Market for digital twins in healthcare expected to grow 67 per cent by 2028

The global market for digital twins applied to healthcare is expected to reach an estimated value of US$21.1 billion by 2028, which represents a compound annual growth rate of 67.0 per cent in the period between 2023 and 2028, according to research by Markets and Markets. However, the growing demand for digital twin technology that helps enrich various healthcare applications is still likely to face barriers such as a lack of technical expertise and data management issues.

In recent years, there has been growing interest in digital twin technology, which involves creating virtual replicas of physical objects, Internet of Things (IoT) sensors, systems or processes. In the health area specifically, the research highlights some emblematic initiatives. One of them, Digi Twins, launched in 2018, has been developing, among other things, personalised health and prevention strategies based on the idea of ‘virtual patients. Companies such as Twin Health and Unlearn have received investment to develop digital twin technologies aimed at improving healthcare and also driving market growth in the coming years.

Obstacles and opportunities

As with other areas that process personal data, digital twins applied to healthcare also face challenges associated with privacy, information quality and implementation costs, the Markets and Markets study points out. In the case of digital twins, data is generally collected from various sources, including electronic medical records, wearables and other medical equipment, and integrated into digital twin systems.

Without high quality data, the accuracy and reliability of digital twins can be compromised and can even affect patient care and treatment results.Without high quality data, the accuracy and reliability of digital twins can be compromised and can even affect patient care and treatment results.

Another critical concern has to do with data privacy. The research recommends that in order to avoid problems, robust data governance structures and security protocols need to be adopted. In addition, implementing digital twin technologies can be costly, involving the acquisition of hardware, software and data storage systems. The expectation is that costs will decrease over time as the technology matures and becomes more widely adopted.

Another challenge is the scarcity of technical expertise. Implementing and maintaining digital twin technologies in healthcare requires specialised skills and knowledge in sectors such as data science, software engineering and machine learning, which are not always available to the extent required. In addition, adapting to emerging technologies is almost always challenging, especially in the healthcare field, with large repositories of unstructured data. Without enough qualified professionals, healthcare organisations can face delays, higher costs and limited access to the benefits of this technology. And to overcome these challenges, they will need to invest in qualification and training programmes and establish collaboration initiatives with academic institutions, the Markets and Markets survey highlights.

Of course, there are also many opportunities in this market. Digital twins generate large volumes of data that can be analysed in time to provide insights into patient health, resource utilisation and operational efficiency in hospitals, national health systems and other environments. As a result, healthcare providers can programme better informed treatments, allocate resources more efficiently and make more effective decisions. All of this will generate benefits on a personal level for patients and working conditions for healthcare professionals, as well as more generally for companies, governments and society.