Module 12 Presentations

Module 12: Data Management and Digitalisation in Regulatory Affairs

Date: 31st January – 2nd February 2024 Module: 12 of the TOPRA MSc Data Management and Digitalisation in Regulatory Affairs Module Leader: Peter Embley

©The Organisation for Professionals in Regulatory Affairs 2023 Presentations are supplied to delegates for their personal reference and are the copyright of the speaker and The Organisation for Professionals in Regulatory Affairs. The presentations must not be copied, stored in a retrieval system or transmitted in any form without prior permission from TOPRA. Agreement must be reached with TOPRA before any part of this material is reproduced, abstracted, stored in a retrieval system or transmitted in any form by any means – that is, electronic, mechanical, photocopying, recording or otherwise.

Data Management and Data Governance

Presenters: Gill Penrose and Tabitha Sleap

Original Content Creation: Nancy Pire-Smerkanich, MS, DRSc

Assistant Professor, Department of Regulatory and Quality Sciences,

University of Southern California School of Pharmacy, USA

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AGENDA TOPICS

Data Governance

•

• Background, History and Legal Basis • Electronic Data Capture (EDC) • Data Input/Output • Data Querying • Data Management Plans

Data Standards

•

• Regulatory Involvement in Data Management and Data Governance (DM/DG)

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Data Governance

• Data governance is a term that is used for many industries on both a macro and a micro level. • The former is a political concept and forms part of international relations and Internet governance; the latter is a management concept and forms part of corporate governance

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Four Pillars of Data Governance

DATA GOVERNANCE

Data governance is necessary for compliance with current regulatory expectations for data integrity in pharmaceutical R&D and manufacturing organizations.

Data Stewardship

Data Management

Data Quality

Data Security

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Four Pillars of Data Governance

Data stewards implement policies in organizations with the goal of increasing data quality. Part of this implementation is “Master” and “Meta” data management which evolve based on new use cases and increasing amounts and types of data.

DATA GOVERNANCE

Data Stewardship

Data Quality

Data Management

Data Security

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Data Governance and Quality Systems

• Data governance policies have become a regulatory expectation as one of the core quality system policies. • It has been stated by the Medicines and Healthcare products Regulatory Agency (MHRA), European Medicines Agency (EMA), World Health Organization (WHO), Pharmaceutical Inspection Cooperation Scheme (PIC/S), and the Australian government’s Therapeutic Goods Administration (TGA) that a data governance system should be an integral part of the pharmaceutical quality system.

We will come back to this!

•

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Data Governance/Quality Systems

• Per the MHRA, a Data Governance system is the “ sum total of arrangements to ensure that data, irrespective of the format in which it is generated, is recorded, processed, retained, and used are complete, consistent, and accurate record throughout the data lifecycle” • Data integrity in Pharma is a key concept in our business. Per the FDA, Data Integrity “ refers to the completeness, consistency, and accuracy of data. Complete, consistent, and accurate data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA). • The European Medicines Agency (EMA) added another four items to round out the ALCOA concept – Complete, Consistent, Enduring and Available. This is referred to as ALCOA+

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Master Data Management (MDM)

Not unique to pharma

•

• MDM is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference • The data that is mastered may include reference data - the set of permissible values, and the analytical data that supports decision making.

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Master Vs. Meta

• Master Data (Gartner definition)

• Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts

• Metadata (Gartner definition)

• Metadata is information that describes various facets of an

information asset to improve its usability throughout its life cycle. It is metadata that turns information into an asset. Generally speaking, the more valuable the information asset, the more critical it is to manage the metadata about it…

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Critical Data

Various ways to “rank” – by amount, lifecycle, risk 1. GMP data – data related to product quality generated during manufacturing 2. GLP data – data from non-clinical studies and the basis of clinical development 3. GCP data – data from clinical studies , both pre and post marketing, including pharmacovigilance data

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Critical Data and Standards

1. GMP data – highly regulated but no data standards (excluding stability data – for now) 2. GLP data – CDISC SEND 3. GCP data – CDISC SDTM and ADaM

Let’s start with Data acquisition – specifically clinical data!

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Digitalized Data Acquisition

EDC : An electronic data capture (EDC) system is a computerized system designed for the collection of clinical data in electronic format for use mainly in human clinical trials .

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HISTORY OF EDC

• LONG (sometimes painful) history of what began as “ remote data entry ” (RDE)

• Began back in the 1980s when desktop computers came into existence

• Similar situation to US CANDAs where each study had its own computer and software • Computers placed at sites where data was entered by clinical study staff and then “sent” to sponsor or CRO • The industry assumed there would be HUGE benefits and accelerated drug development timelines

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Challenges OF EDC

• Poor acceptance at sites

• Change in process; perceived as more work for Study Coordinators

• Same data “cleanliness” issues existed

• RDE systems were not intuitive

• Glorified paper

• No time savings

• Time saved at the back end was lost in the front

• Technology in its infancy

• Not globally feasible

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HISTORY OF EDC

The next 10+ years were spent trying to address site interface and data cleaning methods • Educate Study Coordinators on process/responsibility • Programmed edit checks clean data upon entry • Real-time data entry/reporting was achieved Through the use of the internet, data entry at site became data capture for sponsor

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Efficiency of EDC

Over the last decade the use of EDC in clinical trials has become the norm, with the global EDC systems market valued at $1.25 BN in 2022 with a predicted CAGR of 14.6% to 2030 • In the US the ACA (2010) mandated electronic health records so hospitals were forced to move into all electronic systems • This has not become an automatic or automated data integration but did facilitate eProcessing • The UK and Europe do not yet have such consistency in mandate

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Data Input/Output Front end: Templated CRF Design • Information captured during most, if not all, studies • (Demographics, Med History, Phys. Exam, Vitals, etc.)

• Submission-ready eCRFs • Time savings of WEEKS ! Middle: Data cleaning/reports • Real-time querying • Decision making • Preliminary report/table output Back end: Regulatory Deliverables for countries that require them • CDISC Compliant Datasets

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Efficiencies achieved

• EDC cuts 41% of pre-study preparation time in comparison to using paper CRFs • Use of “standardized” and submission focused eCRFs saves time on both ends of the process • Overall EDC saves on average 30% of the time it takes to conduct a clinical trial • Use of extensive edit checks prevent many incorrect data points from being entered

• Querying can focus on data inconsistencies and missing data programmatically

This is an area where ML/AI will have an impact (Day 3)

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Efficiencies achieved

• Integration with other systems can occur • IRT for efficient randomization • Extraction from electronic health records • Real-time output for analytics (e.g. adaptive designed trials) • Clinical Trial Management Systems (CTMS) which are designed for operational use in clinical trial planning, preparation, performance and reporting.

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BIG Business - Example

• Medidata acquired by Dassault Systèmes for $5.8 billion • Medidata's cloud-based services (data capture and advanced analytics) help with the development of therapeutic innovations and clinical operations performance for pharmaceutical companies, biotechnology firms and others Jun 13, 2019

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New Problems Emerge

• As a result of new technologies and innovations and electronic record keeping, the volume of information collected before, during and after the clinical trials continues to grow

• LARGE amounts of data, sometimes continuously •

Note: Lab data such as EEG, ECG or imaging data is not captured in an eCRF – this is imported using a different methodology and requires data reconciliation

• So, comprehensive data collection and efficient management is now becoming a priority for pharmaceutical companies and clinical research organizations (CROs)

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• The Data Management Plan(DMP) is written to define and document the data management tasks, responsibilities, and deliverables for each clinical trial • The DMP allows the company to proactively assess and plan for the study-specific data management processes, from the receipt of the Case Report Form (CRF) to the study file archiving • The DMP is based on the clinical trial protocol , the CRF , and the CRF instructions and where available , the Statistical Analysis Plan Data Management Planning and Plans (DMP)

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Data Management Plans

• Addressed in multiple US Guidance documents: • Related to Electronic Source Data • Risk Based Monitoring,

AND

• US Dept of HHS, Office of Research Integrity which funds NIH-funded studies addresses data integrity during research process ICH E6, 8 and 9 also highlight the need for responsible Data Management and data integrity

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Data Integrity

From WHO Technical Report Series No. 996: • Increased observations made regarding good data and record management practices (GDRP) during inspections: • Good manufacturing practice (GMP) • Good clinical practice (GCP) • Good laboratory practice (GLP) regarding data reliability are undoubtedly multifactorial • FDA 21 CFR Part 11 was introduced to ensure data traceability and integrity for electronic records and signatures. All systems used for collecting data during a trial need to comply with this rule

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Data Integrity - Manufacturing

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Data Integrity - Clinical

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Data Integrity Issues

• Failures by organizations to apply robust systems that inhibit data risks, to improve the detection of situations where data reliability may be compromised • Lack of adequate investigation and remediation of root causes when failures do arise For example: • Validated computerized systems but fail to adequately review and manage original electronic records • Often only review and manage incomplete and/or inappropriate printouts

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Transition by international regulators/Industry to structured content/structured authoring • Supports more efficient and effective regulatory review • Supports regulatory science initiatives • Data integrity • Pharmacovigilance (signal detection) • Quality metrics • Risk based inspection scheduling • Mitigate drug shortages • Real World Data/Evidence • In support of benefit/risk assessment Data REALLY Matters!

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Per EMA Data Integrity Guidance (2016) • Data integrity enables good decision-making by pharmaceutical manufacturers and regulatory authorities. • Fundamental requirement of the pharmaceutical quality system described in EU GMP chapter 1 • Applying equally to manual (paper) and electronic systems • “The effort and resource assigned to data integrity measures should be commensurate with the risk to product quality ( risk mitigation )” Data Integrity: Key to Public Health Protection

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• Per Medicines & Healthcare products Regulatory Agency (MHRA)- ‘GXP’ Data Integrity Guidance covers principles of data integrity (ALCOA) • Aims to promote a risk-based approach to data management that includes data risk, criticality and lifecycle. (ICH-E6) • Data processes (as a lifecycle) to identify data with the greatest GXP impact to determine the most effective and efficient risk-based control for data review and implementation Data Integrity: Key to Public Health Protection

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Data Integrity: Key to Public Health Protection

Per Guidance for Industry: Data Integrity and Compliance with CGMP

• FDA has increasingly observed cGMP violations involving data integrity during cGMP inspections • Data integrity-related cGMP violations have led to numerous regulatory actions: • Warning letters • Import alerts • Consent decrees

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Data Integrity and Use of Quality Metrics

• Quality metrics are used throughout the pharmaceutical industry: • Monitor quality control systems and processes • Continuous improvement efforts in drug manufacturing • Metrics can also be used by regulators for the following: • Compliance and inspection policies and practices • Risk-based inspection scheduling of drug manufacturers • Improve the ability to predict and possibly mitigate future drug shortages; • Encourage Industry to implement state-of-the-art , innovative quality management systems for pharmaceutical processes

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Data Standard

• A data standard is a set of rules on how a particular type of data should be structured, defined, formatted, or exchanged between computer systems • There are standards for everything, from how blood pressure is collected, to how regulatory materials are submitted electronically to FDA

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“The nice thing about standards is that there are so many of them to choose from.”

-Andrew S. Tannebaum

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The State of Data and Standards Regulatory World View

SPOR Iterative approach to IDMP Falsified Medicines

Structured Product Monograph – SPL Format Utilizing IDMP Data Elements Regulatory Enrolment Process – SPL Format aligning with IDMP Data Elements (future state) eCTD v3.2.2. v4

Directive (FMD) Cross border e Prescriptions Article 81-EU CT Regulation SPOR/IDMP

PQ/CMC ICSR CDISC Activities Medical Device UDI eCTD v4 *IDMP – Federal Notice*

Medical Device (UDI) ICSR FMD IDMP/SPOR

Data Standards as a Global Issue (Ref: VPerkins)

When no Common and Harmonized Data Standards Approach Exists…

• There is no possibility to exchange medicinal product information between regulatory authorities and pharmaceutical industry in a structured and efficient way • Difficulties in ensuring data consistency in evaluating and comparing medicinal product related information across regions, due to the lack of harmonized definitions of terminologies and data sets • Administrative burdens and duplication of efforts requiring substantial human and financial resources to comply with, and handle, different regional requirements

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Benefits of Government Working with Standards Development Organizations

• Input from international experts : Availability of many experts from various disciplines and countries • Supports regulation/guidance development • Governments can make standards a regulatory requirement • Can result in reduced costs for both private and government entities • More efficient operations • Safety

World trade • Provides harmonized import/export requirements • Goods, services, technologies

•

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Joint Initiative Council on SDO Global Health Informatics Standardization

Formed to enable common, timely health informatics standards by addressing and resolving issues of gaps, overlaps, and counterproductive standardization efforts through: • A mutually agreed-upon and used decision process for international standardization needs • Coordinated standards strategies and plans, with the future goal of making all standards available through ISO • An integrated work program • Focused, specific resolution of overlapping or counteracting standards within the participating SDOs existing work programs

Reference: http://www.jointinitiativecouncil.org/

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FDA Involvement with Data Standards Development Organizations (SDOs)

• International Organization for Standardization (ISO) • Identification of Medicinal Products (IDMP) • Individual Case Safety Reports (ICSR)

Health Level Seven (HL7) • Structured Product Labeling (HL7 SPL) • Common Product Model (HL7 CPM) CDISC • Study Data Tabulation Model (SDTM) • Analysis Data Model (ADaM)

•

•

• International Conference on Harmonisation (ICH) • MedDRA

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FDA Data Standards Strategy & Action Plan

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FDA’s Data Standards Program – Goals

• Support open, consensus-based data standards development

• Utilize a well-defined data standards governance function

• Promote electronic submission of standardized data for regulatory review

• Optimize the regulatory review process to fully leverage standardized data

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Legal Basis: FDA Safety and Innovation Act (FDASIA) of 2012

Section 1136: Allows FDA to require standardized fully electronic submissions related to marketing applications

• Twenty-four (24) months after publication of the final guidance: New Drug Applications (NDAs) and Biologics License Applications (BLAs) • Thirty-six (36) months after publication of the final guidance: All original commercial Investigational New Drug Applications (INDs)

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Most basic “standard” - XML

XML = Extensible Markup Language

XML currently being used in the following ways: • Current uses • Labeling documents (SPL)

• Data Definition Files (DDT) for CDISC SDTM and ADaM data • eCTD Backbones (M1 and M2-M5) • Future Uses • RPS bi-lateral communication (maybe someday) • Clinical protocols (ICH WG)

43

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Communication Processed by RA then disseminated to systems

G-SRS

Molecule Data

API Discovery

Regulatory Affairs/Strategy

Regulatory Data Lifecycle (V. Perkins, Bayer)

SmPC

Specs

Scientific Content Created

RIM

Company Core Data Sheet (CCDS)

USPI

CMC

Labeling

Pre-Clin Clinical

ESG Regulatory Agency

Sponsor

Regulatory Operations

DMS/SharePoint/Fileshare

Compile Dossiers For Submission

Legal

Quality

Supply Chain

Pharmacovigilance

R/B Evaluation

Communications back to Sponsor

Decisions

Assess Content

Use Content for Reports and Correspondence

Evaluation of Product Info (Ad/Promo, Claims

Distribute to Functional Reviewers

ESG Regulatory Agency

Data for Customs or Market Regulators

Regulator

Populate Agency Databases

Validate

Data Needed for Inspectorates

Application Submission Received

Parse & Assign To Appropriate Division

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Regulatory Data Lifecycle (V. Perkins, Bayer)

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Key Takeaways

• The world of data standards, management & governance is continually evolving

• Standardisation allows harmonisation AND flexibility

• Data Management & Standards, Data governance and appropriate Data Literacy are key to data integrity, quality and patient safety. These principals are fundamental in responsible pharmaceutical drug development

THANK YOU!

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Acronym List

Acronym

Meaning

Acronym

Meaning

Medical Device UDI

Medical Device Unique Device Identifier

ADaM

Analysis Data Model

ALCOA

Attributable, Legible, Contemporaneous, Original, Accurate Computer Assisted New Drug Application Clinical Data Acquisition Standards Harmonization Clinical Data Interchange Standards Consortium

NIH

National Institutes of Health

CANDA CDASH CDISC

OOS

Out of Specification

PQ/CMC

Pharmaceutical Quality/Chemistry Manufacturing and Control

cGMP CRF CRO DMP eCRF eCTD GDRP GLP GMP GXP ICSR IDMP FMD GCP

current Good Manufacturing Practice

RDE

Remote Data Entry

Case Report Form

SDTM

Study Data Tabulation Model

Contract Research Organisation

SEND

Standard for Exchange of Non-clinical Data

Data Management Plan

SPL

Structured Product Labeling

electronic Case Report Form

electronic Common Technical Document

SPOR Substance, Product, Organisations and Referentials US Dept of HHS US Department of Health and Human Services

Falsified Medicines Directive

Good Clinical Practice

Good Data and Record management Practice

Good Laboratory Practice Good Manufacturing Practice

Good Practice quality guidelines and regulations

Individual Case Safety Report Identification of Medicinal Products

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Lecture 2: Regulatory Information, Intelligence & Knowledge Management

Dennie van de Voort, MSc

Amy Williams

Jr. Manager - Deloitte

Director - Deloitte

13.00 – 14.15

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Agenda

1. Introduction & Learning objectives

2. Regulatory Information Management (RIM) : An Introduction

3. RIM System Capabilities

4. Regulatory Information Intelligence

5. Knowledge management

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Welcome & Learning objectives

Today you will learn more about:

✓ RIMS and Capabilities ✓ Typical stakeholders working with RIMS ✓ Trends in the market

✓ Staying up to date on latest Regulatory Intelligence ✓ How to ensure Knowledge Transfer and Management

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Regulatory Information Management (RIM) : An Introduction

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Evolution of Regulatory Information Management

The future

The present

The past

RIM Capabilities: ePI SCA eSubmissions

RIM Capabilities: eCTD PSUR Variations

Excel: Registration Information

Today

Manual

xEVMPD

ISO IDMP

Manual re-work Event Driven Process

Integrations Data Driven Process

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5

What is Regulatory Information Management (RIM)?

The effective and efficient identification, collection, communication and management of regulatory information for products (in a centralized system)

The planning and reporting of global and local regulatory activity so as to synchronize efforts for maximum efficiency of enterprise regulatory resources

The tracking of product registrations , content and other meta-information for regulated products in a global enterprise to better enable decision making about product portfolios

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Regulatory Information Management System (RIMS)

The Regulatory Information Management System (RIMS) is one central location that contains all regulatory data and documents required for regulatory activities & compliance.

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Overview of RIMS and its benefits

Why is it important?

What are the benefits?

How does this apply?

✓ Decreased compliance risks ✓ Efficient use of data, authoring and submissions ✓ Immediate access to real-time information ✓ Reduced manual efforts ✓ Tracking of Health Authority communications ✓ Tracking of submission timelines and performances ✓ Accelerated time to market ✓ Improved internal communication and reporting

Compliance: Implementation of data standards (e.g. ISO IDMP) Controlled vocabularies to adhere to standards Product data quality: Re-usage of data from one central location Controlled vocabularies for uniform internal terminologies Quality of internal processes: All regulatory content in one location Streamlined E2E regulatory processes

Impacts all stakeholders involved in E2E regulatory process ✓ Contributing along the submission process ✓ From authoring, editing to approval of regulatory content

✓ Involves all activities

related to planning and tracking of submissions and post-marketing activities

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Regulatory data throughout the product lifecycle

Regulatory data is captured throughout the life cycle of a product. Data captured during the pre clinical and Clinical phases is tracked in detail within eTMFs and Clinical Data Management solutions. Data is typically tracked in a RIM once a product is being prepared for Marketing Authorisation Applications. Once a product is commercial , capturing the details of what is approved and where is critical for patient safety and all life cycle maintenance activities are planned and tracked via a RIMS

High-level life cycle of product master data

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RIMS in the System landscape (example)

xEVMPD

EMA SPOR

EC Union Register of medicinal products for human use

EMA

PV

Source

LIMS

CC QualityDocs

Internal systems

RIMS

ERP

SmPC eAF

Serialization

Dossier

External CMOs

Other external sources

Distribution partners

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RIM System Capabilities

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End-to-end regulatory process usually managed in RIMS

End-to-end process

Implement change

Prepare dataset

Track & process of 3 rd acknowledgem ents

Update Registration details

Define submission plan

Submit IDMP & dossier to HA

Review, update and finalize submission plan

HA decision

Submit xEVMPD data

Author content

Publish

Plan content

Change

Stakeholders involved

Pitfalls to avoid

Key Takeaways

• Start from top to bottom: high-level processes with a clear goal and outcome and then drill down to the details • Document the process, dependencies, sources of information, roles and responsibilities

Regulatory Operations

• Focus too early in the process design on the details and roles and responsibilities

•

Regulatory CMC

•

Overcomplicating the process which results in unnecessary lengthy and inefficient processes

•

Labeling

•

Regulatory Strategy / Submission Managers

•

Neglecting stakeholder involvement

•

Quality Affairs

•

Agree with all stakeholders involved!

•

Ignoring continuous improvement

•

• Data Governance Committee / Members

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Regulatory information throughout the product lifecycle

Technology

Submission Planning & Tracking

Dossier Planning & Strategy

R&D

Clinical

Health Authority Interaction

Submission Forecasting

Registration Management

Release

Publishing

Submission

Manufacturing

Pharmaco vigilance

Regulatory Affairs

Pharmaco vigilance

Regulators

Manufacturing

Clinical Pharmacovigila nce

R&D

Manufacturing

Labeling

Platform : Most of the core RIM capabilities are available in platforms, but several years away from mature publishing and label compliance tracking capabilities that can compete with the best-of-breed providers

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Typical layers of information within RIMS

Product

Registrations

Variation/Event

Authoring/publishing

Submission

Query and reporting

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RIM System Capabilities overview

• Submission forecasting & Resource planning • Dossier management • Submission management: assemble publish QC • Product registration management • Health Authority commitments and interactions • Archiving • Labeling Management (content & compliance) • Reporting, Dashboards, Analytics • Data Standards & Data Governance • Regulatory intelligence • Ad / promotions

Product Change Control to ensure alignment with

Supply Chain Clinical Pharmacovigilance Product Release Labeling / Artwork Vendors Manufacturing Etc.

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Example: RIMS Reporting Capability

The reporting of data of a RIM system can help departments with decision making. It creates an overview of the current situation of regulatory data, and allows for further analysis (e.g., Are we on track? What is currently on the market?)

RIMS data

Variation

Status

Status date Status due date

Variation 1 NL

Approved

20/12/2023 01/01/2025

Variation 2 US

Submitted

21/04/2023 01/04/2024

Variation 3 GB

Submitted

05/08/2023 16/12/2024

Variation 4 EU

Planned

05/01/2023 07/05/2024

Other Reporting examples: 1) PSURs (e.g. due date/expiration) 2) Data quality (e.g. indications) 3) Overviews of all active registrations 4) WWMA reporting 5) Manufacturers (deadline)

Report

What Event/Variation is due?

• • •

Which are too late?

Which one is approved?

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But there is more to consider than Technology (Systems) only

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Successful regulatory information management

Successful regulatory information management is more than using a system (technology). Processes, information and organization are impacted.

PROCESSES INFORMATION ORGANIZATION

What is the Data Governance (DG) framework for your processes and data management?

What data / documents are required for you defined RIMS scope?

How do you want to use your RIMS from a business perspective?

PROCESSES

INFORMATION

What is the quality of this data (e.g. aligned to IDMP data standards)?

How will the DG framework be rolled-out in alignment with process implementation

Which processes are in scope?

TECHNOLOGY

What is the strategy for process implementation?

What data will you need for your submissions, is the current quality sufficient?

What is the change management strategy?

EXAMPLE: eAF variation submission

ORGANIZATION

Who is responsible to manage and ensure high quality compliant data?

When will you start using RIMS for regulatory data creation?

What eAF structured data must be maintained within your RIMS?

Successful regulatory information management is only possible in case all POTI aspects are considered

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RIM as an accelerator to work with a more data-driven approach: The document management process will change

Operational Systems

Documents

Data Source

RA

RIMS

Now

Data

PV

Safety Database

Manual

MNF

ERP

Source Systems

Documents

Data Source

RA

RIMS

Future

Data

PV

Safety Database

Automated - SCA

ERP

MNF

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Example Use Case 1: Using RIMS data to submit Registration information - as data

• Regulatory information required for submission is generated from RIMS Examples: • Cover letter • Application form • Annexes to Application Form • eCTD envelope

• Gateway delivery file • Module 3 information

Regulatory approval

M3

authority review

eAF

• Regulator can import data into their systems

• Exchange of information automated in future • Validation • List of Questions • Approval

CTD documents

eCTD submission

< > < > < >

A pproved CC

RIMS

structured data file

structured authoring

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Example Use Case 2: Data driven Labeling utilizing structured data from RIMS

RIMS data fields Composition data in RIMS database

SmPC

Module 3

SPL

=active substance ≠active substance

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Current challenges in Regulatory Information Management

Historically, regulatory information has been managed in a multitude of systems, file shares, and/or intranet sites across the global, regional and local regulatory organizations. As a consequence, getting a global overview of key regulatory information and data has been a significant industry challenge . Challenges are also a result of low efficiency for data standards, governance management, dossier management as well as report and analytics.

7. Data quality

1. Staying current

RIMS

2. High administrative burden

6. Data governance

3. Manual and repetitive work

5. Disparate, aging systems

4. Breaking down silos

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Current challenges in Regulatory Information Management

Having RIM data as the core data set of business processes forces the data to be current, decreases administrative burden and can break down departmental silos. To use RIM data, the data needs to be of high quality – making data governance an important part of RIMS

7. Data quality Quality control Data remediation

1. Staying current RIM data as core of business processes

RIMS

2. High administrative burden Prevent repetition of data by using RIM as source

6. Data governance Dedicated roles Data standardization

3. Manual and repetitive work Automate workflows

5. Disparate, aging systems Move towards E2E solutions

4. Breaking down silos Connecting systems (& departments). Use RIMS as golden source

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Differences in RIMS throughout the market

Pharmaceutical companies are shifting from a silo-based approach of their data to a connected system infrastructure. This is either done via an end to end (E2E) RIM solution or by connecting best of breed systems .

Best of breeds

E2E RIM solution

Vendor x

Vendor a

PV

PV

Vendor e

Vendor b

Simplified integration Simplified purchasing

•

Best systems on the market

•

DM S

DM S

Clinical

•

Clinical

RIMS

Integration can be more complex

•

Manu facturing

Vendor d

Vendor c

QMS

Not necessarily best systems on market Vendor lock-in

•

More complex purchasing

•

Manu facturi ng

RIMS

QMS

•

The Organisation for Professionals in Regulatory Affairs

Trends in the market for regulatory information management

Organizational processes

01

Increases in RIM performance status

▪ Maximalization of RIM system benefits (mid, large companies) ▪ RIM system/process simplifications

Increased industry focus on implementing data quality practices and cross functional data governance strategies.

Regulatory initiatives

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Increase data quality of authoritative sources Access to real-time information Redefining and clarifying roles and responsibilities SPOR/IDMP/DADI planning and implementation Data Submissions (small companies) Introduction of the eCTD 4.0 (projects within 2 years)

02

Shift in RIM team focus

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Data Governance

03

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Data Governance in early adoption

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Change management

04

Challenges in change management

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Cross-functional process integration Improved information exchange

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Reduction of operational complexity

The Organisation for Professionals in Regulatory Affairs

Regulatory Information Intelligence

The Organisation for Professionals in Regulatory Affairs

Regulatory Intelligence

• Regulatory intelligence is gathering and analyzing publicly available regulatory information o Including, communicating the implications and monitoring the current regulatory environment for opportunities to shape future regulations, guidance, policy, and legislations

Health Authority strategy & roadmaps

Organizational changes

Regulations

Policymaking

Competitor developments

Technology developments

Competitor developments

Impact assessment

The Organisation for Professionals in Regulatory Affairs

Regulatory Intelligence impact assessment

• Incoming Regulatory Intelligence requires an effective organizational impact assessment :

• By a dedicated Team or department (usually larger Companies)

• Incorporated in an existing role (usually small/medium companies)

• By use of dedicated technology for Reg. Intel monitoring

• Provided by a dedicated outsourcing partner

• Key to bring in the right experts that understand Global and Local implications, classify the relevance and ensure that the right people are informed and involved • All aspects need to be considered for Regulatory impact assessments: Process, Organization, Information and Technology

The Organisation for Professionals in Regulatory Affairs

Typical example sources to be monitored

• Health Authority websites (such as EMA, FDA, Swiss Medic, etc.) to monitor updates in regulatory Requirements and latest developments

• Global drug dictionaries from WHO-UMC

• IRISS forum, UNICOM and Industry roundtables

• Technology vendors developing Reg. Intel. tooling (e.g., in RIMS)

• Newsletters from different Regulatory sources

• External Industry/Health Authority Working Groups (e.g. International Council for Harmonization (ICH))

The Organisation for Professionals in Regulatory Affairs

Regulatory Intelligence technology capabilities

Typical technology / supporting systems:

• Can monitor hundreds of regulatory sources globally, to integrate with your existing processes and systems and notify you of information that might impact your organization • Have Automated feeds that can be tailored based on business conducted and the applicable jurisdictions/regions • Provide a central repository of global regulations clustered by topic and regulatory initiative • Establish connections between related publications & applicability of regulations for your Organization

• Map regulatory obligations to internal controls, policies, and processes.

The Organisation for Professionals in Regulatory Affairs

Knowledge management

The Organisation for Professionals in Regulatory Affairs

Knowledge management

Knowledge Management is a process that involves the identification, selection, organization, and distribution of information and expertise within an organization. Its main goal is to improve efficiency by reducing the need to rediscover knowledge.

This can be broken down into four elements stages:

1. Creation - where new knowledge is generated or picked up from (e.g., Reg. Intel)

2. Storage - where knowledge is captured and stored in a structured manner

3. Distribution - where knowledge is shared and disseminated throughout the organization 4. Application - where the shared knowledge is used and applied in decision making or problem solving

The Organisation for Professionals in Regulatory Affairs

Goals of knowledge management

• Knowledge retention to mitigate risk of losing key knowledge when employees leave the company.

• Ensure that the right persons receive the right information

Enable Global ways of working

•

• Reduce department silos to ensure knowledge and best practice transfers

• Foster Innovation by facilitating the exchange of ideas, which can lead to new products, services, or improvements in existing processes

• Strengthening market position: knowledge management can help organizations understand their market better, anticipate to changes, and respond swiftly to patient needs

The Organisation for Professionals in Regulatory Affairs

Knowledge management - Approaches

• Knowledge that resides in the minds of employees, which is often gained through personal experience and is difficult to document: • Communities of Practice: These are groups of people who share a craft profession, facilitate the sharing through regular interaction and discussion • Storytelling: Transferring knowledge in an easily digestible and relatable format • Explicit Knowledge meaning knowledge that can be documented, stored, and shared: • Documentation: Creating manuals, guides, procedures, and rules that are easily accessible to all employees. • Databases and Knowledge Repositories: Creating a centralized system where knowledge is stored and can be searched and accessed • Best Practices and Lessons Learned: Establishing structured processes to capture and share lessons learned from projects or other activities. • Mentorship Programs: Experienced staff members share with less experienced

The Organisation for Professionals in Regulatory Affairs

There will always be changes in Regulatory Intelligence & Knowledge, this requires Organization Change Management

The Organisation for Professionals in Regulatory Affairs

Knowledge Management and Reg. Intelligence require continues changes in processes, systems, and culture within an organization. Effective change management is crucial: The need for Change Management

Objectives

Guiding Principles

Leverage Existing Channels

Align to Program Outcomes The messaging and engagement with stakeholders will be rooted in the key program outcomes. Timely & Targeted Communications will be specific and targeted. They will be delivered in a timely manner in conjunction with key milestones.

Wherever possible, existing communication channels and preferred methods of communication for stakeholder groups will be used. Simple & Concise Communications will be simple and concise so that the audiences can easily grasp and understand the key messages. Demonstrate Leadership Support Where possible, executive leadership will be engaged to visibly demonstrate a commitment to the Change and directly engage leadership by reinforcing key messages

Create Awareness Create broad awareness of the changes to the organization to ensure employees feel included in the key activities within their company

1

Generate Understanding Generate clear understanding of the main objectives, goals, and timeline to key stakeholders when and where necessary

2

Demonstrate Change Empathy

Impacts will be communicated with sensitivity. Incl. being cognizant of how the audience of the messages will perceive the content, especially when impacts affect the day-to-day functions of their role.

Promote Acceptance & Commitment Promote acceptance and commitment among significantly impacted or influential stakeholders when and where necessary

3

The Organisation for Professionals in Regulatory Affairs

Change Management Communications Development Process

Understand the Audience Identify and define Stakeholder groups who will be directly or indirectly impacted by the change Assess and document the impact across stakeholder groups and define change readiness per function.

Understand Communication Vehicles

Plan Communications

Execute the Communication Plan

✓

✓

Develop and review communications

Forecast high-level communications activities throughout the initial phase of the project

Identify the existing communication channels within your organisation (enterprise and functional-level) that will serve as the most effective and appropriate platforms for disseminating communications

✓

Facilitate and deliver communications according to plan Refine communications based on understanding of stakeholders’ needs

✓

✓

The Organisation for Professionals in Regulatory Affairs

In Conclusion

✓ RIMS is one central location containing all regulatory data and documents required for regulatory activities & compliance

✓ Technology and business drive current transition into more mature RIM systems

✓ Reg. Intel. & Knowledge

management are important topics to be addressed within every Organization and require effective Change Management practices

and will work towards a more data-driven way of working

The Organisation for Professionals in Regulatory Affairs

What has been covered in this lecture

Learning Objectives

✓ RIMS and Capabilities ✓ Typical stakeholders working with RIMS ✓ Trends in the market

✓ Staying up to date on latest Regulatory Intelligence ✓ How to ensure Knowledge Transfer and Management

The Organisation for Professionals in Regulatory Affairs

Lecture 3: Technical Specifications and Compliance

Dennie van de Voort

Dorien de Vries

Jr. Manager - Deloitte

Senior Consultant -Deloitte

14.30-16.00

The Organisation for Professionals in Regulatory Affairs The Organisationfor

Professionals in Regulatory Affairs