By providing a computer model of each individual patient, digital twins are becoming important components of precision medicine
Precision medicine provides hospitals and healthcare providers with the ability to provide medical treatments that are tailored for a specific individual based on their unique physical characteristics. The futuristic trend of precision medicine is allowing clinicians the opportunity to shift clinical care away from a one-size-fits-all approach to a more personalized paradigm.
A concept in precision medicine that has recently become recognized as having important applications is the ability to create digital twins. The idea of digital twins has existed for several decades but has been almost exclusively used in the context of mechanical devices, until recently.
What Is a Digital Twin in Precision Medicine?
A digital twin is essentially a digital representation of a physical object, often produced through a combination of computer modeling and sensors on or in the object that provide data. The digital “twin” can be subjected to experimental conditions without having to conduct experiments on the physical object. The digital twin can also be monitored to predict outcomes such as components wearing out or unexpected strain being caused by the conditions it is exposed to.
In the medical sense, a digital twin could provide hospitals and providers with a computer model of each individual patient. Instead of providing a patient with a medication to treat a complaint, then evaluating the patient’s response, providers could “administer” a hundred different medications to a hundred digital twins and evaluate the response of each one. These “in silico” trials would allow providers to predict how an individual will respond prior to actually administering a medication or treatment.
James Glazier, PhD, a professor of intelligent systems engineering at the Indiana University Luddy School of Informatics, Computing, and Engineering authored a paper discussing digital twins. The research was published in the prestigious journal Science and in the paper, Glazier argues that the use of digital twins in medicine could be used to better understand how to provide individualized treatment for COVID-19.
The Work of Digital Twins in Personalized Medicine and Health Outcomes
In an interview discussing this paper, Glazier pointed out the benefits that utilizing the concept of digital twins in medicine has to offer. “Digital twins combine a computer model that predicts how the state of a system will evolve with real-time measurements of individuals,” Glazier said. “Medicine, at the moment, is largely reactive: You go to the doctor when you’re sick, or after there’s a major problem. Ideally, what we’d like to be able to do is predict when there’s going to be a problem and make small interventions to prevent the problem from ever becoming serious.”
According to Glazier, using digital twins to evaluate the potential responses of individuals fills an unmet need in medicine. “Medicine lacks a key component of scientific practice because you can’t perform controlled experiments at the level of individuals,” Glazier explained. “Digital twins solve this problem by allowing virtual experiments and controls in which we evaluate what will happen to a specific individual given a specific treatment.”
While the idea of digital twins has many potential applications, Glazier believes a more immediate benefit could be applying it to the treatment of COVID-19 patients. “The COVID-19 pandemic has revealed that we don’t understand the immune system well enough at the individual level to be able to design optimal treatments,” Glazier said. “If we can build models that are able to explore how these immune responses work, we can potentially design better vaccination strategies.”
“COVID-19 is not the first pandemic, and it will not be the last,” Glazier expanded. “The hope is that the work we do on digital twins for infection and immune response will give us most of the pieces needed to rapidly develop detailed predictive models for diagnosis, prognosis and treatment when we face the next pandemic after COVID-19.”
Examples of Digital Twins to Support Clinical Decision Making and Research
The use of digital twins in medicine is not just theoretical. Philips has recently developed a digital heart that can be used to improve treatments and conduct experiments without requiring experimentation on a live subject. Hewlett Packard Enterprise is developing Blue Brain Project, a digital brain and Siemens Healthineers is developing a digital twin model to support clinical decision making and research.
Organizing and practically using the large amount of individualized data needed to implement precision medicine into clinical practice is a potential barrier that hospitals, health systems, and physicians face. The use of digital twins and the growing technology supporting this approach will provide healthcare providers with the ability to implement precision medicine into their clinical care paradigms.