Download - Pk/Pd modelling : Clinical Implications
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Pk/Pd modelling :Clinical Implications
JW MoutonDept Medical Microbiology
Canisius Wilhelmina Hospital
Nijmegen, The Netherlands
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infections are treated with the same
dosing regimen irrespective of the absolute
susceptibility of the micro-organism
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Susceptible
=
SusceptibleMIC = .016 mg/L
MIC = 2.0 mg/L
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Pharmacokineticsconc. vs time
Con
c.
Time0 25
0.0
0.4
PK/PDeffect vs time
Time
Eff
ect
0
1
0 25
Pharmacodynamicsconc. vs effect
0
1
10-4 10-3Conc (log)
Eff
ect
Immunesystem Severity Infection
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Forrest, 1993
Predictors of Clinical Response
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AUIC =125 : a magical number??
• PK models : 125
• Animal studies granulocytopenic : 100
• Animal studies immunocompetent : 40
• Human studies: peak/MIC ratio: > 1:10, AUC/MIC
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•There is a clear relation between pharmacodynamic index and effect.
•At some concentration there is a maximum effect
•Ideally, a dose should be chosen to obtain a maximum effect
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Example Target Controlled DosingIxacin
• Patient 60 yr, pneumonia and suspected bacteraemia/sepsis
• Ixacin 400 mg IV q8h
• Gram negative rod, E-test MIC=0.01 mg/L
• Adjust dose to 100 mg/day
Mouton & Vinks, PW 134:816
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Use of Pharmacodynamics in setting breakpoints
• Known concentration effect relationship– microbiology– clinical effect
• Standard dose used clinically– pharmacokinetic profile– patient/disease specifics
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Breakpoints based on AUC/MIC =100
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•Three studies have shown AUC/MIC predictive for outcome
•One prospective study Peak/MIC more predictive
Quinolones : dose optimalization
To peak or not to Peak?
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•For most quinolones, because of the relatively long half-life, there is a strong correlation between AUC/MIC and Peak/MIC
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Pharmacodynamics of fluoroquinolones against Pseudomonas infection in neutropenic rats
Drusano et.al., AAC, 1993, 37: 483-90.
• Survival linked to Peak/MIC when
ratio > 10/1
• Survival linked to AUC/MIC when
ratio < 10/1
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! ! !
• Proteinbinding in animals/humans
• Duration of treatment
• Extended dosing interval
• Immune system
• Severity of infection
• Bacteriological vs Clinical cure
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T>MIC: how long??breakpoints
• Free fractions of the drug (Fu)?• The same for all micro-organisms?• The same for all beta-lactams?• Efficacy vs emergence of resistance• The same for all infections?• Value in combination therapy?• Variance pk in population?• Static dose vs maximum effect?
• If maximum effect, which max effect?
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Same all beta-lactams?Same all m.o.?
Drug Enterobacteriaceae S. pneumoniae
Ceftriaxone (F) 38 (34-42) 39 (37-41)
Cefotaxime 38 (36-40) 38 (36-40)
Ceftazidime 36 (27-42) 39 (35-42)
Cefpirome 35 (29-40) 37 (33-39)
MK-0826 32 (20-39)
Meropenem 22 (18-28)
Imipenem 24 (17-28)
Linezolid 40 (33-59)
T> MIC for static effect
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Predicted efficacy of ticarcillin and tobramycinpseudomonas
-6 -5 -4 -3 -2 -1 0 1 2 3 4-6
-4
-2
0
2
4
predicted : t > 0.25 * mic ticarcillin and log auc tobramycin
Slope
Y-intercept
X-intercept
1/slope
0.9285 ± 0.07826
-2.815 ± 0.1250
3.032
1.077
r² 0.7830
dcfu predicted
dcfu
measu
red
Mouton ea., aac 1999
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Concentration-time profile of beta-lactamVd = 20 L, Ka = 1.2 h-1, Ke = 0.3 h-1
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0.20
1.20
2.20
3.20
4.20
5.20
6.20
7.20
8.20
9.20
10.20
11.20
12.20
13.20
14.20
15.20
16.20
17.20
18.20
19.20
0.00
1.25
2.50
3.75
5.00
6.25
7.50
8.75
10.0
0
11.2
5
12.5
0
13.7
5
15.0
0
16.2
5
17.5
0
18.7
5
20.0
0
21.2
5
22.5
0
23.7
5
0.95-1.00
0.90-0.95
0.85-0.90
0.80-0.85
0.75-0.80
0.70-0.75
0.65-0.70
0.60-0.65
0.55-0.60
0.50-0.55
0.45-0.50
0.40-0.45
0.35-0.40
0.30-0.35
0.25-0.30
0.20-0.25
0.15-0.20
0.10-0.15
0.05-0.10
0.00-0.05
Conc
Time
Prob
Monte Carlo Simulation of beta-lactamVd = 20 L, Ka = 1.2 h-1, Ke = 0.3 h-1, VC=20%
4h
10h
Mouton, Int J Antimicrob Agents april 2002
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Monte Carlo Simulations in pk/pd (1)
• Estimates of pk parameter values and a measures of dispersion (usually SD)
• Simulate pk curves based here-on
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Target Attainment Rates
• Pharmacokinetics of piperacillin– Population pk using npem2– ‘validation’using classical pk analysis (winnonlin)
• Use parameter estimates for Monte Carlo Simulation– Using sd’s only– Using correlation matrix
• Obtain TARS at various T>MICs
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0 25 50 75 1000
20
40
60
80
100
LoHi
Average
T>MIC %
PR
OB
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Monte Carlo Simulations in pk/pd (2)
• Estimates of pk parameter values and a measures of dispersion (usually SD)
• Obtain covariance matrix or correlation matrix
• Simulate pk curves based here-on :• The result will be SMALLER 95% CI because of
correlation between parameter estimates
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0 25 50 75 1000
20
40
60
80
100
LoHi
Average
T>MIC %
PR
OB
* 1
00
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Needed for TAR
• Pharmacokinetic profile of the drug
• Variation of PK parameters– Estimates of VC
– Population analysis, correlation matrix
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Cumulative Fraction of Response
• TAR at each MIC• Distribution of MICs• Multiply, determine fraction and cum fraction
• Beware !!!!! For prediction, a ‘true’ MIC distribution is needed, NOT a biased collection of strains!!!!!
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0.0625 0.125 0.25 0.5 1 2 40.0
0.1
0.2
0.3
0.4
MIC mg/L
frac
tio
n
After Drusano et al
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Pharmacodynamic properties of beta-lactams
• Efficacy dependent on time above mic
• Relatively concentration independent
Target for concentration profiles optimizing time > mic
Avoid high peak concentrations
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Target Concentrationcontinuous infusion
• Maximum effect time-kill at 4 x MIC• Maximum effect in vitro model 4 x MIC
(Mouton et al 1994)• Effect in endocarditis model 4 x MIC
(Xiong et al 1994)• Effect in pneumonia model dependent on
severity of infection (Roosendaal et al 1985,86)
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Efficacy in Relation to MICcontinuous infusion ceftazidime, K. pneumoniae rat pneumonia
Roosendaal et al. 1986, AAC 30:403; Roosendaal et al. 1985, JID 152:373
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Continuous InfusionPharmacokinetic Considerations
• Protein binding
• Linear relationship between clearance and dose
• Linear relationship between protein binding and dose
• Third compartment effects (CNS)
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Dose Calculationscontinuous infusion
• Total Clearance estimate
• Volume of Distribution
• Elimination rate constant
TBC = Ke x Vd
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Normogram Continuous Infusion
0 20 40 60 80 100 120 140 160 180 2000
1000
2000
3000
4000
5000
6000
64
32
16
8
4
clearance mL/min
do
se m
g/d
ay
Mouton & Vinks, JAC 1996
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Example Target Controlled Dosingcefticostix
• Patient 60 yr, UTI and suspected bacteraemia/sepsis
• Cefticostix 1 g IV q8h• Gram negative rod, E-test MIC=0.12 mg/L• Adjust dose to 30 mg/day CI based on
patient clearance
Mouton & Vinks, PW 134:816
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Example Cost EfficiencyContinuous Infusion Beta-lactam
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Therapeutic Drug Monitoringcontinuous infusion
• Clearance estimate
• Variable clearance (ICU)
• Non-linear clearance
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Ceftazidime concentrationsICU patients
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Piperacillin concentrationscontinuous vs intermittent