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EMA Workshop Non-Clinical Models to Identify PK/PD Indices ... · EMA Workshop Non-Clinical Models...

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EMA Workshop Non-Clinical Models to Identify PK/PD Indices and PD Targets In Vitro G.L. Drusano, M.D. Professor and Director Institute for Therapeutic Innovation University of Florida
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Page 1: EMA Workshop Non-Clinical Models to Identify PK/PD Indices ... · EMA Workshop Non-Clinical Models to Identify PK/PD Indices and PD Targets In Vitro G.L. Drusano, M.D. Professor and

EMA Workshop Non-Clinical Models to Identify PK/PD

Indices and PD Targets In Vitro

G.L. Drusano, M.D. Professor and Director

Institute for Therapeutic Innovation University of Florida

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In Vitro • There are many in vitro systems for

delineating the relationships between drug regimen intensity and in vitro outcomes of interest (bacterial cell kill and resistance suppression)

• I will limit myself to the system we employ in our laboratory – the hollow fiber infection model – first employed by Jurg Blaser and Steve Zinner and used extensively by Mike Dudley

• I have no experience with the other systems

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In Vitro • There are many advantages and disadvantages to

both in vitro systems, as well as in vivo systems – I will concentrate on in vitro systems

• Advantages: 1) any half-life can be simulated 2) any bacterial burden can be examined 3) any organism can be studied 4) Resistance emergence is straightforward to find and study 5) Other physiologic states can be induced and studied (e.g. Non-Replicative Persister Phenotype)

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In Vitro • Advantages (cont’d):

6) The system can be employed at any stage of discovery/development

• Really? Even if I do not know the PK in man? • Yes! Simply look at a small animal half-life for effect

and then empirically dial in longer half-lives likely to be seen in man (e.g. 2, 4, 6, 8 hr half-lives) and ascertain the impact on the dynamic index

• We have done this before (AAC 2011;55:1747-1753 and AAC 2015;59: 3771-3777)

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In Vitro

• What are the disadvantages? 1) THERE IS NO IMMUNE SYSTEM! 2) There is no physiology 3) you cannot look at issues such as tissue penetration and effect on outcome 4) cannot look directly at protein binding issues (we do employ free drug concentration-time curves, but there are other issues)

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In Vitro

Cell Kill and Resistance Emergence

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Resistance Suppression in Pseudomonas aeruginosa

The use of the hollow fiber model for studying antimicrobial regimens was described by Blaser and Zinner and employed extensively by Dudley

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Resistance Suppression in Pseudomonas aeruginosa

Tam V et al. Bacterial-population responses to drug selective pressure: Examination of garenoxacin’s effect on Pseudomonas aeruginosa. J Infect Dis 2005;192:420-428

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Central Compartment (Cc) Infusion + Bacteria

(XT/R)

f(c)

dCc=Infusion-(SCl/V)xCc dt

SCl

dXS=KGS x XS x L - fKS(CcH ξ) x XS

dt dXR= KGR x XR x L- fKR(Cc

H ξ) x XR dt

Kmax ξ •CcH ξ

C H ξ 50 ξ+Cc

H ξ fψξ(Cc

Hξ)=

Y1=XT=XS+XR, IC(1)=1.01x108

Y2=XR , IC(2)= 58

[2]

[3]

[4]

[5]

[6]

, ψ=K and ξ = S,R

[1]

L = (1-(XR + XS)/POPMAX)

[7]

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P. aeruginosa - Prevention of Amplification of Resistant Subpopulation

• The amplification of the resistant sub-population is a function of the AUC/MIC ratio

• The response curve is an inverted “U”.

• The AUC/MIC ratio for resistant organism stasis is circa 185/1

Resistant organisms at baseline

All other data points represent resistant organism counts at 48 hours of therapy

0 50 100 150 200 250

10

100

103

104

106

AUC0-24:MIC Ratio

Resis

tant

Mut

ants

(CFU

/mL)

107

105

Resistance Suppression in Pseudomonas aeruginosa

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Prospective Validation Experiment

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In Vitro – Time to Resistance

Continuous infusion of Avibactam (AUC = 8 x 24 = 192 - then called NXL104) worked and suppressed resistance for the duration of the experiment (D); AUC=192 Q 24 h (E) failed, as did AUC = 96 Q12 h (F) AUC = 64 Q 8 h (G) succeeded for the whole experiment, implying that for this agent Time > Threshold (or Cmin) drives β-lactamase inhibition Note in (F) that resistance did not emerge until after day 10 – you must study long enough

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In Vitro

Impact of Therapy Duration

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Prospective Validation Experiment

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In Vitro – Very Reproducible

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In Vitro

Looking at Agents in Combination

Page 29: EMA Workshop Non-Clinical Models to Identify PK/PD Indices ... · EMA Workshop Non-Clinical Models to Identify PK/PD Indices and PD Targets In Vitro G.L. Drusano, M.D. Professor and

Mono-Rx Pseudomonas aeruginosa

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In Vitro

So, what’s going on? Why the failure of mono-Rx and why the success of combo-Rx?

AAC 2012; 56:231-242

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In Vitro

• So, what is going on? • We looked at the

stability of cefepime over time at different baseline inocula

• Inoculum and time-dependent hydrolysis was seen

• Hypothesis: β-lactamase mediated problem

Antimicrob Agents Chemother 2012;56:231-242

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In Vitro

No resistance emergence!

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In Vitro Success of Combination Therapy

• As a protein synthesis inhibitor, we hypothesize that the aminoglycoside shuts down the expression of the ampC β-lactamase

AAC 2012; 56:231-242

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In Vitro

We have gone as long as 6 months; 1-2 months is standard for us in MTB studies

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In Vitro - Conclusions • This in vitro system is flexible, powerful and

reproducible • It allows study of differences in PK, organisms,

bacterial burden and resistance emergence • It allows linkage of measures of regimen intensity to

effect (cell kill and resistance suppression) • It allows experiments to be carried out for clinically-

relevant durations • All the data are straightforwardly able to be

modeled fully parametrically to increase insight and allow design of validation experiments

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In Vitro - Conclusions

• WHAT IS MISSING IS MODELING ALL THE OUTPUTS AND USING THE DATA TO PEFORM A PROSPECTIVE VALIDATION STUDY – THIS WILL IMPROVE CONFIDENCE!

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Thank You for Your Attention!

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