Assessing Quality of Inhaled Products And Links to Efficacy and Safety

Transcription

1 Assessing Quality of Inhaled Products And Links to Efficacy and Safety Prasad Peri, PhD ONDQA 2011 IPAC-RS Conference Bringing Value To The Patient In A Changing World March 30, Outline of the Presentation FDA proposed updates to the 1998 MDI/DPI guidance Recommended approached to developing/testing inhaled drug products Quality links to efficacy and safety. APSD DDU Challenged in QbD and Efficacy Summary 2 1

2 Current Inhaled Therapies The world market for asthma drugs > $21.94 billion by US market accounting for approximately half of the global total. 3 Orally Inhaled Products for Local Action/Systemic Delivery Propellant driven metered dose inhalers (MDIs) Dry powder inhalers (DPIs) Pre-metered singe dose unit Pre-metered multiple dose unit Drug reservoir Inhalation Sprays HandiHaler TwistHaler Diskus Nebulizers 4 2

3 1998 MDI/DPI Guidance-Comments This draft provides comprehensive recommendations for drug product characterization, manufacturing and quality control to be followed by the manufacturers of MDIs and DPIs. DCU recommendations are non parametric content uniformity tests Do not reflect fully the principles of espoused in ICH Q8, Q9, and Q10 Mass balance requirements are too tight Too prescriptive and we shouldn t be telling how to develop the drug product Working on update to the MDI/DPI Principles of Pharmaceutical Development in ICH Q8(R2) 5 Proposed Approach 6 3

4 What is QbD? Systematic approach to development Begins with predefined objectives Emphasizes product and process understanding and process control Based on sound science and quality risk management 7 Why QbD? Higher level of assurance of product quality for patient Improved product and process design and understanding Quality risk management in manufacturing Monitoring, tracking, and trending of product and process Continuous improvement Cost saving and efficiency for industry Increase efficiency of manufacturing process Minimize and eliminate potential compliance actions Provide opportunities for continual improvement Facilitate innovation More efficient regulatory oversight Streamline post approval manufacturing changes and regulatory processes 8 4

5 QbD Approach Product profile CQAs Risk assessment Design space Control strategy Continual Improvement Quality Target Product Profile (QTPP) Determine critical quality attributes (CQA) Link raw material attributes and process parameters to CQA and perform risk assessment Develop a design space Design and implement a control strategy Manage product lifecycle, including continual improvement 9 QbD Approach Product profile CQAs Risk assessment Design space Control strategy Quality target product profile Proposed dosage form Delivery system Strength (target emitted dose or target metered dose) Purity Stability Aerodynamic performance Continual Improvement 10 5

6 Product profile CQAs Risk assessment Design space Control strategy Continual Improvement QbD Approach-MDIs Critical Quality Attributes-MDIs Assay Impurities and Degradants Delivered Dose APSD Spray Pattern/Plume Geometry Leachables Excipients Foreign Particulate Matter Moisture Content Net Content Device CQAs Dose Counter 11 Linking Strength and CQAs for a MDI Strength (Target Emitted Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered Dose APSD Spray Pattern/Plume Geometry Leachables Amount of Excipient(s) Foreign Particulate Matter Moisture Content Net Content Device CQAs Dose Counter Force to fire/force to count 12 6

7 Linking Purity and CQAs for a MDI Strength (Target Emitted Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered Dose APSD Spray Pattern/Plume Geometry Leachables Amount of Excipient(s) Foreign Particulate Matter Moisture Content Net Content Device CQAs Dose Counter Force to fire/force to count 13 Linking Stability and CQAs for a MDI Strength (Target Emitted Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered Dose APSD Spray Pattern/Plume Geometry Leachables Amounts of Excipients Foreign Particulate Matter Moisture Content Net Content Device CQAs Dose Counter Force to fire/force to count 14 7

8 Linking AP and CQAs for a MDI Strength (Target Emitted Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered Dose APSD Spray Pattern/Plume Geometry Leachables Amount of Excipient(s) Foreign Particulate Matter Moisture Content Net Content Device CQAs Dose Counter Force to fire/force to count 15 QbD Approach-DPIs Product profile CQAs Risk assessment Design space Control strategy Continual Improvement Critical Quality Attributes-DPIs Assay Impurities and Degradants Delivered dose APSD Volatile/Semi volatile leachables Foreign particulate matter Moisture content Device HandiHaler Diskus TwistHaler 16 8

9 Linking Strength and CQAs for a DPI Strength (Target Metered Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered dose APSD Volatile/Semi volatile leachables Foreign particulate matter Net Content Moisture content Device 17 Linking Purity and CQAs for a DPI Strength (Target Metered Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered dose APSD Volatile/Semi volatile leachables Foreign particulate matter Net Content Moisture content Device 18 9

10 Linking Stability and CQAs for a DPI Strength (Target Metered Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered dose APSD Volatile/Semi volatile leachables Foreign particulate matter Net Content Moisture content Device 19 Linking AP and CQAs for a DPI Strength (Target Metered Dose) Purity Stability Aerodynamic Performance Assay Impurities and Degradants Delivered dose APSD Volatile/Semi volatile leachables Foreign particulate matter Net Content Moisture content Device 20 10

11 Material Attributes/Process Parameters to CQAs and Risk Product profile CQAs Risk assessment Design space Control strategy Continual improvement Risk Identification What might go wrong Historical data, theoretical analysis, informed opinions and concerns Risk Analysis Estimation of risk and linking to occurrence and severity of harm Risk Evaluation Compares identified risk to criteria 21 Tougas et al, USP presentation, Dec

12 Risk Assessment for Orally Inhaled Drug Products for Local Action Dry Powder Inhalers APSD, and, DDU or DCU Create Design Space Based on Risk Assessment Armanni et al. On-screen%20version_IPAC2008%20Poster.pdf 23 Potential for Extractables and Leachables Shaw, Arthur J.; Ball, Douglas J.; Beierschmitt, William P.; Colgan, Stephen T.; Lynch, Michael P. and Zweiben, Cindy Extractables and Leachables An Evolving Analytical Role in Drug Product Development. AAPS newsmagazine (September 2010) 24 12

13 Design Space Materials - Process - Product Materials Process Design Space Product While it is possible to have a Design space for all operations, it is not necessary as part of a QbD approach. 25 Developing Design Space for MDI Formulation vs. Droplet Size Product profile CQAs Risk assessment Design space Control strategy Continual Improvement Smith and Hickey; AAPS PharmSciTech 2003; 4 (3) 26 13

14 Product profile Design Space for a DPI Effect of spray drying parameters on APSD CQAs Risk assessment Design space Control strategy Continual Improvement Temperature Airflow Concentration 27 Device Development-1 Product profile CQAs Risk assessment Design space Control strategy Continual Improvement Steckel and Muller, Int J. Pharmaceut, 154, 19-29,

15 Device Development -2 Product profile CQAs Risk assessment Design space Control strategy Continual Improvement USP Workshop, Dec Control Strategies for APSD and DDU Product profile CQAs Risk assessment Design space Control strategy Aerodynamic Particle Size Distribution Current Approach Abbreviated Impactor Measurement (AIM) Delivered Dose Uniformity Zero Tolerance Parametric Tolerance Interval Testing Continual Improvement 30 15

16 APSD Testing The FDA 1998 guidance recommends Cascade impactors within NDAs be of the same design Control temperature and relative humidity Number of actuations based on sensitivity of method Drug substance deposited on the critical stages of the cascade impactor should be characterized Acceptance criteria proposed in terms of appropriate groupings of stages MMAD, GSD, respirable fraction, respirable dose, or fine particle mass are not considered adequate to characterize the particle size distribution of the whole dose 31 Typical APSD Specifications Stage Groups Group 1 (Adaptor- S0) Group 2 (S1-S3) Group 3 (S4-S6) Group 3 (S7-Filter) Acceptance Criteria mcg NMT 15 mcg mcg NMT 10 mcg 32 16

17 Cutoffs for Cascade Impactors at 60L/min 33 Current Trends in APSD Testing Vs. ACI AIM Pictures: Courtesy: ACI -- Ed Warner, Process Drift, PQRI FDA Workshop Dec C-FSA (Fast Screening Anderson) Copley Scientific, Inhalationmag.com, June

18 AIM Concept In 2009/2010 concepts of AIM approach was proposed by IPAC-RS for routine Quality Control. Traditional multistage cascade impaction methods for measuring APSD is labor intensive, operator inconsistency can make them subject to measurement variability. May facilitate Quality-by-Design studies and creation of the Design Space. Briefing document included papers published by Tougas et al in AAPS PharmSciTech The abbreviated impactor measurement concept, Jolyon P.Mitchell, Mark W.Nagel, and Mark Copley 35 Inhalation 2009 AIM concept reduces the 7 or 8 data points associated with the typical full resolution APSD to the 2 mass fractions assigned to fine (FPF) and coarse (CPF) particles. AIM Concept The abbreviated impactor measurement concept, Jolyon P. Mitchell, Mark W. Nagel, and 36 Mark Copley Inhalation

19 AIM Concept Tougas et al, USP, Aerodynamic Particle Size Testing of Orally Inhaled Products: Abbreviated Impactor Measurements and 37 Efficient Data Analysis (AIM/EDA) Dec 2010 IPAC-RS meeting July 2010 Contained data on 8 products (HFA MDI solution, 2 HFA MDI suspension, 2 DPIs, 3 CFC Suspensions). Publication claims that The time required is greatly reduced Improved overall precision Improve quality decisions, i.e., batch disposition. Time savings associated with AIM systems may increase samples evaluated from a batch within a fixed timeframe Reducing the number of manipulations decrease the chances of operator-related errors. Environmentally friendly by using less solvents Simpler apparatus configurations that are more amenable to automation 38 19

20 Preliminary Thoughts on AIM Statistical concerns about APSD portions (large and small particle masses) may be positively correlated to ISM. Multiple distributions can share the same LPM/SPM ratio. Uni-modal and bimodal distributions may share the same mean and variation. While it reduces variability in measurements it comes with loss of full information QC test based on only two measures considers less information than current test 39 Conclusions for AIM AIM is useful as a research tool for quick analysis! FDA recognizes that AIM will save time and hence better throughput. Will this eventually give rise to more samples being tested? If the issues highlighted by the statisticians are addressed there is scope to consider AIM and EDA as a important analytical tool. The Agency believes that better science should lead to better regulations and are open to discussion to alternative approaches to control strategies

21 DDU- Parametric Tolerance Interval Test (PTIT) PTIT is a more scientific and risk based approach to setting DDU specifications Elimination of zero tolerance criteria is appropriate in this context PTIT is an approach consistent with QbD that calls for product and process understanding Clinically relevant specification Understanding of process leads to good control of variability 41 Parametric Tolerance Interval Test (PTIT) Many applicants have proposed PTIT approaches for a number of attributes and parameters. Collaboratively within the FDA the chemists and statisticians have recommended acceptable proposals to the applicants. This avenue may be further explored not only for DDU but other attributes as well

22 Challenges to Linking APSD to Efficacy Computer mode of particle size distribution Drug on lactose particle 43 Aerodynamic Particle Size Distribution 44 Respiratory Drug Delivery 2008 Annual Meeting 22

23 APSD-Monodispersed Albuterol Study In a randomized study 12 patients with asthma inhaled 1 L aerosol of Tc labeled monodispersed albuterol 30 µg at particle sizes of 1.5, 3, and 6 µm MMAD 1.5 µm 3 µm 6 µm 1.5 µm 3 µm 6 µm Total Lung Deposition % of Total Delivered Dose Peripheral Lung Central Lung Deposition Deposition Exhaled FEV1 in ml Monodispersed aerosol may have a role in defining product profile and design space 45 Am J Respir Crit Care Med 2005; 172: APSD - Targeting Inhaled Drugs 6 µm 3 µm 1.5 µm Optimum particle size for inhaled beta-agonists appear to be 3 µm to 6 µm Optimum particle size for inhaled corticosteroids is not known 46 Respiratory Drug Delivery 2008 Annual Meeting 23

24 APSD-Monodispersed Beclomethasone Study In a randomized study 10 patients with asthma inhaled monodispersed beclomethasone at particle sizes of 1.5, 2.5, and 4.5 µm MMAD 2.5 µm 4.5 µm 1.5 µm Monodispersed aerosol may have a role in defining product profile and design space Mean plasma concentration of 17-BMP. Gastrointestinal absorption blocked by activated charcoal ingestion. 47 Br J Clin Pharmacol 2007; 64: Status of QbD for Inhaled products QbD has moved into the implementation phase of product manufacturing and control The cornerstone for QbD in inhaled products has been laid from a quality perspective FDA has seen QbD elements in applications for inhaled products. Much of science is there, and some development is needed Time is right to apply QbD approaches for efficacy and safety assessment based on product s clinical use and risk