Compliant Formulation Development The Key to Successful Pharma Development

Transcription

1 Compliant Formulation Development The Key to Successful Pharma Development Oberägeri, May 4th 2012 Dr. R. Rogasch

2 Regulatory Requirements in Formulation Development EU Scientifc Guidance Documents EMA (Clinical, CMC, Procedural) EP7 General Chapters, Monographs US FDA Guidance Documents (Clinical, CMS, Procedural) USP General Chapters and Methods (Dissolution Method Development, IVIVC requirements, Statistical Methodology) ICH Q8/Q9/Q10 2

3 Regulatory Requirements in Formulation Development EU Scientifc Guidance Documents Formulation Development IMP Procedure (pre-clinical data, dossier submission requirements, clinical studies) CMC requirements (specifications, stability data, pre-process validation) Bioequivalence or Biowaiver approach 3

4 Regulatory Requirements in Formulation Development EU EP7 requirements Generic Drug Development - Legal status of monographs Monographs are official standards The Convention on the Elaboration of a European Pharmacopoeia makes the texts of the Ph. Eur. mandatory in all signatory parties The pharmaceutical legislation in the European Union makes monographs obligatory standards (2001/83/EC, 2001/81/EC) Monographs may be accepted as suitable standards even when not obligatory 4

5 Regulatory Requirements in Formulation Development EU EP7 requirements Generic Drug Development - example Do Ph. Eur. specifications apply throughout shelf-life? A: Yes, specifications apply until time of use for raw materials and throughout period of validity for preparations B: No, Ph. Eur. requirements are for release only From ICH Quality Implementation Working Group - Integrated Implementation Training Workshop Breakout D: Pharmacopoeial Requirements, Kuala Lumpur, July

6 Regulatory Requirements in Formulation Development EU EP7 requirements Generic Drug Development - example Do Ph. Eur. specifications apply throughout shelf-life? A: Yes, specifications apply until time of use for raw materials and throughout period of validity for Preparations (EP7, general notices) B: No, Ph. Eur. requirements are for release only. Implications : EP7 mongraph specifications (impurities) are shelf life indicating! From ICH Quality Implementation Working Group - Integrated Implementation Training Workshop Breakout D: Pharmacopoeial Requirements, Kuala Lumpur, July

7 ICHQ8/9/10 Paradigm in Formulation Development Disclaimer The information within this presentation is based on the ICH Q-IWG members expertise and experience, and represents the views of the ICH Q-IWG members for the purposes of a training workshop. 7

8 QRM as part of development To assess the critical attributes of Raw materials Solvents Active Pharmaceutical Ingredient (API) Starting materials Excipients Packaging materials To establish appropriate specifications, identify critical process parameters and establish manufacturing controls 8 ICH Q9

9 II.3: QRM as part of development To decrease variability of quality attributes: reduce product and material defects reduce manufacturing defects To assess the need for additional studies (e.g., bioequivalence, stability) relating to scale up and technology transfer To make use of the design space concept (see ICH Q8) 9 ICH Q9

10 Key Steps for a product under Quality by Design (QbD) Pharmaceutical Development Prior Knowledge (science, GMP, regulations,..) Product/Process Development DOE : Design of Experiment QRM principle apply at any stage Quality Target Product Profile CQA : Critical Quality Attribute CPP : Critical Process Parameter Risk Management QTPP : Definition of intended use & product Potential CQA (Critical Quality Attribute) identified & CPP (Critical Process Parameters) determined Design to meet CQA using Risk Management & experimental studies (e.g. DOE) Link raw material attributes and process parameters to CQAs and perform Risk Assessment Methodology Product/Process Understanding Opportunities Design Space (DS), RTR testing Technology Transfer PQS & GMP Local Environment Control Strategy Quality System PQS Batch Release Strategy Marketing Authorisation Commercial Manufacturing Quality Unit (QP,..) level support by PQS Continual improvement Manage product lifecycle, including continual improvement 10

11 P2 of CTD as part of a regulatory submission EXAMPLE In line with Quality Risk Management? 11

12 P2 of CTD as Quality Risk Management process? Formulation & Process design Initiate Quality Risk Management Process Risk Assessment Risk Identification Process understanding Risk Analysis Manufacturing Concept Process control Concept Product release Concept Risk Communication Risk Evaluation Risk Control Risk Reduction Risk Acceptance unacceptable Risk Management tools Regulatory strategy Output / Result of the Quality Risk Management Process Risk Review Review the submission Review Events 12

13 Development Formulation understanding Developm. Operation Re-evaluation evaluation and confirmation Target Product Profile Drug substance properties; prior knowledge Proposed formulation and manufacturing process Research FORMULATION DESIGN SPACE Determination of Cause Effect relationships (Risk Identification with subsequent Risk Analysis) Risk-based classification (Risk Evaluation) Parameters to investigate (e.g. by DOE) (Risk Reduction 1. proposal; 2. verified) Phase 2 Phase 1 Process understanding Re-evaluation evaluation and confirmation Product and process characteristics on the PROCESS final drug product DESIGN SPACE BY UNIT OPERATION CONTROL Review events STRATEGY Phase 3 13 Launch

14 Responsibilities in regulatory operations Industry Initiate Quality Risk Management Process EXAMPLE Risk Assessment Team focused Risk Identification Risk Analysis Risk Communication Internal consultation Risk Evaluation Risk Control Risk Reduction Risk Acceptance unacceptable Risk Management tools B) Inspectorates Stakeholder involvement Output / Result of the Quality Risk Management Process Risk Review Review Events 14 A) Reviewers

15 Formulation Strategies for Phase I/II Clinical Programs General Outline The overall sequence for DP development for each phase/clinical trial can be summarized as follows: Define the best formulation, with the choice of excipients based on maximizing the physical and chemical stability of the API Ensure the formulation provides the desired in vitro release of drug Conduct pharmacokinetic studies in animals, if models are available that are known to predict clinical responses. Define the best manufacturing process for DP Place the final DP prototype on accelerated stability in intended packaging Conduct GMP manufacture and packaging of clinical DP Generate batch release data and certificate of analysis (CoA) for clinical DP Initiate an accelerated stability program for clinical DP (batch made at full scale) Submit supporting formulation and analytical data as part of the regulatory filing to request approval (i.e., from the FDA, EU, etc.) for using the DP in a clinical study 15

16 Formulation Strategies for Phase I/II Clinical Programs General Considerations Oral Dosage Forms Material Property Assessment API (solubility, Polymorphism XRD etc.) PSD (DLS, LLD) Morphology (SEM) Compound Dissolution Flow/cohesion Powder compaction Hardness, tensile strength, brittel fracture index Excipient/API interactions Degradation Pathways 16

17 Formulation Strategies for Phase I/II Clinical Programs General Considerations Oral Dosage Forms Bioavailability Enhancement API (solubility enhancement) PSD (micronization) Solubility Screening, w/o partition Precipitation inhibition (API/surfactant/polymer combinations) Amorphous Dispersions ( solid solutions, dispersion in polymer matrix) Coatings (multi-particulates in capsules) Lipid Systems (fat-matrix, SEDDS, SMEDDS, liposomal carrier) 17

18 Formulation Strategies for Phase I/II Clinical Programs IR-Oral Dosage Forms Capsule, Tablet (IR dosage forms) Direct compression Dry Granulation Wet Granulation Tabletting/Capsule Filling Film Coating Hot Melt Extrusion 18

19 Formulation Strategies for Phase I/II Clinical Programs CR - Oral Dosage Forms Capsule, Tablet (CR dosage forms) Matrix Multiparticulates Soft Gel Capsules Liquid filled Capsules Fuctional Film Coating Hot Melt Extrusion Osmotic Systems 19

20 Formulation Strategies for Phase I/II Clinical Programs Solid Orals - Excipients Solid Orals Formulation Excipients Excipient type Materials Approximate ranges (%) Function Brittle fillers Lactose Calcium phosphate, dibasic 10%-95% Imparts hardness and strength to tablets Ductile fillers Mannitol Microcrystalline cellulose Starch 10%-95% Imparts compressibility and tensile strength to tablets Binders Hydroxypropyl cellulose (HPC) HPMC Povidone 5%-10% Provides strength in dry and wet processing of powders Lubricants Magnesium stearate Stearic acid Glyceryl behenate Less than 2% Prevents sticking of formulation to processing surfaces Disintegrants Sodium starch glycolate Croscarmellose sodium Crospovidone Less than 5% Aids in breakup of tablets or granules in aqueous media Controlled release/matrix HPMC Polyethylene oxide Polyvinylpyrrolidone (PVP) 10%-95% Tailors drug release rate Glidants Fumed silica Talc Less than 1% Improves powder flow and prevents static charging Capsules Gelatin HPMC Polysaccharides 1%-5% Unit dose to contain powders or controlled release pellets 20

21 Formulation Strategies for Phase I/II Clinical Programs Solid Orals - Excipients Solubilizers, dispersants, precipitation inhibitors Poloxamer 407 SLS Cyclodextrins HPMC and acid derivatives HPC 0.5%-5% Improve solubility and wettability of hydrophobic drugs and improve bioavailability Chemical stabilizers BHT/BHA Citric acid Less than 1% Mitigate chemical degradation, oxidation Taste masking agents Sucrose Aspartame Mannitol Flavors 1%-5% Hide unpleasant drug taste, essential for chewable formulations Colorants Titanium dioxide, Iron oxides, Dyes and lakes Less than 2% Cosmetic appearance, marketing Coating ingredients Film polymers HPMC Cellulose acetate, Ethylcellulose, Polymeric acrylates 1%-30% Cosmetic or controlled release coatings 21

22 Formulation Strategies for Phase I/II Clinical Programs Solid Orals - Excipients Plasticizers, Anti-tack agent Glycerol triacetate, Fatty acid salts, esters, Polyethylene glycol, Talc Less than 1% Less than 0.5% Improve processability, Prevent sticking 22

23 Formulation Strategies for Phase I/II Clinical Programs Parenteral Dosage Forms Parenteral/injectable Solutions (lyophilization) Colloidal Suspensions (peptides, proteins) Emulsions Liposomal Systems Suspensions 23

24 Formulation Strategies for Phase I/II Clinical Programs Liquid Orals/Parenterals Excipients Excipient type Materials Approximate ranges (%) Function Diluent Water Vegetable oils Polyethylene glycol Propylene glycol 50%-90% Main solubilizing/suspending vehicle for all components Cosolvents Ethanol Polyethylene glycol Propylene glycol N- Methylpyrrolidone 20%-50% Helps with poorly aqueous soluble drugs Buffering agents Sodium chloride Sodium acetate Sodium phosphate (and corresponding acids) Sodium hydroxide Enough for adjusting to desired ph Maintain ph for optimum solubility, and comfort for injectable formulations Bulking agents Sodium chloride Hydroxypropyl methylcellulose (HPMC) Mannitol Dextrose Less than 10% Maintain osmolarity for parenterals, adjust viscosity, mechanical stability for lyophilized cakes 24

25 Formulation Strategies for Phase I/II Clinical Programs Oral Liquid/Parenteral - Excipients Solubilizers/surfactants Hydroxypropyl-betacyclodextrin Sulfobutyletherbeta-cyclodextrin HPMC Polaxamer 407 Sodium lauryl sulfate (SLS) Phospholipids Cremophors Labrasol Vitamin E TPGS Less than 5% Improve drug solubility, emulsification, suspension of drug particles, prevent precipitation Chelating agents Edetate sodium (EDTA) Citric acid/citrate Less than 1% Bind metal impurities to prevent complexation and reactions Preservatives Benzyl alcohol Methyl/ propyl parabens Benzalkonium chloride Thimerosal Less than 2% Prevent microbial growth Chemical stabilizers Butylated hydroxytoluene/anisole (BHT/BHA) Citric acid/citrate Less than 2% Antioxidants, free radical scavengers Flavoring/tastemasking Sucrose, aspartame Peppermint oil, flavors Less than 2% Sweeteners Masking of drug tast 25

26 Project Case Study Disclaimer The information within this presentation is based on the ICH Q-IWG members expertise and experience, and represents the views of the ICH Q-IWG members for the purposes of a training workshop. 26

27 Outline of Presentation Key Steps for Quality by Design Case Study Organization Introducing API and Drug Product Discussion of concepts of Quality Target Product Profile, processes, composition Description of API & Drug Product process development Discussion of illustrative examples of detailed approaches from the case study Batch release 27

28 Purpose of Case Study Illustrative example Covers the concepts and integrated implementation of ICH Q8, 9 and 10 Not the complete content for a regulatory filing Note: this example is not intended to represent the preferred or required approach. 28

29 Case Study Organization 29

30 Basis for Development Information Fictional active pharmaceutical ingredient (API) Drug product information is based on the Sakura Tablet case study Full Sakura case study can be found at Alignment between API and drug product API Particle size and drug product dissolution Hydrolytic degradation and dry granulation /direct compression 30

31 Organization of Content Quality Target Product Profile (QTPP) API properties and assumptions Process and Drug product composition overview Initial risk assessment of unit operations Quality by Design assessment of selected unit operations 31

32 Technical Examples API Drug Product Process focus - Final crystallization step - Blending - Direct compression Quality attribute focus - Particle size control - Assay and content uniformity - Dissolution API Crystallization Blending Compression Real Time Release testing (Assay, CU, Dissolution) 32

33 Process Step Analysis For each example Risk assessment Design of experiments Experimental planning, execution & data analysis Design space definition Control strategy Batch release QRM Design of Experiments Design Space Control Strategy Batch Release 33

34 QbD Story per Unit Operation QTPP & CQAs Process Variables Quality Risk Management Design of Experiments Design Space Control Strategy Batch Release Illustrative Examples of Unit Operations: API Crystallization Blending Compression Real Time Release testing (Assay, CU, Dissolution) 34

35 Introducing API and Drug Product 35

36 Assumptions & Prior Knowledge API is designated as Amokinol Single, neutral polymorph Biopharmaceutical Classification System (BCS) class II low solubility & high permeability API solubility (dissolution) affected by particle size Crystallization step impacts particle size Degrades by hydrolytic mechanism Higher water levels and elevated temperatures will increase degradation Degradates are water soluble, so last processing removal point is the aqueous extraction step Degradates are not rejected in the crystallization step In vitro-in vivo correlation (IVIVC) established allows dissolution to be used as surrogate for clinical performance Drug product is oral immediate release tablet 36

37 Quality Target Product Profile (QTPP) Safety and Efficacy Requirements Tablet Characteristics / Requirements Translation into Quality Target Product Profile (QTPP) Dose 30 mg Identity, Assay and Uniformity Subjective Properties No off-taste, uniform color, and suitable for global market Appearance, elegance, size, unit integrity and other characteristics Patient Safety chemical purity Impurities and/or degradates below ICH or to be qualified Acceptable hydrolysis degradate levels at release, appropriate manufacturing environment controls Patient efficacy Size Distribution (PSD) Particle PSD that does not impact bioperformance or pharm processing Acceptable API PSD Dissolution Chemical and Drug Product Stability: 2 year shelf life (worldwide = 30ºC) Degradates below ICH or to be qualified and no changes in bioperformance over expiry period Hydrolysis degradation & dissolution changes controlled by packaging QTPP may evolve during lifecycle during development and commercial manufacture - as new knowledge is gained e.g. new patient needs are identified, new technical information is obtained about the product etc. 37

38 API Unit Operations Example from Case Study Coupling Reaction Aqueous Extractions Coupling of API Starting Materials Removes unreacted materials. Done cold to minimize risk of degradation Understand formation & removal of impurities Distillative Solvent Switch Semi Continuous Crystallization Centrifugal Filtration Rotary Drying Removes water, prepares API for crystallization step Addition of API in solution and anti-solvent to a seed slurry Filtration and washing of API Drying off crystallization solvents 38

39 Tablet Formulation Pharmacopoeial or other compendial specification 39

40 Drug Product Process API and Excipients Amokinol D-mannitol Calcium hydrogen phosphate hydrate Sodium starch glycolate Lubricant Magnesium Stearate Blending Lubrication Coating HPMC,Macrogol 6000 titanium oxide iron sesquioxide Compression Film coating 40

41 Overview of API and Drug Product Case Study Elements Representative Examples from the full Case Study 41

42 Overall Risk Assessment for Process Process Steps Example from Case Study no impact to CQA known or potential impact to CQA Drug Substance Drug Product current controls mitigate risk known or potential impact to CQA additional study required * includes bioperformace of API, and safety(api purity) CQA Coupling Reaction Aqueous Extractions Distillative Solvent Switch Semi- Continuous Crystallization Centrifugal Filtration Rotary Drying Manufacture Moisture Control Blending Lubrication Compression Coating Packaging in vivo performance* Dissolution Assay Degradation Content Uniformity Appearance Friability Stability-chemical Stability-physical 42

43 Overall Risk Assessment for Process Process Steps no impact to CQA known or potential impact to CQA Drug Substance Drug Product current controls mitigate risk known or potential impact to CQA additional study required * includes bioperformace of API, and safety(api purity) CQA Coupling Reaction Aqueous Extractions Distillative Solvent Switch Semi- Continuous Crystallization Centrifugal Filtration Rotary Drying Manufacture Moisture Control Blending Lubrication Compression Coating Packaging in vivo performance* Dissolution Assay Degradation Content Uniformity Appearance Friability Stability-chemical Stability-physical 43

44 API Semi-Continuous Crystallization Designed to minimize hydrolytic degradation (degradate below qualified levels) Univariate experimentation example FMEA of crystallization process parameters High risk for temperature, feed time, water level Test upper end of parameter ranges (represents worst case) with variation in water content only and monitor degradation Proven acceptable upper limits defined for above parameters Note that in this case study, the distillative solvent switch prior to crystallization and crystallization itself are conducted at lower temperatures and no degradation occurs in these steps 44

45 API Semi-Continuous Crystallization Designed to control particle size Multivariate DOE example leading to predictive model FMEA of parameters using prior knowledge High risk for addition time, % seed, temperature, agitation DOE: half fraction factorial using experimental ranges based on QTPP, operational flexibility & prior knowledge Design space based on predictive model obtained by statistical analysis of DOE data Particle size distribution (PSD) qualified in formulation DOE and dissolution studies 45

46 Risk Assessment: Particle Size Distribution (PSD) Control What is the Impact that will have on PSD? 1) minimal 5) moderate 9) significant What is the Probability that variations in will occur? 1) unlikely 5) moderately likely 9) highly likely What is our Ability to Detect a meaningful variation in at a meaningful control point? 1) certain 5) moderate 9) unlikely Unit Operation Parameter IMPACT P ROB. Detect Crystallization Feed Temperature Crystallization Water content of Feed Crystallization Addition Time (Feed Rate) Crystallization Seed wt percentage RPN 46 Comments Prior knowledge (slowness of crystallization kinetics) ensures that the hot crystallizer feed will be well dispersed and thermally equilibrated before crystallizing. Hence no impact of feed temp variation on crystal size. Prior knowledge (solubility data) shows in DOE that small variations in water do not affect crystalliation kinetics. Fast addition could result in uncontrolled crystallization. Detection of short addition time could occur too late to prevent this uncontrolled crystallization, and thus impact final PSD. To be investigated Prior knowledge (Chemical Engineering theory) highlights seed wt percentage variations as a potential source of final PSD variation Crystallization Antisolvent percentage Yield loss to crystallization already low (< 5%), so reasonable variations in antisolvent percentage (+/- 10%) will not affect the percent of batch crystallized, and will not affect PSD Crystallization Temperature Change in crystallization temperature is easily detected, but rated high since no possible corrective action (such as, if seed has been dissolved) Crystallization Agitation (tip speed) Prior knowledge indicates that final PSD highly sensitive to Agitation, 225 thus requiring further study. Crystallization Seed particle size distribution Seed PSD controlled by release assay performed after air attrition milling. Crystallization Feed Concentration Same logic as for antisolvent percentage

47 Options for Depicting a Design Space Seed wt% Pressure Oval = full design space represented by equation Rectangle represent ranges Simple, but a portion of the design space is not utilized Could use other rectangles within oval Exact choice of above options can be driven by business factors Temperature Large square represents the ranges tested in the DOE. Red area represents points of failure Green area represents points of success. For purposes of this case study, an acceptable design space based on ranges was chosen 47

48 API Crystallization: Design Space & Control Strategy Control Strategy should address: Parameter controls Distillative solvent switch achieves target water content Crystallization parameters are within the design space Testing API feed solution tested for water content Final API will be tested for hydrolysis degradate Using the predictive model, PSD does not need to be routinely tested since it is consistently controlled by the process parameters 48

49 Design Space / Control Strategy Parameter controls & Testing Example from Case Study Particle Size Crystallization Temperature 20 to 30ºC Control between 23 and 27ºC Particle Size Crystallization Feed Time 5 to 15 hours Control via flow rate settings Particle Size Crystallization Agitation 1.1 to 2.5 m/s Quality system should ensure changes in agitator size result in change to speed setting Particle Size Crystallization Seed Wt% 1 to 2 wt% Hydrolysis Degradate Distillation / Crystallization Controlled through weigh scales and overcheck Water Content < 1 vol% Control via in-process assay Particle size will be tested in this example, since the result is included in the mathematical model used for dissolution. 49

50 Drug Product Immediate release tablet containing 30 mg Amokinol Rationale for formulation composition and process selection provided In vitro-in vivo correlation (IVIVC) determination Correlation shown between pharmacokinetic data and dissolution results Robust dissolution measurement needed For a low solubility drug, close monitoring is important 50

51 Drug Product Direct Compression Manufacturing Process Example from Case Study Lubrication Focus of Story 51

52 Example from Case Study Initial Quality Risk Assessment Impact of Formulation and Process unit operations on Tablet CQAs assessed using prior knowledge Also consider the impact of excipient characteristics on the CQAs in vivo performance Dissolution Assay Degradation Content uniformity Appearance Friability Stability-chemical Stability-physical Drug substance particle size Moisture content in manufacture Blending Lubrication Compression Coating Packaging - Low risk - Medium risk - High risk 52

53 Drug Product CQA Dissolution Summary Quality risk assessment High impact risk for API particle size, filler, lubrication and compression Fillers selected based on experimental work to confirm compatibility with Amokinol and acceptable compression and product dissolution characteristics API particle size affects both bioavailability & dissolution Multivariate DOE to determine factors that affect dissolution and extent of their impact Predictive mathematical model generated Confirmed by comparison of results from model vs. actual dissolution testing Possible graphical representations of this design space 53

54 Predictive Model for Dissolution A mathematical representation of the design space Example from Case Study Prediction algorithm: Diss = API MgSt LubT Hard MgSt LubT Factors include: API PSD, lubricant (magnesium stearate) specific surface area, lubrication time, tablet hardness (via compression force) Confirmation of model Batch 1 Batch 2 Batch 3 Model prediction Dissolution testing result 92.8 ( ) 90.3 ( ) 91.5 ( ) Continue model verification with dissolution testing of production material, as needed 54

55 Dissolution: Control Strategy Controls of input material CQAs API particle size Control of crystallisation step Magnesium stearate specific surface area Specification for incoming material Controls of process parameter CPPs Lubrication step blending time within design space Compression force (set for tablet hardness) within design space Tablet press force-feedback control system Prediction mathematical model Use in place of dissolution testing of finished drug product Potentially allows process to be adjusted for variation (e.g. in API particle size) and still assure dissolution performance 55

56 Drug Product CQA - Assay & Content Uniformity Summary Quality risk assessment Potential impact for API particle size, moisture control, blending, and lubrication Moisture will be controlled in manufacturing environment Consider possible control strategy approaches Experimental plan to develop design space using input material and process factors In-process monitoring Assay assured by weight control of tablets made from uniform powder blend with acceptable API content by HPLC Blend homogeneity by on-line NIR to determine blending endpoint, includes feedback loop API assay in blend tested by HPLC Tablet weight by automatic weight control with feedback loop 56

57 Blending Process Control Options Example from Case Study Decision on conventional vs. RTR testing 57

58 Process Control Option 2 Blend uniformity monitored using a process analyser Example from Case Study On-line NIR spectrometer used to confirm scale up of blending Blending operation complete when mean spectral std. dev. reaches plateau region Plateau may be detected using statistical test or rules Feedback control to turn off blender Company verifies blend does not segregate downstream Assays tablets to confirm uniformity Conducts studies to try to segregate API mean spectral standard deviation Pilot Scale Full Scale Plateau region Revolution Number of (block Revolutions number) of Blender Data analysis model will be provided Plan for updating of model available Acknowledgement: adapted from ISPE PQLI Team 58

59 Batch Release Strategy Finished product not tested for assay, CU and dissolution Input materials meet specifications and are tested API particle size distribution Magnesium stearate specific surface area Assay calculation Verify (API assay of blend by HPLC) X (tablet weight) Tablet weight by automatic weight control (feedback loop), %RSD of 10 tablets Content Uniformity On-line NIR criteria met for end of blending (blend homogeneity) Tablet weight control results checked Dissolution Predictive model using input and process parameters calculates for each batch that dissolution meets acceptance criteria Input and process parameters used are within the filed design space Compression force is monitored for tablet hardness Water content NMT 3% in finished product (not covered in this case study) 59

60 Drug Product Specifications Use for stability, regulatory testing, site change, whenever RTR testing is not possible Input materials meet specifications and are tested API PSD Magnesium stearate specific surface area Assay calculation (drug product acceptance criteria % by HPLC) Verify (API assay of blend by HPLC) X (tablet weight) Tablet weight by automatic weight control (feedback loop) For 10 tablets per sampling point, <2% RSD for weights Content Uniformity (drug product acceptance criteria meets compendia) On-line NIR criteria met for end of blending (blend homogeneity) Tablet weight control results checked Dissolution (drug product acceptance criteria min 85% in 30 minutes) Predictive model using input and process parameters for each batch calculates whether dissolution meets acceptance criteria Input and process parameters are all within the filed design space Compression force is controlled for tablet hardness Water content (drug product acceptance criteria NMT 3 wt% by KF) 60

61 Iterative risk assessments Initial QRA Design High Risk Medium Risk Low Risk Control Beginning PHA FMEA Space FMEA strategy FMEA API Crystallization API PSD API PSD API PSD model Blending Blend homogeneity Blending time Blending time Feedback control Lubrication Lubricant Lubrication time Lubricant amount Lubrication time Mg stearate SSA Lubrication time Compression Hardness Content uniformity Pressure Tablet weight Pressure Automated Weight control 61

62 Conclusions Better process knowledge is the outcome of QbD development Provides the opportunity for flexible change management Use Quality Risk Management proactively Multiple approaches for experimental design are possible Multiple ways of presenting Design Space are acceptable Predictive models need to be confirmed and maintained Real Time Release Testing (RTRT) is an option Opportunity for efficiency and flexibility 62