application strategy of pbpk for generic drugs and its
TRANSCRIPT
Application Strategy of PBPK for Generic Drugs
and Its Current Challenges
BUILD A PHARMACEUTICAL COMPANY
June 18, 2017
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Bo Liu
PuraCap Global Presence
HumanwellHealthcare Group
Humanwell
PuraCap Pharma,
Wuhan,China
EPIC
New York PuraCap
Laboratories
LLC, Kentucky
PuraCap
Pharmaceutical
LLC.
New Jersey
PuraCap Caribe LLC.,
Peurto Rico
Yichang
Humanwell
Pharma,
Yichang,China
We have 5 facilities which
are US FDA inspected
and ALL products are
excellent quality for US/
EU markets
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R&D ---Reaching Global Resource
Well Equipped
R&D Labs &
Research Institute
Puerto
Rico
New
Jersey Kentucky
Wuhan,
China
New
York
Wuhan,
China
4 research
centers globally
to support our
R&D projects
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Generic Drugs for US & EU Market
Currently Own FDA Approved ANDAs for US
market
Filed another ANDAs & NDA under FDA
review
Other pipeline products includes ANDAs &
NDA
Over 140 Generic Drugs in our portfolio
PBPK
Difference between Generic and New Drug
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New Drug Too many uncertainties
Generic Drug Absorption unknown
Project
Initiate Preclinical
Phase
Ⅰto Ⅲ
Project
Approve
Post
Launch Product
Enhancement
Project
Initiate
Product
Development
Exhibit
Batches
Pivotal BE/ Clinical
Trial
Product
Approve
Post Approve
Change
In vivo
In vitro PBPK
Preparation for Applying PBPK in
Generic Drug Development
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In vivo
In vitro PBPK
Preparation for Applying PBPK in
Generic Drug Development
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Preparation for Applying PBPK in
Generic Drug Development
PBPK Application Strategy
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RLD
Formulation screen
Prior BE study
Post BE study
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RLD and Formulation Screen Stage
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Application of Virtual Bioequivalence-
Safe Space Design Building
The optimum values of the α and β Weibull parameters were estimated on the basis of the virtual
trials ensuring BE (Cmax and AUC within 80 - 125% of the Target formulation)
Prior BE stage
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Mechanistic
In vitro Modelling
USP 2 Paddle 75RPM
5 mM Phosphate buffer
pH 6.7
Microclimate pH Model
Particle radius estimated (PE)
Lumped scalar (salts) (PE)
Ibuprofen
Free Acid
Ibuprofen Salt
Dis
solu
tio
n%
Time (h)
100
0 0 0.8
In vitro Dissolution Profiles (USP 2)
)tCt(Sthtatath
DNSDR(t) bulksurfaceeff
eff
eff)()()()()(4
)(
Ibuprofen
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Time course in hypothetical Effect Compartment was simulated. PD Endpoint – Dental Pain Relief Score PBPK Virtual BE studies (fasted) crossover design – IBU salt vs free form
Mechanistic understanding
and modelling
Scientifically-based criteria for
demonstrating therapeutic equivalence
Post BE stage
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Drug C BCS 2 drug
Dose: 400 mg
Acid
Soft Capsule
USP method In house method
Post BE stage
No commercial software is used in this case.
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PBPK simulation
Post BE stage
Item Ratio Geometric mean Confidence interval
Prediction based on
USP method (N=40)
Cmax (%) 102.3 98.9 115.5
AUC (%) 94.2 91.5 106.0
Prediction based on in
house method (N=40)
Cmax (%) 79.9 77.6 89.2
AUC (%) 94.1 91.2 100.0
Observed value
(N=33)
Cmax (%) 88.1 78.5 99.1
AUC (%) 97.9 92.4 103.5
AUC ratio Cmax ratio
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The effect of BE on the DDI
Ketoconazole
19 Liu, B. et al. 2016, Biopharmaceutics & Drug Disposition Volume 38 Issue 3 260-270
Pla
sma C
on
cen
trati
on
of
KT
Z (
mg/m
l)
0
2
4
6
8
10
0 3 6 9 12 15
0
2
4
6
8
10
0 3 6 9 12 15
Time ( h )
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Pla
sma C
on
cen
trati
on
of
KT
Z (
µg/m
l)
A. KTZ 100 mg
Time (h)
B. KTZ 200 mg
C. KTZ 400 mg
A. KTZ 100 mg
B. KTZ 200 mg
C. KTZ 400 mg
Time (h)
Ketoconazole
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Time (h) Time (h)
Pla
sma C
on
cen
trati
on
of
MD
Z (
µg/m
l)
Ketoconazole & Midazolam
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0
0.5
1
1.5
2
A B C
Pre
. A
UC
ra
tio
/ O
bs. A
UC
ra
tio
0
0.5
1
1.5
2
A B C
Pre
. C
max r
atio
/ O
bs. C
max r
atio
Ketoconazole & Midazolam
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Pla
sma C
on
cen
trati
on
of
MD
Z (
ng/m
l)
Time (h) [Relative to MDZ Administration] Time (h) [Relative to MDZ Administration]
Ketoconazole & Midazolam
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0
100
200
300
400
500
600
700
800
900
A B C D E
AU
C (
ng/m
l.h)
Observed Simcyp Default Simcyp Optimized
0
100
200
300
400
500
600
700
800
900
A B C D E
AU
C (
ng/m
l.h)
Observed Simcyp Default Simcyp Optimized
Ketoconazole & Midazolam
Desired State (ANDA)
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Paul Seo, 2015 Gpha Fall Techinical Conference
Final Goal for ANDA
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And by
Challenge and Opportunity
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1. Knowledge preparation: in vitro , in vivo and in silico.
2. Develop effective bio-relevant dissolution method
rather than use the USP method (In house method)
3. Pay the attention to the input data (Data Quality)
4. Using PBPK model to define the Clinical Relevant in
vitro Acceptance Criteria,
5. Consider to use PBPK/PD simulation
6. Bridging the clinical trial and in vitro studies
7. The strategy recommended here can effectively
accelerate ANDA development and ensure the BE
success rate.
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