METHODOLOGY

.

RESULTS AND DISCUSSION

CONCLUSIONS

REFERENCES 1. USP Chapter (601): Aerosols, nasal sprays, metered-dose inhalers, and dry powder inhalers.

2. Gonda, I: Development of a systematic theory of suspension inhalation aerosols. A framework to study the effects of aggregation on the aerodynamic behaviour of drug particles, International Journal of Pharmaceutics 1985, 27: 99-116.

3. Cooper, A, Bell, T: Monitoring of droplet size changes in a suspension pMDI by laser diffraction on a Sympatec™ Instrument. In Drug Delivery to the Lungs 19, 2008.

4. Mitchell, JP, Nagel, MW, Nichols, S, Nerbrink, O: Laser diffractometry as a technique for the rapid assessment of aerosol particle size from inhalers, Journal of Aerosol Medicine 2006, 19(4): 409-33.

5. ICH Harmonised Tripartite Guideline Q2(R1) (1994): Validation of analytical procedures, Text and Methodology.

6. ISO Standard 13320-1 (2009): Particle size analysis, laser diffraction methods.

7. Ph. Eur. Chapter 2.9.31: Particle size analysis by laser light diffraction.

8. USP Chapter (429): Light diffraction measurement of particle size.

9. Ward-Smith, RS, Gummery, N, Rawle, AF: Validation of wet and dry laser diffraction particle characterisation methods. Malvern Instruments Ltd. http://www.malvern.com/malvern/kbase.

nsf/allbyno/KB000167/$file/Laser%20Diffraction%20Method%20Validation.pdf.

10. Rawle, A, Kippax, P: Setting new standards for laser diffraction particle size analysis. Malvern Instruments Ltd. http://www.malvern.com/malvern/kbase.nsf/allbyno/KB002403/$fileMRK1399-01.pdf.

11. Schweitzer, M, Pohl, M, Hanna-Brown, M, Nethercote, P, Borman, P, Hansen, G, Smith, K, Wegener, G: Implications and opportunities of applying QbD principles to analytical measurements, Pharmaceutical Technology 2010, 34 (2): 52-59.

12. Borman, P, Chatfield, M, Jackson, P, Laures, A, Okafo, G: Reduced-method robustness testing of analytical methods driven by a risk-based approach, Pharmaceutical Technology 2010, 34(4): 72-86.

13. Jones, SA, Martin, GP, Brown, M.B: High-pressure aerosol suspensions – A novel laser diffraction particle sizing system for hydrofluoroalkane pressurised metered dose inhalers, International Journal of Pharmaceutics 2005, 302: 154-65.

14. Pu, Y, Kline, LC, Berry, J: The application of “in-flight” laser diffraction to the particle size characterization of a model suspension metered dose inhaler, Drug Development and Industrial Pharmacy 2011, 37 (5): 552-58.

15. Blatchford, C: From powder to patient - optimisation of particle sizing techniques, In Drug Delivery to the Lungs 24, 2013.

16. Ranucci, J: Dynamic plume – particle size analysis using laser diffraction, Pharmaceutical Technology 1992, 16: 108-14.

17. Cooper, A, Blatchford, C, Kelly, M: Laser diffraction methodology for particle size distribution (PSD) determination during pMDI product development – A QbD approach. In Respiratory Drug Delivery Europe 2013. Volume 2. Edited by Dalby, RN,

Byron, PR, Peart, J, Suman, JD, Young, PM, Traini, D. DHI Publishing; River Grove, IL: 2013: 197-202.

18. Stein, S, Cocks, P: Size distribution measurements from metered dose inhalers at low temperatures. In Respiratory Drug Delivery Europe 2013. Volume 2. Edited by Dalby, RN, Byron, PR, Peart, J, Suman, JD, Young, PM, Traini, D. DHI

Publishing; River Grove, IL: 2013: 203-08.

Figure 1. Fishbone diagram of sources of variability for laser diffraction data.

The median particle size for the placebo is decreased with increased distance. This is likely due to the increased evaporation of co-solvent, rather

than an indication of multiple scattering. This signal observed for the placebo led to the refractive index of the co-solvent being chosen for the method.

Although the OC decreased with increased firing distance due to reduced beam steer, the active PSD remains reasonably consistent [<10% shift in

d(v, 0.5)] and is considered to be real. A slight increase in active median particle size is consistent with reduced interference from the co-solvent and

therefore the long cylinder is considered to be the most accurate.

Figure 2. A: Optical concentration. B: d(v, 0.5) data for high strength active and placebo for various cylinder lengths.

The selection of sampling criteria (trigger conditions) is critical [3] and they can also interact with the method of shaking and firing, particularly for a

suspension pMDI. Design experiments are crucial for method optimization and for proving method robustness. Parameters, which are selected via a

suitable risk assessment, are evaluated over an appropriate design space, as shown in Figure 3.

Figure 3. PSD data for sample preparation DoE – low strength active.

INTRODUCTION

The aerodynamic particle size distribution (APSD) is a critical quality attribute (CQA) of orally inhaled and nasal drug

products (OINDPs). Cascade impactor methodology [1] is typically used to determine this during development and

registered product testing. Laser diffraction (LD) analysis of the ex-actuator plume has previously been proposed as an

alternative [2] for geometric particle size distribution (PSD) determination.

This is considered appropriate as the measured ex-actuator PSD would be influenced by the active pharmaceutical

ingredient (API) within the formulation in three ways. One, the dry API particles would be present in the actuation plume

after atomisation. Two, droplet formation during atomization may be influenced by the particle size of the API [14]. Lastly, the

API concentration will influence the number of particles within each droplet and hence the measured PSD [2, 3].

This publication will focus on the specific considerations for method development/validation of this methodology [4-10],

using a quality by design (QbD) approach [11, 12]. These data have the potential to correlate with APSD data [13, 14], as

many variables are common to both techniques [15], despite the difference in the principle of measurement (geometric

versus aerodynamic).

Measurements were made with a Sympatec™ instrument, consisting of a Helos (Helium-Neon Laser Optical System)/BF™

laser diffraction sensor with the Inhaler™ dry dispersion accessory (See instrument settings in Table 1). The pMDI unit is

manually actuated into the Inhaler accessory, allowing the actuation plume to pass through the laser (He/Ne @ 633nm)

where light is scattered and then focussed by a chosen lens onto a detector array. The detector consists of 31 concentric

ring elements. The innermost element is referred to as R1 and the outermost element as R31. Scattered light registered on

elements R1-R6 is discounted due to beam steer [16]. The signals from all the other detector elements are combined and a

PSD is inferred from the scattering pattern based on the chosen optical model, after subtraction of background levels.

Table 1. Sympatec™ instrument settings

A QbD Method Development Approach for the Ex-actuator Particle Size Distribution (PSD) Determination of pMDIs by Laser Diffraction Andy Cooper, Chris Blatchford and Stephen Stein

3M Drug Delivery Systems, 3M Health Care Ltd, Morley St, Loughborough, LE11 1EP, UK 03189

Cylinder Long (14cm)Short (8cm)None (4cm)

25

20

15

10

5

0

Op

tica

l Co

nce

ntr

ati

on

(%

) Active

Placebo

(Firing distance)

Cylinder Long (14cm)Short (8cm)None (4cm)

6

5

4

3

2

1

d(v

, 0

.5)

- µ

m

Active

Placebo

(Firing distance)

B A

Validation data for this method are shown in Table 2. Validation was performed on both high and low strength actives. RSD

values are higher than those typically observed for a laser diffraction method for an API [17], however this is likely due to the

inherent product variability (See Figure 1) – measurements are being made of volatile droplets with a wide range of

velocities contributing to differing amounts of evaporation per droplet. Increased variability is therefore expected. However,

one important factor to limit variability is humidity level [3].

Table 2. Method validation data.

This validated method has been used to try and understand trends in APSD data – The data shown in Table 3 shows that

the PSD is influenced by the temperature of the product, which has similar trends to those observed for ACI data in the

literature [18]. The vapor pressure of the formulation increases with temperature, which results in atomization of smaller

droplets, which will contain fewer drug particles, hence a decrease in PSD. Faster propellant/co-solvent evaporation, due to

the increased temperature, will also result in a decrease in PSD.

Table 3. PSD data for a range of temperatures (n=6 at each condition) – high strength active.

There are multiple variables which can influence laser diffraction data, as shown in Figure 1. Aside from the product related

factors, risk assessments of the other variables are required. While some parameters have no impact if they are suitably

controlled (e.g., cleaning), other more critical parameters require experimentation to determine their effects (e.g., trigger

conditions). The Inhaler accessory was chosen since the droplets are entrained in an air flow which dilutes the sample and

reduces potential artefacts such as velocity bias and geometric effects [15].

The length of cylinder used for the Inhaler accessory must be optimized. This dictates the distance between the point of

actuation and the laser beam. The optical concentration (OC) must be sufficient for sensitivity purposes but not too high to

cause multiple scattering. Data are shown in Figure 2A and 2B. The similarity in OC for the active and placebo shows that

the majority of light did not reach the central detector due to the propellant shifting the laser beam (beam steer).

21

2.5

2.0

1.5

1.0

0.5

0.021

2.7

d(v,

0.1

) -

µm

3.3

30

60

delay (s)

Actuation

Shake speed (Hz)21

5

4

3

2

121

2.7

d(v,

0.5

) -

µm

3.3

30

60

delay (s)

Actuation

Shake speed (Hz)21

9

8

7

6

5

4

321

2.7

d(v,

0.9

) -

µm

3.3

30

60

delay (s)

Actuation

Shake speed (Hz)

Optical Concentration trigger threshold at which sampling starts/ends (%)

RESULTS AND DISCUSSION (CONT.)

A QbD approach to development of laser diffraction (LD) methodology to determine the PSD ex-actuator from a pressurized

metered dose inhaler (pMDI) is presented. Robust and repeatable data were obtained, however this is inherently more

variable than methodology for the PSD determination of the API. The LD methodology can be used to understand trends in

cascade impaction data – the industry standard, but more time consuming, methodology for APSD determination.

RESULTS AND DISCUSSION (CONT.)