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Digital Twin technology may save lives and solve the biggest challenges facing humanity


With the speed of AI and technology advancing at an ever-increasing rate, we are constantly asking, ‘What is the next frontier of technology, and how will it advance mankind?’ An answer: the creation of a digital twin for each and every one of us.

What is a digital twin? Simply stated a digital twin is a virtual or digital replica of a living organism, or a part of that organism like a heart or lungs. A digital twin is created from data points such as imaging records, in-person measurements, lab results and genetics. All of that data is then used to map out an exact digital replica of an individual.

Why do we need this? To possibly prevent over 250,000 deaths a year. That’s how many people die each year due to medical mistakes, according to Johns Hopkins.

The human digital twin

The concept itself is simple to understand, a virtual representation of a physical object through its lifecycle. The technology and its uses in healthcare however are potentially endless and revolutionary.

In a recent conversation with Dr. Marko Grobelnik, AI researcher and Digital Champion Slovenia as well as chief technical officer, International Research Center on AI at the Jožef Stefan Institute, he made a profound point on why Digital Twin Technology will be a crucial step in the evolution of healthcare. He noted that healthcare institutions are complex systems with a lot of interleaved processes which are providing results only if they are properly synchronized. Each of the processes carries a certain amount of uncertainty, he said, which can be either harmful or it can cause an unwanted domino-effect with possibly disastrous consequences. To navigate such a complex system through a series of known and unknown obstacles, the digital twin technology can help, since it operates with the breadth to observe and the speed to react which humans don’t have.

His assessment is spot on.

With full development of digital twins, we could speed up work at an exponential rate, saving time, but most importantly lives.

Practical use of a digital twin

Once a digital twin is created, its use in healthcare is to be the test subject for treatments of diseases or injuries before use on the individual or persons at large. Then with enough biological data, we can drive more precise and effective medical interventions that are tailored to the individual patient. This is becoming more and more possible due to the rapid progress in computing power and the ability to crunch extremely large amounts of data.

With enough knowledge of the human genome, an individualized genome sequencing could be created for an individual who might have cancerous tumors. The behavior and response of these tumors could be analyzed and studied digitally by an AI system and an individualized biological agent could then be created to fight the tumors. These agents offer three advantages of traditional treatment:

  • They’re built specifically for the individual and their unique variant of cancer, so the chances of success are materially improved.
  • They’re built from the patient’s DNA, therefore the body will not reject them.
  • The agents will not cause the harsh side effects of chemotherapy or radiation.

Finally, these types of agents should be able to either be injected or maybe even ingested in the form of a pill.

Because digital twins are digital models they can be analyzed to provide the patient with ways to prevent future illness, provide direction for preventive maintenance and even offer performance enhancements. Not simply a cure, but a guide to health and personal maintenance to avoid and prevent future illness.

The reason it is not our current reality is due in large part to extreme complexity of the human genome and the seemingly countless ways it could react to illnesses and medicine. Despite this current roadblock there are projects active that have potential.

For starters, the UK Government initiated the 100,000-genome project to sequence whole genomes from National Health Service’s 85,000 patients. The project is focusing on common types of cancer, and infectious diseases. In the USA studies such as the Human Longevity Inc. and the Mayo Clinic Centre for Individualized Medicine gather genomic information on large numbers of individuals providing more data for scientists and technologists to leverage.

Current practical use cases

Though the full digital twin we have been describing thus far is still in the future, there are current practical use cases that prove we are well on our way, the first of which is patient monitoring. Wearables are something many of us live with today. Whether it be a fitbit or other health and fitness trackers, as a society we have grown accustomed to and accepted this technology as omnipresent. This same tech can be used to feed real-time data to a digital twin in the cloud that will develop models that detect symptoms of illness at early stages.

Second is surgery simulation and risk assessment. One real world example is France-based startup Sim&Cure that has developed a patient-based digital twin for treating aneurysms. Sim&Cure uses simulations and digital twins to help neurosurgeons maximize patient safety as they undergo treatment. It’s not just practice on a simulated patient, it is practice on the exact patient.

Third is diagnosis and treatment decision support. Through data from different health sources like imaging records, in-person measurements, labs and genetics, healthcare professionals will have a complete and real time picture of a patient and their previous and current health status. The digital twin will then simulate the health status of the patient and AI technology will fill in any gaps with the most accurate, relevant, and scientifically solid information available.

An example is the startup, Babylon Health that developed the Healthcheck app. After users respond to a questionnaire about lifestyle and family history, the AI-powered app creates a digital twin giving users insights about their current health and risk factors for future conditions along with practical recommendations for staying healthy.

Fourth is not the patient, but the hospital itself. An NHS trust in Manchester, UK, has collaborated on a partnership with Hitachi Ltd. to digitize its processes and optimize its staff resources. It will also establish a ‘digital twin’ of hospital operations for clinicians and managers to model potential changes in the organization of care. Thus, they are aiming to make the entire hospital work smarter and place caregivers in better positions to provide the best possible care.

The future of digital twin healthcare technology

The technology to create digital twins in healthcare exists. The challenge is for the healthcare industry to start testing and applying this technology to specific problems.

A road map? Scientists at Linköping University in Sweden created digital twins of mice with rheumatoid arthritis by sequencing their RNA into digital models. Computer simulations were then done to determine which drugs would be most effective at treating individual mice.

We need to wait no longer and scale this technology to humans.

If implemented successfully we can say goodbye forever to human clinical trials. We can test all possible vaccines and treatments on digital twins, save lives faster and never test potentially dangerous treatments on humans again. This is the future digital twin technology can create. And this is the future we need.

Tsvi Gal, Head of Enterprise Technology at Memorial Sloan Kettering Cancer Center and a former managing director at Morgan Stanley, contributed to this op-ed.

Mark Minevich is president of Going Global Ventures. He is a global digital cognitive strategist and artificial intelligence expert and venture capitalist. He also serves as executive chair, Digital Pioneers Network and as chief digital strategist at the International Research Centre for AI, under the auspices of UNESCO. He is a member of the B20 digital economy taskforce in the G20 Presidency, a member of the World Economic Forum Council on AI for Humanity, a senior fellow of U.S. Council on Competitiveness, an advisor at Boston Consulting Group and digital fellow at IPsoft/Amelia. Follow him on Twitter @MMinevich.

Tags Artificial intelligence Augmented reality Digital health Digital twin Emerging technologies Healthcare Medical error

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