Quality by design in analytical method developmentpptx

Quality by design in analytical method development

1. M. Pharm Sem -I Presentations Title Quality by design in analytical method development SUBMITTED TO SAVITRIBAI PHULE, PUNE UNIVERSITY , PUNE FOR PARTIAL FULFILMENT OF REQUIREMENTS FOR THE AWARD OF MASTER OF PHARMACY IN THE SUBJECT Pharmaceutical Quality Assurance IN THE FACULTY OF SCIENCE AND TECHNOLOGY Bhujbal Knowledge City, MET’s Institute of Pharmacy, Adgaon, Nashik, 422003. Maharashtra, India Academic Year-2021-2022 1 Presented By-Rhutuja Jogdand, Priyanka Sananse Guided By-Dr.S.P.Ahirrao

2. Introduction QbD, as defined by the ICH (R1), is a systemic approach to pharmaceutical development that begins with stated objectives that emphasise product and process understanding as well as control. QbD does not necessarily imply less analytical testing; rather, it means the right analysis at the right time, and is based on science and risk assessment." QbD implementation aids in the development of rugged and robust methods that help pharmaceutical companies comply with ICH guidelines, which is why pharmaceutical companies are adopting the concept.

3. Why QbD For analytical method 1 To improve method comprehension and sturdiness.
2 To make continual improvement easier
3 The control evaluation performed during the process control is closely related to all analytical methods utilised to monitor and manage our manufacturing process.

4. Traditional analytical method development QbD (lifecycle) Analytical method development Method validation as a check box tool as defined in ICH Q2, validation of analytical procedures:Text and Methodology Suitability of method demonstrated against an analytical target profile,which defines method design and qualifications stages. Impact of variation in method parameters on performance of method is less understood A science based structured approach for identifying and exploring method variables and their impact The term e.g , method verification , method transfer validation and revalidation are confusing in traditional approach In life-cycle approach more clear terms aligned with process validation and equipment qualification terminology are used. Method validation used to describe one – time event performed on completion of method development Method lifecycle validation used to describe all activities that ensure s method procedure fit for purpose data during the whole lifecycle.

5. Analytics target profile Its method for product and process design and development starts with determining the method aim or method intent, as well as the tool for method creation.
It describes the method requirements that should be measured.
For example, seperation identification is a significant quality aspect in the chromatographic process (CQA)

6. Method design 1.To ensure that materials are available and that varied experiment conditions are met.
2.Instrument reliability is evaluated, and an experimental design is created.
3.For proper implementation, a flow chart and decision tree can be created.
4. Throughout the life cycle, method design can be repeated or updated as needed.
A uniform strategy was used to design the method.

7. Critical quality attribute: variables that directly affect product quality and safety are identified first, and their potential impact on method development is investigated. Risk assessment: It is a link between a variable in the input process and a critical quality feature.The risk-based strategy is based on the ICH Q8 and Q9 guidelines. 1 Ishikawa or Fishbone diagram is one of several risk assessment tools. 2.Analysis of the failure mode influence (FMEA) 3. The Pareto principle

8. Critical quality attribute: factors directly affect the quality and safety of product are first orted out and it’s possible effect on method development is studied Risk assessment: It is link between input process variable and Critical quality attribute. Risk based approach is based on ICH guideline Q8 &Q9. various tools for risk assessment are 1 Ishikawa or Fishbone diagram. 2.Failure mode effect analysis (FMEA) 3. Pareto analysis

9. To identify all potential variables such as raw material, instrumental component, and environmental factor, use the Ishikawa or Fishbone diagram. Failure mode effect analysis (FMEA) is a technique for ranking variables according to their risk and selecting the process parameter with the highest risk for further research into its impact on a critical quality attribute.

10. Ishikawa or Fishbone diagram- to identify all potential variable as raw material , instrumental factor and environmental factor. Failure mode effect analysis (FMEA): it is used to rank the variable based on risk and to select the process parameter with higher risk for further studies to under their effect on critical quality attribute.

11. Method qualification Object is to gain ensuring about method performance as per method intent .It is divided into 1. Method installation qualification 2. Method operatonal qualification 3. Method performance qualification

12. Control strategy It is critical to ensure that the technique performs as intended and consistently produces correct results for the purposes of method control.
Risk analysis can also aid in the selection of a specific control method. Life cycle approach It includes continual method performance improvement, and the design space allows for flexibility in analytical method enhancement.Knowledge gained from risk assessment and data gathered from experiment design aid in making justifiable modifications as needed.

13. Different approach suggested for QbD in analytical method development are as follow, 1. MDS approach 2. AQbD work flow

14. MDS approach Components of MDS process is the use of structured risk assessment tools ,as design of experiments and measurement system analysis (MSA) methodologies ,for the evaluation of robustness and ruggedness.

15. Components of MDS approach

16. Application a . HPLC for assay and impurity profile b. Genetically harmful impurity analysis. c. Karl Fischer titration for water content. d. Quantitative colour measurement
e. vibrational spectroscopy for chemical identification
f. Method of dissolution

17. 19 QUALITY BY DESIGN IN ANALYTICAL METHOD DEVELOPEMENT

18. CONTENT Introduction Analytical Quality by Design (AQbd) Implementation of AQbd Case study Conclusion References 20

19. INTRODUCTION:- Quality-by-design (Qbd) has become an important standard in the pharmaceutical industry since it was introduced by the US food and drug Administration. For any entity, quality is one of the basic criteria in addition to safety and efficacy to be accepted and approved as a drug. The quality is the suitability of either a drug substance or a drug product for its intended use. Analytical method are required to be developed and validated during a pharmaceutical manufacturing.as it plays a very pivotal role in product development. A robust, accurate, precise analytical method not only satisfy whether the quality of drug is achieved as per the intended therapeutic use but also serves as a purity check at each stage of product development life cycle. The carelessness in this may lead to a very costly and time consuming procedure. During a method development ruggedness and robustness should be established early to make certain method performance over the lifetime. 21

20. In present days, analytical method failure is becoming more common especially during method transfer. The formation of design space by Qbd approach determines a suitable method control that delivers its intended space and also it eliminates batch failure, increases efficiency and cost effective. According to ICH Q8 guidelines QBD can be defined as “A systemic approach to development that design with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management.” 22

21. APPLICATION OF AQbD:- Analytical Research Development Advanced level of method understanding for each critical factor with Method Operable Design Region will provide flexibility for method transfer from AR & D to QC, Reduction and CPPs adjustable within design space along with other QbD tools. Quality Assurance Investigation of variability or batch failure will become easier,efficient and speedy for root cause analysis through Quality Risk Management during Development, Eliminate batch failures, minimise deviations and costly invstigations. Regulatory Affairs Review and Approval process will become very easy and speedy. Moreover developed and verified design space will provide regulatory flexibility for post approval change management. 23

22. What is Analytical Quality by Design? The introduction of AQbD has made the industry to look beyond quality by testing (QbT) for ensuring product quality and performance . The knowledge acquired during development may support the formulation of a design space and determines suitable process controls. Analogous to process QbD, the result of AQbD is a well understood , fit for purpose, and robust method that consistently delivers the intended performance throughout its lifecycle. AQbD helps the scientific understanding of pharmaceutical process and method and the critical quality attributes are identified and their effect on final quality of product is analyzed. 24

23. DIFFERENCE BETWEEN REGULATORY PERSPECTIVE OF QbD and AQbD 25 Product Quality by Design (QbD) Analytical Quality by Design (AQbD) Quality Target Profile (QTPP)Definition. Analytical Target Profile (ATP) definition. Critical Quality Attributes(CQA) Critical Performance Attributes(CPA) Risk Assessment Critical Material Attributes and critical processing parameters Risk Assessment of critical Method Attributes and critical Method parameters Designing of Experiments and development of Design Space (DS) Designing of Experiments and Development of Method operable Design Region (MODR) Manufacturing Process Validation Analytical Method Validation Implementation of control strategy Implementation of control strategy Continual Process Improvement Continual Method Improvemet.

24. 26 Elements of AQbD

25. ANALYTICAL TARGET PROFILE (ATP): ATP is the initial step taking into account systematic variability, inherent variability,& system suitability for method development and has been mentioned in the ICH Q8 guidelines. Inspite of analytical specification, during the method development, the method is likely to experience a number of changes brought through unintentional deviations, continuous improvement activities or the need to operate the method and /or process in a different environment. ATP is the recognition and the selection of method target analytes (product and impurities),which are likely to affect the method performance at any stage of the method development . The target could be API and impurities, type of analytical technique, analyst, lab environment equipment method operation . The ATP defines what the method has to measure (i.e. acceptance criteria ) and to what level the measurement is required (i.e. performance level characteristics, such as precision, accuracy,range, sensitivity, and the associated performance criterion). The commom ATPs of an instruments like LC-MS/MS could be noise, heat block temperature, buffer pH ,flow rate , column temperature etc . 27

26. CPA (Critical Performance Attributes) ICH Q8 defines CQA or CPA as a physical, chemical, biological, or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality. In this step, the analyst has to identify the critical method parameter that directly affects the method performance . The CPAs will differ from project to project. Critical method parameters (CMPs) are divided into three type viz. parameter regarding analyte, parameter regarding instruments and parameter regarding operation condition. Typical CPAs for chromatographic experiments are sampling ,sampling preparation ,standards reagents, column chemistry, mobile phase composition, pH and flow of mobile phase, column temperature ,detector selection etc. 28

27. Risk Assessment According to ICH Q9 guideline: “It is systematic process for the assessment, control, communication and review of risks to the quality aross the method development”. This step is vital in order to reach a confident level that the method is reliable. Once the ATP and CPA are identified, AQbD emphases on detailed risk assessment of the factors that may lead to possible variability in the method , like analyst method , instrument configuration, measurement and method parameter ,sample characteristics, sample preparation, and environmental condition. According to ICH Q9, risk assessments can be carried out in three steps Risk identification Risk analysis Risk evaluations Risk assessment can be performed from initial stage of method development to continuous method monitoring. 29

28. 30 METHOD OPERABLE DESIGN REGION(MODR) MODR is a systemic series of experiments in which purposeful changes are make to input factors to identify causes for significant changes in the output responses and determining the relationship between factors and responses to evaluate all the potential factors and responses to evaluate all the potential factors simultaneous systemically and speedilys the MODR can also be established in method development phase, which could serve as a source for robust and cost effective method. It is the operating range for the critical method input variable that produces results which consistently meet the goals set out in the ATP. MODR permits the flexibility in various input method parametersto provide the expected method performance criteria and method response without resubmission to FDA. Once this is defined,appropriate method controls can be put in place and verification and method validation can be carried out. If the factors are more than 4, first critical factors has to be screened out by screening designs and then opyimised by the optimization design. If the number of factors are less than 4 it can be directly optimized by the optimization design. Selection of design Selection of model Interpretation of model design

29. 31 Control Strategy A planned set of controls for CMAs & CMVs derived from current detailed method development during lab scale developmental stage ensures method performance and product quality The control strategy is an integrated overview of how quality is assured based on current process and product knowledge. This phase also includes eventual replication of optimized experiments, data collection and analysis to assure that the method remains in the state of control.

30. 32 CASE STUDY :- Tablet Dissolution The case study describes the impact of subtle changes in raw material variability on product performance and the importance of continuous monitoring throughout the product lifecycle to ensure product quality. During routine monitoring of product performance for an extended release tablet, an incidence of high variability in dissolution results was observed. Although all of the lots produced during this period met specifications, the trend in variability raised concerns about the potential for product quality problems to arise in the future. Data analysis to evaluate process capability with respect to dissolution at 12 h was carried out and the results suggested that supplemental tier 2 or tier 3 testing would be required to ensure product quality. Since the root cause of the upward trend in dissolution was not understood, a project was initiated using six sigma methodology to identify the root cause, design an improvement plan, and verify the impact of the corrective action.

31. 33 Six sigma is a well known, structured approach to solving technical problems that have no known solution, have a measurable defect or problem, and identifiable causes. The steps used in a six sigma approach are Define the problem Evaluate the ability to measure the problem Analyze the problem using the appropriate method Improve the process Implement the derived controls In this instance, the project team used production data and analytical method to identify the root cause and develop and implement the corrective action in a few months. Further evaluation of various parameters through multivariate analysis showed the root cause of variability to be directly related to raw material properties.

32. 34 The raw material properties affecting the dissolution rate were identified and new tighter specification was defined and implemented to control the quality attributes of the incoming raw material. The data and trend shown to the left of the vertical red line were before the implementation of control, while the data to the right of the vertical red line are from post- implementation. Following completion of the six sigma “Improve” phase, the process was found to be significantly more robust, as a statistical analysis showed that the process capability was 0.86 before the six sigma project, and 1.93 afterward. The histogram mean 12 h dissolution for before and after the six sigma project illustrates the improved robustness and a shifting of the dissolution mean towards the center of the allowable specification range.

33. 35 Further, a predictive model was developed using a JMP software- based analysis of historical production data. A multivariate dissolution model was created to predict the 12-h dissolution mode was created to predict the 2-h dissolution on an ongoing proactive basis. A pareto analysis of the data versus the CQA ranked the variables by correlation. Five factors, all quality attributes of the formulation excipient and drug substance, were found to be statistically significant. The prediction profiler from the model.the steeper the slope, whether positive or negative, the more that factor contributes to variability in dissolution. The statistical model was validated using four different excipient lots, each converted to 10-13 lots of tablets.

34. 36 The data are presented the predicted dissolution from the model versus the average 12-h dissolution from the multiple tablets lots gave a prediction error of about 1.0%.

35. 37 CONCLUSION: An accurate data analysis tool is necessary to evaluate any process or system to assure that it works consistently as intended. Implementing QbD is one of the approaches that devoutly make scientist to understand the process or system closely. Optimizing process by QbD has become mandatory by some of the regulatory guidelines around the globe. The outcome of AQbD is the understanding from method development to method transfer. AQbD tools are ATP, CPA, Method Optimization and Development with DoE, MODR, and control strategy with risk assessment, method validation, and continuous improvement. QbD has gain impotance in the area of pharmaceutical processes like drug development, formulation,analytical method and biopharmaceuticals.

36. 38 REFERENCE International conference on Harmonization of technical requirements for registration of pharmaceuticals for human use. Pharmaceutical Development Q8.ICH harmonized tripartite guideline, Draft step4, 2008. Yu L. pharmaceutical quality by design: product and process development, understanding and control, Pharmaceutical Research,2008; 25:781-791. Devesh a. Bhatt Smita ,Rane ,QbD APPROACH TO ANALYTICAL RP-HPLC method development and its validation. International Journal of pharmacy and Pharmaceutical Sciences , 2011.

37. 39 4. ICH guidelines 5. Snee RD. Status update: QbD. Pharm process ,2013: 24-26. 6.Walrath I, Glessner C, Cheung A, Ressler D. The new gold standard: Pfizer’s Quality by design approach to trial management pharm Exec, 2013: 48-52. 7. Rathore AS, Winkle H. Quality by design for biopharmaceuticals.Nat Biotechnol,2009: 27:26-34.

38. 40 T hank you