a translational modelling and simulation...
TRANSCRIPT
A translational modelling and simulation approach
to exploit pre-clinical tuberculosis data
Wicha SG, Svensson R, Clewe O, Simonsson USHPharmacometrics Research Group
Dept. of Pharmaceutical BiosciencesUppsala University, Sweden
Global TB drug development pipeline
1
Model-informed Drug Discovery and Development (MID3)
2
Target Authorization and Mechanistic Understanding
Human PK and Dose Prediction
Study Design Optimization
Prediction from/of Early Clinical Responses
Dose Selection and Label Recommendations
Development of a model-based approach to exploit in vitro TB information for translational predictions along the drug development process
…
Marshall et al. CPT Pharmacometrics Syst. Pharmacol. 5. 2016.
In vitro rifampicin time-kill curves
3Clewe et al. JAC. 2016.
Rifampicin (RIF) treated log- and stationary phase cultures of M. tuberculosis (H37Rv)
log stationary
In vitro data:Yanmin Hu & Anthony CoatesSt. Georges University London, UK
The Multistate Tuberculosis Pharmacometric model
4
Culturable
Non-culturable (hidden)
Clewe et al. JAC. 2016.
F Fast growingS Slow growingN Non growing
in vitro
Hollow-fiber system (HFS)
Translational predictions to streamline MID3
5animal
Murine lung infection model
clinical
Early bactericidalactivity (EBA) trial
Translational predictionin vitro
5
Translational factors
6
Drug-specificMycobacterial growth properties
System carrying capacity
Susceptibility of the mycobacterial isolate
System-specific Isolate-specific
Pharmacokinetics• murine• human
0 50 100 150 200
02
46
8
Time [days]
Mycobacterial growth properties
System-specific!• Maximum growth “Bmax”• Pre-incubation period of
target system, e.g.– Hollow-fiber: 4 days– Animal: 20-40 days– Clinical: >150 days
F-dominated culture
S / N-dominated culture
Bmax
FSNCFU(F+S)
7
log1
0 Ba
cter
ial N
umbe
r [/m
L]
Consideration of mycobacterial isolate susceptibility
Translational target
Origin OriginMIC distribution
TargetMIC distribution
8
Clinical – reported MIC values for rifampicin
TargetMIC distribution
Postantibiotic effects (PAE)
9
effect cmtCRIF
Gumbo et al. AAC. 51 2007.
in vitro
Hollow-fiber system (HFS)
Translational predictions to streamline MID3
10animal
Murine lung infection model
clinical
Early bactericidalactivity (EBA) trial
Translational prediction
10
in vitro
Prediction of Hollow fiber system (HFS) experiments
11
600 mg2100 mg4200 mg
Rifampicin regimen
Gumbo et al. AAC 51 2007.
Prediction of HFS experiments
12
Phar
mac
odyn
amic
s
O HFS observations
Phar
mac
okin
etic
s
0 2 4 6 8 10 12
0.0
0.5
1.0
0 2 4 6 8 10 120
24
68
No treatment 600 mg RIF daily
0 2 4 6 8 10 12
0.0
1.0
2.0
RIF
[mg/
L]
0 2 4 6 8 10 12
02
46
8
Time [days]
log1
0 Ba
cter
ial N
umbe
r [/m
L]
FSNCFU(F+S)
0 2 4 6 8 10 12
02
46
80 2 4 6 8 10 12
02
46
8
Prediction of HFS experiments
13O HFS observations
0 2 4 6 8 10 12
01
23
4
RIF
[mg/
L]
0 2 4 6 8 10 12
02
46
8
Time [days]
log1
0 Ba
cter
ial N
umbe
r [/m
L]
4200 mg RIF once weekly2100 mg RIF twice weekly
FSNCFU(F+S)
Phar
mac
odyn
amic
sPh
arm
acok
inet
ics
in vitro
Hollow-fiber system (HFS)
Translational predictions to streamline MID3
14animal
Murine lung infection model
clinical
Early bactericidalactivity (EBA) trial
Translational prediction
14
in vitro
15
log
10 C
FU/m
L at
day
6
1e-02 1e+00 1e+02 1e+04
12
34
56
7
R2 = 0.96
1 100 10000
12
34
56
7
R2 = 0.98
0 20 40 60 80 100
12
34
56
7
R2 = 0.68
1e-02 1e+00 1e+02 1e+04
12
34
56
7
Cmax/MIC
R2 = 0.78
1 100 10000
12
34
56
7
AUC24/MIC
R2 = 0.93
0 20 40 60 80 100
12
34
56
7
%T>MIC
R2 = 0.04
Murine lung infection model • 4 weeks post infection• 2 - 4860 mg/kg
given 1-6 times in 144 h• unbound murine
plasma PK
Prediction of PK/PD indices from animal studies
Jayaram et al. AAC 47 2003.
Model-predicted PK/PD indices
Observed PK/PD indices
in vitro
Hollow-fiber system (HFS)
Translational predictions to streamline MID3
16animal
Murine lung infection model
clinical
Early bactericidalactivity (EBA) trial
Translational prediction
16
in vitro
Prediction of clinical EBA studiesrifampicin
17
PharmacokineticsGeneral Pulmonary Distribution Model[1]
PharmacodynamicsMultistate Tuberculosis Pharmacometric model[2]
[1] Clewe et al. Eur. J. Clin. Pharmacol., 2015.[2] Clewe et al. JAC. 2016.
Plasma
Target site
Prediction of clinical EBA studiesrifampicin
18
observed clinical mean EBApredicted mean EBA (p0.05- p0.95)
Prediction of clinical EBA studiesrifampicin
19predicted mean EBA (p0.05- p0.95)observed clinical mean EBA values (p0.05- p0.95)
Prediction of clinical EBA studiesisoniazid
20
observed clinical mean EBApredicted mean EBA (p0.05- p0.95)
Importance of combining in vitro log-and stationary phase data for
predictions
21
Rifampicin EBA day 0-2 Isoniazid EBA day 0-2
Conclusions and Perspectives
The developed translational approach with efficacy estimates only from in vitro time-kill experiments predicted rifampicin effects observed
– across in vitro systems (hollow-fiber), – in animal studies to determine PK/PD indices,– in clinical early bactericidal activity studies
Perspectives– Evaluation of the approach with further TB drugs/combinations– Extension of the translational framework to prediction of relapse
22
Acknowledgements
23
The research leading to these results has received funding from the Innovative Medicines Initiative Joint Undertaking (www.imi.europe.eu) under grant agreement
n°115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA
companies’ in kind contribution.
Research conducted within the PreDiCT-TB consortiahttp://www.predict-tb.eu