Given the potential of digital twins to replicate the physical world in a digital layout, while gathering constant inputs from the real-world, such products have generated significant interest within the healthcare domain

The global digital twins in healthcare market size is estimated to grow from USD 1.9 billion in 2024 to reach USD 2.5 billion in 2025 and USD 33.4 billion by 2035, representing a higher CAGR of 29.6% during the forecast period.

A digital twin is, in essence, a virtual model that employs the use of real-world data in order to create simulations that can be used to predict how a system or process will perform. With the improvement in technologies such as machine learning and factors such as big data, these programs have garnered immense interest in the healthcare domain to drive innovation and improve performance. Digital twins can be applied for various healthcare benefits including risk prediction / reduction, reduced labor costs, improved patient care and automated decision-making process.

Using technologies such as IoT, Extended Reality (XR), Cloud, and Artificial Intelligence (AI), digital twins can create visual representation, capture, store, analyze data and provide valuable insights for several healthcare applications. Such insights aid improved decision making and optimized productivity. Additionally, digital twins can also be used to perform analysis on different what-if scenarios and help facilities to maximize their operational efficiency. The healthcare industry has started to adopt digital twins to improve personalized medicine and performance of healthcare organizations. Although simulations have been around in the healthcare domain for past decade, the current digital twins offer a variety of applications that general simulations are unable to provide.

Prominent types of digital twins used in the healthcare domain have been mentioned below:

• System Twin: System twin refers to a digital twin of several product twins working in conjugation to represent a system. Such digital twins provide insights into how different assets in a facility interact / relate to one another to improve productivity and efficiency of a set-up. A digital twin of the system brings visibility to complex interconnections and interdependencies of products and processes.
• Process Twin: Process twin refers to a digital twin that encompasses an entire process of a facility; these processes may include manufacturing of medical devices or pharmaceutical drugs. Such digital twins represent the integration of individual system twins that together create a production facility and provide insights into the collaboration of all the units employed in a facility. It is worth mentioning that a process twin is only efficient when its individual components are being efficiently monitored and controlled as well.
• Human Digital Twin: Human digital twin of a human being is a replica or a counterpart in cyberspace. Such digital twins are based on a virtual model developed using characteristic data of an individual that includes age, weight, sex, relatives of the person, past health concerns and more. A key feature of such digital twins is dynamic bidirectional mapping, unlike simulations that only offer a digital snapshot of a real- world entity, human digital twins offer a two-way dynamic flow of information between the physical and real-world entity.

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