Since both drugs give the same final moiety, see if this works.

You can play around with `d2`

to figure out how the Prodrug is given. There are different ways to account for the overall contribution of both drugs. here I am just assuming that each route of administration has its own bioavailability.

```
using Pumas
using Plots
using Random
two_parallel_drugs = @model begin
@param begin
tvcl ∈ RealDomain(lower=0)
tvv ∈ RealDomain(lower=0)
tvka ∈ RealDomain(lower=0)
tvbio1 ∈ RealDomain(lower=0)
tvbio2 ∈ RealDomain(lower=0)
Ω ∈ PDiagDomain(6)
σ ∈ RealDomain(lower = 0.0001)
end
@random begin
η ~ MvNormal(Ω)
end
@pre begin
CL = tvcl*exp(η[1])
Vc = tvv*exp(η[2])
Ka = tvka*exp(η[3])
bioav = (Depot = tvbio1*exp(η[5]), Central = tvbio2*exp(η[6]))
end
@dynamics Depots1Central1
@derived begin
conc := @. Central/Vc
dv ~ @. Normal(conc, σ*abs(conc))
end
end
d1 = DosageRegimen(100, cmt=1)
d2 = DosageRegimen(50, cmt=2, duration = 0.5)
dr = DosageRegimen(d1,d2)
pop = map(subj -> Subject(id = subj, events = dr), 1:10)
param = (
tvcl = 5, tvv = 50, tvka = 0.8, tvbio1 = 0.8, tvbio2 = 0.5,
Ω = Diagonal([0.04,0.04,0.36,0.36,0.04,0.04]),
σ = 0.1
)
Random.seed!(123)
sims = simobs(two_parallel_drugs, pop, param)
plot(sims)
```