Part of Statistics in Pharmaceutical Development Using Quality-by-Design Approach a FDA Perspective

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Part of Statistics in Pharmaceutical Development Using Quality-by-Design Approach – a FDA Perspective Chi-wan Chen, Ph.D. Christine Moore, Ph.D. Office of New Drug Quality Assessment CDER/FDA/Industry Statistics Workshop Washington D.C. September 27-29, 2006

Outline FDA activities for quality Pharmaceutical CGMPs for the 21 st Century ONDQA's PQAS The sought state Quality by plan (QbD) and configuration space (ICH Q8) Application of factual apparatuses in QbD Design of tests Model building & assessment Statistical process control FDA CMC Pilot Program Concluding comments

21st Century Initiatives Pharmaceutical CGMPs for the 21 st Century – a hazard based approach (9/04) http://www.fda.gov/cder/gmp/gmp2004/GMP_finalreport2004.htm ONDQA White Paper on Pharmaceutical Quality Assessment System (PQAS) http://www.fda.gov/cder/gmp/gmp2004/ondc_reorg.htm

The Desired State (Janet Woodcock, October 2005) A maximally proficient, nimble, adaptable pharmaceutical assembling area that dependably creates top notch medicate items without broad administrative oversight A common objective of industry, society, and controller

FDA's Initiative on Quality by Design In a Quality-by-Design framework: The item is intended to meet patient prerequisites The procedure is intended to reliably meet item basic quality traits The effect of detailing parts and process parameters on item quality is comprehended Critical wellsprings of process inconstancy are recognized and controlled The procedure is persistently checked and upgraded to guarantee steady quality after some time

Process Understanding Continuous Improvement Product Knowledge Product Quality Attributes Process Controls Process Parameters Product Specifications Product Design Unit operations, control methodology, and so on. Prepare Design Desired Product Performance Dosage frame, soundness, definition, and so on. Prepare Performance Cpk, power, and so on. Quality by Design FDA's view on QbD, Moheb Nasr, 2006

Design Space (ICH Q8) Definition: The multidimensional mix and collaboration of information factors (e.g., material properties) and process parameters that have been exhibited to give confirmation of value Working inside the plan space is not considered as a change. Development out of the outline space is thought to be a change and would typically start an administrative post-endorsement change prepare. Configuration space is proposed by the candidate and is liable to administrative appraisal and endorsement

Current versus QbD Approach to Pharmaceutical Development

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

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

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

Design Space Determination First-standards approach blend of trial information and unthinking learning of science, physical science, and designing to demonstrate and anticipate execution Statistically composed investigations (DOEs) proficient technique for deciding effect of numerous parameters and their cooperations Scale-up connection a semi-exact way to deal with interpret working conditions between various scales or bits of hardware

Design of Experiments (DOE) Structured, sorted out strategy for deciding the relationship between variables influencing a procedure and the reaction of that procedure Application of DOEs: Scope out starting plan or process configuration Optimize item or process Determine configuration space, including multivariate connections

DOE Methodology (2) Conduct randomized examinations (1) Choose exploratory outline (e.g., full factorial, d-ideal) A B C (3) Analyze data (4) Create multidimensional surface model (for enhancement or control) www.minitab.com

Model Building & Evaluation - Examples Models for process advancement Kinetic models – rates of response or corruption Transport models – development and blending of mass or warmth Models for assembling improvement Computational liquid elements Scale-up connections Models for process observing or control Chemometric models Control models All models require check through factual investigation

Model Building & Evaluation - Chemometrics is the art of relating estimations made on a compound framework or procedure to the condition of the framework by means of utilization of scientific or measurable strategies (ICS definition) Aspects of chemometric investigation: Empirical technique Relates multivariate information to single or different reactions Utilizes various direct relapses Applicable to any multivariate information: Spectroscopic information Manufacturing information

Statistical Process Control - Definitions Statistical process control (SPC) is the use of factual techniques to distinguish and control the exceptional reason for variety in a procedure. Regular cause variety – arbitrary change of reaction brought about by obscure variables Special cause variety – non-irregular variety created by a particular component Upper Specification Limit Upper Control Limit 3 s Target Lower Control Limit Lower Specification Limit Special cause variety?

Process Capability Index (C pk )

Quality by Design & Statistics Statistical examination has different parts in the Quality by Design approach Statistically planned investigations (DOEs) Model building & assessment Statistical process control Sampling arranges (not talked about here)

CMC Pilot Program Objectives: to give a chance to taking an interest firms to submit CMC data in view of QbD FDA to actualize Q8, Q9, PAT, PQAS Timeframe: started in fall 2005; to end in spring 2008 Goal: 12 unique or supplemental NDAs Status: 1 endorsed; 3 under survey; 7 to be submitted Submission criteria More significant logical data exhibiting utilization of QbD approach, item information and process understanding, chance evaluation, control system

CMC Pilot - Application of QbD All pilot NDAs to date contained a few components of QbD, including utilization of proper factual devices DOEs for detailing or process streamlining (i.e., deciding target conditions) DOEs for deciding scopes of configuration space Multivariate chemometric investigation for in-line/at-line estimation utilizing such innovation as close infrared Statistical information introduction and value Concise synopsis information worthy for accommodation and audit Generally utilized by commentators to see how improvement or configuration space was resolved

Concluding Remarks Successful execution of QbD will require multi-disciplinary and multi-utilitarian groups Development, producing, quality staff Engineers, experts, scientific experts, mechanical drug specialists & analysts cooperating FDA's CMC Pilot Program gives a chance to candidates to share their QbD approaches and related measurable devices FDA anticipates working with industry to encourage the usage of QbD