital twin. However, it can also be argued that the creation of a digital twin with personal data is a breach of privacy – especially if this data could be shared with those who aren’t authorised medical professionals. Other critiques of digital twin usage focus on the risks of using genetic information, which can later become a roadblock to e.g. obtaining certain insurance policies or jobs due to health-based discrimination.4 However, there are some potential avenues to alleviating these concerns – for example, ensuring anonymity of data where necessary and exploring the possibility of patients owning their own data.
Experts believe digital twins hold vast potential, not only in emergency medical situations, but also in areas such as physiotherapy. Digital twins can inform on muscle development, for example, changes in spine cells and bone movement in scoliosis with physical therapy can be predicted and best possible exercises to achieve this could be used.2 Moreover, with computational advances and infrastructure improvements, the digital twin could be used as a mobile device allowing it to be transported with the patient anywhere. This could be possible especially with recent developments in 5G.
There is still a need for effective public communication around digital twins, and key to achieving this is the use of standard, accessible language.5 The use of this technology may revolutionise patient care and satisfaction, developing a personalised healthcare system that delivers more effective treatment to patients. However, it is hard to predict public response to this technology and whether it will be welcomed. There is likely to be some opposition, given the ethical concerns of digital twin usage, but it is the hope that people will accept it for its many benefits in healthcare settings.
 Bertalan Mesko (2020), Digital Twins and the Promise of Personalized Medicine. Available from: https://medicalfuturist.com/digital-twin-and-the-promise-of-personalized-medicine/
[Accessed 22nd June 2021]
 Tolga Erol, Arif Furkan Mendi, Dilara Dogan (2020). The Digital Twin Revolution in Healthcare. In: 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), October 2020, Turkey [Online]. Turkey: ISMSIT, pp. 1-3. [Accessed 22nd June 2021]. http://dx.doi.org/10.1109/ISMSIT50672.2020.9255249
 Lindsay James (2021), ‘Digital twins will revolutionise healthcare’. E&T, 16(2): 50-53.
 Godard, B., Raeburn, S., Pembrey, M. et al. Genetic information and testing in insurance and employment: technical, social and ethical issues. European Journal of Human Genetics. 11,S123–S142 (2003). https://doi.org/10.1038/sj.ejhg.5201117
 Sonia Duarte (2019). Digital twins: needs, challenges and understanding.
Available from: https://theodi.org/article/digital-twins-user-research/ [Accessed 20th June 2021]