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What is the Difference Between Individual and Population PK?

Pharmacokinetic analysis is often broken into two areas … “PK” and “population PK”. Sometimes the first term “PK” is also called “individual PK”. I’d like to demystify these two analysis methods in this post. In the analysis of biological samples, we have many different detection technologies, for example mass spectroscopy, UV spectroscopy, radiometric detection, and immunochemistry. Each of these technologies is useful, with none being “better” than any other. They are simply tools that can be used for different types of analysis. Individual PK and population PK are simply two different analysis techniques that we use in pharmacokinetic data analysis.

Individual PK-Noncompartmental Analysis
Individual PK-Noncompartmental Analysis

Individual PK usually has the following features:

  • Noncompartmental methods
  • Use graphical techniques
  • Used for Phase I studies
  • Not useful for predictive work
  • Requires intensive sampling
  • Analysis time is short
  • Can determine
    • Maximum exposure (Cmax)
    • Total exposure (Area under the curve or AUC)
    • Clearance
    • Bioavailability
    • Volume of distribution
    • Terminal half-life (t1/2)

If the data from the individual PK profiles are adequate, the data can be fit to an model. Compartmental fits on individual data have the following features:

Individual PK - Compartmental Fit
Individual PK – Compartmental Fit
  • Compartmental analysis uses exponential equations to describe the curve
  • Accomplished by using theoretical “compartments” and the transfer rates between these compartments.
  • Can be used for simulations (limited possibilities)
  • Can determine: Clearance, bioavailability, volume of distribution, absorption rate, distribution profile, metabolic fate/conversion, terminal half-life (t1/2)

If however, you want to understand how individuals from a population differ from one another, you will need to perform population PK analysis. In this type of analysis, all data from all individuals is considered at the same time in a unified model. Population PK analysis has the following features:

Population PK
Population PK
  • Evaluates entire population
  • Can be used for predictions and simulations
  • Computationally intensive
  • Intensive and sparse sampling
  • Analysis time is longer
  • PK/PD modeling (relationship between drug levels and drug effects)
  • Can determine
    • Clearance
    • Volume of distribution
    • Effect of covariates (e.g. age, weight, sex, kidney function)
The advantages and disadvantages of each analysis method are highlighted below:
Individual PKPopulation PK
AdvantagesAdvantages
  • Simple
  • Robust
  • Model-independent
  • User-friendly software
  • Rapid
  • Robust
  • Provides structural model for PK/PD
  • Any administration schedule/route
  • Linear and Nonlinear PK supported
  • Descriptive and Predictive
  • Studies can be pooled
  • Analysis limited by imagination
DisadvantagesDisadvantages
  • Assumes linear PK
  • Model-independent
  • Single analysis, cannot address multiple doses
  • Study design often limits analysis
  • Less rapid
  • Less user-friendly software
  • More expertise required for analysis
  • Analysis limited by imagination
Hopefully you have a better understanding of the differences between the individual PK and population PK analysis techniques. Each is useful, each has its advantages and disadvantages, but neither is “better”.

Systems with distributed delays are extensions of systems with discrete delays where a single lag time is represented by a distribution of lag times. Distributed absorption times for orally administered drugs serve as an example of a pharmacokinetic (PK) system with distributed delays. Another example is a hematopoietic cell population with distributed lifespans.

Watch this webinar to learn how Certara’s population PK/PD software, Phoenix NLME, can be used to model pharmacokinetic/pharmacodynamic (PK/PD) systems with distributed delays.

About the author

Nathan Teuscher
By: Nathan Teuscher
Dr. Teuscher has been involved in clinical pharmacology and pharmacometrics work since 2002. He holds a PhD in Pharmaceutical Sciences from the University of Michigan and has held leadership roles at biotechnology companies, contract research organizations, and mid-sized pharmaceutical companies. Prior to joining Certara, Dr. Teuscher was an active consultant for companies and authored the Learn PKPD blog for many years. At Certara, Dr. Teuscher developed the software training department, led the software development of Phoenix, and now works as a pharmacometrics consultant. He specializes in developing fit-for-purpose models to support drug development efforts at all stages of clinical development. He has worked in multiple therapeutic areas including immunology, oncology, metabolic disorders, neurology, pulmonary, and more. Dr. Teuscher is passionate about helping scientists leverage data to aid in establishing the safety and efficacy of therapeutics.

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