if you have two drugs, I am assuming that their CL and Vc or Ka parameters are different? They are given at the same time? Is there an interaction between the two drugs such that the PK of one impacts the other?
Your formulation above is incorrect. Assuming that both your drugs are going to the same Central compartment (at which point you cannot differentiate between the drugs), your bioav statement should be written like this
Here, since the assumption is that total bioavailability is 1, you don’t have to specify explicitly that the Central is 1-tvbio. It is implied.
To your question about what value does tvbio take if your estimate of bioavailability if 75%. It should be 0.75 as you stated.
What are you trying to model? Perhaps some more detail can help address your question.
what i mentioned two drugs were , two different formulations of same drug.
when we give oral formulation drug is entering to central compartment from depot1 with absorption rate constant as KA.
prodrug was given in IV formulation. which is converting to drug and release to central compartment ( I am trying to use Depot 2 for prodrug administration, so when it is converted it will enter into central compartment with conversion rate constant as K23)
finally these two formulations release the same drug into Central compartment.
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)