Serious games for in silico training and e-learning
CTS is a suite of simulation-based serious games allowing students in medical, biology, and bioengineering schools to learn and experiment with human physiology, the effect of drugs and fertility treatments.
By exploiting Virtual Physiological Human approaches, CTS offers students a virtual lab to improve their knowledge on the physiology of the menstrual cycle and the impact of fertility drugs.
CTS serious games offer a population of virtual patients with different characteristics, to whom players can administer fertility drugs.
This enables students to learn quickly and effectively in an in silico virtual (hence risk-free) environment.
Proper scoring can be defined by teachers to evaluate students performance.
CTS offers undo actions to go back in time in virtual patient treatments and to consider different drug administration strategies.
CTS enables students to prove their ability to correctly administer, on a virtual patient, any fertility treatment defined in the CTS portfolio.
Like all software services developed within Paeon, CTS is not restricted to reproductive endocrinology, as it is ready to be used with other Virtual Physiological Human Models, other drugs and other treatment protocols.
By interactively playing with the population of Virtual Patients provided by CTS, students easily learn, in silico, how hormone concentrations change during different phases of the menstrual cycle and how follicles grow and go atretic.
By exploiting the CTS drug database filled with virtual versions of the most famous fertility drugs used in current clinical practice (Merional, Decapeptyl, Primolut, etc.), students learn and see, in silico, drug administration effects on the menstrual cycle, in particular on hormones concentrations and follicular growth.
Student training scores are based on a set of Key Performance Indicators, which can be defined by teachers.
CTS offers a predefined set of Key Perfomance Indicators based on time constraints, patient health safety conditions and treatment success criteria.
Students learn how to correctly administer complex clinical treatment protocols by treating virtual patients in silico, before entering into the actual clinical practice.
Performance are automatically evaluated based on the mismatch of their clinical decisions (drug doses and timing) and the correct decisions as defined in the treatment model.
CTS provides a training and learning experience at different gaming levels to drive players along a smooth learning curve.
As the game level gets tougher, CTS offers to the player virtual patients more difficult to treat, also reducing the set of system suggestions available.