Q8, Q9, Q10 - Product Development Case Study Overview.ppt
- 1. International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use Implementation of ICH Q8, Q9, Q10 Product Development: Case Study Overview
- 2. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 3 Product Development: Case Study Overview © ICH, November 2010 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
- 3. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 4 Product Development: Case Study Overview © ICH, November 2010 Key Steps for a product under Quality by Design (QbD) Product/Process Development Pharmaceutical Development PQS & GMP Local Environment Commercial Manufacturing Quality Unit (QP,..) level support by PQS Manage product lifecycle, including continual improvement Design Space (DS), RTR testing Link raw material attributes and process parameters to CQAs and perform Risk Assessment Methodology Potential CQA (Critical Quality Attribute) identified & CPP (Critical Process Parameters) determined QTPP : Definition of intended use & product Quality Target Product Profile CPP : Critical Process Parameter CQA : Critical Quality Attribute Risk Management Opportunities Design to meet CQA using Risk Management & experimental studies (e.g. DOE) DOE : Design of Experiment Control Strategy Technology Transfer Batch Release Strategy Prior Knowledge (science, GMP, regulations, ..) Continual improvement Product/Process Understanding QRM principle apply at any stage Marketing Authorisation Quality System PQS
- 4. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 5 Product Development: Case Study Overview © ICH, November 2010 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.
- 5. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 6 Product Development: Case Study Overview © ICH, November 2010 Case Study Organization
- 6. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 7 Product Development: Case Study Overview © ICH, November 2010 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 http://www.nihs.go.jp/drug/DrugDiv-E.html • Alignment between API and drug product -API Particle size and drug product dissolution -Hydrolytic degradation and dry granulation /direct compression
- 7. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 8 Product Development: Case Study Overview © ICH, November 2010 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
- 8. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 9 Product Development: Case Study Overview © ICH, November 2010 Quality attribute focus Technical Examples • API • Drug Product Compression Real Time Release testing (Assay, CU, Dissolution) Blending API Crystallization - Final crystallization step - Blending - Direct compression - Particle size control - Assay and content uniformity - Dissolution Process focus
- 9. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 10 Product Development: Case Study Overview © ICH, November 2010 Process Step Analysis • For each example - Risk assessment - Design of experiments -Experimental planning, execution & data analysis - Design space definition - Control strategy - Batch release Design of Experiments Design Space Control Strategy Batch Release QRM
- 10. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 11 Product Development: Case Study Overview © ICH, November 2010 QbD Story per Unit Operation Process Variables Design of Experiments Quality Risk Management Illustrative Examples of Unit Operations: QTPP & CQAs Design Space Control Strategy Batch Release Compression Real Time Release testing (Assay, CU, Dissolution) Blending API Crystallization
- 11. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 12 Product Development: Case Study Overview © ICH, November 2010 Introducing API and Drug Product
- 12. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 13 Product Development: Case Study Overview © ICH, November 2010 Assumptions • 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 - Degrades by hydrolytic mechanism • In vitro-in vivo correlation (IVIVC) established – allows dissolution to be used as surrogate for clinical performance • Drug product is oral immediate release tablet
- 13. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 14 Product Development: Case Study Overview © ICH, November 2010 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
- 14. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 15 Product Development: Case Study Overview © ICH, November 2010 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 – Particle Size Distribution (PSD) 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.
- 15. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 16 Product Development: Case Study Overview © ICH, November 2010 API Unit Operations Coupling Reaction Aqueous Extractions Distillative Solvent Switch Semi Continuous Crystallization Centrifugal Filtration Rotary Drying Coupling of API Starting Materials 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 Removes unreacted materials. Done cold to minimize risk of degradation Understand formation & removal of impurities Example from Case Study
- 16. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 17 Product Development: Case Study Overview © ICH, November 2010 Tablet Formulation Pharmacopoeial or other compendial specification
- 17. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 18 Product Development: Case Study Overview © ICH, November 2010 Drug Product Process Blending Lubrication Compression Film coating API and Excipients Amokinol D-mannitol Calcium hydrogen phosphate hydrate Sodium starch glycolate Lubricant Magnesium Stearate Coating HPMC，Macrogol 6000 titanium oxide iron sesquioxide
- 18. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 19 Product Development: Case Study Overview © ICH, November 2010 Overview of API and Drug Product Case Study Elements Representative Examples from the full Case Study
- 19. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 20 Product Development: Case Study Overview © ICH, November 2010 Overall Risk Assessment for Process 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 Drug Substance Drug Product • no impact to CQA * includes bioperformace of API, and safety(API purity) • additional study required • known or potential impact to CQA • known or potential impact to CQA • current controls mitigate risk • no impact to CQA Process Steps CQA Example from Case Study
- 20. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 21 Product Development: Case Study Overview © ICH, November 2010 Overall Risk Assessment for Process 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 Drug Substance Drug Product • no impact to CQA * includes bioperformace of API, and safety(API purity) • additional study required • known or potential impact to CQA • known or potential impact to CQA • current controls mitigate risk • no impact to CQA Process Steps CQA
- 21. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 22 Product Development: Case Study Overview © ICH, November 2010 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
- 22. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 23 Product Development: Case Study Overview © ICH, November 2010 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
- 23. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 24 Product Development: Case Study Overview © ICH, November 2010 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 I M P A C T P R O B . D e t e c t RPN Comments Crystallization Feed Temperature 1 5 1 5 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. Crystallization Water content of Feed 1 5 5 25 Prior knowledge (solubility data) shows that small variations in water do not affect crystalliation kinetics. Crystallization Addition Time (Feed Rate) 9 5 9 405 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. Crystallization Seed wt percentage 9 5 5 225 Prior knowledge (Chemical Engineering theory) highlights seed wt percentage variations as a potential source of final PSD variation Crystallization Antisolvent percentage 1 1 1 1 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 9 5 9 405 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) 9 5 5 225 Prior knowledge indicates that final PSD highly sensitive to Agitation, thus requiring further study. Crystallization Seed particle size distribution 9 1 1 9 Seed PSD controlled by release assay performed after air attrition milling. Crystallization Feed Concentration 1 1 1 1 Same logic as for antisolvent percentage To be investigated in DOE
- 24. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 25 Product Development: Case Study Overview © ICH, November 2010 Options for Depicting a Design Space Large square represents the ranges tested in the DOE. Red area represents points of failure Green area represents points of success. • 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 Pressure • For purposes of this case study, an acceptable design space based on ranges was chosen Seed wt%
- 25. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 26 Product Development: Case Study Overview © ICH, November 2010 Options for Expanding a Design Space • Why expand a Design Space? -Business drivers can change, resulting in a different optimum operating space • When is DS Expansion possible? -Case A: When the original design space was artificially constrained for simplicity -Case B: When some edges of the design space are the same as edges of the knowledge space Temperature Seed wt% Temperature Seed Wt%
- 26. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 27 Product Development: Case Study Overview © ICH, November 2010 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
- 27. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 28 Product Development: Case Study Overview © ICH, November 2010 Design Space / Control Strategy Parameter controls & Testing 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% Controlled through weigh scales and overcheck Hydrolysis Degradate Distillation / Crystallization 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. Example from Case Study
- 28. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 29 Product Development: Case Study Overview © ICH, November 2010 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
- 29. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 30 Product Development: Case Study Overview © ICH, November 2010 Drug Product Direct Compression Manufacturing Process Focus of Story Example from Case Study Lubrication
- 30. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 31 Product Development: Case Study Overview © ICH, November 2010 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 Drug substance particle size Moisture content in manufacture Blending Lubrication Compression Coating Packaging - Low risk - Medium risk - High risk Degradation Content uniformity Appearance Friability Stability-chemical Stability-physical in vivo performance Dissolution Assay Example from Case Study
- 31. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 32 Product Development: Case Study Overview © ICH, November 2010 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
- 32. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 33 Product Development: Case Study Overview © ICH, November 2010 Predictive Model for Dissolution A mathematical representation of the design space Batch 1 Batch 2 Batch 3 Model prediction 89.8 87.3 88.5 Dissolution testing result 92.8 (88.4–94.2) 90.3 (89.0-102.5) 91.5 (90.5-93.5) Prediction algorithm: Diss = 108.9 – 11.96 × API – 7.556×10-5 × MgSt – 0.1849 × LubT – 3.783×10-2 × Hard – 2.557×10-5 × MgSt × LubT Factors include: API PSD, lubricant (magnesium stearate) specific surface area, lubrication time, tablet hardness (via compression force) Confirmation of model Example from Case Study Continue model verification with dissolution testing of production material, as needed
- 33. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 34 Product Development: Case Study Overview © ICH, November 2010 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
- 34. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 35 Product Development: Case Study Overview © ICH, November 2010 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
- 35. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 36 Product Development: Case Study Overview © ICH, November 2010 Blending Process Control Options • Decision on conventional vs. RTR testing Example from Case Study
- 36. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 37 Product Development: Case Study Overview © ICH, November 2010 Process Control Option 2 Blend uniformity monitored using a process analyser • 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 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0 32 64 96 128 Revolution (block number) mean spectral standard deviation Pilot Scale Full Scale Plateau region Number of Revolutions of Blender Data analysis model will be provided Plan for updating of model available Acknowledgement: adapted from ISPE PQLI Team Example from Case Study
- 37. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 38 Product Development: Case Study Overview © ICH, November 2010 Conventional automated control of Tablet Weight using feedback loop: Sample weights fed into weight control equipment which sends signal to filling mechanism on tablet machine to adjust fill volume and therefore tablet weight. Tablet Weight Control in Compression Operation
- 38. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 39 Product Development: Case Study Overview © ICH, November 2010 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)
- 39. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 40 Product Development: Case Study Overview © ICH, November 2010 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 95-105% 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)
- 40. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 41 Product Development: Case Study Overview © ICH, November 2010 Iterative risk assessments Initial QRA PHA FMEA FMEA FMEA API Crystallization Blending Lubrication Compression API PSD Lubricant Lubrication time Hardness Content uniformity Beginning Design Space Control strategy Blending time Lubricant amount Lubrication time Pressure Tablet weight API PSD model Blending time Feedback control Mg stearate SSA Lubrication time Pressure Automated Weight control Blend homogeneity High Risk Medium Risk Low Risk API PSD
- 41. ICH Quality Implementation Working Group - Integrated Implementation Training Workshop slide 42 Product Development: Case Study Overview © ICH, November 2010 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