The FDA Critical Path Initiative In Vitro Techniques and ... · Deposition of Particles in the Lung...
Transcript of The FDA Critical Path Initiative In Vitro Techniques and ... · Deposition of Particles in the Lung...
The FDA Critical Path Initiative – In
Vitro Techniques and In Vivo Imaging
Technology
Anthony J. Hickey
School of Pharmacy, University of
North Carolina at Chapel Hill, NC
PQRI Workshop on Demonstrating Bioequivalence of
Locally Acting Orally Inhaled Drug Products, Bethesda,
MD March 9th, 2009
Objective
This presentation will examine the role that
assessment of aerodynamic particle size
distribution, aerosol deposition, imaging
techniques, and modeling and simulation of
product performance/drug delivery could or
should play in bioequivalence testing and
will review current attempts at establishing
possible IVIVCs for locally acting OIPs.
PRODUCTION
PROCESS
EFFICACYPRODUCT
QUALITYIN-VITRO, IN-VIVO
PERFORMANCE
Crowder, Hickey, Louey and Orr, 2003
Bioequivalence
Broad Bioequivalence Questions
Relevant in vivo “test”
– Anatomically
– Patient Use
– Statistically Discriminating
Suitable models
– Anatomical
– Imaging
– Mathematical
Devices
Actuator
Orifice
Valve
Stem
Characteristics of Interest
Specific Items Measured
Impaction – Historical perspective
Invented for sampling chemical warfare aerosols at Porton Experimental station
Adopted for ambient sampling of environmental aerosols
Most relevant for inhaled pharmaceuticals– Particle size based on mass
– Whole aerosol is sampled
– Chemical analysis used to detect particles
– Aerodynamic diameter relevant to lung deposition
Fig. 3. Schematic representation of the principle of operation of
cascade impactors. (A single jet per impactor stage is shown.
Impactors with multiple jets in each stage function in the same
manner.)
Aerosol Particles
Vacuum
0 Stage Jet
1st Stage Jet
Last Stage Jet
Intervening Stages
Collection Plate
Filter
Fig. 4. Apparatus 1: Assembly of induction port and entrance cone
mounted on cascade impactor.
Fig. 5. Apparatus 2, 3, 4, or 5: General control equipment. (See
Table 3 for component specifications.)
Fig. 9a. Components of Apparatus 5.
Fig. 10. Plot of cumulative percentage of mass less than stated
aerodynamic diameter (probability scale) versus aerodynamic
diameter (log scale).
YSize
XSizeGSD
_
_
Graphically g may be obtained by dividing the
diameter representing the 84th percentile by that
of the 50th (median), or alternatively the 50th by
the 16th. These values are easily derived from
log-probability plots. This value may also be
derived as follows:
2/1
)16(
)84(
)16(
)50(
)50(
)84(
D
D
D
D
D
Dg
269
Operating Manual Andersen 8 stage impactor, Graseby Andersen, Smyrna GA
But impactors
lungs!
???
Flow rate and pressure drop effects are
relevant to patient use.
Can we detect these by inertial impaction?
Issues in aerosol particle size
analysis
Dose delivery from DPIs is highly dependent on inspiratory conditions– All approved DPIs are passive, relying on flow through
DPI to disperse drug
Particle size is tested in vitro at a fixed flow rate
Fixed flow rate fails to account for DPI resistance
In vitro particle size testing of DPIs may not accurately simulate use by a patient
Pressure drop/flow rate for 6
inhalers
Clark and Hollingworth, 1993
R=ΔP0.5
/Q
Peak inspiratory flow for healthy
volunteers
0
50
100
150
200
250
300
800 2300 3300 8000 9000 12000 50000
Airflow resistance (Pa s1.9 L-1.9)
PIF
(L
/min
)
Olsson and Asking, 1994
Flow profiles for Spinhaler
Clark and Hollingworth, 1993
Budesonide Turbuhaler Particle Size
Distribution
0
5
10
15
20
25
30
35
40
45
50
1 1.9 3.2 4 6 8.6
Aerodynamic diameter ( m)
% u
nd
ers
ize
40 Lpm
60 Lpm
80 Lpm
Olsson and Asking, 1994
IVIVC: Quality to Efficacy
Imaging Methods
Gamma Scintigraphy
SPECT
PET
Data Presentation
– Whole Lung
– Central to Peripheral Ratio
– Regions of interest
a. A typical lung ventilation image (200k counts) obtained with 99mTc-
DTPA aerosol;
b. That with 81mKr gas (400K counts);
c. 99mTc-MAA perfusion image (400k counts)
Ishfaq et al., 1984
Planar Gamma- Scintigraphic
Images of Healthy Human Lungs
Positron Emission Tomography (PET)
and Single Photon Emission Computed
Tomography (SPECT) PET
– Uses an indirect measure (pairs of gamma rays from a positron emitting radionuclide)
– Expensive (requires cyclotron to produce short lived redionuclides)
– Greater contrast to background ratio improving giving higher resolution
SPECT
Uses similar principle to gamma scintigraphy but in 3D
Less costly than PET
Less spatial resolution than PET
Zeissman et al, 2006
Other considerations
Overall cost
Accessibility
– Number of instruments
– Location
– Scheduling
SPECT (Single Photon Emission
Computed Tomography)
– Gamma Camera
– Shows the 3D spatial distribution of
radiolabeled aerosol deposition
Human Subject Deposition
Measurements
Healthy
Asthmatic
In vivo Deposition Measurements
Correlation between mean whole lung
deposition and mean impinger FPF
Newman and Chan, 2008LD by gamma scintigraphy, FPF<6.8 m, n=33 inhalers
Correlation between mean whole lung
deposition and mean Impactor FPF
LD by gamma scintigraphy, FPF<5.8 m, n=10 inhalers Newman and Chan, 2008
Correlation between mean whole lung
deposition and the mean percentage of
dose <3 m
LD by gamma scintigraphy, FPF<3.0 m, n=10 inhalers Newman and Chan, 2008
Deposition of Particles in the Lung
Mechanisms of deposition:– Inertial impaction (da> 1μm)
– Sedimentation
– Diffusion (da<1 μm)
– Interception
Deposition in the respiratory regions: da=1-3 µm*
Aerodynamic diameter da:
da=de (ρP/ ) ½
VTS: terminal settling velocity; de: geometric diameter; ρp: particle
density; ρ0: unit particle density (1 g/cm3); :viscosity of atmosphere; : shape factor; Cc: slip correction factor
Gravity
*Patton JS et al. Nat Rev Drug Discov (2007) Jan; 6(1):67-74.
=VTS= 18 18
ρpdegCc2
ρ0dagCc
2
(Re<1)
Regional deposition-fraction curves
US-NCRP (Phalen et al., 1991)
Swift et al., 2007
Computed velocity vector field –
Control Case
Musante and Martonen, 2001
Computed velocity vector field at a
carinal ridge with model tumor
Musante and Martonen, 2001
In Silico Morphology
Mouth
(Oral Cavity)
TB
PU
ET
Larynx
Apiou-Sbirlea et al., 2008
Martonen et al. Resp. Care 45:712-736, 2000
Martonen et al. Resp. Care 45:712-736, 2000
In Silico Morphology: Idealized
Apiou-Sbirlea et al., 2008
In silico Model
(Apiou-Sbirlea et al., 2008)
Data presented for three regions– A Trachea
– B Tracheobronchial
– C Pulmonary
Breathing conditions– Tidal volume 1L
– Frequency 7.5 breaths/min
Plots– x- axis, Aerodynamic diameter (Dae, m)
– y- axis, Deposited fraction (DFX)
0
0.2
0.4
0.6
0.8
1
0.01 0.1 1 10 100
Dae (µm)
DFT
Heyder et al. (1986), J. Aerosol Sci., 17(5):811-825
Conditions:
TV=1000ml
f=7.5 breaths/min
Q=250ml/s
Measured
Simulated
In Silico Model Validation: Particle
Deposition in MALES (T)
0
0.2
0.4
0.6
0.8
1
0.01 0.1 1 10 100
Dae (µm)
DFTB
Conditions:
TV=1000ml
f=7.5 breaths/min
Q=250ml/s
Heyder et al. (1986), J. Aerosol Sci., 17(5):811-825
Measured
Simulated
In Silico Model Validation: Particle
Deposition in MALES (TB)
0
0.2
0.4
0.6
0.8
1
0.01 0.1 1 10 100
Dae (µm)
DFPU
Conditions:
TV=1000ml
f=7.5 breaths/min
Q=250ml/s
Heyder et al. (1986), J. Aerosol Sci., 17(5):811-825
Measured
Simulated
In Silico Model Validation: Particle
Deposition in MALES (PU)
Complicating Factors In vivo
Nasal
Passages
T-B Airways
Pulmonary
Parenchyma
Lymph
Nodes
B
l
o
o
d
G
I
T
r
a
c
t
Schematic Representation Showing Cascade of
Events Following Exposure to Allergen Leading to
Early and Late Phase Bronchoconstriction and
Pharmacotherapeutic Points of Intervention
Conclusions Delivered dose and aerodynamic particle size
are the most important measure of in vitro performance of OIDP.
Flow rate dependence of delivery from DPIs (function of resistance) must be assessed to fully understand performance but cascade impactors cannot be used to simulate in vivoperformance
Conclusions
Imaging techniques exist that are more or less
– Accurate/Precise
– Sensitive
– Costly
– Physiologically relevant (2D/3D)
Computer models exist based on
– Fundamental mathematics of particle behavior
– Computational fluid dynamics
Potential Complicating Factors
Clearance mechanisms
Target Receptors
– Region of Lungs
– Region of the Cell
Disease State
Broad Bioequivalence Questions
Relevant in vivo “test”
– Anatomically
– Patient Use
– Statistically Discriminating
Suitable models
– Anatomical
– Imaging
– Mathematical
Specific Questions
In vivo approaches to Demonstrating Bioequivalence (limit to imaging?)
What approaches are used (2D, 3D, Data presentation by region)?
Anatomically correct physical models for use with imaging?
What's the intended purpose of each test?
Are the tests discriminating?
Are the tests representative of patient use?
What's the biological significance of the tests?
Statistics - what is the metric and what is the target (goal post)?
Would in silico tests link usefully into in vivo performance?
Which "limited" in vivo tests might be useful for the in vivo part of an IVIVC (Is this even possible?)?
ReferencesG. Apiou-Sbirlea, M. Simoes-Pichelin, G. Caillibotte, I. Katz, J. Texereau, J. Fleming, J.
Conway, G, Scheuch and T. Martonen (2008) Validated three dimensional CFD
modeling of aerosol drug deposition in humans – Influence of disease and breathing
regimes, in Respiratory Drug Delivery. Eds. R.N. Dalby, P.R. Byron, J. Peart, J.D.
Suman, S.J. Farr and P.M. Young, Davis Healthcare International Publishing, River
Grove, IL, pp185-195.
T.M. Crowder, A.J. Hickey, M.D. Louey and N. Orr (2003) A Guide to Pharmaceutical
Particulate Science, Interpharm/CRC Press, Boca Raton, FL.
M.M. Ishfaq, S.K. Ghosh, A.B. Mostafa, N.R. Williams* and A.J. Hickey (1984) A
simple radioaerosol generator anddelivery system for pulmonary ventilation studies.
Eur. J. Nucl. Med., 9:141-143.
J Mitchell, S.P. Newman and H.-K. Chan (2007) In vitro and in vivo aspects of cascade
impactor tests and inhaler performance: A review. AAPSPharmSciTech, 8: Article 110
C.J. Musante and T.B. Martonen (2001) Computational fluid dynamics in human lungs
II Effects of Airways Disease, in Medical Applications of Computer Modeling: The
Respiratory System, ed. T Martonen, WIT Press, Southampton, UK, pp147-164.
ReferencesS.P. Newman and H.-K. Chan (2008) In vitro/in vivo comparisons in pulmonary drug
delivery, J. Aerosol Med. and Pulm. Drug Del., 21:77-84.
B. Olsson and L Asking (1994) Critical aspects of the inspiratory flow driven inhalers, J.
Aerosol Med., 7 (Suppl 1.):S43-47.
R.S. Pillai, D.B. Yeates, M. Eljamal, I.F. Miller and A.J. Hickey*, J. Aerosol Sci., 25:187-
197, 1994. Generation of concentrated aerosols for inhalation studies.
D. Swift, B. Asgharian and J.S. Kimbell (2007) Use of mathematical aerosol deposition
models in predicting the distribution of inhaled therapeutic aerosols, in Inhalation
Aerosols Physical and Biological Basis for Therapy, Second Edition, ed. A.J. Hickey,
Informa Healthcare, New York, NY, pp55-82.
H.A. Zeissman, J.P. O’Malley, J.H. Thrall (2006) Single-photon emission computed
tomography (SPECT) and positron emission tomography (PET), in Nuclear Medicine,
ed. J.H. Thrall, Elsevier Mosby, Philadelphia, PA>
Acknowledgements
Hak-Kim Chan
Steve Newman
Gabriela Apiou-Sbirlea
– Joy Conway
– John Fleming
– Gerhard Scheuch
Ted Martonen