QbD Understanding How Excipient Properties Influence Solid Oral Dosage Form Performance

QbD Understanding How Excipient Properties Influence Solid Oral Dosage Form Performance Dr Amina Faham (Dow), Dr Liz Meehan (AstraZeneca) ExcipientFest, Amsterdam NL June 24, 2014

What do you understand by the term QbD, in particular applied to excipients? AstraZeneca Do not share without permission

Traditional versus QbD approach In traditional approaches, industry focused on: Similar excipient lots are used during development and in commercial manufacturing (avoiding variation) Optimized, fixed formulation and fixed process parameters Compliance with compendial specifications for excipients QbD approach encourages: Understanding variation of excipients properties as they relate to critical process parameters and product quality attributes Building robustness and flexibility into manufacturing process Excipient specifications appropriate to ensure product quality AstraZeneca Do not share without permission

Product Quality Attributes Source and Effect/s API Variability Product Variability Excipient Variability Understanding variability & tolerating it = Robustness Process Variability σ 2 Product σ 2 API σ 2 Excipients σ 2 Process σ 2 Interactions Ref: C. Moreton AstraZeneca Do not share without permission 4

Excipient functionality and performance Quantitative performance requirements (i.e. critical material attributes) of excipients Characterisation of excipients to determine their suitability for intended use Must be evaluated and controlled to ensure consistent performance throughout the product life-cycle (e.g. changes in suppliers) Integral to the "Quality by Design" approach that should be employed in drug product development AstraZeneca Do not share without permission

Quality by Design Spec range CQA Product attributes MSA Drug product Safety and efficacy CPP Process parameters Processing Intermediate attributes CMA API Excipients CMA Material attributes Material attributes CMA AstraZeneca Do not share without permission

Quality by Design CQA=Critical quality attributes of the product CMA=Critical material attributes of all input raw materials CPP=Critical process parameters MSA=measurement systems analysis Target Drug Product Profile CQA = f (CMA, CPP) AstraZeneca Do not share without permission

Why QbD for excipients? Excipient properties can affect CQAs of drug product Manufacturability (e.g. flow, compaction) Content uniformity (e.g. segregation) Bioavailability (e.g. disintegration, dissolution) Purity Stability (e.g. chemical and physical incompatibilities) It is important to understand and control the effects of excipient variability AstraZeneca Do not share without permission

Challenges Excipients developed and manufactured specifically for pharmaceutical use are often available in a range of special grades (developed for specific formulation or process) There are multiple suppliers of nominally the same grade lot-to-lot/batch-to-batch/supplier inequivalence or variability variability in excipient properties should be anticipated and appropriate controls must be in place to ensure consistent performance Excipient applications for pharmaceutical development are many and varied AstraZeneca Do not share without permission

Challenges Identification and control of critical material attributes may go beyond monograph specifications and require a thorough understanding of the formulation the process the physical and chemical properties of each ingredient Critical material attributes should be evaluated and controlled to ensure that consistent product performance is achieved throughout the product lifecycle Requires user/supplier collaboration AstraZeneca Do not share without permission

Challenges An excipient may have very different functions in the formulation e.g., diluent, lubricant, glidant It may require different performance characteristics e.g., particle size, size distribution, surface area depending on its use in a formulation, manufacturing process, and dosage form. The development, manufacture, and performance of pharmaceutical dosage forms depend heavily upon the physical and chemical properties of the excipients Physical Particle morphology, powder property, polymorph, hygroscopicity, aqueous solubility, pka, and density Chemical Identity, purity, incompatibility with drug substance or other excipients Mechanical Flowability, compressibility AstraZeneca Do not share without permission

USP versus PhEur : different approach USP Information Chapter <1059> Excipient Performance Overview of the key functional categories of excipients identified in USP NF. Guidance as to which properties might be important for a particular material in a particular application. Cross-references to standard methods that can be used by both manufacturers and users: Makes communication more straightforward Avoids an unnecessary plethora of test variations for a particular parameter. Keeping the tests non-mandatory. Avoiding confusion with mandatory tests and labelling tests. Not imposing limits/specifications. AstraZeneca Do not share without permission

Extract from USP <1059> Not all critical material attributes of an excipient may be identified or evaluated by tests, procedures, and acceptance criteria in NF monographs. Excipient suppliers and users therefore at times may wish to identify and control critical excipient attributes that go beyond monograph specifications. AstraZeneca Do not share without permission

USP versus PhEur : different approach PhEur Within each individual excipient monograph a section exists for non-mandatory Functionality Related Characteristics (FRCs) that should be considered e.g. Croscarmellose sodium Settling volume Degree of substitution Particle size distribution Hausner ratio e.g. Dibasic Calcium Phosphate Particle size distribution Bulk and tapped density Powder flow AstraZeneca Do not share without permission

Excipient variability how much do you need to do? A risk based approach benefits both the patient and the business Not all excipients have an impact on product quality or safety Not all properties of an excipient are equally important In many cases normal excipient variation does not negatively impact the quality and safety of the product The way forward Comprehensive studies of excipient properties are only needed when the excipient properties are expected to impact the critical quality attributes (CQAs) of the drug product The goal is to define control strategy for excipients AstraZeneca Do not share without permission

Case study to exemplify the approach Microcrystalline cellulose Degree of polymerisation ph Bulk density Loss on drying Residue on ignition Conductivity Ether soluble substances Water soluble substances Impurities Particle size distribution Mannitol Conductivity Loss on drying Reducing sugars Assay Particle size distribution Porosity/Specific surface area Bulk density Polymorphic form Impurities Sodium starch glycolate ph Loss on drying Sodium chloride Sodium glycolate Assay (Na) Bulk density Rate/degree of swelling Magnesium stearate Particle size Specific surface area Loss on drying Stearic/palmitic acid level Assay (Mg) To explore every material attribute would require many thousands of experiments Risk assessment is required to focus the experimental programme AstraZeneca Do not share without permission

Assessing the risk of excipient variability Collect existing data/information on the raw materials Excipient monographs, literature examples, Handbook of Pharmaceutical Excipients, supplier certificates of analysis, supplier databases, etc Refer to target product profile target patient populations, geographical markets, etc For each excipient in the formulation, identify potential critical material attributes (functionality) and potential risk factors (security of supply, commercial and regulatory considerations) Score the potential risk for each material attribute and risk factor AstraZeneca Do not share without permission

Possible outcome after risk assessment Microcrystalline cellulose Degree of polymerisation ph Bulk density Loss on drying Residue on ignition Conductivity Ether soluble substances Water soluble substances Impurities Particle size distribution Mannitol Conductivity Loss on drying Reducing sugars Assay Particle size distribution Porosity/Specific surface area Bulk density Polymorphic form Impurities Sodium starch glycolate ph Loss on drying Sodium chloride Sodium glycolate Assay (Na) Bulk density Rate/degree of swelling Magnesium stearate Particle size Specific surface area Loss on drying Stearic/palmitic acid level Assay (Mg) Risk assessment reduces the number of potential CMAs to consider for experimental work Some material attributes could be confounded providing further simplification AstraZeneca Do not share without permission

Next steps Risk assessment scores identify the highest risks excipient attributes Select/source excipient variants Batch select from a particular supplier and within grade (QbD sample sets) From one supplier use different grades (more extreme variation) From multiple suppliers (different ranges of variation) Perform risk mitigation work to study effect of excipient variability (on process and/or product performance) Use outputs to define excipient control strategy AstraZeneca Do not share without permission

Excipient supplier-user collaboration Exchange of information between excipient supplier and user is invaluable Provides benefits to both supplier and user IPEC QbD checklists developed to help facilitate this Available to IPEC Europe members as downloads from the website AstraZeneca Do not share without permission

IPEC QbD checklists For suppliers For Users AstraZeneca Do not share without permission

How HPMC Physicochemical Properties Impact Matrix Tablet Performance ExcipientFest, Amsterdam NL June 24, 2014

Outline Background and HPMC materials HPMC physical properties and how they impact matrix tablet performance HPMC chemical properties and how they impact matrix tablet performance 23

Quality by Design (QbD) Means Design the Product And The Process Design the product to meet patient requirements Design the process to consistently meet product critical quality attributes Understand the impact of starting materials and process parameters on product quality Identify and control the source of process variation Continually monitor and update the process to allow a consistent quality over time

Quality by Design (QbD) The drug product must be safe and efficacious for the patient. I.e., Ensure the dosage form performs as expected. How robust is dosage form performance? How robust is the process to make the dosage form? How robust are the methods to characterize the dosage form? What is the impact of raw material variability? (API? Excipients?) Multiple suppliers? Lot-to-lot variability? 27

Properties vs. Performance Raw material properties Physical Chemical Process Processability E.g. Flowability Process steps and parameters which are critical to quality. Performance Dosage form physical properties Achieving desired performance API release Is desired performance reproducible (e.g. from lot-to-lot, day-to-day)? 28

HPMC Matrix Tablets for Modified-Release Hydrophilic matrix tablets are the most commonly utilized MR dosage form. Simplest. Fastest to develop. Least expensive to manufacture. Hypromellose 2208 is the most common rate-modifying excipient used in hydrophilic matrices. OCH 3 O O HO HO O OCH 3 OH OH OCH OCH 3 O 3 O HO O HO O O O O OH O O CH 3 O OCH OCH 3 3 R = CH 3 OH R 29

HPMC Sustained Release Matrix Tablets Key Hypromellose Formulation Variables Level Molecular weight/viscosity Substitution type Particle size distribution Actives and other excipients can cause the formulation to be more sensitive to HPMC properties

How HPMC Physical Properties Impact Matrix Tablet Performance 31

Hypromellose Level For a selected hypromellose product, polymer level is usually the major drug release rate controlling factor Ford et al. 1985. IJP, 24:327-338 and 339-350 Drug release may be more sensitive to variations in hypromellose properties at low hypromellose levels (< 30%) 10% propranolol HCl, METHOCEL K4M balance lactose, 0.5% mag stearate 32

Particle Size 33

Drug Released (%) Particle Size 100 90 80 caffeine (50%), K15M (30%) - 6 hr metoprolol tartrate (20%), K4M (30%) - 3 hr theophylline (50%), K4M (30%) - 6 hr 70 60 50 40 30 0 10 20 30 40 50 60 70 80 90 100 HPMC Particle Size (% thru 230 mesh) 34

Drug Released (%) Particle Size 100 90 80 acetaminophen (50%), K100M (30%) - 6 hr hydrochlorothiazide (50%), K100 LV (30%) - 3 hr ketoprofen (20%), K4M (30%) - 12 hr 70 60 50 40 30 0 10 20 30 40 50 60 70 80 90 100 HPMC Particle Size (% thru 230 mesh) 35

% PP dissolved METHOCEL K15M Premium CR Propranolol HCl release: effect of particle size 100 80 60 40 f 2 = 48.23 f 2 = 94.14 20 0 0 120 240 360 480 600 720 Time (min) High % thru 230 mesh/ Low Level Low % thru 230 mesh/ Low Level Center Point/ Low Level High % thru 230 mesh/ High Level Low % thru 230 mesh/ High Level Center Point/ High Level Higher polymer level slower drug release Higher polymer level lower variability Drug release were significantly affected by coarser P/S for lower polymer level 36

How HPMC Chemical Properties Impact Matrix Tablet Performance 37

Selection of Hypromellose substitution grade Hypromellose grade has a significant effect on dissolution Methylcellulose and Hypromellose 2906 (A and F Chemistry) typically are not used for CR applications 38

% PP dissolved METHOCEL K15M Premium CR Propranolol HCl release: effect of viscosity 100 80 60 f 2 = 66.90 f 2 = 74.21 40 20 0 0 120 240 360 480 600 720 Time (min) High Viscosity/ Low Level Low Viscosity/ Low Level Center Point/ Low Level High Viscosity/ High Level Low Viscosity/ High Level Center Point/ High Level The similarity factor (f 2 ) was calculated by comparing high vs. low end of the selected physicochemical property Higher polymer level slower drug release Higher polymer level lower variability Drug release were consistent across viscosity range 39

Hypromellose Substitution 50% diclofenac sodium, 40% METHOCEL K15M 9.5% lactose, 0.5% mag stearate 40% salicylic acid, 30% METHOCEL K15M 29% lactose, 1% mag stearate 40

Paracetamol Model Example Ingredient % w/w Weight per tablet (mg) Paracetamol* 50 250 METHOCEL K4M or Pilot Plant HPMC 30 150 Lactose 18 90 Magnesium stearate 1 5 Talc 1 5 Total 100 500 Actual tablet weight: 502 ± 3 mg Hardness: 94 ± 8 N * Paracetamol: Analgesic Aqueous solubility: 14 mg/ml

Paracetamol Released (%) Batch-to-Batch Consistency Batch-to-batch consistency with commercial METHOCEL : Reproducible modified-release performance. 100 80 60 40 20 0 0 200 400 600 800 1000 1200 1400 Time(min) Batch no. 1 Batch no. 2 Batch no. 3 Batch no. 4 Batch no. 5 Batch no. 6 Batch no. 7 Batch no. 8 Batch no. 9 Batch no. 10 Batch no. 11 Batch no. 12 Batch no. 13 Batch no. 14 Batch no. 15 Batch no. 16 Batch no. 17 Batch no. 18 Batch no. 19 Batch no. 20 Rogers TL, Petermann O, Adden R, and Knarr M (2011). Investigation and rank -ordering of hypromellose 2208 properties impacting modified release performance of a hydrophilic matrix tablet, Twenty-Sixth Annual Meeting, Proceedings of the American Association of Pharmaceutical Scientists, Washington DC, Poster no. R6168. 900 ml ph 5.7 phosphate buffer at 37 C 50 rpm paddle speed Tablets placed in sinkers n=6 standard deviation was never more than 2% 50% Cumulative Volume Particle Size (µm) Commercial Batch No. %Me %HP %NaCl 1 22.8 8.3 93.8 0.2 3711 2 23.1 8.7 91.9 0.3 4514 3 22.2 9.1 84.3 0.3 3638 4 22.6 8.4 88.7 0.1 4953 5 22.7 8.2 94.1 0.2 4015 6 23.0 8.5 97.8 0.2 4444 7 23.3 8.7 102.1 0.3 3506 8 23.2 8.8 110.8 0.3 3897 9 23.1 8.6 109.1 0.3 3615 10 23.1 8.6 103.7 0.3 3615 11 22.2 8.6 96.7 0.6 3756 12 23.0 8.8 107.9 0.3 3810 13 23.0 8.7 103.1 0.4 4325 14 23.3 8.7 99.3 0.3 3775 15 23.4 8.7 99.3 0.3 3849 16 22.9 8.5 98.8 0.4 4364 17 22.8 7.9 101.9 0.3 4562 18 23.6 8.4 104.3 0.3 4322 19 23.1 8.7 101.2 0.4 4057 20 23.0 8.7 100.8 0.4 3839 Average 23.0 8.6 99.2 0.3 3996 Std Deviation 0.4 0.3 6.6 0.1 414 2% Viscosity (mpa s) 42

METHOCEL FRCs Impacting Performance ESTABLISHING THE PERFORMANCE DESIGN SPACE Based on this model, rank-order of METHOCEL FRC impact is as follows: %HP (p < 0.05) > 2% viscosity (p = 0.06) > particle size (p = 0.13) > %Me (p = 0.75). Correlations between paracetamol release and HP substitution vs. 2% viscosity reflect findings from the model. Paracetamol release increases with increasing HP content. Trend occurs over a narrow range of 79-86% paracetamol released at 22 hr, reflecting reproducible batch-to-batch modified-release performance. Rogers TL, Petermann O, Adden R, and Knarr M (2011). Investigation and rank -ordering of hypromellose 2208 properties impacting modified release performance of a hydrophilic matrix tablet, Twenty-Sixth Annual Meeting, Proceedings of the American Association of Pharmaceutical Scientists, Washington DC, Poster no. R6168. 43

HP Content (%) Pilot Plant HPMC vs. Commercial METHOCEL 12 11 10 9 8 7 6 5 4 Expanded design space boundaries with pilot plant HPMC. HP substitution was purposefully varied. Premise: There is insufficient batch-to-batch variability in commercial METHOCEL to investigate performance design space proactively. We cannot explore the allowable pharmacopeial design space. Where are the boundaries of robustness? What if we miss optimal performance sweet spots? Breadth of minimum and maximum HP content (4 12%) according to the harmonized pharmacopeia (USP, PhEur, and JP). Commercial Batches 1 through 21 Pilot Plant Batches 1 through 9 Sample identification %Me %HP 50% cumulative volume particle size (µm) %NaCl 2% viscosity (mpa-s) See previous section for FRCs of commercial batches investigated Prototype No. 1 24.2 8.6 78.5 0.1 4466 Prototype No. 2 23.0 11.4 72.0 0.1 4346 Prototype No. 3 24.0 9.1 64.6 0.1 2730 Prototype No. 4 24.4 6.0 84.8 < 0.1 5292 Prototype No. 5 23.1 11.2 70.3 0.1 3356 Prototype No. 6 24.4 6.6 66.8 < 0.1 5476 Prototype No. 7 23.3 7.8 70.5 < 0.1 5092 Prototype No. 8 23.4 9.5 66.1 < 0.1 4999 Prototype No. 9 23.7 10.2 52.4 < 0.1 5009 Rogers TL, Knarr M, Petermann O, and Adden R (2011). Expanding design space boundaries within pharmacopeial limits: Impact of atypical hydroxypropoxyl substitution on drug release from HPMC matrices, Twenty-Sixth Annual Meeting, Proceedings of the American Association of Pharmaceutical Scientists, Washington DC, Poster no. R6167. 44

Modified-Release Performance Pilot plant HPMC data brackets commercial METHOCEL data for HP substitution and paracetamol release. Paracetamol release increases with increasing HP substitution. Efficiently determined that formulation is robust. Rogers TL, Knarr M, Petermann O, and Adden R (2011). Expanding design space boundaries within pharmacopeial limits: Impact of atypical hydroxypropoxyl substitution on drug release from HPMC matrices, Twenty-Sixth Annual Meeting, Proceedings of the American Association of Pharmaceutical Scientists, Washington DC, Poster no. R6167.

Indapamide Example Ingredient % w/w Weight per tablet (mg) Indapamide* 2.5 5 Pilot Plant HPMC 40 80 Lactose 40 80 Microcrystalline cellulose 16.5 33 Magnesium stearate 0.5 1 Talc 0.5 1 Total 100 200 Actual tablet weight: 200 ± 3 mg Hardness: 83 ± 8 N Friability: Weight loss 0.16% * Indapamide: Antihypertensive Aqueous solubility: 75 µg/ml

Indapamide Released (%) Modified-Release Performance Only variable was the HPMC batch used. Same formulation composition. Tried to hold everything constant except HPMC batch. 100 80 60 40 % indapamide released at 17 hr ranged from 60 to 90% 0.1% SLS in 900 ml water at 37 C 50 rpm paddle speed Tablets placed in hanging baskets n=6 standard deviation was never more than 5% 20 0 Breaking point in modified release performance 0 200 400 600 800 1000 1200 1400 Time (min) Step-change increase in API release Proactively determined that API and formulation are very sensitive to variation in %HP substitution. High risk of batch failure. 47

Performance Design Space Modulation of API release spans of ~35% Potential extent of variation unacceptable Proactive exploration of design space identified highly responsive API Breaking point in modified release performance Above HP content of 7.8% HPMC specification recommended Step-change increase in API release

Summary Modified release performance is most significantly impacted by HP substitution of METHOCEL HP substitution is the primary factor modulating modified release Forced-variation prototypes enabled expansion of the design space boundaries of our model formulation APIs highly responsive to METHOCEL FRCs 49

Questions? Thank You! 11/24/11