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Digital twin in healthcare is growing in popularity. They enable doctors and patients to view the same patient from many aspects, thereby saving time and money.
Imagine being able to forecast the effects of experimental treatments without putting a patient’s life in danger. Or making a digital copy of a person’s body, right down to the level of the cells, to help choose the best surgery. What if we could figure out the chances that a pacemaker will keep a person with congestive heart failure alive without the need for surgery? Welcome to a new world where digital twins make precision medicine and preventive care possible.
It is possible for life sciences companies to:
- Make personalized treatments more quickly.
- For doctors to make more accurate clinical decisions.
- For patients with chronic conditions to get personalized treatments that extend and improve their lives.
- For hospitals with limited resources to make better use of their staff, workflows, and capacity.
It’s the era of the digital twin in healthcare.
What is digital twin?
It is easy to say that digital twins are digital representations of actual items. Digital twins are incredibly complex models that employ artificial intelligence (AI) and vast quantities of digital and physical data to accurately simulate a real-world object. This object may be a process (such as a production line), a person, a gadget, or a system. Even digital twins that depict and comprehend regions and cities have been created.
Digital twin in healthcare is used to create digital representations of healthcare data. For example, hospital surroundings, lab findings, and human physiology. To create virtual twins, data covering the individual, the population, and the environment are used.
How big is the digital twin market size?
According to a Grand View Research report, the global digital twin in healthcare market size is expected to reach $3.5 billion by 2030. The market is anticipated to expand at a CAGR of 25.6% from 2022 to 2030. The following are some key developments in the period of 2021–2022:
- In April 2021, Bayern Kapital, the venture capital institution of Germany’s Free State of Bavaria, participated in Virtonomy GmbH’s seed round. Virtonomy GmbH is a digital health startup developing a database-driven software-as-a-service (SaaS) solution for medical device makers.
- In March 2022, Microsoft Corporation announced two advancements in cloud technologies for healthcare and life sciences. In addition to announcing the general availability of Azure Health Data Services, Microsoft Cloud for Healthcare was also updated.
- In July 2022, NUREA reported that its autonomous medical image analysis software has raised more than 1 million euros in investment. The program is utilized for cardiovascular event prevention. NUREA has also been selected for Mayo Clinic’s famous innovation program.
- In Dec 2022, Dassault Systèmes inked an MOU with Ecole Normale Supérieure Paris-Saclay, a prestigious French institution of higher education and research. The agreement intends to promote long-term innovation by enhancing understanding of the academic and scientific use of digital twin in healthcare.
The digital twin in healthcare market forecast report includes profiles of key players based on various things. For example, company overview, business strategies, financial overview, product portfolio, and business segments. The digital twin in healthcare has significant promise and is expected to grow in the future.
Defining new healthy standards
A person who appears to be healthy may disregard the minor signs of a purportedly typical illness. The digital twin in healthcare monitors a person’s medical records, compares them to registered patterns, and analyzes disease symptoms.
In addition, the data can produce digital virtualization of a typical healthy patient and define new healthy standards.
Monitoring the model patient
Applying digital twin in healthcare with virtual patients assists in the monitoring of the model patient. It employs adaptive analytics and algorithms to produce precise results with continuously updated data collection and curation capabilities.
In conjunction with modern technologies, the virtual twin of patients aids physicians in Remote Patient Monitoring (RPM). Better access to healthcare for patients provides family members with peace of mind and daily assurance.
Lowering the hospital’s cost
A hospital’s cost savings increased by 900% after deploying digital twin in healthcare to eliminate patient flow issues. In addition, the new IT software development may be initially more expensive.
However, the savings generated by its services result in long-term growth for hospitals and businesses.
- This digital twin in healthcare would aid the hospital in allocating personnel and supplies. For example, new instruments, beds, and rooms, to areas where they are genuinely required.
- Using digital twins in healthcare within hospital aid in forecasting situations such as cardiopulmonary and respiratory arrest. Hence assisting the hospital organization in providing individualized health care at a lower cost.
- Creates appropriate treatment strategies that are patient-specific.
Leading to an efficient workflow plan
Digital twin in healthcare creates a virtual twin of a hospital. Accordingly, hospitals, administrators, nurses, and doctors can obtain a robust, real-time study of patients’ arrivals and departures. It causes a more efficient workflow plan.
A robust workflow reduces patient wait times while managing appointments and accurate appropriate inventory consumption. Even cardiologists may take care of each patient individually with the help of technology, resulting in increased production.
Let’s look at a few potential use cases for digital twin in healthcare.
Track the bed occupancy
The pandemic highlighted the devastating effects of erroneous bed occupancy forecasts on population health.
Digital twins can mitigate this through improved predictive analytics based on combining internal and external data. It can track patient flow internally and forecast potential spikes using external data such as population demographics and morbidity, and more.
This data, collected and shown via a digital twin, enables providers to think more strategically about capacity and resources based on more accurate forecasts. Digital twin in healthcare can improve both patient care and operational efficiency and profitability.
Utilize the medical devices
Similar to oil refineries, health systems are asset-intensive facilities with monitoring and imaging equipment, respirators, surgical tables, and many other items. They must be available at all times to provide optimal care.
Digital twin in healthcare can offer doctors a real-time insight into how these increasingly interconnected devices are employed, their performance, and the need for maintenance.
This is especially important for robots and other high-value medical technologies, which must be optimized for patient care and income.
Generate the patient simulation
Additionally, this digital twin in healthcare may generate a digital duplicate of each patient’s physique, physiology, and medical history. The twin can provide precise testing of thousands of treatments, resulting in better-informed judgments that can enhance patient outcomes and limit potential harm.
This digital twin in healthcare can usher in a new era of personalized medicine. It’s where patient care is informed to an unprecedented degree by each individual’s medical history and health concerns.
Digital twins apply to nearly every sector of the healthcare industry. With continual improvements, the application is expanding into previously unimaginable new fields. This section will list some key applications of the digital twin in healthcare.
Build personalized medication and treatment plans
Digital twin in healthcare has tremendous promise. One of the most important applications of the digital twin in healthcare is the modeling of organs, single cells, and genetic information.
All of these services can be used to build personalized medication and treatment plans for the patient, as they are based on the patient’s unique genomic makeup, anatomy, physiological traits, lifestyle habits, and behavior.
Digital twin in healthcare can provide a treatment plan with a more individualized focus than precision medicine, which often focuses on small sample groups. However, building replicas or digital twins for a human body is more complex than other procedures. It’s because of the human body’s many components, which can be time-consuming and costly.
In addition to virtual organs, planning surgery, genetic medicine, and individualized health information, we can find the digital twin in many other significant areas.
Create individualized treatment based on diagnosis
In the diagnostics segment, a doctor or physician can use the digital twin in healthcare to collect medical information, blood pressure, oxygen levels, etc. Then they place them on a model of the average human body to make a personalized medical/treatment plan for the patient.
The digital twin in healthcare can show how the real body works at the time of diagnosis or then. The doctor can compare the virtual version of a patient to their physical condition or medical history. Accordingly, doctors can easily customize the treatment plan based on the diagnosis and customize the simulations to track how the body reacts.
In the same way, the twin’s large amount of data will show if the medication works as expected. Additionally, digital twin in healthcare will point out how each patient is responding to the different treatments based on their diagnosis. Thanks to advanced modeling of the human body, the surgeon can make a digital twin of the person for the treatment plan.
With the expanding use of smartphones in the future, billions of people worldwide will have free access to digital twins. Therefore, digital twin in healthcare can help them keep an eye on and track their health stats all the time.
Similarly, if body changes are recorded, the synthetic human twin can prescribe higher-resolution testing that the healthcare system will pay for.
Modify drugs to boost efficiency
Digital twins of medications and chemicals can help clinical researchers modify drugs under development. They may quickly change particle size and components to boost efficiency. For drug testing and efficacy estimation, the virtual human twin is safer.
Digital twin in healthcare can easily vary the particle size and components to increase efficiency. Likewise, the virtual human twin is a safer alternative for testing drugs and making certain assumptions about their efficacy.
In the drug development section, the digital twin in healthcare can model how individuals will react to specific treatments or medications.
By assessing several biomarkers, digital twins can provide crucial insights into human biology if a patient is not responding well to treatment. It can analyze how a medication may impact a patient personally and alter the dosage accordingly.
Long-term, digital twin in healthcare can reduce expenses and save time compared to conventionally costly and protracted clinical trials. In addition, digital twins can be used to categorize and identify pharmacological dangers.
Currently, the digital twin in healthcare is in the infancy stage. Several significant breakthroughs, advances, and research are going on to implement its application in the healthcare industry.
Future applications of the digital twin in healthcare may include clinical trial design, drug research, diagnosis, and care coordination. It helps to expedite the healthcare process and enhance the caregiver experience.
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