In some personalized cancer therapies the elimination of the tumor will be a result of the injection of flesh- eating bacteria deep within the tumor. with the feb activity dead tissue will appear. controlled maggot therapy can be a trigger to remove the mess produced inside the tumor and as it may have unwanted results, it should be strongly, controlled and predicted.
As all the elements change together, we can say the system is a data- dynamic one and the method for this approach will be based on computational modeling to predict and measure every thing in it.
A practical model which exhibits two positive linearly stable steady state populations is for blow fly larvae. the population dynamic is modeled by the equation below:
dn/dt=r_b n(1-n/k_b )-p(n)
here rb is the linear input rate of the larvae to the system and kb is the carrying capacity which is related to the density of dead tissue (food) available. the p(n)-term represents elimination of larvaes, generally by patient's immune system. there is an approximate threshold value nc, below which the elimination of larvae won't occur in an effective matter, while above it the elimination is close to its saturation value: such a functional form is like a switch with nc being the switch value. the dynamics of n(t)is then governed by:
dn/dt=r_b n(1-n/k_b )-(bn^2)/(a^2+n^2 )
With this model some personalized cancer therapies will be extremely enhanced. essential data will be available to find a careful balance between the elements of the system.