Physiologically based pharmacokinetic modelling of … web...Agenda Page 2 PBPK modelling of...
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19 - 21 April 2017 Christoph Niederalt
QuanTI Closing Conference
Physiologically based pharmacokinetic modelling of biologics
Agenda
PBPK modelling of biologics • April 2017 Page 2
• Overview:
Physiologically Based Pharmacokinetic (PBPK) Modelling
• Application Examples
• Albuferon:
Testing hypotheses on relevant mechanisms
• Glucose-Insulin model
Physiologically-based PK modeling
PBPK modelling of biologics • April 2017 Page 3
Wikipedia:
Physiologically based pharmacokinetic (PBPK) modeling is a mathematical modeling
technique for predicting the absorption, distribution, metabolism and excretion (ADME) of
synthetic or natural chemical substances in humans and other animal species.
PBPK Applications
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PK-Sim for Biologics Organ Representation
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Plasma
Enz 1 Enz N
blood
Trans 1 Trans N
…
Blood Flow
Lymph
Flow …
convection
diffusion
cells
Endosome Lysosome
Tissue
Cells
Interstitial
Space
Protection from Catabolism by Binding to FcRn
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• The neonatal Fc receptor for
IgG (FcRn) is expressed by
endothelial cells and circulating
monocytes.
• Ligands: IgG and albumin
(binding at distinct sites)
• Ligands bound to FcRn in acidic
endosomal compartment
recycle back into circulation
extended half-life
figure taken from D. C. Roopenian and S. Akilesh,
Nature reviews immunology, 7, 715, (2007)
Generic PBPK Model for Biologics Protection from Catabolism by Binding to FcRn
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• The FcRn sub-model implemented in PK-Sim® was developed starting from
the model published by Garg and Balthasar#
• Competition with endogenous IgG is taken into account
# A. Garg and J.B. Balthasar. J. Pharmacokinet. Pharmacodyn. 34, 687-709, (2007)
vascular space
interstitial space
endosomal space
cellular space
CL IgG + FcRn IgG-FcRn
Kd (pH 6.0)
blood cells
IgG + FcRn IgG-FcRn Kd (pH 7.4)
IgG + FcRn IgG-FcRn Kd (pH 7.4)
Generic PBPK Model for Biologics Example: Model Development
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IgG antibody (7E3) in wild-type and FcRn-knockout mice
Experimental data are taken from
A. Garg and J.B. Balthasar.
J. Pharmacokinet. Pharmacodyn. 34,
687-709, (2007)
Example: Albuferon Case Study
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Albuferon is an Interferon-a–Albumin fusion protein
co-developed by Human Genome Sciences and Novartis as hepatitis C drug.
Crucial Questions prior to
First-in-Human:
• What Albuferon dose will
be appropriate (safe & efficacious)?
• Does albumin-FcRn binding
prolong half-life as expected?
• Is IFN-a effect at target
similar to “naked” IFN-a?
figure taken from
http://www.hgsi.com/albuferona-albinterferon-alfa-2b.html
Factors Determining Half-Life of Albuferon
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Lysosomal
degradation and
protection from
degradation by FcRn
Using fusion proteins
containing the Fc
fragment of IgG or
albumin is one
approach to half-life
extension
Target mediated
deposition and
degradation in tissue
and blood cells
(effect related)
Model for IFNAR Mediated PK
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Representation of target mediated deposition and clearance
• reversible binding of drug to IFNAR
• irreversible internalization of drug-receptor complex (drug as well as receptor
are degraded once they are internalized)
D
R Cm
Ci
Intracellular
receptor
binding
internali-
zation
lysis
Interstitial
IFNAR Mediated PK – Monkey
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model fit to IFN-b and comparison with IFN-a data (different dosages)
Effect of receptor mediated
deposition and clearance is
seen for the two lower-doses
of IFN-b
Experimental data:
D.E. Mager et al., J. Pharmacol. Exp. Ther. 306 (1), 262-270 (2003); J.M. Collins et al., Cancer Drug Deliv. 2 (4), 247-253 (1985).
evaluation
with IFN-a
Intermediate Summary
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Model representing lysosomal degradation and FcRn salvage established
Model for IFNAR mediated deposition and clearance established
Next step:
Integration of FcRn and TDM model components and prediction of fusion protein
PK
Prediction for Albuferon (Monkey)
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Prediction under the assumption that Kd(Albuferon-FcRn) = Kd(Albumin-FcRn)
• FcRn mediated protection from catabolism
is well represented
• Model without target mediated deposition &
clearance outperforms integrated model
Experimental data:
Pfizer & B.L. Osborn et al., J. Pharmacol. Exp. Ther. 303 (2), 540-548 (2002).
Prediction for Albuferon – Adjusted
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Excellent description of data if Kd to FcRn is reduced by a factor 2.5 only
Experimental data:
Pfizer & B.L. Osborn et al., J. Pharmacol. Exp. Ther. 303 (2), 540-548 (2002).
Prediction for Albuferon – Adjusted
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Excellent description of data if Kd to FcRn is reduced by a factor 2.5 only
Experimental data:
Pfizer & B.L. Osborn et al., J. Pharmacol. Exp. Ther. 303 (2), 540-548 (2002).
In contrast to “naked” interferons for
albuferon the impact of IFNAR mediated
deposition and clearance appears to be
negligible!
Half-life prolongation achieved
Effect at target modified?!
• PBPK model to represent the mechanisms relevant for the PK of biologics
available
• PBPK modelling allows the use of prior knowledge for extrapolation as well as
testing assumptions or hypotheses on relevant mechanisms.
Summary Albuferon Example
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Example: Glucose-Insulin Model (GIM)
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• Diabetes is a major health issue: in 2010, 285 million people with
diabetes worldwide (6.4%); predicted for 2030, 438 million (7.7%)
The REACTION Project Remote Accessability to Diabetes Management and
Therapy in Operational Healthcare Networks
Physiology of the GIM
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Schaller et al. 2013
Processes of the GIM – Organ Level
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Model Development Tolerance Tests (Mean Model)
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Sch
alle
r et a
l. 20
13
www.systems-biology.com www.bayer.com Page 21
Model Development - Clinical Trial (Individualized Model)
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0 2 4 6 8 10 12 14 16 0
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Fitte
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Meal Meal Meal
Fit Subject 117-1
Glu
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Model Data
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Insu
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Time [h]
Glu
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Meal Meal Meal
Prediction Subject 117-2
0 3 6 12 16 21 24
Time [h]Schaller et al. 2013
Model Applications: T1DM - Automatic Blood Glucose Control
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• Initialization with patient data
(physiological parameters,
e.g. weight, height, gender)
• Blood glucose
measurements taken
frequently, stored and
delivered to the controller
• The process works on two
time scales:
• Short: online calculation of
optimal insulin dose based on
recent glucose measurements
• Long: offline “model
adaptation” based on full
measurement data history
Schaller et al. 2016
2 Clinical Trials: Results
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1st trial with i.v. blood
glucose
(red, mean ± stdv)
2nd trial with s.c.
continuous glucose
monitoring (blue, mean ±
stdv)
From 1st -> 2nd:
Increased controller
aggressiveness
Slight increase in low
blood glucose incidence
But:
Very high time-in-target
for control using s.c. CGM
Schaller et al. , unpublished
Glu
co
se
Summary and Outlook
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Development and validation of a PBPK/PD model of the
glucose-insulin metabolism for healthy individuals and
individuals with T1DM
Coupled PBPK models of glucose, insulin and glucagon
Detailed GI-tract model including an incretin effect
model
Integration of a subcutaneous insulin absorption and
a detailed insulin receptor model
Platform for
Automated blood glucose control in clinical environments
Evaluation of novel diabetes treatment strategies on virtual
diabetes populations
Open-Systems-Pharmacology.org
PBPK modelling of biologics • April 2017 Page 26
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