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  • Leon Aarons

    Manchester Pharmacy School

    University of Manchester

    Population Pharmacokinetics

    and Pharmacodynamics

    as a Tool in Drug Development

  • Pharmacokinetics

    and

    Pharmacodynamics

  • Clinical Pharmacokinetics

    Dosage Regimen

    Plasma Concentration

    Site of Action Effect

    Pharmacokinetics Pharmacodynamics

  • Models

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  • The type of model to be developed should be

    driven by the available information and the

    goal of the simulations

    Empirical

    models

    Semi-mechanistic

    models

    Mechanistic

    models

    Descriptive

    Explanatory Rich

    “Poor”

    Extrapolation in

    complex and

    variable environment

    Interpolation in

    simple and

    stable environment

    Information

    needed Goal

    Days Months Years

    Category

  • 0.01

    0.1

    1

    10

    100

    0 2 4 6 8 10

    time

    c o

    n c

    e n

    tr a

    ti o

    n

    1 2t t 1 2C( t ) C e C e

          

  • 1 2

    k12

    k21

    k10

    1 1 12 1 1 10 1 1 21 2 2

    2 2 12 1 1 21 2 2

    ( ) ( ) ( ) ( )

    ( ) ( ) ( )

    dC t V k V C t k V C t k V C t

    dt

    dC t V k V C t k V C t

    dt

       

     

  • PBPK MODEL

  • Pharmacokinetic

    Study Design

  • Sparse Data

  • Tobramycin study

    Objective: to establish dosage regimen guidelines to

    maintain maximum efficacy (Cmax > 6

    mg/L) and minimum toxicity (Cav < 4

    mg/L) in a majority of patients

    Patients: n 97 (after pruning)

    body weight (kg) 42-120

    age (yr) 16-85

    sex (M/F) 52/45

    creatinine clearance 10-166

    (ml/min)

    indication variety of infection

    Study design: no design - routine TDM

    dosage - 20 to 140 mg every 8 to 24 hr

    number of concentrations per individual 1-9

    (median 2)

    duration of therapy - 14 to 520 hr

  • Why?  It seeks to obtain relevant pharmacokinetic

    information in patients who are representative

    of the target population to be treated with the

    drug

     It recognizes variability as an important feature that should be identified and measured during

    drug development and evaluation

     It seeks to explain variability by identifying factors of demographic, pathophysiological,

    environmental or drug-related origin that may

    influence the pharmacokinetic behavior of a

    drug

     It seeks to quantitatively estimate the magnitude of the unexplained variability in the patient

    population

  • Summary

    • PK/PD is model driven

    • PK/PD models aid the interpretation of

    pharmacological data and can be used

    prospectively to design subsequent studies

    learning/confirming

    • Nonlinear mixed effects modelling allows data

    from a variety of unbalanced, sparse designs to be

    analysed

    • Software for nonlinear mixed effects modelling is

    now widely available -

    even for amateurs!

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