Snake venom is comprised of a combination of different proteins and peptides with a wide range of molecular weights and different disposition processes inherent to each compound. This causes venom to have a complex exposure profile. Our study investigates 1) how each molecular weight fraction (toxin) of venom contributes to the overall time course of the snake venom, and 2) the ability to determine toxin profiles based on the profile of the overall venom only. We undertook an in silico simulation and modelling study. Sixteen variations of venom, comprising of two to nine toxins with different molecular weights were investigated. The pharmacokinetic parameters (i.e., clearance,, and volume of distribution,) of each toxin were generated based on a log-linear relationship with molecular weight. The concentration-time data of each toxin were simulated for 100 virtual patients using MATLAB and the total concentration-time data of each toxin were modelled using NONMEM. We found that the data of sixteen mixtures were best described by either two- or three-compartment models, despite the venom being made up of more than three different toxins. This suggests that it is generally not possible to determine individual toxin profiles based on measurements of total venom concentrations only.
Keywords: pharmacokinetics, stochastic simulation and estimation; snakes; venom.