Regulatory Science Symposium: Special Populations Session 1: Pharmacometrics (2017)

In this session, we will discuss the pharmacometrics of special populations with special emphasis on children.

Course Syllabus/Topics

  1. Pharmacometrics: A sophisticated, powerful discipline that uses statistics and equations to capture past experience from a variety of data sources into a use-specific model
  2. Aim of Modeling: To describe and summarize drug exposure and effects after a given dose or doses in individuals and populations
  3. Model Types:
    1. Non-compartmental
    2. Compartmental
  4. Non-Compartmental Models:
    1. Used for bioequivalence, drug interaction, single dose PK studies
    2. Require much sampling – difficult for special population research
    3. Challenges
      1.  Analysis of sparse and unbalanced data
        1. Complex dosage regimes
        2. Simulation of exposure from different regimes than those of study
        3. Linked effects
  5. Compartmental Models: Categorized into Traditional, Population and Physiologic Models
    1. Traditional Compartmental Models:
      1. Require frequent blood sampling
      2. Use rate stripping technique with rate constants and equations to measure drug concentrations with respect to time
      3. Challenges
        1. Only use information from one dosing interval
        2. Biased by sparse and unbalanced data
        3. Assume parameters remain constant
        4. Neglect errors in observations
        5. Need at least one measurement per parameter in the model
        6. Do not distinguish sources of variability
    2. Population Compartmental Models:
      1. Also known as Pharmacometrics
      2. Used to describe
        1. Time course of drug concentrations in the body
        2. Relationship between drug concentration and effects, both desired and undesired
        3. Effects of covariates
        4. Sources of PK variability in population.
      3. Helpful to simulate new scenarios required for hypothesis generation, study design and dose finding and extrapolate dosing in novel population
      4. Used to optimize and personalize therapy for individual patients
      5. Classified into Parametric (for normally distributed data) and non-parametric models
    3. Physiologic Compartmental Models:
      1. Monte Carlo Simulation – foundation for physiologically based pharmacokinetic model
      2. Use combination of organism and drug specific parameters
      3. Predict drug concentration and effects in population(s) of interest
      4. PBPK Software: Simcyp, GastroPlus, PK-Sim


Accompanying text created by Priyanka Ramasamy | Regulatory Science Graduate Student Worker |

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