Language: en

1.2.0
1.2.1
1.2.2
Documentation version: 1.2.3

HTML Summary Links

PoPy outputs HTML summaries of fit_scripts, gen_scripts and tut_scripts.

This page lists the summary outputs for all example scripts used in this documentation. Browse this list to see the variety of PK/PD modelling available in PoPy.

Note, each summary contains a link to the original script. e.g. A tut summary contains a link to the original Tut Script, so you can download each script and re-run all of the examples on this page using your own installation of PoPy. You can also adapt each example script to your own PK/PD modelling requirements.

Example Summaries

Simple Fit Example

Used in Fitting a Simple PopPK Model using PoPy to demonstrate running a Fit Script.

Note

Summary file: Simple Fit Example

Simple Tut Example

Used in Generate data and Fit using Simple PopPK Model to demonstrate running a Tut Script.

Note

Summary file: Simple Tut Example

First order absorption model with peripheral compartment

Used in Fitting a Two Compartment PopPK Model to demonstrate running a Fit Script.

Note

Summary file: First order absorption model with peripheral compartment

First order absorption model with peripheral compartment

Used in Generate a Two Compartment PopPK Data Set to demonstrate running a Gen Script.

Note

Summary file: First order absorption model with peripheral compartment

Note

Example Data: synthetic_data.csv

First order absorption model with peripheral compartment

Used in Generate data and Fit using a Two Compartment Model to demonstrate running a Tut Script.

Note

Summary file: First order absorption model with peripheral compartment

Individual Model Summaries

Elimination Example with KE parameter

Used in Elimination, Clearance and Volume of Distribution to demonstrate elimination with the elimination rate constant, KE.

Note

Summary file: Elimination Example with KE parameter

Elimination Example with Volume of Distribution

Used in Volume of Distribution to demonstrate elimination with the apparent volume of distribution, V.

Note

Summary file: Elimination Example with Volume of Distribution

Elimination Example with Clearance

Used in Clearance to demonstrate elimination with clearance, CL.

Note

Summary file: Elimination Example with Clearance

One Compartment Model with Intravenous Dosing

Used in One Compartment Model with Intravenous Dosing to demonstrate a one compartment model with intravenous dosing.

Note

Summary file: One Compartment Model with Intravenous Dosing

One Compartment Model with Absorption

Used in One Compartment Model with Absorption to demonstrate a one compartment model with absorption.

Note

Summary file: One Compartment Model with Absorption

Two Compartment Model with Intravenous Dosing

Used in Two Compartment Model with Intravenous Dosing to demonstrate a two compartment model with intravenous dosing.

Note

Summary file: Two Compartment Model with Intravenous Dosing

Two Compartment Model with Absorption

Used in Two Compartment Model with Absorption to demonstrate a two compartment model with absorption.

Note

Summary file: Two Compartment Model with Absorption

Three Compartment Model with Intravenous Dosing

Used in Three Compartment Model with Intravenous Dosing to demonstrate a three compartment model with intravenous dosing.

Note

Summary file: Three Compartment Model with Intravenous Dosing

Three Compartment Model with Absorption

Used in Three Compartment Model with Absorption to demonstrate a three compartment model with absorption.

Note

Summary file: Three Compartment Model with Absorption

Bolus Dose with no elimination.

Used in Bolus Dose to demonstrate a single bolus dose with no elimination.

Note

Summary file: Bolus Dose with no elimination.

Infusion Duration Dose with no elimination.

Used in Infusion Duration to demonstrate a single infusion dose parametrised by duration, with no elimination.

Note

Summary file: Infusion Duration Dose with no elimination.

Infusion Rate Dose with no elimination.

Used in Infusion Rate to demonstrate a single infusion dose parametrised by rate, with no elimination.

Note

Summary file: Infusion Rate Dose with no elimination.

Gamma Dose with no elimination.

Used in Gamma Dose to demonstrate a single gamma dose with no elimination.

Note

Summary file: Gamma Dose with no elimination.

Weibull Dose with no elimination.

Used in Weibull Dose to demonstrate a single weibull dose with no elimination.

Note

Summary file: Weibull Dose with no elimination.

Repeated Bolus Dose with first order elimination.

Used in Repeated Dosing to demonstrate a repeated bolus dose with first order elimination.

Note

Summary file: Repeated Bolus Dose with first order elimination.

Repeated Infusion Duration Dose with first order elimination.

Used in Repeated Dosing to demonstrate a repeated infusion duration dose with first order elimination.

Note

Summary file: Repeated Infusion Duration Dose with first order elimination.

Repeated Infusion Rate Dose with first order elimination.

Used in Repeated Dosing to demonstrate a repeated infusion rate dose with first order elimination.

Note

Summary file: Repeated Infusion Rate Dose with first order elimination.

Repeated Gamma Dose with first order elimination.

Used in Repeated Dosing to demonstrate a repeated gamma dose with first order elimination.

Note

Summary file: Repeated Gamma Dose with first order elimination.

Repeated Weibull Dose with first order elimination.

Used in Repeated Dosing to demonstrate a repeated weibull dose with first order elimination.

Note

Summary file: Repeated Weibull Dose with first order elimination.

Model containing additive error only and additive error only input data

Tut script used in Residual Error Model to demonstrate additive noise only model.

Note

Summary file: Model containing additive error only and additive error only input data

Model containing proportional error only, with proportional only data

Tut script used in Residual Error Model to demonstrate proportional noise only model.

Note

Summary file: Model containing proportional error only, with proportional only data

Model containing both proportional and additive error

Tut script used in Residual Error Model to demonstrate proportional and additive noise model.

Note

Summary file: Model containing both proportional and additive error

Mixed error model fitted to mixed error data, but with incorrect variance definition

Fit script used in Residual Error Model to demonstrate fitting mis-specified proportional and additive noise model to proportional and additive noise synthetic data.

Note

Summary file: Mixed error model fitted to mixed error data, but with incorrect variance definition

Sine circadian model

Used in Example DERIVATIVES using x[TIME] to demonstrate a PK/PD model with a circadian input function for a single individual.

Note

Summary file: Sine circadian model

Direct PD Model

Used in Example DERIVATIVES for PD Model to demonstrate an individual PK/PD model with a bolus dose, one compartment PK and single PD compartment.

Note

Summary file: Direct PD Model

Direct PD Model Simultaneous PK/PD Parameter fit

Used in Example PREDICTIONS for PD Model to demonstrate an individual PK/PD model with a bolus dose, one compartment PK and single PD compartment.

Note

Summary file: Direct PD Model Simultaneous PK/PD Parameter fit

One Compartment Model with Absorption estimating KA

Used in Uncertainty and Standard Errors to show how we estimate confidence in a single parameter problem.

Note

Summary file: One Compartment Model with Absorption estimating KA

One Compartment Model with Absorption estimating KA and V

Used in Uncertainty and Standard Errors to show how we estimate confidence in a two parameter problem.

Note

Summary file: One Compartment Model with Absorption estimating KA and V

One Compartment Model with Absorption estimating KA and CL

Used in Uncertainty and Standard Errors to show how we estimate confidence in a two parameter problem.

Note

Summary file: One Compartment Model with Absorption estimating KA and CL

One Compartment Model with Absorption estimating V and CL

Used in Uncertainty and Standard Errors to show how we estimate confidence in a two parameter problem.

Note

Summary file: One Compartment Model with Absorption estimating V and CL

One Compartment Model with Absorption estimating KA, V and CL

Used in Uncertainty and Standard Errors to show how we estimate confidence in a three parameter problem.

Note

Summary file: One Compartment Model with Absorption estimating KA, V and CL

Population Model Summaries

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

Used in Inter-Subject Variation (ISV) to demonstrate inter-subject (or between-subject) variability.

Note

Summary file: One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.01

Used in Inter-Subject Variation (ISV) to demonstrate inter-subject (or between-subject) variability.

Note

Summary file: One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.01

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.5

Used in Inter-Subject Variation (ISV) to demonstrate inter-subject (or between-subject) variability.

Note

Summary file: One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.5

One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0

Used in Inter-Subject Variation (ISV) to demonstrate inter-subject (or between-subject) variability.

Note

Summary file: One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.2

Used in Inter-Occasion Variation (IOV) to demonstrate inter-occasion (or between-occasion) variability.

Note

Summary file: One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.2

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

Used in Inter-Occasion Variation (IOV) to demonstrate inter-occasion (or between-occasion) variability.

Note

Summary file: One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

Used in Inter-Occasion Variation (IOV) to demonstrate inter-occasion (or between-occasion) variability.

Note

Summary file: One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

Diagonal matrix generation diagonal matrix fit using separate univariate normals

Used in Modelling Correlation in Random Effects to demonstrate correlation between random effects.

Note

Summary file: Diagonal matrix generation diagonal matrix fit using separate univariate normals

Diagonal matrix generation diagonal matrix fit

Used in Modelling Correlation in Random Effects to demonstrate correlation between random effects.

Note

Summary file: Diagonal matrix generation diagonal matrix fit

Diagonal matrix generation full matrix fit

Used in Modelling Correlation in Random Effects to demonstrate correlation between random effects.

Note

Summary file: Diagonal matrix generation full matrix fit

Full matrix generation diagonal matrix fit

Used in Modelling Correlation in Random Effects to demonstrate correlation between random effects.

Note

Summary file: Full matrix generation diagonal matrix fit

Full matrix generation full matrix fit

Used in Modelling Correlation in Random Effects to demonstrate correlation between random effects.

Note

Summary file: Full matrix generation full matrix fit

Body Weight Covariate

Used in Covariates to demonstrate using weight as a covariate.

Note

Summary file: Body Weight Covariate

Depot + One compartment PK with BLQ

Used in Generate BLQ observations and fit different error models to demonstrate using ~rectnorm() distribution to model observations below LLQ.

Note

Summary file: Depot + One compartment PK with BLQ

Depot One Comp PK with BLQ observations set to LLQ

Used in Generate BLQ observations and fit different error models to demonstrate replacing BLQ observations with LLQ.

Note

Summary file: Depot One Comp PK with BLQ observations set to LLQ

Depot One Comp PK with BLQ observations set to 0.5*LLQ

Used in Generate BLQ observations and fit different error models to demonstrate replacing BLQ observations with 0.5*|llq|.

Note

Summary file: Depot One Comp PK with BLQ observations set to 0.5*LLQ

Depot One Comp PK ignoring BLQ observations.

Used in Generate BLQ observations and fit different error models to demonstrate removing BLQ observations from data set.

Note

Summary file: Depot One Comp PK ignoring BLQ observations.

Glossary

Troubleshooting

Documentation

HTML Summary Links

Example Summaries

Simple Fit Example

Simple Tut Example

First order absorption model with peripheral compartment

First order absorption model with peripheral compartment

First order absorption model with peripheral compartment

Individual Model Summaries

Elimination Example with KE parameter

Elimination Example with Volume of Distribution

Elimination Example with Clearance

One Compartment Model with Intravenous Dosing

One Compartment Model with Absorption

Two Compartment Model with Intravenous Dosing

Two Compartment Model with Absorption

Three Compartment Model with Intravenous Dosing

Three Compartment Model with Absorption

Bolus Dose with no elimination.

Infusion Duration Dose with no elimination.

Infusion Rate Dose with no elimination.

Gamma Dose with no elimination.

Weibull Dose with no elimination.

Repeated Bolus Dose with first order elimination.

Repeated Infusion Duration Dose with first order elimination.

Repeated Infusion Rate Dose with first order elimination.

Repeated Gamma Dose with first order elimination.

Repeated Weibull Dose with first order elimination.

Model containing additive error only and additive error only input data

Model containing proportional error only, with proportional only data

Model containing both proportional and additive error

Mixed error model fitted to mixed error data, but with incorrect variance definition

Sine circadian model

Direct PD Model

Direct PD Model Simultaneous PK/PD Parameter fit

One Compartment Model with Absorption estimating KA

One Compartment Model with Absorption estimating KA and V

One Compartment Model with Absorption estimating KA and CL

One Compartment Model with Absorption estimating V and CL

One Compartment Model with Absorption estimating KA, V and CL

Population Model Summaries

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.2

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.01

One Compartment Model with Absorption and Inter-subject Variance f[CL_isv]=0.5

One Compartment Model with Absorption and no inter-subject Variance f[CL_isv]=0

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.2

One Compartment Model with Absorption and Inter-occasion Variance f[CL_isv]=0.5

One Compartment Model with Absorption and no inter-occasion Variance f[CL_iov]=0

Diagonal matrix generation diagonal matrix fit using separate univariate normals

Diagonal matrix generation diagonal matrix fit

Diagonal matrix generation full matrix fit

Full matrix generation diagonal matrix fit

Full matrix generation full matrix fit

Body Weight Covariate

Depot + One compartment PK with BLQ

Depot One Comp PK with BLQ observations set to LLQ

Depot One Comp PK with BLQ observations set to 0.5*LLQ

Depot One Comp PK ignoring BLQ observations.

Additional Information

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