Difference between revisions of "D'Onofrio chemotherapy model"

From mintOC
Jump to: navigation, search
(Created page with "{{Dimensions |nd = 1 |nx = 4 |nu = 2 }} This cancer chemotherapy model is based on the work of d'Onofrio. The corresponding dynamic describes the effect...")
 
m (Text replacement - "<bibreferences/>" to "<biblist />")
Line 111: Line 111:
  
 
== References ==
 
== References ==
<bibreferences/>
+
<biblist />
  
 
[[Category:ODE model]]
 
[[Category:ODE model]]

Revision as of 21:28, 30 December 2015

D'Onofrio chemotherapy model
State dimension: 1
Differential states: 4
Continuous control functions: 2


This cancer chemotherapy model is based on the work of d'Onofrio. The corresponding dynamic describes the effect of two different drugs administered to the patient. An anti-angiogetic drug is used to suppress the formation of blood vessels from existing vessels and thereby starving the tumors supply of proliferating vessels. In addition a cytostatic drug effects the proliferation of the tumor cells directly. The dynamic of the problem is given by an ODE model.

Mathematical formulation

For t \in [t_0, t_f] the optimal control problem is given by


\begin{array}{llcl}
 \displaystyle \min_{x, u} & x_0(t_f) &+& \alpha \int_{t_0}^{t_f} u_0(t)^2 \text{d}t   \\[1.5ex]
 \mbox{s.t.} & \dot{x}_0(t) & = & - \zeta x_0(t) \text{ln} \left( \frac{x_0(t)}{x_1(t)} \right) - F \; x_0(t) u_1(t), \\
             & \dot{x}_1(t) & = & b x_0(t) - \mu x_1(t) - d x_0(t)^{\frac{2}{3}}x_1(t) - G u_0(t) x_1(t) - \eta x_1(t) u_1(t),  \\
             & \dot{x}_2(t) & = & u_0(t),  \\
             & \dot{x}_3(t) & = & u_1(t), \\ [1.5ex]
             & 0 & \leq & u_0(t) \leq  u_0^{max},  \\
             & 0 & \leq &  u_1(t) \leq u_1^{max}, \\
             & x_2(t) & \leq & x_2^{max},  \\
             & x_3(t) & \leq & x_3^{max}.
\end{array}

where the control u_0 denotes the administered amount of anti-angiogetic drugs and u_1 the amount of cytostatic drugs. The state x_0 describes the volume of tumor and x_1 the volume of neighboring blood vessels. The remaining states x_2 and x_3 are used to constraint the maximum amount of drugs over the duration of the therapy.

Parameters

In the model these parameters are fixed.


\begin{array}{rcl}
t_0 &=& 0,\\
(\zeta, b, \mu, d, G) &=& (0.192, 5.85, 0.0, 0.00873, 0.15),\\
(x_2(0), x_3(0), u_0^{max}, x_2^{max}) &=& (0,0,75,300).
\end{array}

The parameters (x_0(0), x_1(0), u_1^{max}, x_3^{max}) can be taken from the parameter sets shown in the following section. To the remaining parameters (F, \eta) exists no experimental data.

Reference Solutions

The problem can be solved with the [multiple shooting method]. For the following solutions the control functions and states are discretized on the same grid, with 100 nodes. The unknown parameters are chosen from the following parameter sets

Parameter set 1


\begin{array}{rclrcl}
x_0(0) &=& 12000,& x_1(0) &=& 15000,\\
u_1^{max} &=& 1,& x_3^{max} &=& 2.\\
\end{array}

Parameter set 2


\begin{array}{rclrcl}
x_0(0) &=& 12000,& x_1(0) &=& 15000,\\
u_1^{max} &=& 2,& x_3^{max} &=& 10.\\
\end{array}

Parameter set 3


\begin{array}{rclrcl}
x_0(0) &=& 14000,& x_1(0) &=& 5000,\\
u_1^{max} &=& 1,& x_3^{max} &=& 2.\\
\end{array}

Parameter set 4


\begin{array}{rclrcl}
x_0(0) &=& 14000,& x_1(0) &=& 5000,\\
u_1^{max} &=& 2,& x_3^{max} &=& 10.\\
\end{array}

Furthermore in the objective function \alpha =0 is chosen.

Source Code

C code

/* volume of tumor */
rhs[0] = - zeta*x[0]*log(x[0]/x[1])-F*x[0]*u1_;
/* volume of neighboring blood vessels */
rhs[1] = b*x[0] - (mu + d*pow(x[0],2.0/3.0))*x[1] - G*u0_*x[1] - eta*x[1]*u1_;
/* amount of anti-angiogetic drug */
rhs[2] = u0_;
/* amount of cytostatic drug */
rhs[3] = u1_;

Variants

In <bibref></bibref> can be found other approaches to solving this problem, using indirect methods and Pontryagins maximum principle.

References

There were no citations found in the article.