# Bioavailability and Lag

[Generated automatically as a Fitting summary]

## Inputs

### Description

Name: | biolag_abs_bio
Title: | Bioavailability and Lag
Author: | Wright Dose Ltd
Abstract: |

One compartment model absorption dosing with bioavailability and lag parameters.

Keywords: | identifiability; bioavailability; lag
Input Script: | `biolag_abs_bio_fit.pyml`
Input Data: | `synthetic_data.csv`
Diagram: |

### Initial fixed effect estimates

    f[KA] = 0.5000
    f[CL] = 1.0000
    f[V] = 15.0000
    f[ANOISE_STD] = 5.0000
    f[BIO] = 1.0000
    f[LAG] = 1.0000

## Outputs

### Final objective value

    61.1707

which required 7 iterations and took 0.33 seconds

### Final fitted fixed effects

    f[KA] = 1.0000
    f[CL] = 9.8757
    f[V] = 99.4422
    f[ANOISE_STD] = 1.1184
    f[BIO] = 1.0000
    f[LAG] = 17330305271811044994732808569468172962138947584.0000

### Fitted parameter .csv files

Fixed Effects: | `fx_params.csv (fit)`
Random Effects: | `rx_params.csv (fit)`
Model params: | `mx_params.csv (fit)`
State values: | `sx_params.csv (fit)`
Predictions: | `px_params.csv (fit)`

## Plots

### Dense sim plots

Alternatively see All dense_sim graph plots

## Comparison

### Compare Main f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[KA] | 1.0000 | 0.5000 | 1.0000 | 0.5000
f[CL] | 9.8757 | 1.0000 | 8.8757 | 8.8757
f[V] | 99.4422 | 15.0000 | 5.6295 | 84.4422
f[BIO] | 1.0000 | 1.0000 | 0.0000 | 0.0000
f[LAG] | 17330305271800001222703620234922333683813711872.0000 | 1.0000 | 17330305271800001222703620234922333683813711872.0000 | 17330305271800001222703620234922333683813711872.0000

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[ANOISE_STD] | 1.1184 | 5.0000 | 0.7763 | 3.8816

### Compare Variance f[X]