Digital twins have emerged as transformative innovations in the healthcare sector. A prominent application of digital twins in healthcare is the creation of patient-specific simulations. By developing virtual replicas of an individual’s disease – reflecting their unique physiological characteristics, medical history, and genetic information – healthcare professionals can gain valuable insights and make more informed decisions about patient care. These virtual models allow for testing various treatment options in a risk-free environment, thus aiding in personalizing and optimizing medical treatments. Digital twins can help predict and monitor disease progression, simulate the effects of different medications, and provide real-time feedback on treatment outcomes. By leveraging digital twins, healthcare providers can enhance patient outcomes and offer more precise, individualized care. What sets Twinome Health apart is its capability to continually integrate new patient data into the digital twin, enabling more accurate predictions akin to weather forecasting. In contrast, other patient clinical decision support approaches are static, based on a single moment. Twinome Health adopts a longitudinal approach, tracking the patient throughout their treatment.