Pharmacokinetics and pharmacodynamics Antibiotics in critically ill patients Dr Tim Felton PhD MRCP FFICM Consultant in Intensive Care Medicine University Hospital of South Manchester & Senior Lecturer The University of Manchester
UKCPA Critical Care Group Advanced Practitioner Meeting Friday 30th September 2016
Healthy volunteers v’s Critically ill patients P ip e r a c illin c o n c e n tr a tio n (m g /L )
Piperacillin 4 grams IV TDS 150
150
100
100
50
50
0
0 0
4
8
12
16
T im e (h o u r s )
20
24
0
4
8
12
16
20
24
T im e (h o u r s )
Felton - unpublished
Healthy volunteers v’s Critically ill patients P ip e r a c illin c o n c e n tr a tio n (m g /L )
Piperacillin 4 grams IV TDS 300
300
200
200
100
100
0
0 0
4
8
12
16
T im e (h o u r s )
20
24
0
4
8
12
16
20
24
T im e (h o u r s )
Felton - unpublished
P ip e r a c illin c o n c e n tr a tio n (m g /L )
Critically ill patients Risk of toxicity 300
200
100
Variability 0 0
4
8
12
16
20
24
T im e (h o u r s )
Risk of clinical failure and emergence of resistance
D r u g c o n c e n tr a tio n (m g /L )
Pharmacokinetics • Absorption • Distribution • Volume of distribution • Tissue penetration • Metabolism • Elimination • Clearance
150
100
50
0 0
2
4
T im e (h r s )
6
8
Trough Concentration/MIC ratio (Log Scale)
Altered clearance Acute kidney injury
Augmented renal clearance
Creatinine clearance (ml/min/1.73m3) Udy et al. Chest. 2012;142:30-39.
Volume of distribution • Hydrophilic antibiotics • Endothelial damage • Large volume fluid resuscitation • Fluid extravasation • Increase interstitial volume Gonçalves-Pereira J et al. Critical Care 2011. 15:R206
Effect of protein binding Highly protein-bound agents • Ceftriaxone • Flucloxacillin • Ertapenem • Increase free fraction – Increased activity – Enhanced clearance
Roberts JA et al. Clin Pharmacokinet 2013. 52:1-8.
Obesity • Small number of studies • Obesity may cause alterations to PK • Not enough data to suggest different dosage
Alobaid AAC 2016. 00531-16
Renal replacement therapy
Amikacin clearance • CVVHDF 1.8 1.3 l/hr • CVVH 1.3 1.0 l/hr
Beumier et al. Critical Care 2014, 18:R105 Roger at al. AAC 2016. 00828-16
Other extra-corporeal circuits
• Similar to critically ill patients • Circuit saturations
Skekar JCC 2012. 27;741.e9-18
Non-linear pharmacokinetic 9
Vor iconazole Concent r at ion ( m g/ L)
8 7 6 5 4 3 2 1 0 0
29
58
87
116
145
174
203
232
261
290
319
348
Tim e ( hour s)
From William Hope
Hydrophilic antibiotics
Lipophilic antibiotics
Low Vd Renal clearance
High Vd Hepatic clearance
Altered in ICU
Higher Vd Cl: Renal function
Vd unchanged Cl: Hepatic function
Examples
Beta-lactams Aminoglycosides Glycopepetides Linezolid
Fluroquinolones Macrolides Tigecycline
General PK
PK alteration in critically ill patients
Roberts JA et al. Lancet ID. 2014. 14; 498-509
Pharmacokinetic variability
Roberts JA et al. Clin Infect Dis. 2014. 58:1072-83
Target site penetration
Felton et al. CPT 2014; 96:438-448
Pharmacodynamics Pre-Clinical
Effect
Clinical
Biomarkers Bacterial burden Microbiological cure Biomarker Clinical Cure Survival Survival
Toxicity
Resistance
()
Minimum inhibitory concertation More than S and R
D r u g c o n c e n tr a tio n (m g /L )
Relate PK to effect(s) 150
Cmax/MIC
100
AUC/MIC 50
fT>MIC %
Cmin/MIC
0 16
18
20
T im e (h r s )
22
24
Bacterial killing T>MIC
Cmax/MIC
AUC/MIC
Beta-lactam
Aminoglycoside
Fluroquinolone
Carbapenem
Fluroquinolone
Aminoglycoside
Linezolid
Metronidazole
Azithromycin
Macrolide
Daptomycin
Linezolid
Exposure-response relationship 1 .0
0 .8
P r o b a b ilit y
0 .7 0 .6 0 .5 0 .4 0 .3 0 .2
Therapeutic window
Emergence of resistance
0 .9
R esponse T o x ic it y
0 .1 0 .0 2
3
4
5 D ru g e x p o s u re
6
7
8
Exposure-response relationship Meropenem
Cefipime
Tam VH et al. JAC 2002. 50:425–428 Li C et al. AAC 2007. 51:1725-1730
Suppressing emergence of resistance
Tam et al. AAC 2007;51:744-747
Suppressing emergence of resistance
Felton TW et al. AAC 2013. 57:5811-5819
Toxicity Daptomycin
Gentamicin
• Not defined for β-lactams – But adverse events (neurotoxicity) more common in renal impairment – Suggests a exposure-response relationship Bhavnani SM et al. CID (2010) 50:1568–1574 Rybak MJ et al. AAC (1999) 43:1549-55
Toxicity P r o b a b iltiy o f g e n t a m ic in to x ic ity (% )
Toxicity target: gentamicin AUC 200 mg.hr/L 8
6
4
2
0 4
5
6
7
8
9
10
G e n t a m ic in d o s e ( m g /k g )
Chen et al. Unpublished
Exposure-response relationship 1 .0
0 .8
P r o b a b ilit y
0 .7 0 .6 0 .5 0 .4 0 .3 0 .2
Therapeutic window
Emergence of resistance
0 .9
R esponse T o x ic it y
Range of exposures in a population
0 .1 0 .0 2
3
4
5 D ru g e x p o s u re
6
7
8
Effect of variability P r o b a b ilit y o f t a r g e t a t t a in m e n t
fT>MIC 50% Breakpoint for piperacillin 1 .0
4 g q 8 h o v e r 3 0 m in u te s 0 .8
0 .6
0 .4
0 .2
0 .0 0 .2 5 0 .5
1
2
4
8
16
32
64
128
M in im u m in h i b it o r y c o n c e n t r a t io n ( m g /L )
Felton TW et al. AAC 2012; 56(8):4087–4094
Effect of variability Current β-lactam regimens: • DALI study – 20% of patients do not achieve 100% fT>MIC
• Felton et al – 15% of patients do not achieve 50% fT>MIC – 60% of patients do not achieve Cmin/MIC >3.4
Felton et al. CPT 2014. 96:438-48 Roberts JA et al. CID 2014. 58:1072-83
How can we overcome pharmacokinetic variability?
EXTENDED AND CONTINUOUS INFUSIONS
( m g /L )
P i p e r a c il lin c o n c e n t r a t i o n
O v e r 5 m in u t e s e v e r y 8 h o u r s
O v e r 4 h o u rs e v e ry 8 h o u rs
O v e r 2 4 h o u r s , c o n t in u o u s in f u s io n
250
250
250
200
200
200
150
150
150
100
100
100
50
50
50
0
0 0
4
8
12
16
20
T im e ( h r s )
fT > MIC 16 mg.L-1
24
0 0
4
8
12
16
20
24
0
4
T im e ( h r s )
8
12
16
20
24
T im e ( h r s )
5 minutes 8 hours
4 hours 8 hours
24 hour infusion
45%
66%
100%
Simulation Probability of target attainment
fT>MIC 50% Breakpoint for piperacillin 1.0
4g q8h over 4 hours 4g q8h over 30 minutes
0.8 0.6 0.4 0.2 0.0 0.25 0.5
1
2
4
8
16
32
64 128
Minimum inhibitory concentration (mg/L) Felton TW et al. AAC 2012; 56(8):4087–4094
Intermittent arm
Continuous arm
P-value
fT>MIC 100%
29%
82%
0.001
Clinical cure
43%
70%
0.037
ICU-free days
17
19.5
0.14
80%
90%
0.47
Survival (hospital discharge)
Dulhunty JM et al. CID 2013. 56:236–44
BLING II A Multicenter Randomized Trial of Continuous versus Intermittent β-Lactam Infusion in Severe Sepsis
• Piperacillin-tazobactam, ticarcillin-clavulanate or meropenem • Continuous or 30-minute intermittent infusion • 432 participants • No difference in: – – – –
ICU-free days 90-day survival Clinical cure Organ-failure free days Dulhunty et al. AJRCCM 2015. 192;1298-1395
How can we overcome pharmacokinetic variability?
THERAPEUTIC DRUG MONITORING
Dosing Nomograms
Pea et al. AAC 2012;56:6343-6348
Dosing Nomograms
Pea et al. AAC 2012;56:6343-6348
Dose adjustment protocol
Guess?
De Waele et al. ICM 2014. 40:380-7
PK-PD target attainment
De Waele et al. ICM 2014. 40:380-7
Bayesian dose optimisation
Felton TW et al. AAC. 2014 58(7):4094-4102
Bayesian dose optimisation
Individual PK Bayesian estimate from a population PK model
Target associated with suppression of resistance
Felton TW et al. AAC 2014. 58:4094-102.
Feedback dose alteration
Scaglione F et al. ERJ 2009. 34:394-400
Combinations β-lactam + aminoglycoside or quinolone • Pre-clinical models – Synergistic killing – Suppression of emergence of resistance – Particularly Pseudomonas
• Clinical trials – Small, not convincing – Best evidence in Pseudomonas bacteraemia and CF Turnidge J. 2014. Fund. of Antimicrobial PK & PD. 153-198
Healthy volunteers v’s Critically ill patients P ip e r a c illin c o n c e n tr a tio n (m g /L )
Piperacillin 4 grams IV TDS 300
300
200
200
100
100
0
0 0
4
8
12
16
T im e (h o u r s )
20
24
0
4
8
12
16
20
24
T im e (h o u r s )
Felton - unpublished
Conclusion • PK variabilty • Standard regimens result in sub-optimal target exposures for many patients • ↓ exposure: treatment failure, resistance • ↑ exposure: toxicity • One dose does not fit all
• The Future is TDM
Questions?
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