Modeling and Characterization of Powder Dispersion in DPIs

May 31st, 2019

Analytical TechnologyBoris Shekunov

Takeda Pharmaceutical Company Limited

1

Reference

CRC Press

March 25, 2019

ISBN 9781138064799 - CAT# K33394

Chapter 1:

Physicochemical Properties of Respiratory Particles and FormulationsBoris Shekunov

(Mechanisms of dispersion for solid and liquid aerosols,

different formulation approaches, optimization strategies

and regulatory considerations)

2

“Misconceptions” and Challenges with DPI formulations

• Air-flow independent therapy and variability in total lung delivery• Device resistance and application of high resistance devices by patients with reduced lung

function• Development of new integrated device-formulation systems• Development of high-dose DPIs• Understanding of powder dispersion mechanisms• Interparticle interactions and powder agglomeration • Effects of coarse and fine lactose on powder mixing and aerosolization• Properties of engineered particles• Particle dissolution and uptake• Stability of amorphous formulations

Formulation-Flow-Device Paradigm: Relate the material characteristics of the formulation (e.g. particle adhesion/cohesion and aggregate strength) with the flow rate, pressure drop and inhaler resistance to the inhaler performance in terms of the FPF

3

Deposition profiles

Nasopharyngeal -impaction-sedimentation-electrostatic

Tracheobronchial -impaction-sedimentation-diffusion

Pulmonary -sedimentation-diffusion

4

Physical inhaler- patient interface: flow rate and pressure drop

(a) Influence of the inertial impaction parameter, dA2Q, on mouth-throat deposition and (b) variability of total lung deposition for porous engineered particles vs. pressure drop across DPIs (from: Weers J., Clark A. The impact of inspiratory flow rate on drug delivery to the lungs with dry powder inhalers. Pharm Res. 2017)

5

Generalized model of dispersion

B

A

• Flow, Q, through a device with the pressure differential, ΔP, and volume of the active dispersing zone, V, define the rate of turbulent energy dissipation, ε.

• The input-output parameters: initial fine particle fraction, FPF0, the resulting fine particle fraction, FPF, and the maximum achievable fine particle fraction, FPFmax

• Two most important functions: breakage frequency (Γ) and turbulent stress (σ)

6

In vitro delivered fine particle doses (FPD) vs. label claim

From: A. H. de Boer et al. Dry powder inhalation: past, present, and future. Expert Opinion on Drug Delivery, 14:4, 501 (2017). Tested at 4 kPa (high resistance devices) or 2 kPa (low resistance devices); range of flow rates 40–75 L/min using a NGI.

7

Effect of device resistance (RD) and flow rate (Q) on energy of dispersion

• ρ is air density

• For most commercial DPIs, RD typically in the range 0.01-0.07 kPa1/2 min/L

• Device parameter, Z = 2 × 103 – 5 × 103 depends only weakly on the inhaler type

∆"#.%= '()* = +,-../,-.0.123..43

8

Mechanism of dispersion in DPIs

σ erosion

σ rapture

σ compression

σ collision

Γ

σa (10-3) << σb (10-1) ≈ σc (10-1) < σ’b,c (100) << σe (101) <σf (102) <σd (102)

9

Dependence of FPF on airflow

• Γ ~ εx: the power x ≈ 1/3 – 1/2 (within the same dispersion mechanism) is the exponent of the turbulent energy dissipation rate

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0 0.5 1 1.5 2 2.5

log(-ln

(1-FPF))

log(Q, L/min)

Insert I

Insert II

Insert III

Experimental data from: Gac J, Sosnowski TR, Gradon L. Turbulent flow energy for aerosolization of powder particles. Aerosol Sci. 2008

!"#(− ln 1 − )*) ) = - + 30 − 1 !"#1

x ≈ 0.47

10

Dependence of FPF for Micronized and Engineered Particles

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.4 0.6 0.8 1 1.2 1.4

log(-ln

(1-FPF))

logQ

micronized

engineered

11

Types of flow dependencies

“ideal” inhaler and formulation

FPF = 0

FPF = 1

inhaler design issues

variable dispersion mechanism

Q

formulation issues

12

Aggregate strength: key to determination of powder performance

!" = $( &''()*

+ ,-.+

, = −0123-4

Tensile strength:

Interparticle force defined by the Johnson-Kendall-Roberts (JKR) relationship:

K - dependent on aggregate size and W is the work of adhesion

13

Conclusions from the aggregate model

(a) The aggregate strength is inversely proportional to dp

(b) Surface asperities can significantly decrease both the interparticle bond and aggregate strength (by a factor ~2qy/dp where y is the diameter of asperity and q number of contacts. The same applies for binary mixtures consisting nanoparticles resulting in a minimum strength at a certain surface coverage

(c) For binary mixtures consisting large carrier particles, the carrier-drug bond increases at least by a factor of 2, given the same W and contact cross-section, compared to the bond between drug particles themselves. However the balance of strength for such aggregate depends on the drug-carrier surface coverage and packing order of drug particles

(d) Both parameters, K and σT, become dependent on the aggregate (or cross-section) size when they are comparable to the size of primary particles. In particular, K has a smaller value for the fracture cross-sections close to the aggregate surface

14

Formulation design: dilemma with lactose carriers and adhesive blends

Functions of carriers:

(a) “Dilution” of formulation: ordered mixtures (b) Enhance dispersion(c) Fixed dose combinations

σp ≈ 2.4 kPa

σpc (max) ≈ 29 kPaTheoretical drug loading:

!"!#

≃ % &'()*+#'#(#)*+

15

Ternary blends with lactose

Moderating effects of fine lactose particles:

(a) “Energetic” sites (b) Small lactose-drug aggregates (c) Disruption of ordered layer

σp ≈ 1.5 kPa

σpc ≈ 5-10 kPa

16

Control of dispersion using particle engineering• Reduced density - smaller aerodynamic

diameter

• Large volume diameter - reduced strength of agglomeration

• Larger surface asperity / rugosity – reduced interparticle interactions

• Smaller specific work of adhesion / cohesion -reduced interparticle interactions

• Increased shape factor – reduced interparticle interactions

• Larger specific surface area – improved dose uniformity

• Smaller number of particles in aggregate –faster dispersion Spray-dried large (c)- and small (d) - porous particles

(G J Weers and DP Miller, J Pharm Sci. 2015)

Spray-Freezing(B. Shekunov data)

Spray-Drying with FCA(NYK Chew, B Shekunov, HHYTong, et al., J Pharm Sci, 2005)

1 µm 1 µma b

In: A. H. L. Chow, H. H. Y. Tong, P. Chattopadhyay, B. Shekunov. Particle Engineering for Pulmonary Drug Delivery. Pharm Res, 24 (2007)

17

Aerosolization Performance of Different Engineered Materials

18

Analytical aspects for assessing formulation performance

• Predictions of aggregate strength using physicochemical measurements (e.g. AFM, microscopy, BET, IGC)

• More detailed data analysis from cascade impactors

• Use of particle size methods

• Utilization of Standardized Entrainment Tubes (SET)

• Flexible DPIs design (inserts, mold modifications)

• In combination with theoretical quantitative models and CFD

| Title | DD/MM/YY

19

Regulatory considerations

• Solid-State: Physicochemical characterization of API(s) and excipients relevant to their functionality in drug product; compatibility with diluents c; effects of environmental moisture a,b, low temperature b; temperature cycling b,d; moisture content a,b; sameness / therapeutic equivalence of API (generics).

• Particulate and Surface: PSD (for APIs and carriers); ASPD; single actuation FPD a,b,d; (delivered) dose content uniformity (DCU) a,b,d (containers intra-and inter-batch) or uniformity of dosage units a,c,d; DCU and FPD at various flow rates a and at various lifestages (i.e. beginning, middle, end) a,b,d; FPD with spacer b; actuator / mouthpiece deposition a,b,d; shaking requirements; drug delivery rate and total drug delivered c; foreign particulate matter.

• Formulation: Assay, mean delivered dose vs. label claim a,b,d; DCU a,b,d; dose proportionality (for different strengths and/or APIs); formulation / inhaler robustness; drug product stability; qualitative (Q1) sameness and quantitative (Q2) equivalence of excipients and media physicochemical similarity c (generics). aDPIs; bpMDIs; cnebulizers; dnon-pressurized metered dose inhalers

20

Design of efficient and robust inhalation products

• Inhaler designed for formulation

• More efficient use of quantitative aerodynamic dispersion models and CFD

• Wider applications of in vitro analytical technology in R&D

• Optimization of ternary mixtures

• Engineered particles for new drugs including biological molecules and

amorphous formulations

• Particle designed for complete performance: aerosolization within inhaler -

deposition / distribution in the airways - drug release / uptake / clearance at

the site of action

• Assessment of manufacturing feasibility and GMP implications

| Title | DD/MM/YY