# 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] = 0.5
    f[CL] = 1
    f[V] = 15
    f[ANOISE_STD] = 5
    f[BIO] = 1
    f[LAG] = 1

## Outputs

### Final objective value

    39.6302527643

which required 5 iterations and took 0.55 seconds

### Final fitted fixed effects

    f[KA] = 0.40372
    f[CL] = 2.6242
    f[V] = 16.151
    f[ANOISE_STD] = 0.90054
    f[BIO] = 1
    f[LAG] = 0.0016458

### 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] | 0.403719 | 0.5 | 0.192562 | 0.096281
f[CL] | 2.62417 | 1 | 1.62417 | 1.62417
f[V] | 16.151 | 15 | 0.0767324 | 1.15099
f[BIO] | 1 | 1 | 0 | 0
f[LAG] | 0.00164579 | 1 | 0.998354 | 0.998354

### Compare Noise f[X]

Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[ANOISE_STD] | 0.900542 | 5 | 0.819892 | 4.09946

### Compare Variance f[X]