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Contents

  • Learning Paths
    • Getting Started with the Learning Paths
      • How to Use the Learning Paths
    • Path 1: Julia Fundamentals for Pumas
      • Module 1: Introduction to Julia
      • Module 2: Data Wrangling and Visualization in Julia
    • Path 2: Pumas Fundamentals of Data and Model Structure
      • Module 3: Introduction to Pumas
      • Module 4: Population PK and PK/PD Modeling with Pumas
    • Path 3: Pumas Fundamentals of Model Development
      • Module 5: Structural Model Definitions
      • Module 6: Absorption Models
      • Module 7: Random Effect Models
      • Module 8: Error Models
      • Module 9: Covariate Model Definitions
    • Path 4: Pumas Fundamentals of Model Simulation
      • Module 10: Simulations in Pumas
      • Module 11: Visual Predictive Checks
    • Path 5: Pumas Workflows
      • Module 12: Covariate Modeling
      • Module 13: Censored Data Modeling
    • Path 6: Reporting in Pumas
      • Module 14: Reporting
  • Tutorials Catalog
    • Julia
      • Fundamentals
      • Data Wrangling
      • Plotting
    • Pumas
      • Introduction
      • Advanced Topics
      • From NONMEM to Pumas
      • Introduction Tutorials to PKPD modeling in Pumas
      • Simulations
      • Discrete Response Models
      • Covariate Selection Methods
      • Forests Plots
      • Bayesian Models
      • Plot Customization
      • Reporting
    • PK Modeling
      • Introduction to PK Modeling
      • Oral Absorption & Bioavailability
      • Multi-Compartment & Complex Dosing
      • Nonlinear & Special Kinetics
      • Physiological & Drug-Specific Models
      • Population & Clinical PK
    • DeepPumas
    • AI for Drug Development
  • Previous Versions of Pumas

Learning Paths

Getting Started with the Learning Paths

  • The Learning Paths are designed to help you navigate through the Pumas ecosystem. Each path consists of a series of modules that cover different aspects of using Pumas, from the fundamentals of Julia programming to advanced modeling techniques.
  • The paths are structured to provide a comprehensive learning experience, allowing you to build your knowledge progressively. You can choose to follow a specific path or explore individual modules based on your interests and needs.
  • The paths are designed to be flexible, allowing you to learn at your own pace and focus on the areas that are most relevant to you. Whether you are a beginner or an experienced user, the Learning Paths will help you gain the skills and knowledge needed to effectively use Pumas for your modeling and simulation needs.

How to Use the Learning Paths

  • How to run Pumas tutorials using Quarto and Julia

Path 1: Julia Fundamentals for Pumas

Module 1: Introduction to Julia

  • Getting Started
  • Types
  • Strings
  • Data Structures
  • Programming Constructs
  • Variable Scoping
  • Exercises
  • Solutions

Module 2: Data Wrangling and Visualization in Julia

  • Specifying Directories
  • Reading and Writing Data
  • DataFrames
  • Arrays and Vectors
  • Wrangling DataFrames
  • Categorical Variables
  • Date/Time Variables
  • Plotting and Data Visualization
  • Exercises

Path 2: Pumas Fundamentals of Data and Model Structure

Module 3: Introduction to Pumas

  • Pumas’ Capabilities and Features
  • Installation, Access and Setup

Module 4: Population PK and PK/PD Modeling with Pumas

  • Data Representation
  • Model Representation
  • Model Representation Using Latexify
  • Compartmental PK Models
  • Parameter Estimation and Estimating Parameter Uncertainty
  • Interpretation of Pumas Model Output
  • Model Diagnostics and Evaluation
  • Bootstrap and Sampling Importance Resampling
  • Sequential and Simultaneous PKPD Models
  • Comparison to NONMEM for NONMEM Users (see from NONMEM to Pumas)

Path 3: Pumas Fundamentals of Model Development

Module 5: Structural Model Definitions

  • Differential Equations
  • Analytical Solutions
  • Statistical Models Without Differential Equations

Module 6: Absorption Models

  • Bioavailability
  • First-Order Absorption
  • Zero-Order Absorption
  • Delayed Absorption
  • Combined First- and Zero-Order Absorption

Module 7: Random Effect Models

  • Understanding Normal vs LogNormal for Modeling PK Parameters
  • Between Subject Variability
  • Understanding Interoccasion Variability (IOV) Modeling in Pumas
  • Understanding Correlated Interoccasion Variability (IOV) Modeling in Pumas
  • Non-Gaussian Random Effect

Module 8: Error Models

  • Residual Unexplained Variability
  • Non-Gaussian Distribution Models

Module 9: Covariate Model Definitions

  • Defining Covariates
  • Covariate Model Parameterization
  • Comparing Nested Models with the Likelihood Ratio Test

Path 4: Pumas Fundamentals of Model Simulation

Module 10: Simulations in Pumas

  • Reproducibility when doing Simulations
  • Creating Populations
  • Simulating Scenarios
  • Simulations Incorporating Parameter Uncertainty
  • Exposure Metrics Generated from Simulations for Exposure-Response Analyses
  • Steady-State Modeling

Module 11: Visual Predictive Checks

  • Simulations for VPCs
  • Plotting VPCs
  • Prediction-Corrected VPCs
  • VPCs of Derived Endpoints

Path 5: Pumas Workflows

Module 12: Covariate Modeling

  • Automated Stepwise Covariate Modeling
  • Forest Plots
  • Lasso-Based Covariate Selection

Module 13: Censored Data Modeling

  • Concentrations Below the Lower Limit of Quantification

Path 6: Reporting in Pumas

Module 14: Reporting

  • Run Reports
  • Quarto in Pumas
  • Summary Tables using SummaryTables.jl
  • Report/Publication-Ready Parameter Estimate Tables
  • Run Listings for Pumas Models
  • Submission-Ready Reports with Typst/Quarto

Tutorials Catalog

Julia

Fundamentals

  • Getting Started with Julia
  • Julia Syntax
  • Functions
  • Strings

Data Wrangling

  • Reading and Writing Data
  • How to Handle XPT Files
  • Manipulating DataFrames
  • Reshaping DataFrames
  • Handling Factors and Categorical Data
  • Handling NAs and Missing Values
  • Handling Dates and Times

Plotting

  • Introduction to AlgebraOfGraphics.jl
  • Grammar of Graphics with AlgebraOfGraphics.jl
  • Geometries
  • Statistical Visualizations
  • Plot Customization
  • Using Wide Data Formats
  • Advanced Layouts
  • Inserting Custom Vertical/Horizontal Lines
  • Add Text Labels
  • Adjusting Legend Markers
  • Empirical Cumulative Density Function Plots

Pumas

Introduction

  • Introduction to Pumas
  • Fitting models with Pumas
  • Covariate models
  • Introduction to Noncompartmental Analysis
  • Introduction to Superposition in Pumas
  • Introduction to Optimal Design

Advanced Topics

  • Absorption Models

From NONMEM to Pumas

  • Comparing NONMEM and Pumas models
  • NONMEM style BQL models (M1-M4) in Pumas
  • Translation from NONMEM to Pumas of “Case Study I: Building a Covariate Model”
  • Translation from NONMEM to Pumas of “Case Study II: Building a PopPK model with multiple doses”
  • Translation from NONMEM to Pumas of “Case Study III: Development of a population PKPD model”

Introduction Tutorials to PKPD modeling in Pumas

  • Case Study I: Building a Covariate Model
  • Case Study II: Building a PopPK model with multiple doses
  • Case Study III: Development of a population PKPD model

Simulations

  • Generating and Simulating Populations
  • Reproducibility when doing Simulations
  • Multivariate Covariate Simulations in Pumas with Copulas.jl

Discrete Response Models

  • Logistic Regression
  • Ordinal Regression
  • Poisson Regression
  • Negative Binomial Regression
  • Time to Event Models

Covariate Selection Methods

  • Introduction to Covariate Selection Methods
  • Forward Selection
  • Backward Elimination
  • Mixed Covariate Selection Methods
  • Running in a Distributed Batch Job

Forests Plots

  • A Forest Plot Workflow in Pumas

Bayesian Models

  • Introduction to Bayesian Models in Pumas
  • Random Effects in Bayesian Models
  • Posterior Postprocessing - Plots and Queries
  • Markov Chain Monte Carlo Convergence
  • Model Comparison with Crossvalidation
  • Fitting Non-Identifiable Models

Plot Customization

  • Plot customization for Noncompartmental analysis - Single dose
  • Plot customization for Noncompartmental analysis - Multiple dose

Reporting

  • Creating tables with SummaryTables.jl
  • Generated quarto documents with QuartoTools

PK Modeling

Introduction to PK Modeling

  • PK1: One-compartment intravenous bolus dosing

  • PK2: One-compartment oral dosing

  • PK3: One-compartment 1st and 0-order input

  • PK5: One-compartment intravenous plasma/urine I

  • PK6: One-compartment intravenous plasma/urine II

  • PK8: Two compartment distribution models

  • PK16: Two-compartment intravenous plasma/urine

  • PK38: Invitro/Invivo Extrapolation II

Oral Absorption & Bioavailability

  • PK04 (Part 1): One-compartment oral dosing
  • PK04 (Part 2): One-compartment oral dosing
  • PK9: Modeling of fraction absorbed and nonlinear bioavailability across the liver
  • PK10: Simultaneous fitting of IV/PO data
  • PK42: Saturable absorption via transporters

Multi-Compartment & Complex Dosing

  • PK12: Intravenous and oral dosing
  • PK13: Bolus plus constant rate infusion
  • PK14: Multi-compartment model oral dosing
  • PK41: Multiple intravenous infusions – NCA versus regression
  • PK43: Multiple absorption routes
  • PK46: Long infusion and short half-life

Nonlinear & Special Kinetics

  • PK17: Nonlinear Kinetics (Capacity I-IV, Flow, Hetero/Autoinduction)

  • PK18: Capacity II - Ethanol kinetics

  • PK19: Two compartment with limited capacity metabolite model

  • PK20: One-compartment model with capacity limited elimination for IV bolus

  • PK21: Heteroinduction model

  • PK22: Non-linear Kinetics - Autoinduction

  • PK24: Non-linear Kinetics - Flow II

  • PK48: One-compartment Michaelis-Menten kinetics - Drug and metabolite in urine

Physiological & Drug-Specific Models

  • PK26: Target mediated drug disposition
  • PK27: Allometry - Elementary & Complex Dedrick plot
  • PK30: Turnover I - SC Dosing of Hormone
  • PK31: Turnover II - Intravenous Dosing of Hormone
  • PK32: Turnover III - Non-linear Disposition
  • PK33: Transdermal input and kinetics
  • PK34: Reversible metabolism
  • PK40: Enterohepatic recirculation
  • PK45: Reversible metabolism of drug A and its metabolite B
  • PK47: Plasma protein binding modeling
  • PK49: Turnover IV - Factor II data in healthy volunteers
  • PK52: Simulated impact of disease on r-hSOD kinetics

Population & Clinical PK

  • PK50: Analysis of multiple subjects concentration and response-time profiles
  • PK51: Multi-compartment drug/metabolite
  • PK53: Linear antibody kinetics

DeepPumas

  • Getting started with DeepPumas
  • Discovery of complex feedback in a neural-embedded Friberg model using real world data
  • DeepPumas Epidemiology: force-of-infection across heterogeneous countries

AI for Drug Development

  • Machine Learning Fundamentals

Previous Versions of Pumas

  • Pumas 2.5