PK/PD Modeling

Introduce pharmacodynamic modeling by linking exposure to response using direct and delayed effect models.
Tip

Module goal: Learn how pharmacokinetic exposure becomes pharmacodynamic response and build the foundations of PK/PD modeling.

Module Overview

Until now, we focused primarily on pharmacokinetics.

We learned how to:

  • build population PK models
  • estimate parameters
  • describe variability
  • explain variability using covariates
  • evaluate model adequacy

Those models describe:

Dose → Concentration

But concentration is usually not the final question.

We often care about:

  • biomarker response
  • efficacy
  • toxicity
  • clinical outcome

This module introduces pharmacodynamics (PD).

PD extends the workflow into:

Dose → PK → PD

The goal is no longer only describing exposure.

The goal becomes understanding response.

Learning Objectives

By the end of this module, you will be able to:

  • explain the difference between PK and PD
  • describe direct and delayed response models
  • understand the concept of multiple endpoints
  • interpret common PK/PD parameters
  • introduce ODE thinking for delayed response
  • connect PK models to response prediction

Lessons in This Module

Lesson 1: What Is PK/PD Modeling?

Introduce pharmacodynamics and explain how exposure becomes response.

Topics:

  • PK versus PD
  • multiple endpoints
  • exposure-response relationships
  • warfarin overview

Lesson 2: Direct Effect Models

Introduce response models where concentration directly drives effect.

Topics:

  • linear effect model
  • Emax model
  • EC50
  • saturation
  • simple simulations

Lesson 3: Delayed Response and ODE Intuition

Introduce delayed response behavior and the idea of rates of change.

Topics:

  • response delay
  • turnover
  • basic ODE intuition
  • indirect response concepts

Lesson 4: Joint PK/PD Modeling

Introduce simultaneous PK and PD thinking.

Topics:

  • PK endpoint
  • PD endpoint
  • multiple endpoints
  • linking exposure and response
  • warfarin example

Lesson 5: Interpreting PK/PD Models

Interpret parameters and understand how models explain response.

Topics:

  • Emax
  • EC50
  • kin
  • kout
  • parameter interpretation

Software Used

This module continues using nlmixr2.

library(tidyverse)
library(nlmixr2)
library(nlmixr2data)

We will continue using:

  • ggplot2
  • nlmixr2
  • simple simulation workflows

Dataset Used

This module introduces a PK/PD dataset.

Conceptually:

Subject → PK Endpoint + PD Endpoint

Unlike earlier modules, each subject may contribute multiple outcome types.

Examples include:

  • concentration measurements
  • response measurements

This introduces the idea of multiple endpoints.

Conceptual Workflow

Population PK focused on:

Dose → Concentration

PK/PD extends this:

Dose → Concentration → Response

Response may occur:

  • immediately
  • gradually
  • indirectly

This motivates new model structures.

How This Module Connects to Previous Modules

Previous modules asked:

What exposure occurred?

This module asks:

What response occurred?

Population PK remains important.

PK/PD builds on it.

Conceptually:

Structure → Variability → Covariates → Diagnostics → Response

What This Module Does Not Do

This module does not focus on:

  • advanced multiple-endpoint workflows
  • TMDD
  • Bayesian PK/PD
  • PBPK
  • QSP
  • advanced mechanistic systems

Those belong in later specialized courses.

This module focuses on foundations.

Expected Outputs

By the end of this module, you should be able to:

  • describe PK/PD relationships
  • interpret direct and delayed response
  • recognize multiple endpoints
  • explain basic ODE thinking
  • connect exposure to response

Next Step

Start with Lesson 1 to understand how concentration becomes response.