‘In silico’ modeling or computational modeling is the use of computers to simulate complex systems using mathematics, statistics, physics, and computer science. In biomedical engineering, computational modeling simulates human biology and the progression of diseases has a wide application and represents a fresh alternative to traditional methods of research, i.e. trials on human subjects and in animal models. ‘In silico’ (virtual) simulations of clinical trials are vital when there is a population that cannot be investigated clinically or can be put at risk, such as critically ill patients, patients with rare diseases and neonatal/pediatric patients. At the same time, they provide more reliable results than animal trials since animal models can fail to summarize the severity of human pathophysiology, due to physiological discrepancies and lack of methodology accuracy. Virtual models of patients are individualized, mechanistic and they can be always validated. Moreover, computational simulations are effectively (almost) free of ethical limitations, low-cost, flexible, and reproducible.
A digital twin is a recently new emerging technology that builds on ‘in silico’ representations of an individual, simulating the anatomy, physiology, and pathology of human systems in real-time. A digital twin works through data derived from sensors that are attached to the individual or in its environment and it can represent medical devices, patients, and healthcare delivery systems. It allows personalized medicine with more detailed medical interventions, supporting the clinical decisions and improving the technology of medical equipment. Furthermore, computational simulation is used to predict biological or toxicological properties (using Quantitative Structure-Activity Relationship – QSAR models) based on the structural properties of chemicals, to understand whether or not compounds released from medical devices are dangerous. Finally, modeling could be used to track the evolution of infectious diseases to classify effective interventions and to design drugs for safer and more effective medication, predicting drug-safe effects.
Although in the last years computational modeling has been used for numerous applications and great progress has been made, there is still a lack of understanding of the pathophysiology of human systems and room for improvement for the best development and use of medical devices. In this special issue, we encourage original and review papers on computational modeling in biomedical engineering, with a special interest in digital twin for medical applications.
Topics of interest include but are not limited to
- digital twin in healthcare;
- simulation / modeling of:
- virtual pathophysiological patients for research or clinical purpose;
- clinical trials to better understand the relationship between patients, disease, and treatments;
- biomechanics of bones, muscles, and orthopedic prosthetics
- dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features (QSAR models);
- evolution of infectious diseases;
- drug side effects;
- health and biomedical data.
Dr Marianna Laviola – Marianna.Laviola@nottingham.ac.uk
University of Nottingham
November 30, 2022