Role of Digital Twin Technology in Healthcare

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Developments in healthcare technologies are setting new standards at present and encouraging exploration into emerging technologies to advance care and enhance the lives of patients globally

Digital Twins are virtual replicas of objects, individuals, or systems spanning their life cycles

The article introduces the role of digital twins in the healthcare system, the advantages, and the challenges that come with it

Pharma 4.0 introduces emerging technologies that are gradually shaping the healthcare landscape. Ranging from the integration of intelligent automation and advanced analytics to emerging technologies like ADCs and cell & gene therapies, Pharma 4.0 conceals several innovative and holistic approaches up its sleeves. One such technology that has spread like wildfire is Digital Twins. In this article, we will navigate the digital twin technology, its application in healthcare, and how it is supposed to revolutionize the healthcare system.

An Introduction to Digital Twin

A digital twin is a virtual representation of an object, an individual, or a system. It runs simulations, uses AI and ML, real-time data, and spans the lifecycle of the object, individual, or system. Reduced downtime, cost-efficiency, and flexibility are among the many benefits that come with digital twins.

Simply put, a digital twin is a virtual replica. In the healthcare system, a digital twin can be anything from a patient or a device to medical equipment or a drug. Simulations are run using a virtual replica of an individual's health profile to predict outcomes.

The global digital twins in the healthcare market was valued at $1.6B in 2023 and is expected to reach $21.2B by 2028, exhibiting a CAGR of 67% from 2023 to 2028.

How Does Digital Twin Technology Work?

The digital twin technology uses a combination of the Internet of Things (IoTs) and intelligent automation (AI & ML). Digital twins are built from conceptual models like BIM, CAD, or GIS. The Internet of Things possesses Unique identifiers (UIDs) that enable created Digital twins to communicate and interact over the Internet. Using this integration of conceptual models and IoTs, digital twin technologies allow researchers and analysts to run simulations to test patients for surgeries, clinical trials, and more.

Advantages of Digital Twin Technology in Healthcare

Digital twin technology offers a passel of benefits in the healthcare setting, optimizing both productivity and decision-making. Let’s take a look at a few benefits of digital twin technology:

Enhanced Patient Outcome: A researcher can simulate different treatments and procedures on the digital twin of a diabetic patient, containing all the relevant health data. Using digital twins, researchers can identify better and personalized treatment options suited for the patient without any intervention and side effects

Time Savvy and Cost Cutting: Digital twin technologies help you skip the complexities of carrying out several trials by running virtual simulations

Robust Data Collection and Analytics: With digital twins, researchers, and analysts unlock extensive data that can be used in analytics to reveal groundbreaking insights on treatment procedures, trials, and life cycles of the devices and drugs. The analytics deduced from the collected data can be used in decision-making

Highly Flexible: Digital twin technology is extensively flexible and can be used in regulated environments such as preclinical and clinical trials. When compared to traditional clinical trials, digital twins offer spontaneous modifications without human volunteers and the need to start over

Challenges to Digital Twin Technology

Digital twins offer numerous benefits in healthcare settings but there are some challenges and limitations that need to be addressed.

Lack of Big Data: Digital Twin relies heavily on big datasets, including electronic health records, medical imaging, and payor records. The abundance of unsupported and invalidated data negatively impacts the outcomes of digital twin technologies and remains a major concern

Technological Barrier: Handling big data requires advanced technological capabilities and machinery to handle such a massive volume of data. Integrating digital twin technology into healthcare requires collaboration with tech companies and a robust infrastructure, which can be costly and overwhelming

Data Compliance: Using patient data emanates ethical concerns. Data breaches in digital twin technology can negatively influence the outcomes and question its credibility

Comprehension of Human Physiology: Human physiology is complex and requires on-point representation for a digital twin model. A tiny glitch in the system can be detrimental to the assessment of a drug, device, or service

Data Analytics by Octavus Consulting

When it comes to transforming complex data into actionable insights, Octavus Consulting remains an ideal choice for Biopharma, healthcare, and MedTech companies. With a combined 40 years + of experience in data handling, our proficient analysts dive deep into the intricacies of datasets to dispel ambiguity and light up the room with enlightening insights to empower companies in decision-making.

Conclusions and Perspectives

Emerging technologies are redefining healthcare landscapes with innovative solutions to complex healthcare enigmas. Digital twin technology offers a promising foothold in the evolving healthcare landscape. Big data plays a crucial role in enhancing the foundation of emerging technologies in healthcare. Octavus Consulting has been mentoring biopharma companies in advanced data analytics and empowering them to augment their decision-making capabilities. Know more about Octavus’ vast offerings by reaching out at bd@octavusconsulting.com