Quality by Design Facilitating Real Time Release (RTR) Practical Challenges and Opportunities during RTR Implementation

Transcription

1 Quality by Design Facilitating Real Time Release (RTR) Practical Challenges and Opportunities during RTR Implementation Carl E. Longfellow Ph.D., Senior Director, New Product and Process Development,

2 Discussion Topics Introduction History leading to QbD initiative What is RTR? RTR Essential Elements People Science - Statistical Tools - Control Strategy Quality Systems and Processes Challenges and Opportunities Benefits 2

3 History What lead to QbD initiative Not new to other industries Lack of continuous improvement is an outcome of regulatory oversight - No business driver to improve processes - High cost to file regulatory changes globally - Relatively short timelines and limited experience to develop robust processes Short comings recognized by regulatory authorities ICH guidelines established Q8-Pharmaceutical Development Q9-Quality Risk Management Q10-Pharmaceutical Quality Systems FDA CMC Program

4 Major Takeaways RTR is not the goal of Quality by Design (QbD). It is a possible outcome of QbD development RTR is possible when there is a high level of product and process understanding, a robust control strategy (including PAT), and science and risk-based quality systems aligned with Q10 QbD and RTR raise the bar on quality. Returning to routine sampling and testing for product release may not be possible.

5 Real Time Release (RTR) Regulatory Definition 2001 EMEA NOTE for GUIDANCE ON PARAMETRIC RELEASE (CPMP/QWP/3015/99) System of Release that gives assurance that the product is of intended quality based on the information collected during the manufacturing process and on the compliance with specific GMP requirements related to parametric release - It is therefore based on the successful validation of the manufacturing process and review of the documentation on process monitoring carried out during manufacturing to provide the desired assurance of the quality of the product FDA PAT GUIDANCE, September RTR is the ability to evaluate and ensure the acceptable quality of in-process and/or final product based on process data 5

6 Real Time Release Essential Elements Science People Systems REAL TIME RELEASE ICH Q8 Pharmaceutical Development ICH Q9 Quality Risk Management ICH Q10 Quality Systems

7 Real Time Release Elements - People Multidisciplinary and cross-functional teams are a key to making QbD a success Operations Regulatory Affairs Technology Quality Operations Formulation Development Analytical Development Chemometrics Statistics

8 Real Time Release Elements - Science Real Time Release Quality Systems Control Strategy and Processes Product and and Process Knowledge Technology Analytical Technology Compliance Statistical Tools Excellence Science Quality Risk Management Knowledge Management 8

9 Statistical Tools Sampling plan justification Estimation of acceptable coverage to demonstrate product quality- raise the bar over USP Operational Characteristics (OC) Curve Simulations

10 Statistical Tools- Development of Sampling Plans How often do we sample and where do we sample? - Statistical rationale for sampling (in combination with risk assessments/prior knowledge) - Sampling of tablets during the compression unit operation for a low dose tablet (as it may be more prone to segregation) may be different than that for a high dose tablet - Rationale for placement of PAT device in manufacturing equipment - Why is the NIR for blender placed in the bottom of the blender versus the top (or side) and is the sample representative of the batch? 10

11 Statistical Tools - Operating Characteristics Curves Operating Characteristic (OC) Curves are often used to illustrate the performance of a lot acceptance test. These curves provide a way to compare the performance of different tests. Probability of Lot Acceptance High probability means lots will typically be found acceptable by the test being evaluated Steepness of the curve indicates the discrimination of the test A calculation relevant to the Acceptance Criterion Thomas Pyzdek, Quality Engineering Handbook, Second Edition, Marcel Dekker Inc.

12 Statistical Tools - Operating Characteristics Curve for UDU Test Coverage is the proportion of dosage units within % LC and is considered a relevant measure of the uniformity of the batch. At 98% coverage, USP would pass the batch 90% of the time, but there is zero chance of the second plan passing the batch Operating Characteristic Curve (Median of Results) 100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Pr. of Passing Coverage USP Wyeth Development of a content uniformity test suitable for large sample sizes Sandell et. al., Drug Information Journal, Vol. 40, pp , 2006.

13 Statistical Tools Simulations Monte Carlo Simulations Monte Carlo Simulations* - A technique that converts uncertainties in input variables of a model into probability distributions. By combining the distributions and randomly selecting values from them, it recalculates the simulated model many times and brings out the probability of the output. - MCS allows several inputs to be used at the same time to create the probability distribution of one or more outputs. - Different types of probability distributions can be assigned to the inputs of the model. When the distribution is unknown, the one that represents the best fit could be chosen. - The use of random numbers characterizes MCS as a stochastic method. The random numbers have to be independent; no correlation should exist between them. - MCS is a sampling method that generates the output as a range instead of a fixed value and shows how likely the output value is to occur in the range. *Sanford Bolton, Charles Bon Pharmaceutical Statistics- Practical and Clinical Applications, Fourth Edition, Marcel Dekker,

14 Monte Carlo Simulations Contour Plots for Potential Scenarios WTmean NIRmean Indicates potential scenarios where a batch would have a high probability of passing plan Note: Plus signs represents cases with probability between 6-8%, empty squares for probability between 8-10%, and solid squares for probability above 10%. Simulations Help provides an assessment of risk for chosen coverage

15 Real Time Release Elements - Science Real Time Release Quality Systems Control Strategy and Processes Product and and Process Knowledge Technology Analytical Technology Compliance Statistical Tools Excellence Science Quality Risk Management Knowledge Management 15

16 Control Strategy Control Strategy: A planned set of controls, derived from current product and process understanding, that assures process performance and product quality. The controls can include parameters and attributes related to drug substance and drug product materials and components, facility and equipment operating conditions, in-process controls, finished product specifications, and the associated methods and frequency of monitoring and control. (ICH Q10) Ensures input quality attributes and process parameters are maintained within the approved design space(s)---thus product should meet specifications without finished product testing. PAT is one of the key tools that enable RTR Its application should be based on a risk evaluation

17 What is RTR? Control Strategy example for a high dose, roller compaction process. Robust control strategy = Increased assurance of quality = RTR Particle Size Analyzer Control of RC output within pre-established range helps control hardness NIR for tablets online testing, At Line automatic tablet weight checking Uniformity/weight control NIR Uniformity of Blend NIR Uniformity of Blend Fette Control Loops Weight / uniformity control

18 Blending Content for API and FE %API and %FE Rotations

19 RSD %RSD Rotations

20 Particle Size Output

21 Compression FT-NIR Interim Report NIR Report for This Pull Date(mm/dd/yy): 01/11/07 Time: 9:51:40 Operator: Administrator Batch Number: XXXXX Sample: XXX mg tablets - Pull No: x Index FileName Id %API %FE %Target 1 B xxx mg B xxx mg B xxx mg B xxx mg B xxx mg B xxx mg B xxx mg B xxx mg B xxx mg B xxx mg Summary for API Conc (%): Average: 99.2% Minimum: 97.3% Maximam: 101.2% Std. Dev: 1.0 Note: Summary based on the actual (not rounded) individual results.

22 Summary by Individual Tablets Distributions Mean: 100.5% Rel.DVS% Distributions PPK: Rel.DVS% Capability Analysis LSL Target USL Quantiles maximum 100.0% 99.5% 97.5% 90.0% 75.0% 50.0% 25.0% 10.0% 2.5% 0.5% 0.0% quartile median quartile minimum Moments Mean Std Dev Std Err Mean upper 95% Mean lower 95% Mean N Specification Lower Spec Limit Upper Spec Limit Spec Target Value Portion Below LSL Above USL Total Outside % Actual Overall, Sigma = LSL -3s Mean +3s Target USL Capability CP CPK CPM CPL CPU Portion Below LSL Above USL Total Outside Index Percent Lower CI Upper CI PPM Sigma Quality Benchmark Z Z Bench Z LSL Z USL Index

23 Summary by Individual Tablets (Run chart) Y Overlay Plot Active FE Y Rel.DVS% Rel.HPMC% Rows

24 Real Time Release Elements Quality Systems and Processes ICH Q10 Alignment Science and Risk based Approach to Quality Disaster recovery plans Chemometric Model Maintenance Handling of outliers Batch release process in the RTR environment Quality risk management (enabler) Tracking and trending of data 24

25 Quality Systems and Processes - Development of Disaster Recovery Systems Things to consider What do we do if a PAT measurement system stops functioning? What do we do when all the PAT measurement systems stop functioning? What do we do if the chemometric model is no longer appropriate? - What are the alternative procedures and sampling plans for sample/batch analysis and release? 25

26 Decision Tree for Failure Modes PAT Failure During the Manufacturing Process Predefining reaction ensures proactive quality as compared to thinking of reaction after event - reactive quality 26

27 Quality Systems and Processes Chemometric Models- Establishment and Maintenance How do you transfer small scale models to large scale equipment? - Need to assess variability due to equipment, personnel, environment, measurement systems, materials etc. and refine models as necessary What are the procedures for chemometric model maintenance? How often would a periodic check on the model performance be performed? What are the criteria for the revision of models in the RTR environment and how does this differ from the R&D/monitoring environment? 27

28 Quality Systems and Processes- Handling of Outliers Development of mechanisms/predefined systems to handle outliers in the measurement systems (proactive quality) - Should use a holistic assessment of the process measurements (inprocess + final product) to assess product/process performance and impact to quality - Reaction to outlier s must be risk based - # of occurrences dictate reaction to outliers(setting of zero tolerance criteria critical) - The reaction to an outlier after significant process/product history should be different than an outlier observed when the amount of historical information is minimal - Consider potential impact of an outlier to patient safety and efficacy

29 Quality Systems and Processes- Batch Disposition and RTR Points to consider for batch disposition in a RTR environment Use of electronic batch records and identification of exceptions (flagging) that foster easier batch release Development of SPCs and a process/product monitoring system provide a real time assessment of process/product performance 29

30 Quality Systems and Processes- Batch Disposition Points to Consider, Continued What is the relationship between the PAT attribute measured and the acceptance criteria for the drug product? Dissolution of an extended release product if attribute measured as a surrogate for dissolution is polymer concentration, need to establish correlation between polymer concentration and dissolution (models) Need to define strategy for defining dissolution (or other quality attribute) in a Certificate of Analysis (CoA). Options include: - Generate a dissolution result based on model developed to demonstrate correlation to polymer and use in CoA. Indicate that the dissolution is a calculated value and not a measured value - Defining polymer concentration in CoA and indicate that this is a surrogate for dissolution 30

31 Quality Systems and Processes- Quality Risk Management What it is NO RISK NO REWARD KNOW RISK KNOW REWARD 31

32 Quality Systems and Processes- Quality Risk Management Points to Consider Procedures for the implementation of QRM uniformly across the entire organization Use of the same language (terminology), process Establish criteria for re-evaluation of risks and mitigation plans time, event or knowledge based Training program Various levels awareness, participant, facilitator, team leader) to ensure effective utility of the tool Choice of the right QRA/QRM approach (Risk filter, FMEA, HACCP) Utilize tool in a proactive manner, not in a reactive fashion

33 Quality Systems and Processes- Tracking and Trending Procedures (and processes) for tracking and trending of data Identify what needs to be tracked and trended (and Why?) - Process inputs (including raw material characteristics, parameters), process outputs, process capability measurements (cycle times, yields, process capabilities) Identify tools/process for tracking and trending - Establishing procedures/systems within quality systems Establish rules for tracking and trending - When are we going to react and how? Establish responsibilities for process Training Continuous improvement

34 Challenges and Opportunities Associated with RTR Regulatory challenges (global harmonization) Risk Management better understanding is necessary Resources Initial capital commitment is needed for PAT Personnel with diverse background necessary for successful PAT implementation Culture/mindset challenges (proactive versus reactive quality) Impact to QP/Q release person (understand control strategy, RM approach, quality systems, etc for RTR environment) Quality Systems Development Will need quality systems to be based on risk management principles (e.g. Need systems in place for PAT equipment failure) Robust change control systems needed 34

35 Benefits from RTR, QbD, PAT RTR/QbD can lead to lower manufacturing costs (faster cycle times, fewer rejects, reduced QC resources, and greater yields) Demonstration of Process/Product Knowledge can lead to RTR and other examples of regulatory flexibility (e.g. fewer post-approval supplements) Use of PAT/QbD can facilitate Technology Development and Transfer (TD&T) process Understanding of process/product makes TD&T easier Continuous Quality Verification (ASTM Standard Guide E )--not today s 3 batch validation Even higher level of product quality for our patients 35

36 Acknowledgements Steve Simmons Chunsheng Cai Carlos Conde-Reyes Plinio Delos-Santos Parimal Desai Joseph Devito Lori Henning Nirdosh Jagota Shailesh Singh Merlin Utter T.G. Venkateshwaran Dominic Ventura 36