Design of Experiments as a Tool for QbD in Pharmaceutical Product Development. Dr Dehghan M. H Professor in Pharmaceutics, Y B Chavan College of Pharmacy, Aurangabad Date:23rd Jan’ 2016

Pharmaceutical Development Aim: To design a quality product and its manufacturing process to consistently deliver the intended performance of the product. “Quality cannot be tested into a product Quality should be built in by design” NDA –Merck & Co 2006 “Januvia” first product approved based on QbD

Pharmaceutical Development Components of Drug Product Drug Substance Excipients B. Drug Product Formulation Development Overages Physicochemical and Biological Properties Manufacturing Process Development Container and Closure system Microbiological Attributes Compatibility. Ref.: ICH Q8 (R1)

Traditional vs. QbD Approach to Pharmaceutical Development Traditional Approach QbD Approach Quality assured by testing and inspection Quality built into product & process by design, based on scientific understanding Data intensive submission – disjointed information without “big picture” Knowledge rich submission – showing product knowledge & process understanding Specifications based on batch history Specifications based on product performance requirements “Frozen process,” discouraging changes Flexible process within design space, allowing continuous improvement Focus on reproducibility – often avoiding or ignoring variation Focus on robustness – understanding and controlling variation

Pharmaceutical Development & Product Lifecycle Product Design & Development Process Design & Development Manufacturing Development Continuous Improvement Product Approval Candidate Selection

Statistical Process Control Pharmaceutical Development & Product Lifecycle Statistical Tool Product Design & Development: Initial Scoping Product Characterization Product Optimization Design of Experiments (DOE) Process Design & Development: Initial Scoping Process Characterization Process Optimization Process Robustness Model Building And Evaluation Statistical Process Control Manufacturing Development and Continuous Improvement: Develop Control Systems Scale-up Prediction Tracking and trending

Product Knowledge Continuous Improvement Quality by Design Process Understanding Product Knowledge Product Specifications Product Quality Attributes Process Controls Process Parameters Desired Product Performance Process Design Unit operations, control strategy, etc. Product Design Dosage form, stability, formulation, etc. Cpk, robustness, etc. Process Performance Quality by Design FDA’s view on QbD, Moheb Nasr, 2006

Overview of QbD Quality Target Product Profile (QTPP) Product Design and Understanding Process Design and Understanding Control Strategy Continuous Improvement Quality Target Product Profile (QTPP) Define Critical Quality Attributes (CQAs) Perform risk assessment Link raw material attributes and process parameters to CQAs Design and implement a control strategy Manage product lifecycle, including continuous improvement

Quality Target Product Profile-QTPP What is QTPP? A set of elements that defines the drug product The target or goal set in advance A guide to Drug Product development What forms the basis for QTPP? The RLD and its label Applicable regulatory guidelines When to define QTPP? At the start of development Knowledge gained in development may change some elements

Components of QTPP Components related to safety, efficacy, identity, purity and potency Critical and non-critical components, e.g. Critical: Assay, content uniformity Non-critical: Appearance Fixed and variable components Fixed elements must be present e.g. Dosage form, strength Variable elements may have a range of acceptable values e.g. Tablet weight, assay

An Example of QTPP components for IR tablet Dosage Form Route of administration Strength Weight Pharmacokinetics Appearance Identity Assay Impurities Content uniformity Friability Dissolution Residual solvents Specific requirements Scored tablets Weight variation between two halves Dissolution of half tablet Orally Disintegrating tablets Hardness Disintegration time Container closure Extended Release products Alcohol induced dose dumping

Critical Quality Attributes CQAs are a subset of the QTPP Include critical parameters that are likely to change based upon variations in raw materials and processes CQAs ensure that DP remains within safe and effective levels. QTPP components ---------------------------------------Dosage Form Route of administration Strength Weight Pharmacokinetics Appearance Identity Assay CQAs Assay (efficacy) Impurities (safety) C.U. (efficacy) Dissolution (efficacy) Critical Quality Attributes (CQA’s) ----------------------------- Assay (efficacy) Impurities (safety) C.U. (efficacy) Dissolution (efficacy)

What factors affect drug product CQAs? Properties of Input Materials- Identify Critical Material Attributes (CMAs) Properties of in-process materials- CQAs of one step become CMAs for a downstream unit operation Manufacturing process parameters- Identify Critical Process Parameters (CPPs)

Risk Assessment Risk assessment for Formulation – starting material properties, levels of components Manufacturing process Steps for risk assessment List out all components / processes Prepare the process flow chart Identify all potential failure modes for each item with risk query (what might go wrong?) Risk analysis Risk evaluation

Risk Assessment Various formal methodologies available for risk assessment Failure Mode Effects Analysis & Failure Mode Effects & Criticality Analysis Hazard & Operability Analysis Supporting statistical tools It is neither always appropriate nor always necessary to use a formal risk management process….. The use of informal risk assessment processes can also be considered acceptable. – ICH Q9 A risk-based justification based on experience and data is always necessary!

Risk Assessment Quality by Design for ANDA: An Example for Immediate-Release Dosage Forms Generic product development for Acetriptan Tablets, 20 mg. Acetriptan is a BCS Class II compound displaying poor aqueous solubility (less than 0.015 mg/mL) across the physiological pH range. It exists in three different polymorphic forms which may affect dissolution. Polymorph III is the most stable polymorph. Drug product is prepared with roller compaction process.

Risk assessment for formulation components Formulation Variables Drug Product CQA Formulation Variables Drug Substance PSD MCC/Lactose Ratio CCS Level Talc Level Magnesium Stearate Level Assay MEDIUM LOW Content Uniformity HIGH Dissolution Degradation Products

Risk assessment of DP manufacturing process Drug Product CQAs Process Steps Pre-RC* Blending and Lubrication Roller Compaction Milling Final Blending and Lubrication Compression Assay MEDIUM LOW Content Uniformity HIGH Dissolution Degradation Products * RC: Roller compaction

Justification for assigned risks

Control Strategy A planned set of controls, derived from current product and process understanding that ensures process performance and product quality…..” ICH Q8 (R2) & Q10 Control Strategy includes following elements (but not limited to): Input material attributes (e.g. drug substance, excipients, container closure) Equipment operating conditions (process parameters) In-process controls Finished product specifications Controls for each unit operations Methods and frequency of monitoring and control.

QbD Tools Design of experiments (DoE) Process Analytical Technology (PAT)

Experimental Designs 1. Success / Failure Useful for screening of variables with significant impact on DP CQAs 1. Success / Failure One run, no factors varied, one outcome, yes/no Easy to design, easy to analyze Lack of comparison, inefficient 2. OFAT, One-Factor-at-a-Time Several runs, one factor varied, two outcomes Easy to Design, has comparison of outcomes Limited number of experiments gives limited information Can’t find interactions and is inefficient

Design of Experiments (DOE) Structured, organized method for determining the relationship between factors affecting a process and the response of that process Multiple runs, multiple factors varied at a time Multiple outcomes, will find interactions Is much more efficient Comparison of outcomes Used in optimization studies, enables creation of “design space”

Scope of Experimental Design Expertise and Experience Define the measured responses (CQA) Identify factors (CPPs/CMAs) Select 2-7 factors to be treatments Depending on qualitative/quantitative factors select levels or values Select a design

Some Designs P B: Plackett- Burman Designs

DOE Methodology (1) Choose experimental design (e.g., full factorial, d-optimal) (2) Conduct randomized experiments Experiment Factor A Factor B Factor C 1 + - 2 3 4 A B C (3) Analyze data (4) Create multidimensional surface model (for optimization or control) www.minitab.com

Polynomial mathematical interaction expression Y= B0+B1X1+B2X2+B3 X12 +B4 X22 +B+5 X1 X2 + B6 X1X+B7X12+B8X12X22 Y – Response (CQA) Bi – Regression coefficient for various terms containing the levels of the independent variables. X – Independent variables (CMA/CPP)

CONTOUR PLOT FOR TABLET HARDNESS CONTOUR PLOT FOR Tablet dissolution(T50%) GRAPH OBTAINED BY SUPER IMPOSITION OF TABLET HARDNESS & DISSOLUTION

Design Space (ICH Q8) Statistically designed experiments (DOEs) An efficient method for determining impact of multiple parameters and their interactions and for the generation of design Space Definition of Design Space: The 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. Design space is proposed by the applicant and is subject to regulatory assessment and approval

Design Space Dependent Response Space Independent Factor Space ?

Conceptual Design Space Operation Space Opt Region of Interest Factor Space, X and Y Response Space, the contours Region of operability Uncertain space

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Process Inputs and Outcomes Critical Quality Attributes Design Space Process Step Input Materials Output Materials (Product or Intermediate) Measured Parameters or Attributes Control Model Process Measurements and Controls Input Process Parameters

Process Analytical Technology (PAT) Timely measurements during processing Critical quality and performance attributes Raw and in-process materials At-line, on-line or in-line measurements Founded on “Process Understanding” Opportunities for improvement More reliable and consistent processes (& product) Less failures, less reworks, less recalls Flexibility w.r.t. scale and equipment Better / faster Quality Systems Process Enhancement Opportunities

PAT in Tablet manufacturing

Examples of PAT Real-time Blend Uniformity by using TruProcess™ Analyzer Spectral Probe NIR Analyzer installed on viewing window of Glatt FBD without any dryer modification

References Guidance for Industry: Q8(R2) Pharmaceutical Development Guidance for Industry: Q9 Quality Risk Management Guidance for Industry: Q10 Pharmaceutical Quality System Guidance for Industry PAT: A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance Quality by Design for ANDAs: An Example for Modified Release Dosage Forms Quality by Design for ANDAs: An Example for Immediate Release Dosage Forms G A Lewis, Didier Mathieu, Roger Phan-Tan-Luu. Pharmaceutical Experimental Design , publishers Informa Healthcare, New York.

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