YASH BAJAJ, B.TECH INTEGRATED, MPSTME, NMIMS
Under guidance of Seema Shah
Healthcare is rapidly embracing digital twin technology. The goal of this trend is to deliver data-driven personalized medicine.
Digital twins are built on computer-based, or in silico, models that are fed individual and population data.
Researchers are aided by these digital representations of human physiology in their studies of disease, new drugs and devices. Healthcare industry
leaders and FDA authorities suggest that digital twins help to accelerate medical innovation and regulatory approval.
In the future, these tools may even help doctors accurately optimize the performance of patient-specific treatment plans.
In short, digital twins can help healthcare providers bring lifesaving innovations to market faster, at reduced costs and with increased patient safety.
Healthcare is now also starting to capitalize on this powerful digital tool.
In healthcare, a digital twin can be defined as a life-long, rich data record of a person combined with AI-powered models that can ‘interrogate’ the datato provide answers to a range of clinical questions.
A digital twin can be used to predict the outcome of specific procedures. It can provide assistance in determining the right therapy option for a specific patient. Or, if behavioral data and social determinants are also integrated, digital twins can help to better manage chronic diseases and population health.
Digital Twins of complete human beings are still a futuristic dream now.However, some headway has been made with for example Dassault’s commercially released “Living Heart” — the first realistic model of a human organ that accounts for electricity, mechanics, and blood flow in the heart. The software can turn a 2D scan from an individual human into a personalized full-dimensional model of his or her heart.
The user can manipulate it — stick in pacemakers, reverse its chambers, cut any cross-section, and run hypotheticals. The Digital Twin has been pieced together from information shared by numerous research groups. To make a Digital Twin of a whole human body, all organs need to be modelled and
integrated. Since many organs are more complex than the heart (e.g. the brain) this may still take a lot of work to achieve.
Digital twin technology in healthcare aims to improve pre-operative planning, reduce medical risks, and generate more accurate therapy for patients. Digital twin technology can also be used in hospitals to simulate work flow processes to identify inefficiencies and make improvements such as reducing patient wait time and developing strategies for efficient use of diagnostic testing equipment.
we can hope to create digital twins of organs like the heart, or even of single cells, for individual patients. Simulations can then be run to find out how different people would react to different treatments. At that point, we will have taken the massive step from, generalized, traditional and sometimes even inaccurate research to the provision of truly personalized medical care with models that can be run at low cost and almost in real time to aid diagnosis and treatment plans. This will augment the advances that we have already made in precision medicine.
A digital twin can also provide assistance in determining the right therapy option for a specific patient. For prostate cancer, for example, treatment options range from surgery and radiation therapy to less invasive treatments like hormone therapy. Various subsets of these therapies can also be combined, adding even more complexity. A digital twin encompassing apatient’s imaging records, laboratory results and genetic data, combinedwith a model of the prostate cancer clinical pathway helps to ensure optimal decision-making with regard to the treatment, of that particular patient.
REFERENCES -
https://www.challenge.org/insights/digital-twin-in-healthcare/
https://www.dr-hempel-network.com/digital-health-technolgy/digital- twins-in-healthcare/
