Market Size of Digital Twins In Healthcare Industry
Study Period | 2019 - 2029 |
Market Size (2024) | USD 2.12 Billion |
Market Size (2029) | USD 8.58 Billion |
CAGR (2024 - 2029) | 32.30 % |
Fastest Growing Market | Asia Pacific |
Largest Market | North America |
Market Concentration | High |
Major Players*Disclaimer: Major Players sorted in no particular order |
Digital Twins In Healthcare Market Analysis
The Digital Twins In Healthcare Market size is estimated at USD 2.12 billion in 2024, and is expected to reach USD 8.58 billion by 2029, growing at a CAGR of 32.30% during the forecast period (2024-2029).
The major factors driving the market are the growing investments in digital twin technology, the increasing adoption of digital twin technology, and rising advancements in artificial intelligence utilization in healthcare.
The growing investments in digital twin technologies can lead to the launch of new solutions, which are expected to increase the accessibility of digital twin technologies in healthcare and drive the market studied over the forecast period. For instance, in October 2023, the National Institutes of Health (NIH) awarded researchers from Cleveland Clinic and Metro Health a USD 3.14 million grant to use healthcare digital twins to better understand and address health disparities. Hence, such investments by government organizations are expected to accelerate the launch of new digital twins software in the healthcare sector, further driving the market studied over the forecast period.
Similarly, in December 2023, Twin Health, a metabolic care startup, reported that it had received USD 140 million in series C funding. The company is expected to use this funding to expand its whole-body twin technology, aimed at preventing and reversing metabolic disease. Hence, such huge investments by private venture capitalist firms are also expected to drive the market studied over the forecast period.
Furthermore, the increasing utilization of AI technologies and digital solutions in the healthcare sector is also expected to drive the market studied over the forecast period. For instance, according to an article published in Digital Medicine in March 2024, the rapid growth of big data and continuous advancement in data science (DS) and artificial intelligence (AI) in the healthcare sector have the potential to significantly accelerate digital twins research and development by providing scientific expertise, essential data, and robust cyber technology infrastructure. Hence, the high growth of artificial intelligence in the healthcare sector is expected to increase the adoption of digital twin technologies in healthcare, ultimately driving the market studied over the forecast period.
Moreover, increasing strategic activities such as mergers and collaborations by key players in the market to develop novel digital twin technologies are also expected to drive the market.
For instance, in December 2023, Quantum Genomics reported that it had entered exclusive negotiations for a merger with ExactCure, a French HealthTech company that develops medical devices based on a digital twin of the patient for the development of artificial intelligence device to tailor drug administration to each individual's profile. Similarly, in June 2023, QurAlis Corporation, a clinical-stage biotechnology company developing precision medicines for amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases, and Unlearn, a technology company, entered a collaboration to accelerate and optimize QurAlis' clinical program in ALS with Unlearn's advanced generative artificial intelligence (AI) technology.
In conclusion, the growing investments in digital twin technologies, the increasing utilization of AI technologies and digital solutions in the healthcare sector, and the increasing strategic activities of key players are expected to drive the studied market over the forecast period. However, the high implementation costs of digital twin technology, coupled with data management issues, are expected to restrain market growth over the forecast period.