Digital twins revolutionize climate science and experimental design

In a recent article, The Economist highlighted the transformative role of digital twins in both scientific research and practical applications.

Scientists have long been familiar with computer models. In fact, some of the earliest uses of computers to replicate real-world phenomena were developed by physicists interested in understanding the behavior of subatomic particles and meteorologists aiming to forecast the weather. Over the past 75 years or so, computer modeling has become an essential tool in scientific research, supporting everything from climate change predictions to pandemic monitoring.

However, it is only recently that these models have become advanced enough to be considered "digital twins"—virtual replicas of real-world entities capable of simulating their behavior in real time. This leap forward has been driven by advancements in sensor and imaging technologies, as well as improved methods for data collection, transfer, and analysis. Today, digital twins are offering new insights into the human body and the Earth, while also shaping the design of innovative experiments. The impact of this evolution is particularly evident in healthcare, where digital twins have seen rapid growth in recent years, according to Michelle Oyen, a biomedical engineer at Washington University in St. Louis. She attributes much of this surge to the push towards personalized medicine.

The idea is that if an individual's entire organ can be accurately simulated, the effects of diseases and potential drug treatments can also be modeled in great detail. Dr. Oyen herself uses digital twins to model the development of the placenta during pregnancy, examining how this affects the risk of stillbirth. Similar research is being conducted for other organs, such as the lungs and kidneys. Researchers have even made strides in simulating the intricate networks of neurons in the human brain to better understand and study epileptic seizures. The heart is of particular interest to engineers because it is a complex system of valves and chambers that contracts and relaxes up to a hundred times per minute to circulate blood throughout the body. While all hearts adhere to the same physical principles, each operates uniquely due to variations in diet, lifestyle, age, and physical condition. 

These factors influence how cardiac tissue responds to electrical signals and how smoothly blood flows through the heart's chambers. Understanding these variations is crucial for effective treatment of heart disease. A digital twin could offer valuable insights. At Queen Mary University of London, Caroline Roney is using virtual models to improve treatments for atrial fibrillation, a common cardiac arrhythmia affecting about 1.4 million people in Britain. Atrial fibrillation, caused by irregular electrical signals in the upper heart, can lead to serious conditions like stroke or heart failure if left untreated. Current treatments often involve ablation, which uses heat or cold to create small scars in the heart to disrupt faulty electrical signals. 

Dr. Roney is focused on customizing treatment using digital twins to model individual hearts and predict their reactions to ablation. Advances in scanning technology allow for highly precise replicas of the heart's structure and composition, within less than a millimeter. These virtual models can also simulate patterns of electrical conductivity based on data from electrocardiograms (ECGs), enabling predictions about how the heart will respond to ablation and potential changes due to aging. Furthermore, digital twins of different organs can be developed separately and then integrated, using outputs from one organ as inputs for others. 

Dr. Roney is involved in the Ecosystem for Digital Twins in Healthcare, a European consortium working to combine digital twins of various organs to create a comprehensive virtual human body. This approach aims to enhance the reliability of modeling drug effects and surgical outcomes. The consortium plans to publish a detailed strategy for achieving this integration in September. 

Some researchers aspire to apply digital twin technology to planetary systems by integrating models of specific Earth processes, potentially offering significant practical benefits. Thomas Coulthard, a physical geographer at the University of Hull, is developing a digital twin for local areas to help manage responses to heavy rainfall and storms. This model simulates the effects of opening and closing sluice gates and barriers on surface water, enabling water companies and landowners to evaluate the potential outcomes of various actions and inactions. Creating a global network of such models will be a complex, long-term endeavor. 

Meanwhile, others are focusing on broader scales. Thomas Huang, a data scientist at NASA’s Jet Propulsion Laboratory, is working on a digital twin of Earth's climate. His aim is to leverage real-time data to enhance predictions of global warming's impact on weather patterns. Huang's main challenge is not data availability, but the integration of diverse data sources. Accurate climate modeling requires harmonizing data from various formats, including satellite sensors, ground stations, and ocean floats. Digital twins also play a crucial role in the design of large-scale experiments. 

For example, CERN uses virtual models to simulate and optimize the Large Hadron Collider's performance, while the James Webb Space Telescope’s digital twin assists in planning maintenance and operational adjustments. These digital twins not only provide real-time predictions but also continuously update based on live data, accelerating scientific progress. David Wagg from the Alan Turing Institute highlights that such dynamic, two-way modeling significantly enhances the pace and effectiveness of scientific research, making digital twins an increasingly essential tool in science.