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Course details

  • Duration

    40 h 0 m
  • Language

    English

(201-OD) Intermediate Population Modeling using Phoenix NLME

Cost - $1,440 (Academia $720)

This course will help you fill the gaps to become a better Population Pharmacokinetic and Pharmacodynamic (PK/PD) modeler.  This e-learning course focuses on Population PK/PD modeling and simulation using the intuitive interface of Phoenix NLME.   This course topics include: population PK analysis with covariates, covariate search methods, complex PK models including multiple absorption processes and parent-metabolite models, Emax PK/PD models, an introduction to categorical response PD models, and modeling BLQ data in Phoenix NLME. 

The concepts of each topic are explained in detail via instructional videos. Exercises are introduced and you are expected to practice concepts learned by performing the exercises on your own. Step by step solution videos are also provided to check your work. Your understanding of the concepts discussed is tested via short quizzes throughout the course.

Contact info@certarauniversity.com for academic discount

Software Used

Phoenix NLME

 A temporary license is provided to subscribers of this course.

Accessing the Course

After registering for this course, login to www.certarauniversity.com and see the course under the Catalog Section ‘My Courses’. 

You will have access to this course for a period of 3 years after the purchase.

The purchase is for a single seat in the course. No sharing the login between different individuals is allowed. Additional seats must be purchased if more than one person wishes to take the training course.

Course Length: 

The course provides approximately 10 hours of video instruction which includes a practical component that you can do at your own pace. It is expected to take participants about 40+ hours to complete, including time to perform the tasks in Phoenix.

Prerequisites

It is assumed that learners have familiarity with individual PK/PD modeling as well as introductory level population PK/PD modeling experience. Participants should have a good background in pharmacokinetics and pharmacodynamics, and prior experience with the Phoenix is recommended. Participants should also be able to perform the tasks in both the following Certara University courses:

Instructor

Christopher Mehl

Christopher Mehl is a Senior Software Trainer with Certara University, and has been with Certara since 2003. His educational background is a BS in Molecular Biology from the Ohio State University, and an MS in Pharmacology from the University of Wisconsin. He has conducted over 200 training courses with Certara products such as Phoenix WinNonlin, IVIVC, NLME, PKS, and Trial Simulator. These include workshops at the US Food and Drug Administration, universities, customer sites, and courses open to the public.

Training material

  • Welcome!
  • Course Navigation
  • Course Materials
  • How to get help
  • Questions
  • Course Overview: Intermediate Population PKPD Modeling Using Phoenix NLME
  • Lecture: Review of Basic Compartmental Models
  • Quiz 1: Review of Compartmental Modeling
  • Lecture: Statistical Aspects of Population Analysis, Part 1
  • Lecture: Statistical Aspects of Population Analysis, Part 2
  • Quiz 2: Statistical Aspects of Population Modeling
  • Exercise 1: Pop PK Base Model
    • Instructions for Exercise 1, Part 1: Exploratory Data Analysis
    • Exercise 1: 1-Compartment IV Bolus Solution, Part 1: Exploratory Data Analysis
    • Instructions for Exercise 1, Part 2: PK Compartment Modeling
    • Exercise 1: 1-Compartment IV Bolus Solution, Part 2: Population Modeling & Comparison
  • Lecture: Covariate Modeling, Part 1: Background
  • Lecture: Covariate Modeling, Part 2: Plots & Comparisons
  • Lecture: Covariate Modeling, Part3: Covariate Search Methods
  • Quiz 3: Covariate Modeling
  • Exercise 2: Covariate Modeling
    • Exercise 2: Covariates Setup, Part 1
    • Exercise 2: Covariates Setup, Part 2
    • Instructions for Exercise 2: Population PK Covariate Search & Selection, Part 1: Exploratory Data Analysis
    • Exercise 2: Population PK Covariate Search & Selection, Solution Part 1: Exploratory Data Analysis
    • Instructions for Exercise 2: Population PK Covariate Search & Selection, Part 2: Fit a PK Compartment Model to the Individual Subject Data
    • Exercise 2: Population PK Covariate Search & Selection, Solution Part 2: Fit a PK Compartment Model to the Individual Subject Data
    • Instructions for Exercise 2: Population PK Covariate Search & Selection, Part 3: Fit a Population Base Model to the Data
    • Exercise 2: Population PK Covariate Search & Selection, Solution Part 3: Fit a Base Population PK Model to the Data
    • Instructions for Exercise 2: Population PK Covariate Search & Selection, Part 4: Perform a Stepwise Covariate Search
    • Exercise 2: Population PK Covariate Search & Selection, Solution Part 4: Perform a Stepwise Covariate Search
    • Instructions for Exercise 2: Population PK Covariate Search & Selection, Part 5: Re-run Population Model with Select Covariates and Compare Results
    • Exercise 2: Population PK Covariate Search & Selection, Solution Part 5: Re-run Population Model with Selected Covariates, Compare Results
  • Exercise 3: PK/PD Simulation with Continuous Data
    • Exercise 3: PKPD Emax Model with Continuous data: Background & Setup
    • Instructions for Exercise 3: PKPD Emax Model with Continuous data
    • Exercise 3: PKPD Emax Model with Continuous Data: Solution
  • Lecture: PK/PD Modeling Binary Outcomes; includes Background for Exercise 4
  • Quiz 4: PD Modeling of Binary Responses
  • Exercise 4: PK/PD Modeling Binary Outcomes
    • Instructions for Exercise 4, Part 1: Exploratory Data Analysis
    • Exercise 4: PKPD Modeling Binary Outcomes: Solution Part 1
    • Instructions for Exercise 4, Part 2: Fit a Model to the Placebo Logits
    • Exercise 4: PKPD Modeling Binary Outcomes: Solution Part 2
    • Instructions for Exercise 4, Part 3: Derive Initial Estimates for Emax and E50, and Fit a Combined Logit Model to the Data for All Dose Groups
    • Exercise 4: PKPD Modeling Binary Outcomes: Solution Part 3
    • Instructions for Exercise 4, Part 4: Create Additional Plots to Compare the Treatment Groups
    • Exercise 4: PKPD Modeling Binary Outcomes: Solution Part 4
  • Lecture: Modeling Multinomial Categorical Responses, Part 1
  • Lecture: Modeling Multinomial Categorical Responses, Part 2
  • Quiz 5: Multinomial Categorical Responses
  • Exercise 5: Modeling Multinomial Categorical Responses
    • Instructions for Exercise 5, Part 1: Review the Exploratory Data Analysis
    • Exercise 5: Modeling Multinomial Categorical Responses: Solution, Part 1
    • Instructions for Exercise 5, Part 2: Use Data Tools to Get Initial Estimates for the PD Parameters
    • Exercise 5: Modeling Multinomial Categorical Responses: Solution, Part 2
    • Instructions for Exercise 5, Part 3: Construct the Base Multinomial Categorical Response Model
    • Exercise 5: Modeling Multinomial Categorical Responses: Solution, Part 3
    • Instructions for Exercise 5, Part 4: Refine the Multinomial Categorical Response Model
    • Exercise 5: Modeling Multinomial Categorical Responses: Solution, Part 4
    • Instructions for Exercise 5, Part 5: Construct the Base Multinomial Categorical Response Model
    • Exercise 5: Modeling Multinomial Categorical Responses: Solution, Part 5
    • Instructions for Exercise 5, Part 6: Create Probability Plots vs Time and vs Concentration
    • Exercise 5: Modeling Multinomial Categorical Responses: Solution, Part 6
  • Lecture: Covariate Styles and Options
  • Lecture: Handling Crossover Studies and Inter-Occasion Variability (IOV) in PHX NLME
  • Quiz 6: Covariate Styles and Options
  • Exercise 6: Handling Crossover Studies and Inter-Occasion Variability (IOV)
    • Instructions for Exercise 6, Part 1: Exploratory Data Analysis
    • Exercise 6: Handling Crossover Studies and Inter-Occasion Variability (IOV) in PHX NLME: Solution, Part 1
    • Instructions for Exercise 6, Part 2: Construct the Base Pop PK Structural Model
    • Exercise 6: Handling Crossover Studies and Inter-Occasion Variability (IOV) in PHX NLME: Solution, Part 2
    • Instructions for Exercise 6, Part 3: Add a model Comparer object, and Use Reset to allow IOV Modeling
    • Exercise 6: Handling Crossover Studies and Inter-Occasion Variability (IOV) in PHX NLME: Solution, Part 3
    • Instructions for Exercise 6, Part 4: Add Period as an Inter-Occasion Covariate (IOC)
    • Exercise 6: Handling Crossover Studies and Inter-Occasion Variability (IOV) in PHX NLME: Solution, Part 4
    • Instructions for Exercise 6, Part 5: Investigate Whether there is a Formulation Effect
    • Exercise 6: Handling Crossover Studies and Inter-Occasion Variability (IOV) in PHX NLME: Solution, Part 5
  • Lecture: Graphical Model Basics and Setup for Exercise 7: IV/SC & Bioavailability
  • Exercise 7: Simultaneous Fitting of IV & SC data with Bioavailability Estimation
    • Instructions for Exercise 7, Part 1: Exploratory Data Analysis
    • Exercise 7: Graphical Model IV/SC & Bioavailability: Solution Part 1
    • Instructions for Exercise 7, Part 2: Build a Graphical Model to fit IV/SC data for all Subjects
    • Exercise 7: Graphical Model IV/SC & Bioavailability: Solution Part 2
    • Instructions for Exercise 7, Part 3: Build a Graphical Model with XF Ratio to fit IV/SC data for All Subjects
    • Exercise 7: Graphical Model IV/SC & Bioavailability: Solution Part 3
  • Exercise 8: Multiple Absorption Routes
    • Exercise 8: Multiple Absorption Routes: Setup
    • Instructions for Exercise 8, Part 1: Construct the Graphical Model
    • Exercise 8: Multiple Absorption Routes: Solution, Part 1
    • Instructions for Exercise 8, Part 2: Review Results and Refine the Model
    • Exercise 8: Multiple Absorption Routes: Solution, Part 2
  • Exercise 9: Simultaneous Modeling of Parent Drug and Multiple Metabolites
    • Exercise 9: Modeling Parent Drug and Multiple Metabolites: Setup
    • Instructions for Exercise 9, Part 1: Exploratory Data Analysis
    • Exercise 9: Modeling Parent Drug and Multiple Metabolites: Solution, Part 1
    • Instructions for Exercise 9, Part 2: Build a Graphical Model to Simultaneously Fit Parent & Metabolite Data
    • Exercise 9: Modeling Parent Drug and Multiple Metabolites: Solution, Part 2
    • Instructions for Exercise 9, Part 3: Map Input Data, Specify Initial Estimates, and Run the Model
    • Exercise 9: Modeling Parent Drug and Multiple Metabolites: Solution, Part 3
    • Instructions for Exercise 9, Part 4: Modify the Graphical Model to have Reversible Metabolite Formation
    • Exercise 9: Modeling Parent Drug and Multiple Metabolites: Solution, Part 4
  • Quiz 7: Graphical Model Interface
  • Lecture: Covariance Modeling and Interpreting the Omega Matrix (includes shrinkage)
  • Quiz 8: Covariance Modeling and Interpreting the Omega Matrix
  • Lecture: Modeling BLQ Data in Phoenix NLME
  • Quiz 9: Modeling BLQ Data in Phoenix NLME
  • Exercise 10: Modeling BLQ Data in Phoenix NLME
    • Exercise 10: Analysis of BQL Concentrations: Setup
    • Instructions for Exercise 10, Part 1: Use Data Tools to Perform BQL Replacements
    • Exercise 10: Analysis of BQL Concentrations: Solution, Part 1
    • Instructions for Exercise 10, Part 2: Model Data with BQL Set to Missing
    • Exercise 10: Analysis of BQL Concentrations: Solution, Part 2
    • Instructions for Exercise 10, Part 3: Model Data with BQL Set to LLOQ/2
    • Exercise 10: Analysis of BQL Concentrations: Solution, Part 3
    • Instructions for Exercise 10, Part 4: Model Data with BQL Replaced According to the M3 Method
    • Exercise 10: Analysis of BQL Concentrations: Solution, Part 4
    • Instructions for Exercise 10, Part 5: Compare the Best Models for Each BQL Replacement Method
    • Exercise 10: Analysis of BQL Concentrations: Solution, Part 5
  • Lecture: Visual Predictive Check (VPC) Options for Continuous Data
  • Quiz 10: Visual Predictive Check (VPC) for Continuous Data
  • Lecture: Ordinary Differential Equation (ODE) Solvers
  • Lecture: NLME Run Mode Algorithms
  • Quiz 11: Phoenix NLME Run Algorithms
  • End of On-Demand Course Survey v2
  • Thank you from Certara University Training