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Process Capability, cGMP, and Product

Quality

Lawrence X. Yu, Ph.D.

Deputy Director

Office of Pharmaceutical Quality

Center for Drug Evaluation and Research

Food and Drug Administration

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What is Pharmaceutical Quality?

• Janet Woodcock

– A high quality drug product as a product free of contamination and reproducibly delivering the therapeutic benefit promised in the label

• Free of contamination: CGMP focus

• Reproducibly delivering the therapeutic benefit promised in the label: QbD focus

• Therefore, Pharmaceutical Quality = QbD + CGMP?

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What is Quality by Design?

• ICH Q8(R2)

– The pharmaceutical Quality by Design (QbD) is a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management

• Quality by Design Tools – Design of experiments (DoE)

– Risk assessment

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Overview of QbD

DEFINE Quality

Target Product Profile

Process Design and

Understanding

Product Design and

Understanding

Control

Strategy

TARGET DESIGN and

UNDERSTANDING IMPLEMENTATION

Continual

Improvement

Labeled Use

Safety and Efficacy

L. X. Yu. Pharm. Res. 25:781-791 (2008)

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Quality by Testing vs. Quality by Design

• Quality by Testing

– Specification acceptance criteria are based on one or more batch data

– Testing must be made to release batches

• Quality by Design

– Specification acceptance criteria are based on performance

– Testing may not be necessary to release batches

L. X. Yu. Pharm. Res. 25:781-791 (2008)

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Pharmaceutical QbD Objectives

• Achieve meaningful product quality specifications that are based on assuring clinical performance

• Increase process capability and reduce product variability and defects by enhancing product and process design, understanding, and control

• Increase product development and manufacturing efficiencies

• Enhance root cause analysis and post-approval change management

L. X. Yu et al. AAPS J. 16:771-83 (2014)

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Concept of Process Capability

• First introduced in Statistical Quality Control Handbook by the Western Electric Company (1956).

• Process capability is defined as the natural or inherent behavior of a stable process that is in a state of statistical control

• ISO, AIAG, ASQ, ASTM ….. published their guideline or manual on process capability index calculation

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• Cp: process capability index

where σST is the inherent variability of a stable process, USL = upper specification limit, and LSL = lower specification limit.

• Cpk: minimum process capability index

Process Capability Index

Cpk = min (Cpku, Cpkl)

ST

MeanUSLCpku

3

ST

LSLMeanCpkl

3

ST

LSLUSLCp

6

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Cpk Value Sigma Value

Area under normal distribution curve

(% Conforming level*)

Non-conforming parts per million (ppm) Capability

Rating Unilateral Specification

Bilateral specification*

0.333 1 68.27 158650 317300 Terrible

0.667 2 95.45 22750 45500 Poor

1.0 3 99.73 1350 2700 Marginally

capable

1.333 4 99.9936 32 64 Capable

1.667 5 99.99994 0.3 0.6 Good

2.0 6 99.9999998 0.001 0.002 Excellent

* Process mean is centered at middle of the specification limits and has normal distribution

Cpk Values and its Corresponding non-Conforming Rate

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• Process performance is a statistical measure of the overall variability of a measured quality attribute from a process that may not have been demonstrated to be stable

Process Performance Index

SD

LSLUSLPp

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Ppk= min (Ppku , Ppkl )

Ppku= SD

MeanUSL

3

Ppkl= SD

LSLMean

3

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Difference between Cpk and Ppk

• Cpk represents the potential process capability (i.e.

how well a given process could perform when all

special causes have been eliminated).

• Ppk addresses how the process has performed

without the demonstration of the process to be

stable.

• Forecast future batch failure rate

– Cpk (Yes) ; Ppk (No)

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Process Capability Requires a Stable Process

That is in a State of Statistical Control

• A state of statistical control (i.e. stable state) means that the process exhibits no detectable patterns or trends and hence the variation seen in the data is due to random causes and inherent to the process

• Generally use “Control Charts” to determine if the process is in state of control

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Control Chart

• Definition: a graphical display of a product quality characteristic that has been measured or computed periodically from a process at a defined frequency

• Every control chart consists of: – A set of data – A central line (CL) (mean) – Two statistical process control limits (UCL and LCL) (Is the process

Stable?)

• Upper and Lower Specification Limits (USL and LSL) – Patient’s need ( Safety and Efficacy) (Is the process Capable?)

Quality

attribute

(unit)

Sample #

4.0

5.0

6.0

30 40 50 60

USL

LSL

CL

Figure 1. Control chart. A control chart displays measurement of a quality attribute over time. When appropriate tools detect the presence of special cause variation, continual improvements can be initiated to correct and/or prevent potential failures so that the process remains in a state of statistical control. Thus, the expected range of process outputs can be reliably predicted and the well sought goal of product and process robustness is achieved and maintained. (USL, upper specification limit; LSL, lower specification limit)

UCL

LCL

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Sources of Variation

• Variation can be categorized as

either:

– Common causes of variation

• Inherent to a system, random, always present and hence predictable within statistical limits

• Eliminate inherent variability (noise) is difficult

– Special causes of variation

• Exterior to a system, non-random, not always present

(intermittent)

• can cause changes in the output level, such as a spike, shift, drift, or non-random distribution of the output.

• Are usually easier to be detected, controlled or eliminated

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What are GMPs?

• GMP refers to the Current Good Manufacturing Practice regulations... CGMPs provide for systems that assure proper design, monitoring, and control of manufacturing processes and facilities... This includes establishing strong quality management systems, obtaining appropriate quality raw materials, establishing robust operating procedures, detecting and investigating product quality deviations, and maintaining reliable testing laboratories. This formal system of controls at a pharmaceutical company, if adequately put into practice, helps to prevent instances of contamination, mix-ups, deviations, failures, and errors.

CGMP: New Inspection Protocol Project

• Goal: To develop a new paradigm for inspections and reports that will advance pharmaceutical quality

– Standardized approach to inspection

– Data gathering to inform “quality intelligence” of sites and products

– Risk based and rule based process, using expert questions

– Semi-quantitative scoring to allow for comparisons within and between sites

– More common inspection report structure

– Recognize and reward positive behaviors in cases where

facilities exceed basic compliance

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NIPP Project Organization

New Inspection Protocols Project (NIPP) CDER and ORA

Surveillance Inspection Subgroup

For Cause Inspection Subgroup

Pre-Approval Inspection Subgroup

Observations to inform premarket review decisions

Observations on state of quality in a facility to assess quality risk

Escalation/ transition to “For Cause” when conditions indicate

Evidence of cGMP violations to support enforcement

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Quality System

• Management Responsibilities

• Quality Unit Responsibilities

• Training and Personnel Development

• Process Performance and Product Quality Monitoring System (PPPQMS) & Preventative Action

• Investigations and Corrective Action

• Change Management System

• Data Integrity – All Systems Oversight

Continuous improvement

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Quality Metrics

• Vision – A more rigorous and comprehensive approach to quality

surveillance that allows for improved monitoring of

current status across the inventory of FDA-regulated

drug products and manufacturing sites

• Goals: Objective measures

– Quality of a drug product

– Quality of a site

– Effectiveness of systems associated with the manufacture of pharmaceutical products

• Draft Guidance published July 27, 2015 – http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegu

latoryInformation/Guidances/UCM455957.pdf

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FDA Draft Quality Metrics Guidance, July, 2015

• Metrics FDA Intends to Calculate

– Lot acceptance rate

– Product quality complaint rate

– Invalidated Out-of-Specification rate

– Annual product review or product quality review on time rate

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FDA Draft Quality Metrics Guidance, July, 2015 (continued)

• Optional Metrics

– Quality Culture • Senior management engagement

• corrective action and preventive action effectiveness

• percentage of your corrective actions involved re-training of personnel

– Process Capability/Performance • Process capability is a leading, useful indicator. However, its

calculation is relative complex

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Amgen

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Business Case

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Excuses not to Use Process Capability, therefore, not to Improve…

• “My specification acceptance criteria are too narrow…”

– Provide evidence and discuss with the FDA

• “Process capability requires 30 or more batches”

– You can always calculate process performance when the number of batches is small or the process is not stable.

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Summary

• Process capability is a leading, useful indicator although its calculation is relative “complex”

• Quality standard should be clinically relevant and a surrogate of clinical performance

• Pharmaceutical Quality = QbD + CGMP