Harnoor Baidwan
2 posts
Apr 10, 2025
2:15 AM
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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.
The global digital twins in healthcare market size is estimated to grow from $1.9 billion in 2024 to $33.4 billion in 2035, growing at a CAGR of 30% during the forecast period, till 2035.
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.
Currently, over 90 digital twins are either commercially available in the market or are under development for various healthcare related applications including diagnosis, health monitoring and surgical planning. The majority of this domain is constituted of small players established during the period 2016-2020; in fact, this number constitutes 30% of the total companies. This is followed by companies (20%) established during the period 1950-2000. Examples of companies that were established recently include (arranged in reverse chronological order of their year of establishment, established since 2020) Basetwo (2022), Edith (2022), AI Body (2020), EmbodyBio (2020), Mindback AI (2020), Predictiv (2020) and Twinsight (2020).
Presently, the domain is dominated by the presence of small companies (30%), followed by mid-sized (25%) and very large (25%) players. Examples of small players engaged in this market space include (arranged in alphabetical order, based in North America and established post-2015), Altis Labs, Basetwo, MAI, Navv Track, Verto and VictoryXR.
Most of the digital twins (42%) are process twins. This can be attributed to their ability to optimize organization efficiency, reduce downtime and minimize the risks associated with their assets. This is followed by whole body twins (35%) and body parts twin (32%). Notable examples of whole-body digital twins include (in alphabetical order, developed by large and very large players based in Europe), Bodylogical, Emma Twin, Healthcheck and an unnamed technology by PwC.
Currently, the majority (88%) of digital twins are currently commercially available, followed by products / services that are currently under development. Notable examples of the digital twins that are currently available in the market, includes (in alphabetical order, developed by mid-sized companies based in North America), BreathEasy, Gemini Digital Twins, HighIQ Smart Hospital Solutions, TwinRCTs II, TwinRCTs, Whole Body Digital Twin, and other unnamed technologies by Faststream Technologies, Gramener, Leucine and Twin Health.
Since the emergence of digital twins, they have found their use in various healthcare applications. Such twins enable personalized medicine by creating virtual models of individual patients, aiding in treatment planning, predicting outcomes, monitoring patients in real-time and allowing for proactive interventions. Furthermore, they facilitate medical education and training by providing realistic scenarios for students and professionals to learn from, improving overall healthcare practices. Notable examples of companies that offer digital twins for asset / process management applications (arranged in alphabetical order, based in North America) include, Basetwo, Navv Track, Neo PLM, Verto and VictoryXR. This is followed by digital twins intended for personalized treatment (31) and health monitoring (27).
Research Methodology
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Last Edited by Harnoor Baidwan on Apr 10, 2025 2:37 AM
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