Simulation of oscillatory dynamics of blood testosterone levels using the crossover method

Abstract

Blood testosterone levels oscillate periodically in humans. The in vivo dynamics of this biochemical system cannot be simulated in silico using a continuous deterministic solution of a previously reported mathematical model. The use of the stochastic simulation algorithm (SSA), however, has been reported to generate sustained oscillations that are qualitatively and quantitatively consistent with the experimental observations. Although the SSA is capable of accurately simulating a biochemical network, it is extremely inefficient from a computational standpoint. In this work, we have attempted to simulate the above mentioned model using a deterministic-stochastic crossover method, for three separate sets of parameters. Each time, not only did the results show the existence of sustained oscillations but also that the computational time was at least four times lower than the corresponding SSA solution. The crossover method can hence be proposed as a viable alternative to the SSA for simulating biochemical systems that are commonly encountered in systems biology applications.