Digital twin for personalized medicine development

Area of Science:

• Healthcare Technology
• Digital Health
• Personalized Medicine

Background:

• Digital Twin (DT) technology, an Industry 4.0 innovation, integrates AI, IoT, and ML.
• DTs create dynamic, data-driven patient replicas for advanced medical applications.

Purpose of the Study:

• To review the evolution, architecture, and technologies of DTs in healthcare.
• To explore the transformative applications of DTs in personalized medicine (PM).

Main Methods:

• Review of existing literature on Digital Twin technology in healthcare.
• Analysis of AI, IoT, and ML integration for patient replica creation.
• Exploration of applications in disease simulation, diagnostics, and treatment optimization.

Main Results:

• DTs enable real-time patient monitoring and predictive analytics.
• Personalized treatment plans are optimized using genetic and lifestyle data.
• DTs facilitate simulations for disease progression and diagnostic improvements.

Conclusions:

• DT integration offers significant potential to enhance healthcare outcomes and efficiency.
• Addressing challenges like data privacy, interoperability, and ethics is crucial.
• Future advancements in AI, cloud computing, and blockchain will drive precision medicine.