Quality by Design and Process Analytical Technology

Quality by Design
Need of QbD
Implementation of QbD
Analytical QbD
Process Analytical Technology
GMP
QA
QC

1. Quality by Design and Process Analytical Technology By Chandani Chandarana Assistant Professor SSR College of Pharmacy, Silvassa . 1/22/2020 1

2. What is QbD ? QbD (Quality by Design) is defined in the ICH Q8 guideline as “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and understanding and process control, based on sound science and quality risk management” 1/22/2020 2

3. Requirement of QbD 1/22/2020 3 Current approch QbD approch Quality is assured by testing and inspection. Here, any specifications are based on batch history. Here Quality is built into product & process by design and based on scientific understanding. It includes only data intensive submission which includes disjointed information without “big picture”. It includes Knowledge rich submission which shows product knowledge & process understanding. Here, any specifications based on batch history . Here, any specifications based on product performance requirements. Here there is “Frozen process,” which always discourages changes. It focuses on reproducibility which often avoids or ignores variation. Here there is Flexible process within design space which allows continuous improvement. It focuses on robustness which understands and control variation

4. Advantages of QbD For industry It helps in better understanding of the process. It reduces batch failure. It ensures better design of products with fewer problems in manufacturing. It allows for continuous improvement in products & manufacturing process. For FDA It enhances scientific base for analysis. It provides better consistency. It provides more flexibility in decision making. It ensures decisions are made on scientific base & not on obsereved information. 1/22/2020 4

5. A QBD DEVELOPMENT PROCESS MAY INCLUDE It is started with a target product profile that illustrates the use, safety and efficacy of the product. Then, introduces a target product quality profile that the formulators and process engineers use as a quantitative surrogate for aspects of clinical safety and efficacy of the product during development. The collection of relevant prior knowledge about the drug substance, potential excipients and process operations into a knowledge space is also done. Application of risk assessment tools to prioritize knowledge gaps for further investigation is necessary. e. Formulation of a design to find the critical material (quality) attributes of the final product that is necessary to be controlled to meet the target 1/22/2020 5

6. Also formulate the design of manufacturing process to produce a final product having the required critical materials attributes. Find out the critical process parameters and raw material attributes that should be controlled to achieve these critical material attributes of the final product. Risk assessment must be used to prioritize process parameters and material attributes for experimental verification. Combination of prior knowledge with experiments is important to establish a design space or other representation of process understanding. 1/22/2020 6

7. Making of a control strategy for the entire process that must include raw material controls, process controls and monitors, design spaces around individual or multiple unit operations, and/or final product tests. The control strategy must encompass expected changes in scale and can be guided by a risk assessment. Monitoring and update of the process to assure consistent quality continuously. 1/22/2020 7

8. Elements of QbD 1/22/2020 8

9. Elements involved in QbD based product development 1/22/2020 9

10. The Target Product Quality Profile (TPQP) TPQP has been defined as a “prospective and dynamic summary of the quality characteristics of a drug product that ideally will be achieved to ensure that the desired quality, and thus the safety and efficacy, of a drug product is realized” This includes dosage form and route of administration, dosage form strength(s), therapeutic moiety release or delivery and pharmacokinetic characteristics (e.g., dissolution and aerodynamic performance) appropriate to the drug product dosage form being developed and drug product-quality criteria (e.g. sterility and purity) appropriate for the intended marketed product. The concept of TPP in this form and its application is novel in the QbD paradigm. 1/22/2020 10

11. Basis for product design Dosage form Route of administration Strength, maximum and minimum Release/delivery of the drug Pharmacological characteristic Drug product quality criteria Pharmaceutical elegance 1/22/2020 11

12. Critical Quality Attributes Once TPQP has been identified, the next step is to identify the relevant CQAs. A CQA has been defined as “a physical, chemical, biological, or microbiological property or characteristic that should be within an appropriate limit, range, or distributed to ensure the desired product quality” Identification of CQAs is done through risk assessment as per the ICH guidance Q9. Prior product knowledge, such as the accumulated laboratory, nonclinical and clinical experience with a specific product-quality attribute, is the key in making these risk assessments. Such knowledge may also include relevant data from similar molecules and data from literature references. 1/22/2020 12

13. Role of CQA 1/22/2020 13

14. Decision tree for CQA 1/22/2020 14

15. CQA for drug substance and drug product 1/22/2020 15

16. The use of robust risk assessment methods for identification of CQAs is novel to the QbD paradigm CQAs of solid oral dosage forms are typically those aspects affecting product purity,strength , drug release and stability. CQAs for other delivery systems can additionallyinclude more product specific aspects, such as aerodynamic properties for inhaledproducts , sterility for parenteral , and adhesion properties for transdermal patches. For drug substances, raw materials and intermediates, the CQAs can additionallyinclude those properties (e.g., particle size distribution, bulk density) that affect drugproduct CQAs. 1/22/2020 16

17. Critical Process Parameter Critical process parameters (CPPs) are defined as “parameters whose variability have an impact on a CQA and therefore should be monitored or controlled to ensure the process produces the desired quality”. Process robustness is defined as the ability of a process to demonstrate acceptable quality and performance and tolerate variability in inputs at the same time. To demonstrate the reproducibility and consistency of a process, process capability should be studied. Process capability is a statistical measure of the inherent process variability for a given characteristics. The most widely accepted formula for process capability is six sigma. Process capability index is the value of the tolerance specified for a particular characteristic divided by the process capability 1/22/2020 17

18. If the CpK is significantly greater than one, the process is defined capable. If the process capability is low, there are five step procedures to progressively reduce the variability of the process. 1/22/2020 18

19. Quality Risk Assessment Quality risk management is a systematic process for the assessment, control, communication and review of risks to the quality of the drug (medicinal) product across the product lifecycle. The initial list of potential parameters which can affect CQAs can be quite extensive but can be reduced and prioritized by quality risk assessment (QRA) 1/22/2020 19

20. Overview of quality risk management process 1/22/2020 20

21. QRA is a science based process that can aid identification of CPPs and thus eliminating risk, resulting in high confidence that the analytical method will meet the QTTP under all conditions of use. Thus, a large number of parameters can actually be safely eliminated by use of QRA tools, for example failure mode effects analysis (FMEA) and Ishikawa diagrams on the basis of prior knowledge and initial experimentation. In FMEA the variables are ranked on the basis of the likelihood failure will occur (probability), affect on the pharmaceutical results (severity), and difficulty of detection ( detectability ), resulting in a risk priority number (RPN). Factors with an RPN above a cut-off level can then be evaluated by subsequent studies whereas factors with a lower RPN can be eliminated from further study. Ishikawa diagrams segregate risks into different categories, for example those associated with instrumentation, materials, methods, measurements, laboratory climate, and human factors. 1/22/2020 21

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23. A fault tree analysis is used to link the potentially critical quality attribute “content uniformity” to a potential failure mode and potential causes. Four main causes, i.e., raw and intermediate material properties, processing parameters, equipment and design parameters as well as environmental factors, and the associated sub-causes were identified and afterwards systematically listed in an Ishikawa diagram 1/22/2020 23

24. Design Space The ICH Q8(R2) States that the design space is multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post approval change process. 1/22/2020 24

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26. Design space is proposed by the applicant and is subject to regulatory assessment and approval1. Design space is potentially scale and equipment dependent, the design space determined on the laboratory scale may not be relevant to the process at the commercial scale. Therefore, design-space verification at the commercial scale becomes essential unless it is confirmed that the design space is scale-independent 1/22/2020 26

27. Control Strategy The ability to evaluate and ensure the quality of in-process and/or final product based on process data which typically include a valid combination of measured material attributes and process controls. ICH Q8(R2). Control strategy is defined as “a planned set of controls, derived from current product and process understanding that assures process performance and product quality”. The control strategy in the QbD paradigm is established via risk assessment that takes into account the criticality of the CQA and process capability. 1/22/2020 27

28. The control strategy can include the following elements: procedural controls, in process controls, lot release testing, process monitoring, characterization testing, comparability testing and stability testing Particularly, the control strategy may include: Control of raw material attributes (e.g., drug substance, excipients and primary packaging materials) based on an understanding of their impact on process-ability or product quality. Product specifications Procedural controls Facility controls such as utilities, environmental systems and operating conditions Controls for unit operations that have an impact on downstream processing or end-product quality (e.g. the impact of drying on degradation, particle size distribution of the granulate on dissolution 1/22/2020 28

29. PAT Used in QbD Online and Offline analysis design space 1/22/2020 29 A system for designing, analyzing and controlling manufacturing through timely measurement of critical quality performance attributes of raw and in process materials and processes with the goal of ensuring final product quality. Multidimensional combination of and interaction of input variables and process parameters that have been demonstrated to provide Quality Assurance Linkage between process inputs (inputs variables and process parameters) and critical quality attributes Proposed by Applicant Working within the design space: not considered as a change

30. Online and Offline analysis design space 1/22/2020 30

31. Formulation by Design 1/22/2020 31

32. Process flow diagram for orally dispersible tablet 1/22/2020 32

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35. Risk analysis of Critical Process Parameters 1/22/2020 35

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41. AQBD Analytical Target Profile (ATP) This analytical procedure is capable of quantifying related substances in XYZ drug product over the range of 0.1% (the reporting threshold specified in ICH Q3B) to 0.2% (specification criterion). The accuracy and precision of the procedure are maintained as reportable results fall within ± 0.02% of the true value with an 80% probability determined with a 95% confidence when 0.1% to 0.2% related substances are measured. To satisfy the ATP above, analytical procedures are required to conform to the “Performance criteria” shown below. Specificity: Not affected by the excipient components of the drug product, capable of determining the target impurities specifically with sufficient discrimination capability. Sensitivity: The quantitation limit (S/N ratio is not less than 10) is not more than 0.1%. Range: In the range between 0.1% and 0.2%, reportable results fall within ± 0.02% of the true value with an 80% probability determined with a 95% confidence. Other requirements Linearity: The analytical procedure shows linearity in the range between 0.05% and 1.0%. The correlation coefficient of the regression equation is not less than 0.99 and the regression line passes through the origin. 1/22/2020 41

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43. Analytical Procedure Development Selection of analytical techniques Physicochemical properties of the drug substance Formulation of the drug product 1/22/2020 43

44. Characterization of impurities (Target impurities) Evaluation and determination of analytical techniques 1/22/2020 44

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46. Analytical procedure design A screening study was carried out examining the organic solvent (acetonitrile) ratio in the mobile phase, buffer pH, and column temperature, the parameters known to have a significant impact on peak retention and separation in HPLC analysis. A detection wavelength of 220 nm was selected on the basis of the already determined UV spectrum of XYZ drug substance and the UV spectrum data for the target impurities. The analytical columns used were AAA, BBB, and CCC 1/22/2020 46

47. An experiment was made in a 2-level full factorial design with three factors to develop a multiple regression model for the number of peaks and the minimum resolution. AAA was selected as the analytical column because it produced the best peak shape. Figure presents contour plots at column temperatures of 30°C, 35°C, and 40°C. The red area in each contour plot represents the region within which the number of peaks is less than 7 and all of the target impurities (Imps 1 to 6) are not separated from each other. On the other hand, each blue area indicates the region within which the resolution between the closest peaks is less than 1.5. It was predicted from the regression model that the number of peaks would be 7 or more and the resolution between the closest peaks would be 1.5 or more in cases where the acetonitrile ratio in the mobile phase would be about 40%, the buffer pH about 7 to 8, and the column temperature about 40°C (white area). 1/22/2020 47

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49. HPLC operating conditions Detector: An ultraviolet absorption photometer (detection wavelength: 220 nm). Column: AAA (4.6 mm ID × 150 mm, particle diameter 5 µm) Mobile phase: A mixture of borate buffer solution, pH 8.0 and acetonitrile (60:40) Flow rate: Adjust the flow rate so that the retention time of XYZ is about 15 minutes. Column temperature: A constant temperature of about 40°C. 1/22/2020 49

50. Primary risk assessment The performance of an HPLC analytical procedure for impurities is greatly characterised by its specificity, namely, separation performance. Thus, factors considered to affect separation performance were extracted and compiled into a cause and effect diagram as presented in Figure 3. For each factor, more detailed factors were extracted and classified according to respective characteristics as shown in Table 1. The assessment was carried out by utilizing the findings gained in the initial screening study and the general knowledge and the experience regarding the analytical technique. 1/22/2020 50

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56. Experimental evaluation HPLC operating conditions 1/22/2020 56

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58. 1/22/2020 58 HPLC operating conditions Detector: An ultraviolet absorption photometer (detection wavelength: 220 nm) Column: AAA (4.6 mm ID × 150 mm, particle diameter: 5 µm) Mobile phase: A mixture of borate buffer, pH 8.0, and acetonitrile (55:45) Flow rate: A constant flow rate of 1.0 mL/min Column temperature: A constant temperature of about 39ºC Sample injection volume: 5 µL

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60. Secondary risk assessment For the factors categorized as Factor N in the primary risk assessment, an FMEA was conducted using the optimized analytical procedure. Prior to the determination of risk priority, Risk Priority Number was defined as follows: Risk Priority Number (RPN) = S × O × D 1/22/2020 60

61. 1/22/2020 61 Table shows the results of the FMEA and those of the risk reductions achieved for the factors under Factor N with a medium or high risk priority. For the factors considered to bear a potential risk, a reduction of the risk was undertaken by setting system suitability or establishing SOPs

62. Verification of Analytical Procedure Performance: The analytical procedure was verified for performance in accordance with the ICH Q2 Guideline on Validation of Analytical Procedures using the performance criteria laid down in Section 1 according to the ATP. The results confirmed that the established analytical procedure fulfilled the requirements based on the performance criteria, thus demonstrating the performance of this procedure. 1/22/2020 62

63. Specificity Using forced degradation samples or orthentic impurity samples, specificity of the analytical procedure was confirmed by conducting confirmatory verification of the separation performance elaborated during the development of the procedure. 3.2 Accuracy Accuracy of the analytical procedure was evaluated in terms of the recovery of the impurity from the spiked samples. The spiked sample preparations were conducted at 3 concentrations in the range of 0.1% (reporting threshold) to 0.2% (specification value). 3.2 Precision (repeatability and intermediate precision) Precision of the analytical procedure was evaluated in terms of the recovery of the impurity from the spiked samples. The spiked sample preparations were conducted at 3 concentrations in the range of 0.1% (reporting threshold) to 0.2% (specification value). 3.3 Linearity Linearity was verified in the range of 0.1% (reporting threshold) to 0.2% (specification value). The results gained were analyzed for linear regression to evaluate for linearity. 1/22/2020 63

64. Control Strategy: For HPLC operating conditions, it has been experimentally demonstrated that the variability of parameters does not affect the separation performance of this analytical procedure within the verified region on the basis of the optimization study results shown in Section 2.2.3. Thus, the risks associated with Factor X had already been reduced during the development of this analytical procedure, indicating that the ranges presented in Section 3.6 can be a method operable design region (MODR), i.e., a robust region within which the analytical results are not affected. 1/22/2020 64

65. Process analytical technology  ( PAT ) Process analytical technology  ( PAT ) has been defined by the United States  Food and Drug Administration  (FDA) as a mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of  Critical Process Parameters  (CPP) which affect  Critical Quality Attributes  (CQA). The concept actually aims at understanding the processes by defining their CPPs, and accordingly monitoring them in a timely manner (preferably in-line or on-line) and thus being more efficient in testing while at the same time reducing over-processing, enhancing consistency and minimizing rejects.

66. PAT is process analysis in real-time. At-line real-time analytical measurements can replace off-line time consuming chemical analyses. Locating information in those measurements, identifying the important process parameters and creating a model able to measure the quality instantaneously are the main stakes in PAT. MVA is the key tool.

67. The basics PAT is a term used for describing a broader change in pharmaceutical manufacturing from static batch manufacturing to a more dynamic approach. It involves defining the Critical Process Parameters (CPPs) of the equipment used to make the product, which affect the Critical Quality Attributes (CQAs) of the product and then controlling these CPPs within defined limits. This allows manufacturers to produce products with consistent quality and also helps to reduce waste & overall costs. This mechanism for producing consistent product quality & reducing waste presents a good case for utilizing continuous manufacturing technologies. The control of a steady state process when you understand the upstream & downstream effects is an easier task as common cause variability is easier to define and monitor.

68. The variables It would be acceptable to consider that raw materials used to manufacture pharmaceutical products can vary in their attributes e.g. moisture content, crystal structure etc. It would also be acceptable to consider that manufacturing equipment does not always operate in exactly the same fashion due to the inherent tolerance of the equipment and its components. It is therefore logical to say that variability in raw materials married with a static batch process with inherent variability in process equipment produces variable product. This is on the basis that a static batch process produces product by following a fixed recipe with fixed set-points. With this in mind the PAT drive is to have a dynamic manufacturing process that compensates for variability both in raw materials & equipment to produce a consistent product.

69. PAT implementation The challenge to date with PAT for pharmaceutical manufacturers is knowing how to start. A common problem is picking a complex process and getting mired in the challenge of collecting and analyzing the data. The following criteria serve as a basic framework for successful PAT roll-outs: Picking a simple process. (Think Water for Injection (WFI) or Building Monitoring System (BMS) All details and nuances are well understood and explained for that process. Determine what information is easily collected and accessible through current instrumentation. Understanding the appropriate intervals for collecting that data. Evaluating the tools available for reading and synchronizing the data.

70. PAT Tools in order to implement a successful PAT project, a combination of three main PAT tools is essential: Multivariate data acquisition and data analysis tools: usually advanced software packages which aid in  design of experiments , collection of raw data and statistically analyzing this data in order to determine what parameters are CPP. Process analytical chemistry (PAC) tools: in-line and on-line analytical instruments used to measure those parameters that have been defined as CPP. These include mainly near infrared spectroscopy  (NIRS); but also include  biosensors ,  Raman spectroscopy ,  fiber optics  and others. Continuous improvement  and/or  knowledge management  tools: paper systems or software packages which accumulate Quality Control data acquired over time for specific processes with the aim of defining process weaknesses and implementing and monitoring process improvement initiatives. These products may be the same or separated from the statistical analysis tools above .

71. 1/22/2020 71 QUALITY OBJECTIVES & GMP QUALITY CONTROL Quality control (QC) is a procedure (s) intended to ensure that a manufactured product or performed service adheres to a defined set of quality criteria or meets the requirements of the client or customer . It is a combination of all the characteristics of a product that determine the degree of acceptability of the product. QC is similar to, but not identical with, quality assurance (QA).

72. QUALITY CONTROL VERSUS QUALITY ASSURANCE The terms often used interchangeably to refer to ways of ensuring the quality of a service or product . Quality Assurance: The planned and systematic activities implemented in a quality system so that quality requirements for a product or service will be fulfilled . Quality Control: The observation techniques and activities used to fulfill requirements for quality. An evaluation to indicate needed corrective responses; the act of guiding a process in which variability is attributable to a constant system of chance causes 1/22/2020 72

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74. 1/22/2020 74 INTRODUCTION TO GMP Good manufacturing practice (GMP) is a system for ensuring that products are consistently produced and controlled according to quality standards. It is designed to minimize the risks involved in any pharmaceutical production that cannot be eliminated through testing the final product. BASIC FUNDAMENTALS INCLUDES Quality Safety Effectiveness

75. 1/22/2020 75 GMP covers all aspects of production, including; Personnel Premises Equipment Starting materials Production & In-process control Laboratory Control Packaging & Labeling Holding & distribution (ware house) Documentation : There must be systems to provide documented proof that correct procedures are consistently followed at each step in the manufacturing process - every time a product is made .

76. 1/22/2020 76 Why is GMP important? Avoids poor quality medicines, a health hazard Saves waste of money for both government and individual consumers. Helps boost pharmaceutical export opportunities Reduces and prevents errors Prevents contamination & cross contamination Minimizes variance in drug potency Prevents toxicity Prevents mislabeling Avoids adulteration

77. 1/22/2020 77 ORGANIZATION AND PERSONNEL Lay out of clean rooms Wear clean clothing Wear protective apparel to prevent contamination Practice good sanitation If sick or have open lesions that would impact the drug, excluded from direct contact with the product Regular medical check-ups

78. 1/22/2020 78 BUILDING AND FACILITIES Building will be adequately sized for proper storage of equipment and material Operations will be performed in specific areas Raw materials received will be placed in quarantine until tested Rejected material will be separated Adequate lighting Adequate environmental controls Air breaks on drains

79. EQUIPMENTS 1/22/2020 79 Maintained in a good state & qualified (Design, Cleanliness, Installation, Performance) Placed in appropriate place ( temperature & humidity control) Will be cleaned with approved cleaning agents will not affect product written schedule of cleaning clean after each batch ID number on equipment

80. 1/22/2020 80 STARTING MATERIAL Received in Quarantine not used until released Written procedures on receipt, handling and sampling Stored off the floor Each container marked with lot number, name and status (released, quarantined, rejected)

81. 1/22/2020 81 PROCESS CONTROL There will be written procedures Document activities batch record log books Work Instruction & operating procedures Control contamination Line clearance & Cleanliness & tanks, paddles etc Keep organized

82. 1/22/2020 82 WARE HOUSE It shall be clean Sections clearly identified: quarantine - yellow released - green rejected - red FIFO : First In - First Out Track inventory and sold lots

83. 1/22/2020 83 PACKAGING AND LABELLING The written display on the container Document receiving Separate labeling to avoid mix up Set procedures for appropriate: Identity Storage Handling Sampling Testing Inspection prior to issuance Label control begins with design

84. 1/22/2020 84 QC LAB Have specifications, standards, sampling plans, test procedures Shall have a calibration and maintenance program written with a time period for performance Document all testing use logbooks Stability testing done Reserve samples will be kept for final products over the period of the expiration date

85. 1/22/2020 85 DOCCUMENTATION Records maintained Batch records testing investigations training maintenance Cleaning If it was not documented, then it did not happen!

86. DUTIES OF H.O.D 1/22/2020 86 Authorization of written procedures Control & Monitoring Process validation Calibration of analytical apparatus Plant hygiene Training Retention of records Monitoring of compliance of GMP Inspection and investigation to assure quality

87. DUTIES OF PRODUCTION INCHARGE 1/22/2020 87 To ensure following: Product produced, stored and documented as per quality Approve instruction for production operations & strict implementation Evaluation of production records and its availability to QC Check maintenance of department, premises and equipment Ensure process validation Training

88. DUTIES OF QUALITY CONTROL INCHARGE 1/22/2020 88 To approve, reject the starting material, packaging material, intermediate, bulk and finished good. Evaluate batch record Approve sampling instruction Ensure necessary testing Check maintenance of department, premises and equipment To ensure training of other QC personnel’s