# Recalling time in the pre block "t"

**URL:** <https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759>\
**Category:** Uncategorized\
**Created:** [September 18, 2022, 4:07pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759 "2022-09-18T16:07:36Z")\
**Posts on this page:** 12\
**Page:** 1

<div class="post-metadata">

**Author:** ![ahmed.salem](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@ahmed.salem](https://discourse.pumas.ai/u/ahmed.salem)\
**Post date:** [September 18, 2022, 4:07pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/1 "2022-09-18T16:07:36Z")

</div>

Hello,  
I was able to run the following code few days ago

```auto
mod = @model begin
        @param begin
            TVCL ∈ RealDomain(lower = 0.00001)
            tvKTV ∈ RealDomain(lower = 0.00001)
            TVVc ∈ RealDomain(lower = 0.000001, upper = 8) 
            wt_cl ∈ RealDomain()
            wt_v ∈ RealDomain()
            circuit ∈ RealDomain()
            ecmo ∈ RealDomain()
            Ω ∈ PDiagDomain(3)
            σ_add ∈ RealDomain(lower = 0.0001)
            σ_prop ∈ RealDomain(lower = 0.0001)
        end
        @random begin
            η ~ MvNormal(Ω)
        end
        @covariates WT AGE_D ISMALE SCR GFR AGEYRS TYPE_MODELING IS_BLEEDING IS_CIRCUIT_CHANGE ECMO_DAYS Occassions IS_CIRCUIT_CHANGE_UPDATE IS_BLEEDING_UPDATE
        @pre begin
            KTV = tvKTV*exp(η[1])*(ECMO_DAYS/6)^ecmo
            CL = TVCL * exp(η[2])*(1-exp(-KTV*t))*(WT/50)^wt_cl*circuit^IS_CIRCUIT_CHANGE
            Vc = TVVc * exp(η[3])*(WT/50)^wt_v
      
        end
        @dynamics Central1
      
        @derived begin
            CP = @. Central / Vc
            CONC = @. Normal(abs(CP), sqrt(CP^2*σ_prop+σ_add))
        end
end

```

However, I am receiving the following error

```auto
ERROR: ArgumentError: Using explicit time in the pre or dcp blocks with Central1 <: ExplicitModel is not support.
Stacktrace:
 [1] macro expansion
   @ /builds/PumasAI/PumasSystemImages-jl/.julia/packages/Pumas/MxXdQ/src/dsl/model_macro.jl:1281 [inlined]
 [2] top-level scope
   @ ~/data/code/UFH_ECMO_UTAH/UFH_UTAH/ECMO_UTAH_NEW.jl:23

```

Could you please help ?

---

<div class="post-metadata">

**Author:** ![vijay](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/vijay/32/96_2.png) [@vijay](https://discourse.pumas.ai/u/vijay)\
**Post date:** [September 18, 2022, 4:23pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/2 "2022-09-18T16:23:30Z")

</div>

@ahmed.salem the previous use of `t` was a bug that has been addressed as you can see here [Release Notes for Pumas 2.2.0 · Pumas](https://docs.pumas.ai/stable/releasenotes/ReleaseNotesPumas-2.2.0/#Bug-fixes-and-minor-improvements)

Use a differential equation model that automatically gets covered to a linear ODE. And in that you can use the model as is.

---

<div class="post-metadata">

**Author:** ![ahmed.salem](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@ahmed.salem](https://discourse.pumas.ai/u/ahmed.salem)\
**Post date:** [September 18, 2022, 6:09pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/3 "2022-09-18T18:09:45Z")

</div>

I see, thanks … I adjusted the model accordingly:

```auto
mod = @model begin
        @param begin
            TVCL ∈ RealDomain(lower = 0.0001)
            tvKTV ∈ RealDomain(lower = 0.0001)
            TVVc ∈ RealDomain(lower = 0.0001) 
            wt_cl ∈ RealDomain(upper = 2)
            wt_v ∈ RealDomain(upper = 2)
            circuit ∈ RealDomain(lower = 0.0001)
            ecmo ∈ RealDomain()
            Ω ∈ PDiagDomain(3)
            σ_add ∈ RealDomain(lower = 0.00001)
            σ_prop ∈ RealDomain(lower = 0.00001)
        end
        @random begin
            η ~ MvNormal(Ω)
        end
        @covariates WT AGE_D ISMALE SCR GFR AGEYRS TYPE_MODELING IS_BLEEDING IS_CIRCUIT_CHANGE ECMO_DAYS Occassions IS_CIRCUIT_CHANGE_UPDATE IS_BLEEDING_UPDATE
        @pre begin
            KTV = tvKTV*exp(η[1])*(ECMO_DAYS/6)^ecmo
            CL = TVCL * exp(η[2])*(1-exp(-KTV*(t+ 1e-10)))*(WT/50)^wt_cl*circuit^IS_CIRCUIT_CHANGE
            Vc = TVVc * exp(η[3])*(WT/50)^wt_v
      
        end
        @dynamics begin
                Central' = -(CL/Vc) * Central
        end 
      
        @derived begin
            CP = @. Central / Vc
            CONC = @. Normal(abs(CP), sqrt(CP^2*σ_prop+σ_add))
        end
end

```

However I am getting the following warning message and the fit function does not allow estimation

```auto
modfit = fit(mod, estimation, param, Pumas.FOCEI())
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
Iter Function value Gradient norm 
     0 Inf NaN
 * time: 4.100799560546875e-5
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
FittedPumasModel

Successful minimization: false

Likelihood approximation: Pumas.FOCE
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
Log-likelihood value: -Inf
Number of subjects: 159
Number of parameters: Fixed Optimized
                                  0 12
Observation records: Active Missing

```

I tried even to initialize the ODE at very small time 1e-10 but I am not able to get it work in Pumas, although I did the same run in another software and it ran successfully with the same results as when I used to use the closed form solution. So, I do not think there is a problem with model specification. I am wondering if this problem is due to the settings of the ODE solver? please let me know

---

<div class="post-metadata">

**Author:** ![patrick](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/patrick/32/206_2.png) [@patrick](https://discourse.pumas.ai/u/patrick)\
**Post date:** [September 18, 2022, 6:55pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/4 "2022-09-18T18:55:00Z")

</div>

Did you try `findinfluential`? Maybe there’s an issue with one of the covariates you use.

---

<div class="post-metadata">

**Author:** ![ahmed.salem](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@ahmed.salem](https://discourse.pumas.ai/u/ahmed.salem)\
**Post date:** [September 18, 2022, 7:34pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/5 "2022-09-18T19:34:22Z")

</div>

Thanks for the reply. I tried to use this function. It seems that ID = 20 is the problem

```auto
modfit = findinfluential(mod, estimation, param, Pumas.FOCEI(), k = 100)
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ SciMLBase /builds/PumasAI/PumasSystemImages-jl/.julia/packages/SciMLBase/mndcy/src/integrator_interface.jl:345
100-element Vector{NamedTuple{(:id, :nll), Tuple{String, Float64}}}:
 (id = "20", nll = Inf)
 (id = "112", nll = 304.7092273740628)
 (id = "125", nll = 262.8198478415608)
 (id = "248", nll = 261.1547795464976)
 (id = "185", nll = 218.91950414263349)
 (id = "25", nll = 212.6464723493648)
 (id = "181", nll = 207.2863831956399)
 (id = "232", nll = 187.74712293115962)
 (id = "123", nll = 184.22096771056218)
 (id = "74", nll = 182.15866723353736)
 (id = "139", nll = 181.86417917383557)
 (id = "19", nll = 178.08662883120795)
 (id = "192", nll = 175.88409508526817)
 (id = "131", nll = 175.62432969437899)
 (id = "200", nll = 165.37169632282868)

```

I had a closer look at this subject’s data

```auto
julia> @chain df begin
               @rsubset :ID ∈ [20]
               select(_,:ID,:TIME,:evid,:mdv, :AMT,:RATE,:cmt,:WT,:ECMO_DAYS,:IS_CIRCUIT_CHANGE)
       end
15×10 DataFrame
 Row │ ID TIME evid mdv AMT RATE cmt WT ECMO_DAYS IS_CIRCUIT_CHANGE 
     │ Int64 Float64 Int64 Int64 Float64? Float64? Int64 Float64 Int64 Int64             
─────┼─────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ 20 0.0 1 1 121.38 71.4 1 3.57 4 0
   2 │ 20 1.36667 0 0 missing missing 1 3.57 4 0
   3 │ 20 1.7 1 1 803.25 89.25 1 3.57 4 0
   4 │ 20 10.7 1 1 535.5 107.1 1 3.57 4 0
   5 │ 20 15.7 1 1 3727.08 128.52 1 3.57 4 0
   6 │ 20 17.6167 0 0 missing missing 1 3.57 4 0
   7 │ 20 17.7333 0 0 missing missing 1 3.57 4 0
   8 │ 20 23.95 0 0 missing missing 1 3.57 4 0
   9 │ 20 25.9 0 0 missing missing 1 3.57 4 0
  10 │ 20 41.8667 0 0 missing missing 1 3.57 4 0
  11 │ 20 43.95 0 0 missing missing 1 3.57 4 0
  12 │ 20 44.7 1 1 835.38 139.23 1 3.57 4 0
  13 │ 20 49.9833 0 0 missing missing 1 3.57 4 0
  14 │ 20 50.7 1 1 3070.2 153.51 1 3.57 4 0
  15 │ 20 65.7833 0 0 missing missing 1 3.57 4 0

```

I am not able to identify any red flag. Also, as I mentioned previously, I did not experience this issue when using the closed form solution or when I fitted the data using another software. Also, I get the same warning even when running simulations.  
Could this issue happen since there are close times like 1.36 and 1.7 when using ODE? thanks

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [September 18, 2022, 8:06pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/6 "2022-09-18T20:06:52Z")

</div>

It’s a bit special that the infusions are back-to-back. We’ll try to see if we can reproduce the issue with a similar regimen.

In the other software, do you happen to know how the ODE was solved? Numerical integration or matrix exponential?

---

<div class="post-metadata">

**Author:** ![patrick](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/patrick/32/206_2.png) [@patrick](https://discourse.pumas.ai/u/patrick)\
**Post date:** [September 18, 2022, 8:12pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/7 "2022-09-18T20:12:05Z")

</div>

t is in an exp function call in the pre block, I don’t think any software would be able to use matrix exponentials, would it?

---

<div class="post-metadata">

**Author:** ![andreasnoack](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/andreasnoack/32/22_2.png) [@andreasnoack](https://discourse.pumas.ai/u/andreasnoack)\
**Post date:** [September 18, 2022, 8:19pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/8 "2022-09-18T20:19:59Z")

</div>

In NONMEM, you can refer to time in the PK block, but it will be considered piece-wise constant between events which allows for using the matrix exponential. Other software packages might use a similar interpretation.

---

<div class="post-metadata">

**Author:** ![ahmed.salem](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@ahmed.salem](https://discourse.pumas.ai/u/ahmed.salem)\
**Post date:** [September 18, 2022, 8:34pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/9 "2022-09-18T20:34:26Z")

</div>

> [@andreasnoack](#):
>
> Numerical integration or matrix exponential

I am not sure about the ODE solver type. But one thing to note is that the other software has only one option to use SAEM algorithm but I used FOCEI in Pumas but still this issue happen even when I do simulations so I think it is due to the ODE solver when including this subject in the data.

---

<div class="post-metadata">

**Author:** ![patrick](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/patrick/32/206_2.png) [@patrick](https://discourse.pumas.ai/u/patrick)\
**Post date:** [September 19, 2022, 7:34am UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/10 "2022-09-19T07:34:04Z")

</div>

I was able to recreate locally. Let me try to figure out what is required for this to run. The issue is related to the fact that infusions stop just as another one starts. I’ll return when I have further information 🙂

---

<div class="post-metadata">

**Author:** ![patrick](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pumas.ai/patrick/32/206_2.png) [@patrick](https://discourse.pumas.ai/u/patrick)\
**Post date:** [September 19, 2022, 11:37am UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/11 "2022-09-19T11:37:07Z")

</div>

Okay, so what you’re hitting is the age old problem of computers having to represent numbers. Long story short, you never have full precession in calculations on a computer, so for example 0.2+0.1 ends up not being 0.3

```auto
julia> 0.2+0.1
0.30000000000000004

```

Something similar is happening here. You can mitigate it by adding an ever so slightly small number to your rates, such that the infusion ends a very short time earlier. For example you can add 1e-8 to your subject’s rates, and it works.

```auto
df=DataFrame(:ID=>fill(20, 15), :dv=>fill(missing,15), :time=>[0.0,1.36667,1.7,10.7,15.7,17.6167,17.7333,23.95,25.9,41.8667,43.95,44.7,49.9833,50.7,65.7833], :evid=>[1,0,1,1,1,0,0,0,0,0,0,1,0,1,0],:AMT=>[121.38,missing, 803.25,535.5,3727.08,missing,missing,missing,missing,missing,missing,835.38,missing,3070.2,missing], :RATE=>[71.4+1e-8,missing,89.25+1e-8,107.1+1e-8,128.52+1e-8,missing,missing,missing,missing,missing,missing,139.23+1e-8,missing,153.51+1e-8,missing], :cmt=>fill(1,15),:WT=>fill(3.57,15), :ECMO_DAYS=>fill(4,15),:IS_CIRCUIT_CHANGE=>fill(0,15))

sub = read_pumas(ans, id=:ID, time=:time, evid=:evid, amt=:AMT, rate=:RATE, cmt=:cmt, covariates=[:WT, :ECMO_DAYS, :IS_CIRCUIT_CHANGE])

mod = @model begin
        @param begin
            TVCL ∈ RealDomain(lower = 0.0001)
            tvKTV ∈ RealDomain(lower = 0.0001)
            TVVc ∈ RealDomain(lower = 0.0001) 
            wt_cl ∈ RealDomain(upper = 2)
            wt_v ∈ RealDomain(upper = 2)
            circuit ∈ RealDomain(lower = 0.0001)
            ecmo ∈ RealDomain()
            Ω ∈ PDiagDomain(3)
            σ_add ∈ RealDomain(lower = 0.00001)
            σ_prop ∈ RealDomain(lower = 0.00001)
        end
        @random begin
            η ~ MvNormal(Ω)
        end
        @covariates WT IS_CIRCUIT_CHANGE ECMO_DAYS
        @pre begin
            KTV = tvKTV*exp(η[1])*(ECMO_DAYS/6)^ecmo
            CL = TVCL * exp(η[2])*(1-exp(-KTV*(t)))*(WT/50)^wt_cl*circuit^IS_CIRCUIT_CHANGE
            Vc = TVVc * exp(η[3])*(WT/50)^wt_v
      
        end
        @dynamics begin
                Central' = -(CL/Vc) * Central
        end 
      
        @derived begin
            CP = @. Central / Vc
            CONC = @. Normal(abs(CP), sqrt(CP^2*σ_prop+σ_add))
        end
end

julia> simobs(mod, sub, init_params(mod))

```

Hope this helps. Please ask if you need a clarification.

---

<div class="post-metadata">

**Author:** ![ahmed.salem](https://avatars.discourse-cdn.com/v4/letter/a/858c86/32.png) [@ahmed.salem](https://discourse.pumas.ai/u/ahmed.salem)\
**Post date:** [September 19, 2022, 12:35pm UTC](https://discourse.pumas.ai/t/recalling-time-in-the-pre-block-t/759/12 "2022-09-19T12:35:27Z")

</div>

I see, I tried yesterday to round the times also and I was able to get the estimation process to work including the whole dataset. So, I believe that what you are proposing makes sense. Also, I will try to add these little values to the infusions and will let you know. Thanks so much!