Transcript Diapositive 1

NATIONAL
VETERINARY
SCHOOL
TOULOUSE
Pharmacokineticpharmacodynamic integration in
veterinary drug development:
an overview
P.L. Toutain
National Veterinary School ;Toulouse France
EMEA : Focus group meeting on PK/PD
London 24 September 2008
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What is PK/PD?
•
PK-PD modeling is a scientific
tool to quantify, in vivo, the key PD
parameters of a drug, which allow
to predict the time course of drug
effects under physiological and
pathological conditions (intensity
and duration)
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What is the main goal of a
PK/PD trial
 It is an alternative to dosetitration studies to discover an
optimal dosage regimen
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An overview on the
concept of PK/PD
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Dose titration
Dose
Response
Black box
PK/PD
PK
PD
Response
surrogate
Dose
Plasma
concentration
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Why is plasma concentration profile a
better explicative (independent)
variable than dose for determining a
dosage regimen ?
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Dose vs. plasma concentration profile
as independent variable
Dose
Dose
X
F%
Clearance
Time
Mass
(no biological
information)
Concentration profile
(biological information)
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PK/PD applications
1. in vitro to in vivo extrapolation
2. Measure in vivo key PD
parameters (efficacy, potency,
selectivity, affinity…)
3. predict dosage regimen
4. sources (PK or PD) variability in
drug response (antibiotics)
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Application of PK/PD modelling
in veterinary medicine
•
•
•
•
•
Antibiotics
NSAIDs
ACEI
Hormones
others
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An example of application of
PK/PD to determine a dosage
regimen for a NSAID in cat
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As for a conventional dose titration, PK/PD
investigations generally require a relevant
experimental model (here a kaolin
inflammation model)
Possibility to perform PK/PD in patient
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As for a conventional dose titration, PK/PD
investigations require to measure some
relevant endpoints
• To measure the
vertical forces, a
corridor of walk is
used with a force
plate placed in its
center.
• The cat walks on
the force plate on
leach.
Video
Measure of vertical forces exerted on force plate
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Measure of vertical forces
exerted on force plate
• The measure of
vertical force and
video control are
recorded
 Vertical forces (Kg)
Video
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Surrogate endpoint for pain
 withdrawal time: timer stopped when cat
withdraws its paw
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Measure of pain with analgesiometer
• Cat is placed in a Plexiglas
box.
• A light ray is directed to its
paw to create a thermal
stimulus.
• The time for the cat to
withdraw its paw of the ray
is measured.
Video
 withdrawal time of the paws
(second)
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150
1600
100
1400
1200
Pain score (%)
50
1000
0
800
-50
600
Observed response
-100
400
Fitted response
-150
Observed concentration
200
Meloxicam concentration (ng/mL)
PK/PD results: analgesic effect
Fitted concentration
-200
0
0
4
8
12
16
20
24
28
32
36
Time after meloxicam administration (h)
Cn
Imax +
dR
= Kin (1) - Kout R
dt
IC50n + Cn
•Emax/Imax
•EC50
•Slope
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The 3 structural PD parameters:
Dose titration (DT) vs. PK/PD
ED50/EC50
Emax
Emax 1
1
1
2
2
Emax 2
Slope
Sensitivity
shallow
steep
ED501 ED502
Efficacy
DT & PK/PD:
Same Emax
Potency
ED50 vs EC50
• Range of useful
concentrations
• Selectivity
Only PK/PD
Simulated dose-response:
Drug xxx: analgesic effect
100
50
Pain score (%)
0
0.1 mg/kg
0.2 mg/kg
0.3 mg/kg
0.4 mg/kg
0.5 mg/kg
1 mg/kg
-50
-100
-150
-200
-250
0
4
8
12
16
20
24
Time (h)
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Simulations drug xxxx: once vs. twice a day
Simulated time course of pain
100
90
80
Pain (%)
70
60
50
5 mg/kg
2 x 2.5 mg/kg
5 mg/kg split in 12
40
30
20
10
0
0
4
8
12
16
20
24
Time (h)
Mean effect  32 %
Mean effect  52 %
Mean effect  96 %
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Why to prefer a PK/PD
approach to a classical
dose-titration?
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1. ED50 vs EC50
A variable vs. a parameter
ED 50
Plasma _ clearance  EC 50

Bioavailab ility
PD
PK
ED50 - is a hybrid variable (PK and PD)
- is not a genuine PD drug parameter
EC50 is a PD parameter allowing extrapolation
•Between formulations
•Between physiological status (renal failure)
•Between species
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Why to prefer a PK/PD approach to
a classical dose-titration?
2.The separation of PK
and PD variability
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PK/PD variability
• Consequence for dosage adjustment
PK
Dose
PD
BODY
Receptor
Effect
Plasma
concentration
Kidney function
Liver function
...
Clinical covariables
• disease severity or duration
• pathogens susceptibility (MIC)
PK/PD population approach
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PK Variability
1.6
Doxycycline
Concentrations mg/mL
1.4
n = 215
1.2
1
0.8
0.6
0.4
0.2
0
-5
0
5
10
15
20
25
30
Time (h)
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Pathogens %
MIC distribution
Pasteurella multocida (n=205)
40
35
30
25
20
15
10
5
0
SUSCEPTIBLE
0.06250.125 0.25
0.5
1
2
4
MIC (m g/mL)
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Dosage regimen: application of
PK/PD concepts
The 2 sources of variability : PK and PD
PD: MIC
PK: exposure
AUC [0, 24 h] Distribution
16
Pathogens %
Fréquences (%)
14
12
10
8
6
4
2
40
35
30
25
20
15
10
5
0
SUSCEPTIBLE
0.06250.125 0.25
0
3 4 5
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
AUC (µg.h.mL-1)
0.5
1
2
4
MIC (m g/mL)
Distribution of PK/PD surrogates (AUC/MIC)
Monte-Carlo approach
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Metaphylaxis:
dose to achieve a POC of 90% i.e. an AUC/MIC of 80 h
(Drug xxxx: empirical antibiotherapy)
Dose distribution
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The main limits of the
PK/PD modeling
The main limits of the PK/PD
modeling:
Clinical validity of surrogates
Biomarker and surrogate for NSAID
EC50action
Whole blood assay
EC50 in vivo effect
Plasma
Inhibition
concentration of COX
Inhibition
of PGE2
production
Suppression
of lameness
Requires 95% PGE2
inhibition
EC50 response
EC50 response >> EC50 effect
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Clinical endpoint vs.
surrogate/biomarkers
• True clinical endpoints are patient
feeling, wellbeing, survival rate etc.
– because therapeutic endpoints may
be unavailable, impossible to
evaluate, time taking…
 biomarkers & surrogates
Measuring response
e.g.: ACE inhibitors
Binding affinity
biomarker
ACE inhibition
Renin/angiotensin
aldosterone
modulation
surrogate
Clinical outcome
Continuity
Objectivity
Sensitivity
reproducibility
Blood pressure
Survival time
Well-being
Validity +++
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PK/PD modeling
Modelling issues:
Need professional skill
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PK / PD modelling
CONCLUSION
• A powerful tool for many applications
• Requires clear understanding of
theoretical background and computer
software
• Veterinary pharmacologists should be
encouraged to consider PD, and not
only PK.
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PK / PD modelling
CONCLUSION
• The pharmaceutical industry must not
hesitate to introduce state-of-art
science and technology into its R&D,
due to concerns about regulatory
impacts
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