The Aerosol Drug Management Improvement Team ADMIT Slide Deck 2018

Part 3 Pulmonary Aerosol Delivery Nicolas Roche

Pulmonary aerosol delivery Where are the targets? Localisation of drug receptors How can lung deposition be assessed? What are the factors that influence aerosol deposition? Lung disease and deposition Patient’s skills and behaviour

Pulmonary aerosol delivery Where are the targets? Localisation of drug receptors How can lung deposition be assessed? What are the factors that influence aerosol deposition? Lung disease and deposition Patient’s skills and behavior

Located throughout the airways and lung Pulmonary aerosol delivery Inflammation and glucocorticoid receptors Adcock AJRCCM 1996 airways and lung Located throughout the airways and lung Muscarinic receptors Mak & Barnes, ARRD 1990 Beta2 adrenoreceptors Ikeda BJP 2012

Inflammation and glucocorticoid receptors (GR) are located throughout the airways and lung GR: Airways GR: Lung Adcock AJRCCM 1996

Beta2 adrenoreceptors are located throughout the airways and lung Ikeda BJP 2012

Muscarinic receptors are located throughout the airways and lung Ikeda BJP 2012

Pulmonary aerosol delivery Where are the targets? Localization of drug receptors How can lung deposition be assessed? Patient’s skills and behavior Lung disease and deposition What are the factors that influence aerosol deposition?

Methods to assess lung deposition Inference From particle size distribution (modelling) In vivo measurements Direct visualisation = scintigraphy Indirect assessment = charcoal-block method (dosage of pharmacological agents or metabolites in blood or urine) In vitro modeling from in vivo measurements Functional respiratory imaging Using computational fluid dynamics

Deposition vs particle size: «basic» physics Carvalho Int J Pharm 2011

Anatomy plays a role: need for complex mathematical modeling Fernandez Tena , Arch Bronchoneumol 2012

(99mtechnetium or 131iodine) Scintigraphy 2-dimensional (planar) low-energy gamma emitters (99mtechnetium or 131iodine) 3-dimensional SPECT = single-photon emission computed tomography PET = positron-emission tomography high-energy positron emitters

Volume change Resistance change CT-scan-derived modeling basis Functional respiratory imaging (FRI) – using Computational Fluid Dynamics to assess treatment effect Volume change Resistance change CT-scan-derived modeling basis Dr. Ir. Jan De Backer, CEO FluiDA

Functional respiratory imaging (FRI) – using Computational Fluid Dynamics (CFD) to assess deposition Step 1 CT scan of patient’s lungs captured to develop 3D patient-specific anatomical models1 Inhaler characteristics such as fine particle fraction, mass median aerodynamic diameter (MMAD) and geometric standard deviation (GSD), and plume velocity are incorporated into the CFD model1 Step 2 0.5 1.0 1.5 2.0 3.5 100 80 60 40 20 Flow (L/min) Time (s) 2.5 3.0 30 L/min 57 L/min 47 L/min Inhalation factors such as flow rate profile and duration are entered into the algorithm1 Step 3 Deposition modeled with CFD1 Step 4 CFD, computational fluid dynamics; CT, computed tomography 1. FLUIDDA nv, Kontich, Belgium

Computational Fluid Dynamics (CFD) vs in vivo scintigraphy Vinchurkar Inhal Toxicol 2012

Pulmonary aerosol delivery Where are the targets? Localization of drug receptors How can lung deposition be assessed? Patient’s skills and behaviour Lung disease and deposition What are the factors that influence aerosol deposition?

Factors influencing aerosol deposition Device (internal resistance…) Content (pharmacological agents, excipients, propellants) Inhalation technique Adherence Preference Adequate particle size (MMAD) & respirable dose/fine particle fraction Appropriate treatment delivery MDIs and BAIs propel the content into the airways With DPIs, inhalation is the only propellant Haughney J et al. Respir Med 2010;104:1237–45; Papi A et al. Eur Respir J 2011;37:982–5

Determinants of lung deposition: the patient Manipulation Preparation of inhalation Dose preparation Actuation Exhalation to Functional Residual Capacity Inhalation manoeuvre/ profile Preparation of inhalation Volume (high Flow slow (4-5 sec, 30 L/min for MDIs, quick for DPIs Shape (sharp vs progressive) Breath-holding > 4 sec Airways Airways anatomy Oropharynx, larynx Lower respiratory tract Airflow obstruction

Determinants of lung deposition: the device and its content Particle chemical characteristics Particle size distribution Aerodynamic diameter Fine particle fraction (<5µm) Plume characteristics (MDI, soft mist inhaler) Speed Temperature Inspiratory flow required to deaggregate the formulation (DPI) , Depends on technological characteristics including internal resistance

Deposition versus particle size Fine particle fraction Respirable mass Based on data from a mathematical model Adapted from Pritchard JN. J Aerosol Med 2001; 14(Suppl 1):S19–26 1. Mitchell JP, Nagel MW. KONA 2004;22:32–65

Deposition versus particle size No influence of disease/airflow obstruction when delivering ultra-fine particles Mean FEV1: 43% (COPD)-70%(asthma) N=8 per group De Backer JAMPDD 2010

In vitro mean fine particle mass Flow dependency varies between DPIs 30 20 10 In vitro mean fine particle mass (% label claim) DPI A DPI B 16% 21% 6% 18% Flow rate 28.3 L/min Flow rate 60 L/min Taylor A et al. Int J Clin Pract. 2005;59:7–12