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2018 Quality by Design CurriculumComprehensive CMC Training and Consulting Support

for Modern Drug Development

BioAssay

SCIENCESA Division of Thomas A. Little Consulting

Thomas A. Little Consulting and BioAssay Sciences

Major biotechnology and pharmaceutical companies have selected Thomas A. Little Consulting (TLC) solutions for QbD training and implementation consulting.

TLC has two core products for QbD and Modern Drug Development and MFG1. Consulting services for Risk Assessment, Formulation, Upstream, Downstream, Release Testing

Bioassay and Analytical Methods development and validation for CMC team support2. A comprehensive QbD JMP/SAS based training curriculum

Thomas A. Little Consulting (TLC) is an internationally recognized scientific and engineering consulting firm with a proven record for achieving results. TLC has an extensive health authority and QbD curriculum for method, product and process development, data analysis, characterization, optimization and control. TLC is a strategic partner of SAS/JMP.

TLC works actively with the drug development team to assure product development and submission study design, data analysis, riskassessments, design of experiments, assay development and validations all meet the high standards of regulatory review and use best in class approaches to product development and report generation.

TLC has developed specific courses in analytics, data analysis, design of experiments, performance modeling, statistical process control, assay development and method validation, measurement systems analysis, mixture design of experiments, quality risk managementand failure modes and effects analysis. These courses are used by a variety of fortune 500 companies to train their analysts, scientists and engineers. TLC has extensive experience in the biotechnology, pharmaceutical and medical device industries and has trained over 150,000 professionals globally.

Who Uses TLC’s Consulting and Curriculum?

Biologics and Pharmaceuticals Health Authorities

Allergan FDA (CBER, CDER and CVM)Alnylam CFDAAudentes Therapeutics KFDABoehringer IngelheimBontiBristol-Myers SquibbCatalentCevaEmergent BiosolutionsJounce TherapeuticsGenentechGilead SciencesGlenmark Pharmaceuticals SAHalozyme TherapeuticsNovavaxPfizer Portola PharmaceuticalsRegeneron PharmaceuticalsRevanceTakeda PharmaceuticalThermo Fisher Scientific

Comprehensive Drug Dev Curriculum and Experience

Days 2018 QbD and Modern Drug Development CurriculumProcess

Sciences

Analytical

Sciences

Quality

AssuranceFormulation

1 Introduction to QbD and Critical Quality Attributes • • • •

3 Statistical Methods and Data Analysis • • • •

2 Design of Experiments • • • •

1 Advanced Design of Experiments • • •

2 Analytical Method Development and Validation • • •

2 Quality Risk Management and Risk Assessment • • • •

2 Root Cause Analysis and CAPA • • •

2 Robust Optimization, Design Space and Tolerance Design • • •

1 Statistical Methods for Process Validation • •

2 Stability Analysis • • • •

2 Process Control Design using SPC/PAT • • •

2 Bioassay Design, Control and Validation • •

1 Nonlinear Modeling (Dose Response) • • •

23 Total 21 22 15 17

© Thomas A. Little Consulting 2015-2018

Introduction to QbD and Critical Quality Attributes

Detailed Course Outline

Section I: Introduction to Quality by Design

FDA and EU guidance on QbDPurpose and opportunityQbD benefits and impact on FDA submissionsSystematic product development

Section II: Systematic Product Development

Market understandingTarget Product Profile (TPP)Quality Target Product Profile (QTPP)Critical Quality Attributes (CQAs)CQA flow down and line of sight

Course Purpose: Foundations in Quality by Design, organizational alignment and development objectives alignment. Defines CQAs, product development requirements, line of sight and requirements flow down. (1 day)

Section III: QbD Implications to Analytical Method and Process Development

Method development implicationsProcess development implicationsQbD and Validation (Lifecycle Approach)

For:

ProcessAnalyticalQualityFormulation

TPP/QTTP

CQAs

Defined Processes and Materials

High Level Risk Assessment

Low Level Risk Assessment

Formulation, Dose and Stability

Process Char. and Parameter Set Points

Analytical Method Development

Analytical Method Validation & Control

Product Knowledge

Design Space and Tolerance Design

Process KnowledgeCPPs and CMAs &

Control Plan

Process Validation, Control and Capability

CMC Requirements

Validation and Control

Clinical

Statistical Methods and Data Analysis


Section I: Introduction to SAS/JMP Table commands Column commands Row commands Subset commands Saving Scripts, Journals and Projects

Section II: Statistics Foundations and Distribution Analysis Measures of center and spread Standard error and central limit theorem Normal distribution t distribution and confidence intervals Test for normality Individuals and tolerance intervals (normal) Process capability (normal) Nonnormal distribution fitting and process capability

Course Purpose: General data analysis skills, hypothesis testing, capability, exploratory data analysis, equivalence testing and model building. (3 days)

Section III: Nominal X, Continuous Y Contour plots, Components of Variance, REML and POV Sample size for the mean and standard deviation t test – one sample t test – two sample Test for differences in variances t test – paired One-way ANOVA and F test N-way ANOVA Nonparametric data analysis (optional)

Section IV: Continuous X, Continuous Y Simple linear regression, correlation Orthogonal regressionMultiple regression ANCOVA

For:


Quality Risk Management and Risk Assessment


Section I: Quality Risk Management Principles and Process Risk management principles Risk management process Responsibilities Risk assessment Risk control Risk communication Risk review

Section II: Risk Analysis Tools Basic quality tools and risk weighted analysis Cause and effect diagrams Process flow and risk assessment Pareto and Risk Weighted Pareto analysis Histograms, capability, simulation and Margin Control charts Regression DOE (product and process) and MSA

Course Purpose: QbD templates, risk Assessments prior to product development and study designs. QTPP, CQAs, high level and low level risk assessment. (2 days)

Section III: Technical Risk Assessment Application areas for High Level risk assessmentFactor response, low level risk assessment

Section IV: Methods for Reducing Risk Risk assessment action plans and risk reduction Risk communication

For:ProcessAnalyticalQualityFormulation

Product Development Team Leader:

Key DS Characteristics Product Design Requirements and Critical Quality Attributes

DS ComponentAttribute

No.

Product Quality

Attribute Name

Critical Quality

Attribute Purpose

Test or Measurement

Definition

Attribute

Target

Attribute

Upper Limit

Attribute

Lower Limit

1

2

3

4

API- Active Pharmaceutical Ingredient 5

6

7

8

910

1

2

3

4

Excipients 5

6

7

8

9

10

1

2

Impurities 3

4

5

Design of Experiments


Section I: Introduction to DOE

Section II: Experimental Preparation

Section III: Full Factorial Designs

Section IV: Screening Designs Augment design

Section V: Custom Designs Generating custom designs Evaluating custom designs Analysis of custom designsSimulation for full distribution modeling Strategies to minimize experimental size Adding covariate and uncontrolled factors Life or repeated measures experiments Blocking designs Mixtures in custom designs Setting constraints in a DOE

Course Purpose: Study designs, product, analytical method and process characterization and analysis for development. (2 days)

For:


Analytical Method Development and Validation


Section I: Statistical Foundations and Variation Assessment Introduction to assay and test development, validation and MSA Review of basic statistics Variation analysis methods

Section II: DOEs for Assay Development and Evaluation Assay characterization experiments DOE for variation reduction DOE for robustness Establishing the linear range of the method

Section III: Chemical and Biological Method ValidationRobustnessStabilitySpecificity Linearity Precision (Repeatability, Intermediate Precision, Reproducibility) Limit of Blank, Limit of Detection, Limit of QuantitationSuitability Range Intermediate precision

Course Purpose: Study Designs and analysis for robustness, stability, specificity, precision, accuracy, linearity, LOB, LOD/LOQ, intermediate precision and range. (2 days)

For:

ProcessAnalyticalFormulation

Robust Optimization, Design Space and Tolerance Design


Section I: Distribution and tolerance design foundations System, parameter and tolerance design Tolerance design methods

Section II: DOE review and robust design principles Eight robust design principles

Section III: DOE using custom designs Custom designs Strategies to minimize experimental size Adding covariate and uncontrolled factors Special topics for custom designs (optional) Blocking designs Setting constraints in the design

Course Purpose: Product and process optimization, design space generation, edge of failure determination, and PAR and NOR ranges and tolerances. (2 days)

Section IV: Robust optimization methods Tighten the tolerance of X Design to the flats Use interactions to tune out sensitivities Use parameter combinations

For:


Section V: Tolerance design and margin analysis Tolerance design procedure Tolerance stack up analysis

Advanced Design of Experiments


• Custom DOE Basics Review and Analysis including Design Space, Edge of Failure and CPP identification

• Modeling how the influence of CPPs may be reduced/controlled once NOR/PARs have been selected

• Setting Acceptance Limits for DOE Validation runs• Advanced Linear Modeling and Response Parameterization DOE • Advanced Nonlinear Modeling and Response Parameterization DOE• Mixture DOE• Scale Up/Scale Down Model Calibration• Supersaturated Experiments • Analysis of Incomplete or Partially completed DOEs • Analysis of Single and Multiple Uncontrolled Factors in a DOE • Setting Constraints and Disallowed Combinations within a DOE• Split Plot and Strip plot designs• Central Composite Design for Optimization• Path of Steepest Assent for Optimization• Evolutionary Operations or how to run a DOE within a Defined

Design Space

Course Purpose: Extend the Experimenters Knowledge of DOE (2 days)

For:


Stability Analysis


Section I: Stability Definition and Introduction FDA guidelines

Section II: Stability Study Design Sample size Test conditions

Section III: Stability Data Analysis and Life Prediction Extendibility and Confidence Intervals Shelf Life Determination All batches pooled All batches with individual fits Common slope Common Intercept

Section IV: Stress and Accelerated Stability Testing

Course Purpose: Determination of expiry and rates of degradation under ambient, accelerated and storage conditions. (1 day)

For:


Process Control Design using SPC/PAT


Section I: Introduction and Basic Statistics SPC a basis for control Basic statistics Normal distribution Standard error of the mean Central limit theorem

Section II: Ten Requirements for Designing Effective Process Controls 1. Clear product specifications2. Effective metrology3. Process characterization4. Sampling plan5. Control chart selection (variables and attributes)6. Alarms, closing the loop and out-of-control action plans

(OCAP)7. Process documentation8. Operator and engineering training9. Database10. Routine line audits

Course Purpose: Process control design, monitoring and associated adjustment protocols. (2 days)

Section III: Process Capability Determining process stability prior to computation of capability Cp and Cpk , PPMSigma and z as measures of process capability Tests for normality Distribution fitting for nonnormal parameters

Section IV: Process Control Implementation Roles and Responsibilities

For:

ProcessAnalyticalQuality

Root Cause Analysis and CAPA, Technical Problem Solving


Section I: Introduction to root cause analysis Need for improvement Savings associated with root cause analysis Eight+ basic quality tools

Section II: Define and contain the problem Define the problem Contain the problem Determine scope, objectives and goals Project leadership and planning

Section III: Measure the problem Map the process Determine data collection plan Establish metrics and capability

Section IV: Analyze data and determine root cause Analyze and summarize the data Analyze and summarize the process map Determine root causes and summarize all findings

Course Purpose: Determination of root cause and corrective actions. (2 days)

Section V: Improve performance Brainstorming solutions and CAPA Benefit, cost, risk and complexity determination Measuring solution effectiveness

Section VI: Control and standardize improvements Process owner Select controls

For:


Nonlinear Modeling (Dose Response, Relative Potency)


Section I: Basics of Linear Modeling Basics of Linear Modeling Linear Regression Sniper Plots Fit Special

Section II: Nonlinear Models Nonlinear platform Model selection Model evaluation Adding X factors

Section III: Bio Assay and Relative Potency EC50 Potency and Relative Potency Parallelism Test options

Course Purpose: All nonlinear responses, potency and dose response determination. (1 day)

Section IV: Nonlinear DOE

For:

ProcessAnalytical

Statistical Methods for Process Validation


Section I: Process Qualification and Validation Introduction Process Validation and Drug Quality General Approach to Process Validation Statutory and Regulatory Requirements for Process Validation Process Validation Recommendations

Section II: Stage 1: Process Design Building and Capturing Process Knowledge and Understanding Establishing a Strategy for Process Control

Section III: Stage 2: Process Qualification Design of a Facility and Qualification of Utilities and Equipment Process Performance Qualification PAT during Qualification PPQ Protocol PPQ Protocol Execution and Report

Course Purpose: Statistical basis for lot variation analysis, PPQ study design and analysis. (1 day)

Section IV: Stage 3: Continued Process Verification Establishing a Monitoring Program Data Analysis Trending and ongoing Capability Monitoring Deviations/Investigations and CAPA Change Control Complaints CPV Data Review and Reporting

Section V: Analytical Tools for Process Validation DOE design space DOE, CPP and PAR analysis POV and Sample Size during PV Process Capability and Design Margin Control Charts during Validation ANOVA and ANOM Equivalence Testing

For:

ProcessQualityFormulation

Certified QbD Practitioner

Participants may be awarded the Certified QbDPractitioner certification. Participants must complete all coursework and demonstrate application to formulation, analytical methods, processes and or process controls.

Curriculum Deployment Strategy

Curriculum is divided into five (4) day training sessions. It is recommended that each 4 day training session be followed by one day of direct application where the instructor works with individual teams to accomplish their relevant work and apply the instruction received, making a total of 5 days for the deployment of one session.

Each one week session should be followed by 6-8 weeks to apply and absorb the training received.

Using this method one group of participants would cycle through the curriculum in a year.

Session 1 1 Introduction to QbD and Critical Quality Attributes

3 Statistical Methods and Data Analysis

1 Application Consulting

Session 2 2 Quality Risk Management and Risk Assessment

2 Design of Experiments


Session 3 2 Analytical Method Development and Validation

2 Robust Optimization, Design Space and Tolerance Design


Session 4 1 Mixture DOE

1 Stability Analysis

2 Process Control Design using SPC/PAT


Session 5 2 Root Cause Analysis and CAPA

1 Nonlinear Modeling (Dose Response, Relative Potency)

1 Statistical Methods for Process Validation


QbD Curriculum

Deployment Annual Plan

QbD Curriculum 2018 Annual Plan

Using the curriculum, determine how many people you want to train, which location, and then dates are coordinated and secured.

Maximum Class size is 20 persons. Additional persons up to 30 may be added at an additional per person cost.

Year Quarter Month Week Day

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Session 1 1 Introduction to QbD and Critical Quality Attributes 21-23

3 Statistical Methods and Data Analysis


Session 2 2 Quality Risk Management and Risk Assessment

2 Design of Experiments 25-26

1 Application Consulting 27-28

Session 3 2 Analytical Method Development and Validation 24-25

2 Robust Optimization, Design Space and Tolerance Design 25-26


Session 4 1 Mixture DOE 6-7

1 Stability Analysis

2 Process Control Design using SPC/PAT


Session 5 2 Root Cause Analysis and CAPA

1 Nonlinear Modeling (Dose Response, Relative Potency) ?

1 Statistical Methods for Process Validation 27-28


2016 Q1

QbD Curriculum

2015 Q1 2015 Q2 2015 Q3 2015 Q4

Benefits of Full QbD Implementation

Organizational alignment to QbD/ICH guidanceCost savings and latitude in manufacturing to adjust controls within design spaceFirst time quality – one and done, avoids excessive rework and redo’sFewer and less critical audit findingsEase of Tech TransferSuccessful submissionsReliably achieved development timelinesAlignment to market opportunitiesAchieve time to revenue forecastTimely phase exitEffective and safe treatment of indication

Now is the Time to Act, Next Steps

1. Set the goal. Make 2018 the year QbDmoves from an idea to a core competency

2. Organizational alignment, socialization and communication of goals

3. Build an annual training and consulting plan, request quotation

4. Schedule training and consulting5. Make sure SAS/JMP software is available

prior to training6. Align to phase development and phase

review/exit process for deliverables7. Measure/monitor progress and success8. Achieve the goal of agency alignment and

effective product development and submission

Fast Track Means Working With FDA to Minimize Risk and Time to BLA/Market

BioAssay Development and Validation

RobustnessSpecificity Linearity Precision (Repeatability, Intermediate Precision, Reproducibility) Suitability and ValidityRange Intermediate precision

SAS/JMP ScriptData AutomationReport GenerationSystems Suitability and Validity CriteriaControl plan

Binding AssaysCell Based AssaysAnimal AsssaysImmunoassays and Cut Points

Directly Support BioAssay Characterization, Qualification, Validation and Control

BioAssay


Web site for QbD consulting, www.QualityByDesignConsulting.comICH Q8, http://www.fda.gov/downloads/Drugs/.../Guidances/ucm073507.pdfICH Q9, http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q9/Step4/Q9_Guideline.pdf

ICH Q10, http://www.fda.gov/downloads/Drugs/Guidances/ucm073517.pdfICH Q2, http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q2_R1/Step4/Q2_R1__Guideline.pdf

FDA EMA QbD, http://www.fda.gov/Drugs/DrugSafety/ucm388009.htmWeb site for Thomas A. Little Consulting, www.thomasalittleconsulting.com Web site for SAS/JMP. www.jmp.com

12601 Wildflower LaneHighland UT, 84003 [email protected]

References

BioAssay


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