Mathematical modelling of the human body as a subject is relatively young yet medical problems and diseases associated with it are as old as humankind.

Cure Data offers a breakthrough computer-based mathematical model of the human body. It integrates theoretical-experimental-clinical multivariable information about genes, proteins, cells, tissue, organs and systems into a quantitative descriptor — "digital twin" — that bridges the existing wide gap between clinicians, biologists, mathematicians, computer scientists and patients by assisting them in the study and analysis of complex biological processes that cannot be done through traditional in vivo and in vitro approaches.

The digital twin recognizes the complexity of biological phenomena, e.g., electromechanical and chemoelectrical events, pharmacological effects including co-localisation and co-transmission by multiple neurotransmitters, receptor polymodality, drug interactions and many more, and treats them with a high degree of mathematical rigor and analysis.

Digital twin computing provides a coherent framework for existing fragmentary experimental and clinical observations, and leads to advances in clinical diagnosis and personalized medicine. It has already demonstrated its importance in everyday clinical and research settings in unravelling intricacies of hidden mechanisms of common, however poorly understood and thus not well diagnosed and treated, conditions such as functional dyspepsia, irritable bowel syndrome, (hypo)hypertonic inertia of the gravid uterus, uterine dystocia, painful and overreactive urinary bladder, nocturnal incontinence, and others.

By unravelling the mystery of diseases and providing a quantitative, in addition to qualitative, data relevant to a particular patient, digital twin computing paves the way for: personalized treatment, advancements in pharmaceutical medicine, design and development of new diagnostic methods and tools, prediction and prevention of unwanted life-threatening side effects, and thus offers better and safer patient care and management.