Analyzing solutions of y'= r-ky using W lambert function?

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The discussion focuses on solving the initial value problem (IVP) represented by the differential equation y' = r - ky, with y(0) = y0, using the W Lambert function. The solution is expressed as y = (y0)e^(-kt) + (r/k)(1 - e^(-kt)). The analysis specifically addresses how the initial drug amount (y0) affects the time (t) to reach steady-state in pharmacokinetics, particularly when y = 0.99(r/k). The derived formula for t is t = -ln(0.01(r/(r - ky0)))/k, indicating the relationship between y0 and the time to steady-state.

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kochibacha
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consider this IVP
y'=r-ky , y(0)=y0
y= (y0)e^(-kt) + (r/k)(1-e^(-kt))
if y,y0,r,t are provided, we should be able to solve for k and that's the problem but what I'm really interested is analyzing this problem

if we let y=0.99 (r/k) find t in terms of all other variables

Of courses, if y0 = 0 we can see that t= -(ln 0.01)/k

i wonder if y0 is not zero is it possible to analyze variable t using any knowledge or technology from mathematics?

this problems is derived from real application of pharmacokinetics IV infusion where

y= amount of drug at time t
y0 = initial amount of drug at t = 0
r = infusion rate
k = elimination rate constant
(r/k) = amount of drug at steady-state (as t --> infinity the amount of drug will approach this value and 99% of (r/k) is a good approximation of amount of drug at steady-state)

so what I really ask is how the initial amount of drug reflects the time to reach steady-state ( for example. how much we increase y0 in order to halve the time to reach steady-state )
 
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I'm sorry you are not generating any responses at the moment. Is there any additional information you can share with us? Any new findings?
 
Let's see what I can whip up...
y' + ky = r is a first-order, linear, non-homogenous ODE with k \neq 0 and r \neq 0, both of which I assume to be constant.
The general solution is (by partitioning into homogenous and particular solutions) C_0 e^{-kt} + \frac{r}{k}. Given an initial value, y(0) = y_0, the unique solution is (y_0 - \frac{r}{k})e^{-kt} + \frac{r}{k}. (Same as yours, but rewritten.)

You then ask what I assume to be is the time at which this solution is equal to 0.99\frac{r}{k}.

(y_0 - \frac{r}{k})e^{-kt} + \frac{r}{k} = 0.99\frac{r}{k}
(y_0 - \frac{r}{k})e^{-kt} + 0.01\frac{r}{k} = 0
(y_0 - \frac{r}{k})e^{-kt} = -0.01\frac{r}{k}
e^{-kt} = -0.01\frac{\frac{r}{k}}{y_0 - \frac{r}{k}}
e^{-kt} = -0.01\frac{r}{k y_0 - r}
Immediately, we see that \frac{r}{k y_0 - r} < 0 for there to be a real-valued, finite solution.

It's worth noting that if k = 0, we get a linear polynomial as a solution to the ODE, for which there is no steady state unless r = 0 as well, in which case it's y_0 as the solution is just a constant. If k \neq 0 and r = 0, the only steady state would be 0, for which your approximation fails to give a finite solution to the problem. If k y_0 - r = 0, the solution to the ODE would be \frac{r}{k}, which has a steady-state but the approximation fails as well.

In any case, assuming \frac{r}{k y_0 - r} < 0, the solution is:
e^{-kt} = -0.01\frac{r}{k y_0 - r}
-kt = \ln{\left(-0.01\frac{r}{k y_0 - r}\right)}
t = -\frac{\ln{\left(-0.01\frac{r}{k y_0 - r}\right)}}{k} = -\frac{\ln{\left(0.01\frac{r}{r - k y_0}\right)}}{k}
 

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