Innovative Approaches to Pharmaceutical Development and Manufacturing Seminar Series

Transcription

1 CAMO European Pharmaceutical Seminars Jan/Feb 2009 Innovative Approaches to Pharmaceutical Development and Manufacturing Seminar Series The Increasing Need of Multivariate Analysis for Process Understanding and Control (Session 1). Brad Swarbrick, Product Manager CAMO Software AS

2 Seminar Outline: The Increasing Need of Multivariate Analysis for Process Understanding and Control 1. The Original Intention of PAT and QbD 2. Regulatory guidance allowing the implementation of PAT 3. PAT and QbD: The Design Space and Desired State of Materials 4. The Multivariate Nature of Processes 5. Principal Component Analysis, The Workhorse of MVA. 6. Variability Reduction: Smart Manufacturing and MAFSS 7. Fundamentals of Multivariate Statistical Process Control (MSPC) 8. Combining Data for and Overall Process Model: The HHL Approach 9. Systems Approach to Quality using Multivariate Analysis: Maintaining the Desired State

3 Session I : The Increasing Need of Multivariate Analysis for Process Understanding and Control Presentation outline 1. The Original Intention of PAT and QbD 2. Pragmatic Guidance I. CGMP s for the 21st Century II. The PAT Framework and Quality by Design (QbD) III. ICH and ASTM Guidance: Harmonised Approaches. 3. Design Space and the Desired State: The Multivariate Nature of Processes

4 Session I : The Increasing Need of Multivariate Analysis for Process Understanding and Control Presentation outline 1. The Original Intention of PAT and QbD 2. Pragmatic Guidance I. CGMP s for the 21st Century II. The PAT Framework and Quality by Design (QbD) III. ICH and ASTM Guidance: Harmonised Approaches. 3. Design Space and the Desired State: The Multivariate Nature of Processes

5 The Original Intent of PAT Most pharmaceutical companies write off 5-10% of annual productivity to waste and rework. A recent report indicated that around 75% of product recalls are due to manufacturing issues. Under a PAT framework, Quality cannot be tested into products, it should be built in, or by design The US FDA addressed the need for better process understanding in it s 2002 document CGMP s for the 21st Century

6 The Four Key Aspects of PAT Multivariate Data Analysis, representing a move away from current one variable at a time approaches. Process Analysers, monitoring the quality of products as they exist in the process. Process Automation and Control, allowing real time quality decisions. Knowledge Management, modern quality systems approaches.

7 The Present Situation The Pharmaceutical Community has arrived at a cross road, one path goes towards the Desired State and the other maintains the Current State. The path towards the desired state is unfamiliar to many, while the current state provides the comfort of predictability It is hoped that companies will move towards the desired state.

8 Session I : The Increasing Need of Multivariate Analysis for Process Understanding and Control Presentation outline 1. The Original Intention of PAT and QbD 2. Pragmatic Guidance I. CGMP s for the 21st Century II. The PAT Framework and Quality by Design (QbD) III. ICH and ASTM Guidance: Harmonised Approaches. 3. Design Space and the Desired State: The Multivariate Nature of Processes

9 CGMP s for the 21st Century First drafted in 2002, in an attempt to modernise pharmaceutical development and manufacture. Sub-titled, A Scientific, Risk- Based Approach Written to encourage pharmaceutical manufacturers to use current and state of the art tools to ensure Quality, through Process Understanding.

10 Industry Expectations It is anticipated, through this guidance, that Industry will, Adopt new and innovative technological advances. Adopt the latest quality management systems. Adopt Risk-Based approaches to quality management (ICH Q8) (ICH Q10) (ICH Q9) Conduct quality reviews, compliance and inspection based on state of the art pharmaceutical science (PAT and QbD)

11 Quality by Design Philosophy Risk Assessment (Q9) Modern Data Analysis Science Based Tools Modern Quality Systems Approach Product FMEA Raw Materials Process FMECA PHA HAZOP MSA DoE MVA CQA s CPP s Process and Product Understanding Iterative in Nature Variability Reduction Increased Public Health and Safety

12 The Desired State Product Quality and Performance achieved and Assured by Design of Effective and Efficient Manufacturing Processes ICH Q8 EWG

13 General Themes Understand your processes Reduce Variability Produce more Consistent products (Desired State) Reduce Regulatory Oversight through a Scientific Risk-Based Approach to Quality Question: How Do I Achieve This?

14 PAT Framework: Allowing Innovation PAT is Process Centric, Not Product Centric to Quality. PAT is not just expensive analysers. Data collected on a process can be analysed Multivariately. Process Understanding allows the implementation of continuous improvement, without regulatory review. PAT framework is supported by GAMP5, ICH and the ASTM E55 subcommittee on PAT.

15 Benefits of Impelementing PAT Reduction of Process Cycle Times by incorporating Real Time Process Monitoring and Control Strategies. Reduction/Prevention of Waste and Re-Work. Real Time Release Improve energy and material usage and increase production capacity, without factory expansion.

16 Quality by Design (QbD) Quality cannot be tested into products, it should be built in, or by design CGMP s for the 21 st Century

17 ICH Guidance: The Q8, Q9, Q10 Triangle Define Critical Product and Process Attributes and determine their risk to the business and the Patient Monitor Critical Product and Process Attributes using PAT and real time control strategies to ensure and document quality Continuous validation and improvement strategies based on knowledge gained and mitigation of any risks.

18 ICH Q8: Pharmaceutical Development ICH Q8 creates an opportunity for applicants to demonstrate an enhanced knowledge of product performance over a wide range of material and process attributes. This knowledge may be gained in a structured manner by the use of, Design of Experiments (DoE) Multivariate Data Analysis PAT Risk Management (FMEA, HAZOP, etc)

19 Design Space: As Defined by ICH Q8 The multidimensional combination and interaction of input variables and process parameters that have been demonstrated to provide assurance of quality Design Space Desired State Undesired State

20 ICH Q10: Pharmaceutical Quality System ICH Q10 provides a model for a pharmaceutical quality system throughout the entire life cycle of a product. In conjunction with local regulatory authorities, ICH Q10 intends to enhance, Process performance and product quality monitoring systems. Corrective Action and Preventative Maintenance (CAPA) Change Management System Management review of process and product quality.

21 The Q10 Approach to PAT DATA HISTORIAN SiPAT, SynTQ, ABB, Symbion, etc Spectroscopic Analysers Process Inputs and Outputs Environmental Outputs Process Interface Raw Materials Granulation and Drying Blending and Milling Compression and Coating

22 ASTM Guidance The American Society for Testing and Materials (ASTM) has formed the E55 subcommittee on PAT to address the practical aspects of PAT implementation. This subgroup has members from all over the world working on pragmatic guidance to the qualification and validation of PAT based systems. ASTM guidance incorporates all of the ideas of the FDA and ICH guidance documents.

23 ASTM Guidance Documents Standard practice for risk management as it impacts the design and development of processes for pharmaceutical manufacture Standard practice for process understanding related to pharmaceutical manufacture and control Standard guide for the application of continuous processing technology to the manufacture of pharmaceutical products Standard guide for application of process capability Standard practice for process sampling Practice for sampling considerations for pharmaceutical applications of Process Analytical Technology.

24 ASTM Guidance Documents Standard practice for pharmaceutical process design utilising Process Analytical Technology Standard practice for qualification of Process Analytical Technology systems Standard practices for Multivariate Analysis related to Process Analytical Technology Standard practice for identification of critical attributes of raw materials in the pharmaceutical industry Guide for validation of Process Analytical Technology Methods

25 A Brief Note on GAMP5 The International Society of Pharmaceutical Engineers (ISPE) has recently published the GAMP5 guidance entitled, A Risk- Based Approach to Compliant GxP Computerised Systems. This guidance was written to address industries shift towards PAT based systems and provides pragmatic guidance to the qualification of such systems. GAMP5 is also compatible with the recently published ASTM E2500 guidance entitled, Standard Guide for Specification, Design and Verification of Pharmaceutical and Biopharmaceutical Manufacturing Systems and Equipment.

26 Session I : The Increasing Need of Multivariate Analysis for Process Understanding and Control Presentation outline 1. The Original Intention of PAT and QbD 2. Pragmatic Guidance I. CGMP s for the 21st Century II. The PAT Framework and Quality by Design (QbD) III. ICH and ASTM Guidance: Harmonised Approaches. 3. Design Space and the Desired State: The Multivariate Nature of Processes

27 The Practical Nature of PAT The guidance is in place, the ideas are out there, but How do we implement PAT? Need to focus on those products and unit operations that are going to provide the most business and safety benefits first. Remember, all processes are perfectly designed to achieve the results it actually gets! The process always works perfectly. Do you understand your systems?

28 The Multivariate Nature of Processes If processes relied on one input variable, then manufacturing would be simple! However, real processes rely on factors such as, Raw Material Quality Process Design and Equipment Operator Skill and Perception. Multivariate Data Analysis (MVA) tools form one of the four key aspects of PAT. MVA can be applied to any measured data.

29 Multivariate Tools for Defining the Design Space 15 PC2 Scores 10 5 DexM DexM Lac Suc Suc MCC Starch MgSt MgSt SLS SLS SLS 0 DexA DexA StAcid StAcid StAcid CA Ibu Ibu -15 Para Theoph PCA Space All M, X-expl: 63%,18% Understanding Raw Material Characteristics using Principal Component Analysis (PCA) and SIMCA PC1

30 Understanding Material Variability Direction of Maximum Variation

31 What Variables Affect Product Quality? 1.0 PC2 Correlation Loadings (X) Yield Bottles Dispens 0.5 Batch 17 Conc Adjustment 0 Initial Conc Batch 4 Batch 8 Batch 25 Batch Batch 3 11 Batch 7 Batch 6 Batch Batch Batch 14 27Batch Batch 309 Batch Batch Batch Batch Batch Batch 10 Batch 21 Batch 2 Batch 2822 Batch 31 Batch 5 Batch 19 Recovery PC RESULT5, X-expl: 40%,33%

32 Is The Product Mixed?

33 Is My Product Dry?

34 The Holistic PAT Approach Unit Operation Local Design Space Holistic PAT Approach Complete Design Space

35 Session I Conclusions Regulatory Guidance Exists for the Pragmatic Implementation of PAT Multivariate Data Analysis is a key area of successful PAT implementation The data analysis tools are available and MUST become part of the pharmaceutical scientists skill set. Many applications and improvement areas exist in processes for the immediate use of PAT.

36 The Next Steps Training of technical, quality and regulatory staff in the areas of Multivariate Data Analysis and Design of Experiments. Identify key processes and use the multivariate tools to analyse historical data. Identify Critical Process and Quality Parameters that need to be closely monitored. Match the Process Analytical Technology to the problem.