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Lifecycle Management Concepts to Analytical Procedures: A Compendial PerspectiveHoracio N. Pappa, CQE, Ph.D.,

Director – General Chapters Global Science and Standards Division, U.S. Pharmacopeia

27 TutorialsOverflowing with Rich Content & Tangible Takeaways for the Analytical Universe

LEADING ORGANIZATIONS SHOWCASING BEST-IN-CLASS INNOVATION AND PROCESSES, INCLUDING:

U.S. Pharmacopeia – American Society for Quality – GXP BioTechnology – Pharmalytik PAREXEL – Frolich Institute – BioMarin – Bayer HealthCare – Abbott Vascular – CAI

SynoloStats – Asklepion Pharmaceuticals – AVQC – ValGenesis – Relypsa

SEND YOUR TEAM! THIS EVENT IS CO-LOCATED WITH:STABILITY TESTING & PROGRAM MANAGEMENT

KEYNOTE SESSION AND SPEAKER

Analytical Procedures & Methods Validation • Develop a Roadmap for Analytical Methods Validation • Implement Continued Process Verification Protocols • Develop and Validate a Stability-Indicating Analytical Method • Effective Use of Statistics for the QC Scientist • Learn Best Practices for Method Transfer Studies • Determine Acceptance Criteria for System Suitability Tests • Analyze Samples from In-Process Through the Final Product • Adopt a Systematic Approach for Robustness with DoE • Evaluate Characteristics through Simple Statistical Analys

Laboratory Data Integrity Compliance • Understand MHRA’s Final Guidance on the Major Differences with FDA • Implement of Policy, Governance, Validation and Risk Management • Master Your Laboratory Metrics • Discover New Solutions for Old Equipment • Perform Risk-Based Evaluations • Prepare for and Perform a Laboratory Data Integrity Audit • Understand and Prevent Behavioral Non-Compliance • Govern Data in Cloud Computing • Cybersecurity – Addressing Malicious Threats • Master data lifecycle elements & audit trail review • Discover the key to an integrity culture • Experience a case study in lab data integrity remediation

REGISTER BEFORE MAY 25TH AND SAVE $300

ANALYTICAL PROCEDURES & METHODS VALIDATION

LABORATORY DATA INTEGRITY COMPLIANCE CONGRESS

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Day One – June 25, 2018

12:00 Conference Registration Coffee and Lite Snacks On-the-Go Chairperson’s Opening Remarks Lifecycle Management Concepts to Analytical Procedures: A Compendial PerspectiveHoracio N. Pappa, CQE, Ph.D., Director – General Chapters Global Science and Standards Division, U.S. Pharmacopeia • Current method lifecycle: <1224>; <1225>; <1226> • Analytical QbD • Fitness for Use • Analytical Target Profile • Proposed New USP General Chapter <1220> • The Analytical Procedure Lifecycle • Stage 1 – Procedure Design, Development & Understanding • Stage 2 – Procedure Performance Qualification • Stage 3 – Procedure Performance Verification

The MHRA Guidance on Data Integrity and the Major Differences with FDA’s DraftSteven S. Kuwahara, Ph.D., Principal Consultant,GXP BioTechnology, LLC. • Major differences with the FDA guidance • Definitions related to data integrity • Inclusion of other GMP requirements • Coordination with other organizations • References Takeaway Tools • MHRA’s final guidance • FDA’s draft guidance

FDA Insight on Analytical Method Development for BiologicsFDA Invited

Afternoon Refreshment Break Overcome Top Challenges to Build Quality Systems in Analytical and Stability LaboratoriesKim Huynh-Ba, Executive Director, Pharmalytik Pharmaceutical Quality System (PQS) is the foundation of pharmaceutical development and commercialization. Decisions must be made based on science and risk-based approaches. This session introduces PQS and its building blocks to support the analytical and stability laboratories, and also discusses analytical challenges to maintain a Quality Management System and support the product lifecycle that focuses on the patient. The following topics are discussed: • Quality Systems in the analytical laboratories • Establishment of validated state • Management of incidents and deviations • Continuous improvement and lifecycle management • Product lifecycle management

The Convergence of Laboratory Quality SystemsCarmen Medina, MPH, PhD(c), VP Techinical Services, PAREXEL International, Former FDA InvestigatorThe following 30 minutes promises to raise your awareness about convergence, how it applies to Quality Systems, and why understanding this prevents dangerous blind spots and risks within your organization. Quality Systems, when designed to interface effectively, work as a unified force for good, resulting in continuous improvement, risk mitigation and opportunity capture. Participate in this general session and learn to: • Design and refine your Quality Systems to ensure enterprisewide synergy • Identify which systems historically provide the greatest return on your investment

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JUNE 25-27 BAHIA RESORT HOTELSAN DIEGO, CA

STABILITY TESTING & PROGRAM MANAGEMENT

Implement Best-In-Class Procedures that Survive the Product Lifecycle

Join us for an incredible content-driven experience led by expect stabilitarians!

Learn more at www.kenx.org/events

5:00 Scholarship Award and Welcome Reception

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Day Two – June 26, 2018

7:00 Coffee and Lite Breakfast

Select Between Knowledge Exchange Sessions (1-2) Effectively Manage Method Transfer StudiesBette Monnot-Chase, Director, CMC & Quality, Asklepion Pharmaceuticals

• Learn key considerations for effective design of method transfer studies • Understand the role of test specification, standard and sample selection on acceptance criteria • The method transfer protocol: Determine the appropriate test parameters and acceptance criteria • Understand how to incorporate third party vendors • Learn the approaches for data analysis • Planning for regulatory submission: Understand the key features of an easy-to-read validation report

Analytical Data Integrity, it all Matters, but what Really Matters NOW?Jay Chenier, Data Integrity Consultant, formerly, Process Owner, Global Computer Validation, GlaxoSmithKline

• Attributable, Legible, Contemporaneous, Original, Accurate Better be ACCURATE • The laboratory is the main area of regulator focus • What regulators are finding in the laboratory and what they are doing about it • What regulatory sanctions mean for your company & what it costs • What you must do NOW

Select Between Knowledge Exchange Sessions (3-4)

Develop a Roadmap for Analytical Methods Validation Norman Fraley, Executive Director, Frolich Institute

Part 1 – The What • Understand the requirements between different method types • Determine which aspects of validation are critical to know • Create your checklist of inputs and outputs • Reasonableness check for protocols • Alternate meanings of standard terminology • Equipment checks • QA constraints • Talent constraints

Part 2 – The How • Developmental completeness • Confirm your pre-val • Matrix vs. neat • Instrument vs. method • All data pass all criteria • What constitutes a deviation or discrepancy • Mid validation tweaks

Knowledge ExchangeAttendees take part in a round-the-room survey of routine validation practices, challenges and hurdles. Mini AAR to share “aha” moments.

Tangible Takeaways • Generic roadmap for validation • Example of a modified roadmap • Templates for a standardized validation report • Readiness checklist

Laboratory Data Integrity – Successful Implementation of Policy, Governance, Validation and Risk ManagementEileen Cortes, Associate Director for QA and Validation, BioMarin

Part 1 – Data Integrity Policy and Governance Planning • Principles of Data Integrity • ALCOA & ALCOA-plus • Applicability to paper and electronic data • Data Integrity management governance • Quality culture & training • Quality risk management: How to apply QRM principles • Data lifecycle management • How to design and validate systems to assure Data Integrity • Quality auditsPart 2 – Implement and Maintain a Data Integrity Program • Data Integrity program focus and functional aspects • Risk management considerations (using ALCOA-plus model) • Data lifecycle elements and audit trail review

Knowledge ExchangeAttendees take part in a round-the-room Data Integrity “knowledge” check and identify their Data Integrity maturity level (before and after). Attendees identify challenges and potential strategies, following regulatory agencies expectations and industry practices.

Takeaway Tools • Example of a Data Integrity policy • Example of a Data Integrity governance plan • Example of an audit trail review standard • Generic process flow for data lifecycle approach: Executable template • Risk identification assessment template

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10:00 Networking Refreshment Break Select Between Knowledge Exchange Sessions (5-6) Implementation of Continued Process Verification in the Analytical LaboratoryAnthony Chikere, Sr. Mgr. Process Validation/Cleaning and CPV, Bayer HealthCare, Berkeley

Part 1 – CPV Key Concepts: Monitoring the Process vs. Monitoring the Methods • Analytical Methods: A key part of overall control strategy • Role of analytics in drug development • Parallel’s with drug product development • QbD approach to analytical methods • Lifecycle management of analytical procedures

Part 2 – CPV in Analytical Laboratory: Monitoring of Analytical Controls • Risk-based approach – Key to Effective Implementation • Monitoring and control of assay performance capability • Developing meaningful signals and escalation ruleli • Control charts for ongoing monitoring and control • Assay capability/transfer assessment • Instruments/equipment performance verification • Methods revalidation: When and why?

Knowledge ExchangeAttendees take part in a round-the-room survey of your company’s CPV strategy, experience and challenges and evaluate a baseline to where industry is (based on ISPE information).

Takeaway Tools • Analytical methods monitoring as part of CPV plan • Developing meaningful signaling and escalation rules • CPV signal assessment template • QbD considerations for analytical methods: FDA perspective

Master Your Laboratory Metrics Through Data IntegrityCarmen Medina, MPH, PhD(c), VP Techinical Services, PAREXEL International, Former FDA Investigator Metrics support sustainable commercialization and can provide a competitive edge throughout the establishment if effectively applied. But metrics are only as strong as the Data Integrity platform upon which they stand. PAREXEL’s innovative approach to integrating quality metrics with quality-centric lifecycle process validation permanently sharpens your focus around these two essential quality systems. This integrative model provides a cost-effective framework for enduring compliance and commercialization. This 90-minute session demonstrates the following:

I. An integrated approach to Data Integrity at each critical phase of lifecycle process validation II. The design and optimization of your PV program to ensure early risk detection related to process outputs and Data Integrity III. Essential components needed to integrate PV metrics to an enterprise-wide analytics platform IV. Elements of a 360º data feedback-loop for predictability, rapid accountability, targeted risk mitigation and continuous improvement

12:00 Focus Group Luncheons (7-8)

Advanced Analytical Professional Master Class

Eileen Cortes, Associate Director for QA and Validation,BioMarinThis master class is for senior-level professionals who have a deep understanding of analytical procedures and methods validation. The session is constructed from participants experiences in which key issues are addressed and best practices are exchanged: • What is your greatest regulatory concern? • What is your greatest challenge? • What innovative process or technology can you share with your peers?

Impact of Human Factors on Data Integrity LaboratoryNorman Fraley, Executive Director, Frolich Institute

• Understand the integrity threat • Identify the root of behavior • Know the roles of QA, management and personnel • Discover the key to an “integrity culture”

Select Between Knowledge Exchange Sessions (9-10) Development and Validation of a Stability–Indicating Analytical Method

Peju Odunusi, Group Leader, Stability, Abbott Vascular

Part 1 – Development of Stability-Indicating Methods • What is a stability-indicating method? • The importance of a stability-indicating method • Stage approach in developing an HPLC method • Challenges in developing a stability-indicating method • Stress testing and forced degradation as tools for validating stability indicating methods • Stress testing conditions for drug substance and drug product • Final optimization step of HPLC method development • Documentation practices

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Part 2 – Validation of Stability-Indicating Methods • Guidelines for analytical method validation • Phase appropriate method validation • Generating a validation protocol for registration submission • Validation parameters to satisfy stability indicating power of a method • Validation report documentation • Method transfer process and expectations

Knowledge ExchangeParticipants share ideas on how phase appropriate method validation was conducted on a finished product.

New Data Integrity Solutions for Old Laboratory EquipmentEric Collier, Discipline Lead Automation and IT, Commissioning Agents, Inc.

Part 1 - Data Integrity Requirements in the Laboratory Environment • Understand aspects of Data Integrity in lab systems • Discuss mechanisms of effective IT architecture • Maintain security updates and patches on isolated servers • Evaluate LIMS effectiveness and architecture • Evaluate how eNotebooks can interface to LIMS • Discuss elements of data historization • Resolve contextualized data to the manufacturing enterprise

Part 2 - Case Study of Laboratory Remediation for Data Integrity • Assess Data Integrity failure pathways • Review typical lab set ups and processes • Evaluate use of Security Information and Event Management (SIEM) tools • Resolve laboratory network profiles • Apply standards for laboratory system deployment • Apply network security profiles • Review cryptographical tools for one-off situations

Knowledge ExchangeAttendees participate in a lab equipment workshop to identify potential failure pathways and threats to existing laboratory equipment and apply session tools for comprehensive remediation strategies.

Takeaway Tools • Tools for Data Integrity assessment • Assessments for SIEM tool selection • Models for laboratory network architecture • Evaluation tools for lab network effectiveness • Templates for network qualification testing • Tool resources for encryption

2:45 Afternoon Refreshment Break


Statistics for the QC Scientist

Tara Scherder, Partner, SynoloStats LLC

Part 1 – Understanding Variability • Inference from a sample • Measuring uncertainty • Accuracy and precision • Total Error/USP 1210 • Practical vs. statistical difference

Part 2 – Match the Tool to the Application • Robustness: DOE • Root cause analysis: Exploratory data analysis • Stability: Regression • Robustness and root cause analysis: Variance component analysis • Ongoing method performance: Control charts • Comparison/transfer: Equivalence

Knowledge ExchangeAttendees evaluate statistical results from several case studies

Takeaway Tools • Expert answers to case studies • Presentation “Common Mistakes in Data Analysis”

Understand and Prevent Data Integrity Behavioral Non-ComplianceJay Chenier, Data Integrity Consultant, formerly, Process Owner, Global Computer Validation, GlaxoSmithKline Part 1 – What is Behavioral Non-Compliance? • An overview of behavioral non-compliance • Examples from laboratories • What are the sources of behavioral non-compliance? • How do people justify it?

Part 2 – How to Build a Culture of Positive Behaviors • Create the right environment • Start at the top • End the blame game – It’s about organizational learning • Big picture fixes for problems • Expect bumps in the road • This isn’t free, but what is the cost of not changing the culture?

Knowledge ExchangeTake an around the room survey of examples of behavioral non-compliance you’ve seen in your career (could be former job), and what was done to address the problem. Did it really fix the problem?

4:45 Close of Day Two

3:15 - 4:45

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Day Three – June 27, 20187:00 Coffee and Lite Breakfast Select Between Knowledge Exchange Breakfasts (13-14)

Lab Data Integrity - Risk Management Tools & TechniquesByron Mattingly, Ph.D., Software Division Chair, American Society for Quality

• Is a risk-based approach always the right one for controlling risk? • Understand a risk-based approach in the context of Lab Data Integrity • Quick overview of best practice risk management tools • Applying risk management tools and techniques for Data Integrity and Part 11 compliance • How risk management tools and techniques fit within an overall risk-based approach to lab Data Integrity

Advanced Data Integrity Master ClassJay Chenier, Data Integrity Consultant, formerly, Process Owner, Global Computer Validation, GlaxoSmithKlineThis master class is for senior-level professionals who have a deep understanding of laboratory data management. The session is constructed from participants experiences in which key issues are addressed and best practices are exchanged: • What is your greatest regulatory concern? • What is your greatest challenge? • What innovative process or technology can you share with your peers?


System Functionality Excellence via Suitability Tests and Acceptance CriteriaSteven S. Kuwahara, Ph.D., Principal Consultant, GXP BioTechnology, LLC.

Part 1 – Evaluating Test Methods • Define a suitability test • Method knowledge for choosing suitability tests • What constitutes excellence in suitability tests?Part 2 – Suitability Testing is not a Validation • Is it a control test? • Suitability tests must include the whole system • Examples for USP system suitability tests Part 3 – Determine the Acceptance Criteria for the System Suitability Tests • Be more stringent than the criteria for the test results • USP and other criteria • Setting your own criteria

Part 4 – Design a Complex of Tests • Usually a single test is not enough to define the suitability • What is the test system measuring and how do your tests define its quality? • Document the system suitability tests and their results • Monitoring for continuing verification

Takeaway ToolsCopy of the USP chromatography system suitability tests

Preparing for and Performing a Laboratory Data Integrity AuditSteve Thompson, Senior Manager, Professional Services, ValGenesis, Inc. – South San Francisco, CA

Part 1 – How to Prepare for a Laboratory Data Integrity Audit • Determine if you need to perform an audit • How to write an effective Audit Plan • What to do days/hours before the actual audit • Know what to take with you and what to not take • Gaining an understanding of the systems and data

Part 2 – How to Perform a Laboratory Data Integrity Audit • Assess a Quality Management System (QMS): What to look for • Learn what to ask for and how to ask for it • Methods to ensure requests are fulfilled • Tricks of the trade, techniques auditors use to audit • FRAUD, is a powerful word! • How to close an audit, and prepare for the next, if needed

Knowledge ExchangeAttendees share their own experience with planning and performing laboratory Data Integrity audits. Real-life examples are given of actual situations encountered during audits, from both an auditor’s perspective and situations encountered as an interviewee during an inspection.

Takeaway Tools • Laboratory Data Integrity audit preparation & planning checklist • High-level auditor playbook example

10:00 Mid-Morning Refreshment Break Select Between Knowledge Exchange Sessions (17-18)

Establishing Validation for an Analytical Method to Monitor Organic ImpuritiesKim Huynh-Ba, Executive Director, Pharmalytik Changes in the Active Pharmaceutical Ingredients (API) and drug products can cause an increase of organic impurities or formation of new impurities. Therefore, monitoring impurities are considered a critical activity to ensure the quality of the pharmaceutical products. This session discusses the establishment of a method validation to monitor these

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impurities. It also examines validation protocol and strategies for impurity analytical methods.

• Understand regulatory expectations surrounding impurities in API and Drug Products • Discuss deficiencies citations related to impurity controls • Design validation study for the analytical method • Determine acceptance criteria based on the new FDA policy • Discuss FDA, WHO, and USP initiatives on organic impurities

Implement Data Integrity Risk ManagementByron Mattingly, Ph.D., Software Division Chair, American Society for Quality

• What is analytical Data Integrity? • Understanding Data Integrity risk to data audit trails • Where do the greatest Data Integrity risks lie? • How “chain of custody” breaks down for analytical data flows • Why checkpoint manifests? • The importance of feedback mechanisms for controlling risk along interface boundaries • Using risk management tools and techniques to mitigate data integrity risk • Examples of risk-based thinking from a data integrity audit

Knowledge ExchangeAttendees leverage risk management tools and techniques as they apply to lab Data Integrity in the analytical lab.

Tangible Takeaways • Examples of using risk partitioning for simplifying chain of custody and data audit flows • Templates for risk management tools and techniques used in analytical labs for Data Integrity

12:00 Focus Group Luncheons (19-20)

Evaluate Analytical Validation Characteristics through Simple Statistical Analysis Junghae Scott, Director QC, Relypsa, Vifor Pharma Group Company

Part 1 – Analytical Validation Recap • Chemical method validation characteristics • Overview of ICH Q2(R1) Validation of Analytical Procedures: Text and Methodology

Part 2 – Statistical Evaluation of Validation Data as a Non-Statistician • Simple statistical analysis to evaluate validation characteristics • Overview of USP <1010> Analytical Data-Interpretation & Treatment • Lifecycle management of analytical procedures and validation • How to calculate and interpret the validation data

Knowledge ExchangeAttendees take part in discussing the challenges and industrial practices.

How to Use Cloud Computing in an Analytical Regulated EnvironmentJohn Hannon, Business Lead Automation and IT, Commissioning Agents, Inc.

Part 1 - Advantages of Cloud Computing Services Across the Enterprise • Understand types and definitions of cloud services • Discuss information requests to support audits, regulatory inspections and Data Integrity • Understand types of service level agreements • Evaluate security, data archival, backups and other regulatory related topics • Evaluate availability and fault tolerances • Understand cloud capabilities and cloud limitations

Part 2 - Case Study of Cloud-Based Enterprise Implementation • Assess models of cloud implementation for enterprise systems • Create a cloud-based virtual infrastructure and environments • Migrate validated data and maintain validation • Increase the user based and maintain licensing • Structure reporting tools across the enterprise • Use virtual desktops

Knowledge ExchangeAttendees participate in a short workshop to discuss potential enterprise applications and how they would be applied to cloud computing strategies.

Takeaway Tools • Policy elements for cloud computing use • Assessments for cloud provider selection • Models for cloud-based service level agreements • Information requests to support audits, regulatory inspections and Data Integrity • Templates for qualification testing of cloud-based applications • Tool resources for cloud-based application implementation

Select Between Knowledge Exchange Sessions(21-22)

Adopt a Systematic Approach for Method Robustness with Effective Design of Experiments (DoE)Tara Scherder, Partner, SynoloStats LLC & Katherine Giacoletti, Partner, SynoloStats LLC

Part 1 – Why use Statistical Design of Experiments? • USP <1220> Analytical Procedure Lifecycle & Analytical Target Profile (ATP) • Compliance and business benefits of DOE • Maximize information per experimental run • Reduce overall experimentation: Evaluate multiple

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analytical attributes in fewer experiments • Increase understanding of robustness factors on the method

Part 2 – Apply DOE to Method Robustness Studies • Robustness & QbD for analytical methods • Understand interactions: Factorial designs • Extending to more levels, more factors: Optimize and/or find robust ranges • DOE Planning • Modern DOE: More bang for your buck

Knowledge ExchangeAttendees work together on example DOE plans for robustness in development and validation.

Takeaway Tools • DOE planning handout • DOE phase of understanding map Cybersecurity, Data Integrity & Validation – Addressing Malicious Threats to the Life Science IndustrySteve Thompson, Senior Manager, Professional Services, ValGenesis, Inc. – South San Francisco, CA

Part 1 – Understand Malicious Threats and Attack Vectors • Learn how attackers attack from the outside • Once inside, understand their methods to maximize damage • Understand why they’re motivated to wreak havoc • Learn how Data Integrity can be jeopardized • Know the potential costs to your organization • Shed light on the dark side

Part 2 – How to Protect, Detect, and Remediate Attacks • Is protection futile? • What are the best ways to detect attacks? • Have I already been attacked and, if so, how do I know? • What do I do if there’s a breach • Does Validation secure and protect systems? • How can I successfully remediate an attack?

Knowledge ExchangeAttendees walk away with answers to the bulleted questions in Parts 1 and 2. An open-exchange allows attendees to share their experience with: A) Attacks encountered; B) Responses; C) Lessons learned.

Takeaway Tools • A cybersecurity check-list • A list of useful terms, definitions and resources

2:45 Afternoon Refreshment Break

Choose Between Knowledge Exchange Sessions (23-24)

Performance By Analyzing Samples from In-Process Through the Final ProductSteven S. Kuwahara, Ph.D., Principal Consultant, GXP BioTechnology

Part 1 – Validate All Testing Methods • There are validations and validations • In-process testing may require different test methods from final product testing • Demonstrate equivalence of test methods • Evaluate the process to determine what kind of testing is required • Raw material may be considered to be the first in-process materialPart 2 – . Are There any Regulations? • Talk to your regulator • In-process limits may be more relaxed than final product limits • What are the Critical Process Parameters and the Critical Quality Attributes?Part 3 – What About Process Analytical Technology (PAT)? • PAT may offer advantageous outcomes • ASTM Guidance • Analyze substances versus measuring parametersPart 4 – Setting Up the Measurement Points • How to predict product characteristics • Use a process monitoring system • Validate test methods and processes

Knowledge ExchangeAttendees review examples from warning letters.

Takaway Tools • Copy of the PAT guidance document • Excerpts from a paper on continuous QC in continuous processing

Data Integrity of Automated Laboratory Equipment and SystemsRashida Ray, President, Array Validation Quality and Compliance (AVQC), Inc.

Part 1 – Data Integrity: What Is It and What Is Expected of Us? • Paper vs. Electronic systems • Hybrid systems and how to handle them • The marriage of part 11/annex 11 • Data integrity shortfalls and challenges • Data integrity best practices

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Part 2 – Successful Implementation of Data Integrity in Protocols and Remediation Activities • Getting to know your system • Hacking the system: Getting everyone involved • Incorporate Data Integrity in procedures and quality systems • Incorporate Data Integrity into your test protocols • Data Integrity remediation • Resolving Data Integrity issues

Knowledge ExchangeAttendees take part in a mock Data Integrity remediation of a laboratory system

Tangible Takeaways • Templates for a Data Integrity assessment • Templates for a Part 11/Annex 11 assessment

4:30 Close of Conference

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For More Information Contact:John Kirchner, Executive DirectorPhone: 954 732 3663 (USA)Email: [email protected]

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