From Virtual Model to Clinical Reality: Review on AI Enabled In Silico Twins in Organ Transplantation

Abstract

The major difficulties seen in organ transplantation are organ rejection and infection during the surgery, shortage of organs and mainly the donor-recipient matching. By finding solutions to these problems the AI enabled In Silico twins plays a key role in development seen in organ transplantation.[3] The combination of AI In Silico twins, a virtual replica of individual patients created by using physiological, biological and clinical data. These virtual models can predict the organ rejection by [6] immunosuppressive therapy, organ function and disease progression and also help in medical treatment based on the type of organ. The AI enabled In Silico twins provide a real time data and gives the information about the organ function and donor selection. By combining the AI in organ transplantation medical procedure, the positive outcomes will be enhanced. The In-Silico twins technology will reduce ethical risks and minimize the clinical trials and clinical errors in patients. This technology gives a safer procedure by creating the virtual replica by using the physiology of organs and predict better donor-recipient matching and modify the clinical practice and improve the transplant success rapidly developing through AI and it is continuously evolving in all sectors; the virtual twins could soon become an essential tool making the transplant safer and more successful for patients throughout the world.