# Direct PD Model Simultaneous PK/PD Parameter fit

[Generated automatically as a Tutorial summary]

## Model Description

Name:

  direct_pd_simul

Title:

  Direct PD Model Simultaneous PK/PD Parameter fit

Author:

  PoPy for PK/PD

Abstract:

A simple direct PD Model, based on the amount of drug in the body. That simultaneously fits PK and PD parameters.
The amount in the central compartment is determined by K, which has been previously estimated for each individual.
The amount in the central compartment influences the rate of removal of a biomarker (KOUT).

Keywords:

  pd; one compartment model; direct

Input Script:

  `direct_pd_simul_tut.pyml`

Diagram:

## Comparison

### True objective value

    -203.7595

### Final fitted objective value

    386.5798

### Compare Main f[X]

Name | Initial | Fitted | True | Abs. Error | Prop. Error
--- | --- | --- | --- | --- | ---
f[CL] | 5 | 2… | 2 | 3.76e-03 | 0.19%
f[V] | 15 | 48.2 | 50 | 1.81e+00 | 3.63%
f[BASE] | 500 | 799 | 800 | 8.03e-01 | 0.10%
f[KOUT] | 0.1 | 0.0288 | 0.03 | 1.16e-03 | 3.87%

### Compare Noise f[X]

Name | Initial | Fitted | True | Abs. Error | Prop. Error
--- | --- | --- | --- | --- | ---
f[PK_ANOISE] | 5 | 0.509 | 0.5 | 8.81e-03 | 1.76%
f[PD_ANOISE] | 5 | 8.22 | 0.3 | 7.92e+00 | 2641.53%

### Compare Variance f[X]

No Variance f[X] values to compare.

## Outputs

### Fitted f[X] values (after fitting)

    f[CL] = 2.0038
    f[V] = 48.1868
    f[BASE] = 799.1967
    f[KOUT] = 0.0288
    f[PK_ANOISE] = 0.5088
    f[PD_ANOISE] = 8.2246

### Generated data .csv file

Synthetic Data:

  `synthetic_data.csv`

### Gen and Fit Summaries

- Gen: Direct PD Model Simultaneous PK/PD Parameter fit (gen)

- Fit: Direct PD Model Simultaneous PK/PD Parameter fit (fit)

## Inputs

### True f[X] values (for simulation)

    f[CL] = 2.0000
    f[V] = 50.0000
    f[BASE] = 800.0000
    f[KOUT] = 0.0300
    f[PK_ANOISE] = 0.5000
    f[PD_ANOISE] = 0.3000

### Starting f[X] values (before fitting)

    f[CL] = 5.0000
    f[V] = 15.0000
    f[BASE] = 500.0000
    f[KOUT] = 0.1000
    f[PK_ANOISE] = 5.0000
    f[PD_ANOISE] = 5.0000