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.

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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