Are Digital Twins Capable of Growing People’s Body Parts?

By Rebecca Lam

17 December 2018

As the popularity of digital twins is steadily increasing, experts are beginning to consider the benefits and complexities of utilizing digital twins for the human body. As healthcare budgets are consistently under increasing pressure, AI tools such as the digital heart twin could make financial savings in the millions through predicting outcomes and avoiding unnecessary surgery. Could we begin making digital twins of the human body to plant and predict a patient’s health outcomes? Digital twins were developed from the Internet of Things, as a way to devise highly capable simulation models from physical objects. The virtual technology has been integrated into industries such as oil & gas, energy, and manufacturing, to predict how objects and processes within these industries would behave in the real world. The concept of digital twins is entering medicine to simulate the human body through medicine and virtual, customizable models of organs. Simulated organs have the ability to change how medicine works, in a hyper-personal and less invasive way.

 

enhancing the human body using digital twin

 

Using The Digital Twin Platform To Analyze Patient’s Body Health

The ‘virtual self’ of a patient is similar to a digital twin of a piece of machinery. Digital twins could potentially provide methods of analyzing healthcare practices, such as preventative care and the monitoring of disease and wellness. Similar to a digital twin of an oil rig, the digital twin of a patient can track areas of performance optimization, enhancement, functionality, and derangement. Although the opportunity is present, from a practical aspect, it would be difficult to apply. The complexity of human organisms and the difficult mechanism of systems within the human body make building a human digital twin a convoluted process.

 

Restoring Human Body Parts and Fighting Dangerous Illnesses Using Digital Twin

According to Slate.com, Kirby Vosburgh from Harvard University and the Center for Integration of Medicine and Innovative Technology states, ‘There are basically two camps of experts on this general topic’, referring to those who suggest that big data will take over medical knowledge and those who believe that digital knowledge cannot expand to represent the variety of conditions and qualities of every individual. Despite this, the relationship between digital twins and the human body remains hopeful. Recent cases have shown digital twins used to pick the correct medication to treat tumors. Customized medication has been another growing area, to anticipate infections and enhance human performance. Digital twin models will gather a consistent amount of data throughout a human’s lifetime, evaluating these models in whole populations provides opportunities to detect patterns and trends of well-being versus illness.

 

digitizing human DNA using virtual twin technology

 

The Overall Challenges of Digital Twin Regarding Human Health and Wellbeing

The integration of digital twins within the human body will be challenging – but if it succeeds, it could change healthcare immensely. The power of predictive insight into healthcare will change how humans function. Digital twins will allow the power to push past the limitations of medicine, and utilize data as a tool to truly understand the human body. Challenge Advisory is delighted to announce the launch of our Digital Twin Technology Investment Workshop taking place in the financial heartland of London, in June 2019. The two-day workshop will be designed to support the growth and adoption of digital twin technology by discussing its benefits and latest innovations along with the investment still required.  Find out more information and purchase limited early-bird tickets here.

 

Discover all the hidden benefits of this technology by being introduced to the biggest business players in the world and take part in our private mastermind event where you can connect with the biggest leading forces across all industries that successfully utilize virtual twin – join here.

Generic placeholder image
Rebecca Lam

Related Articles