Technology Innovations Driving Transformation in Regulatory · Validated Data - Pharmaceuticals “without complete, accurate, reliable, or retrievable raw data about the HPLC system’s

Copyright ©2020 Version 1. All rights reserved.1

“The Regulatory Analytics: Stories of Technology Innovations Driving Transformation in Regulatory

Compliance”

January 29th | Republic of Work, Cork


Lorcan Malone | Chief Executive

INSPIRE EVENT with Wednesday, 29th January 2020


Questions – Slido.com #Inspire2020

Alan Crowley – Head of Delivery

Version 1


Speakers

Karl O’ConnellHead on Integration

ICBF

Michael PhelanBusiness Technology Leader in Data Science

Johnson & Johnson

David Hawe Data Scientist

Cork Institute of Technology


Decision Science

Michael Phelan – Business

Technology Leader in Data Science

Johnson & Johnson

CONFIDENTIAL AND PROPRIETARY

SUPPLY CHAIN

BUSINESS

TECHNOLOGY

Labels, Flow & DNA

Observations from a Regulated Industry

LABELS

7

DECISION SCIENCE

AI (ML / NN / RL)BI / DashboardsSoftware Eng / APIs

Developing intuitive

Decision Support Solutions

helping decision makers take

Action from Data driven Insights

many career

opportunities

in AI

Data

Scientist

Data

Engineer

Data

Architect

Business

Analyst

Software

Engineer

Solutions

Architect

Citizen

Data

Scientist

B u s i n e s s

O p p o r t u n i t y

AI LABELS

FLOW

SCBT – Research Design & Engineering

DECISION FLOW - Solution Components

11

DATA

ETL, Storage

COMPUTE

Cognitive Services,

ML Models, AI, Simulation

CONSUME

API, RPA, Visualise


DECISION FLOW - Customer Experience

12

RA

W T

EX

T

SQL

noSQL

Translate to English

Intent, Entity &

Sentiment Analysis

NLP

pre-processing

ML Classification

Phone

Email

Fax

Move to folder /

label email

Dashboard

RPA

Speech

to Text

Analogue

to Digital

Attachments

Data is unlike any other

asset

It never depletes

It never wears out

Same data used across unlimited

use-cases at near zero marginal cost

Bill Schmarzo, CTO Hitachi Vantara


Adopting an AGILE APP-Based Approach

14

PARTNER

Active customer

engagement & ownership

PRODUCTION

• Asking the right question?

• Quality impacts (CSV)?

• Business support / ROI

QUESTION

• PoC App based solution

(1 Question = 1 App)

• Limited data sources

• no automation or integration

• 3-4 sprints


Agile Decision ScienceWhat is the Question?

Failure is good!

What’s the business

impact?

DNA

DNA


What is a Data Attribute?

Example: 1 Excel Workbook = 1 ERP

17

• Worksheets = ERP tables – (e.g., vbak, vbup, vbkd, vbuk, vbap etc.)

• Columns of each sheet = EPR Attributes– (e.g., abdis, abhob, abhod, abhov, etc.)

• Rows of data = potential information!

• Identify the data attributes that explain an organisation!

Tables

Attributes


FLOW and REUSE of an Attribute

18

Example: data initially collected for ERP (L4) & MES (L3) systems

PROFILE: type of data, dispersion, ranges, categorical etc.

BI: individual or blended attributes (rule based business logic)

AI: model features – individual or synthetically blended combinations

Curation: NLP semantic mapping with internal / external data sources

Explore non-linear relationships (e.g. MES product flow in Graph DB’s)RPA

vbak.aedat

vbak.abdis

Ensure most

important attributes

are always captured

accurately


Active customer engagement

& collaboration

What is the Question?

Solutions Focused

App – Based, Agile Releases

Create Reusable Flows


Management of Validated Data

David Hawe – Data Scientist

Cork Institute of Technology

mathematics.cit.ie

Management of Validated Data

David Hawe [email protected]

Department of Mathematics @CIT

• .

Data Lifecycle

Data Lifecycle

Data Lifecycle

Data Lifecycle

“Data validation … ensures the correspondence of the final (published) data with a number of quality characteristics.”

(Simon 2013)

Validated Data - Finance

“Data validation … ensures the correspondence of the final (published) data with a number of quality characteristics.”

(Simon 2013)

• Some Examples:• Name: \18• Date of Birth: 14/01/1888• Salutation and gender

Validated Data - Finance

https://govzilla.com/blog/2019/05/pharma-medical-devices-data-integrity-breaking-down-keywords-and-citation-trends-from-the-fda/

Validated Data - Pharmaceuticals


“without complete, accurate, reliable, or retrievable raw data about the HPLC system’s qualification, you lacked complete assurance that the system was operating as intended” (FDA issued 483 in 2015)

ScientificData

MgmtSystem

Data Lake/Warehouse

LaboratoryInformationMgmtSystem

Standalone Instruments

Electronic Laboratory Notebooks

Distributed Control

System/ Historian

Enterprise Resource Planning

Paper/Paper on

glass

Other Systems

The boring stuff:• Accurate - Legible - Contemporaneous - Original

Attributable - Complete - Consistent - Enduring Available when needed

• Data in systems should be at least as accurate as those recorded by paper means.

• Reviewed & Verified• When a mistake is realised correct the recorded

data. This is traceable in audit logs.• Backup/Archive


• Interestingly, there is massive opportunities for streamlining reporting and analysis in terms of how systems are used.


} Reports &Analysis(Risk Based)

Future Strategy

ScientificData

MgmtSystem

Data Lake/Warehouse

LaboratoryInformationMgmtSystem

Standalone Instruments

Electronic Laboratory Notebooks

Distributed Control

System/ Historian

Enterprise Resource Planning

Paper/Paper on

glass

Other Systems

• Quality data for ML and AI • Static models for subsequent real-time use.

• Analysis• Domain expertise• Documentation (ensure reproducibility)• Resources• Auditing

• Inappropriate samples• Gender bias

Validated Data - Analysis

• Deviations/Investigations• Annual Reviews/Continuous Validation• Process Analytical Technology – the unused data• Never miss a case

Uses of Validated Data

• MSc in Data Science and Analytics• HDip in Data Science and Analytics• MSc in Artificial Intelligence• MSc in Cybersecurity• MSc in Cloud Computing• Certificate in Biopharmaceutical Processing • Higher Diploma in Science in Cloud Computing• Certificate in Automation & Control Systems• Certificate in SCADA & Automation Systems• Certificate in Industrial Automation• Certificate in Intelligent Manufacturing Systems

Relevant Programs @CIT

[1] Guideline on process validation for finished products - information and data to be provided in regulatory submissions. European Medicines Agency

Report, 21 November 2016, EMA/ CHMP/CVMP/QWP/BWP/70278/2012-Rev1,Corr.1

[2] Methodology for data validation 1.0 Revised edition June 2016 EssnetValidat Foundation Marco Di Zio, Nadežda Fursova, Tjalling Gelsema, Sarah Gießing, Ugo Guarnera, Jūratė Petrauskienė, Lucas Quensel-von Kalben, Mauro Scanu, K.O. ten Bosch, Mark van der Loo, Katrin Walsdorfer [3] UNECE 2013 Glossary of terms on statistical data editing

http://www1.unece.org/stat/platform/display/kbase/Glossary [4] Simon A., (2013a) Definition of validation levels and other related

concepts v01307. Working document. Available at https://webgate.ec.europa.eu/fpfis/mwikis/essvalidserv/images/3/30/Eurostat_-_definition_validation_levels_and_other_related_concepts_v01307.doc

[5] 09 June 2010 EMA/INS/GCP/454280/2010 GCP Inspectors Working Group (GCP IWG) Reflection paper on expectations for electronic source data and data transcribed to electronic data collection tools in clinical trials

References

https://webgate.ec.europa.eu/fpfis/mwikis/essvalidserv/images/3/


Blockchain

Karl O’Connell – Head of Integration

The Irish Cattle Breeding Federation

Reducing Carbon Emissionsand

Finding the Tastiest Steak

AgTech-It’s in our DNA

Our Vision“Empowering sustainable farming through collaboration and

excellence in genetics and big data solutions”


About ICBF

Next generation of animals are more environmentally and economically sustainable than the last.

World-leading (research => implementation).

• 2nd in world to launch dairy genomics.

• Beef Genomics => largest cattle genomics project globally.

Carbon EfficientGenetic Gain

Sustainable Farming


Overview• Grass based seasonal

• 0.95m beef cows

• 66,000 herds

• Avg herd size: 14 cows

• Export 90% beef

• Grass based seasonal

• 1.5m dairy cows

• 17,000 herds

• Avg herd size: 80 cows

• Export 90% of milk produced

Dairy Beef


Yearly Data Figures

2.4 Million

BVD Records

102kHerds

7.7 MillionFarm Movements

850kAI Records

1Oracle Exadata Platform

6.5 MillionLive Animals

2.2 Million

Slaughter Records

2.4 Million

Animal Births

4.8 Million

Milk Recording

Records


Genomics

Non-Genomic Index

Genomic Index


Genotype Data SetsBovine Genome

• Contains 3 billion nucleotides

• Scientists have discovered 40 million SNPs

3 billion rows of data per animal

Ireland Genotypes

380k animals per year on a 54k SNP Chip

First full genome sequence cost $300 million

Today costs = $1,000


Genotype Data Sets

1,800,000,000

8,600,000,000

18,300,000,000

62,700,000,000 95,000,000,

000

Start Jan-15 Mar-16 Mar-18 Aug-19

Genotype Records


Farm of the FutureIoT & Big Data

• IoT devices in agriculture will reach 75M in 2020

• Growing 20% annually

Geofencing & tracking

• Smart sensors

• Smart tractors

Blockchain

• Traceability

• Consumer Feedback

Climate & Environment

• Low carbon cows

• Sustainable farming


Breeding for Tasty Steak

Important to the consumer

• Tenderness

• Juiciness

• Taste

• Traceability

• Environmental Impact


Breeding for Tasty Steak (Meat Eating Quality)

• Sensory testing with trained panellists to generate breeding values.

• Partnerships with Eolas, Teagasc, Industry through MTI.

• Already being used in a “structured way” by Meat & Livestock Australia (MSA grading).

• Can we use consumer data in a more “unstructured” way?

Can consumer pick the difference?How does the consumer compare with trained panellist?

AgTech: It’s in our DNA

Our partnership with ICBF

IT Delivery Partner for 15 years

Considered an extension of the in-house team

Main Duties:

✓ Install & Support of core Oracle Database (Exadata / ZFS)

✓ Cloud service configuration and management

✓ Bespoke system and app development

✓ Provide support and advice across breadth of our services


How does Blockchain impact ICBF?

Enable Farm to Fork traceability using Blockchain technology to include

additional parties involved in the supply chain.

Consume

r

ICBF Industry▪ Enables surgical like recalls

▪ Further enhances Ireland’s already stellar agri image, adding value to the industry as a whole

▪ In line with strategic mission

▪ Enabler of current programs:-> Meat tasting => crowd

source!-> GHG Emissions = increased

consumer awareness

▪ Increased understanding, visibility, trust & transparency

▪ Informed purchase decision (buy local / buy green / buy tasty.


Is there a precedent?

Wyoming Beef Chain: https://beefchain.com

https://beefchain.com/


Project Scope & Objectives

Scope:

• Technical Proof of Value limited to:

• Single participant (ICBF)

• Mocked external participants

Objectives:

• Help ICBF better understand Blockchain technology

• Technical understanding

• Business impact understanding

• Industry Engagement Tool

Run by Version 1 Innovation Labs


Solution Overview

API Gateway

Consumer

ICBF

Future Participants

• Standards

• Suppliers

• Distributors

• Supermarkets

Mobile App Blockchain Network


Mobile App


Outcome• “Proof of Value” (PoV) solution developed

• Solution provides a real understanding of what Blockchain means to ICBF

• Blockchain demonstrates real value in Supply Chain use cases

• Solution attracted international attention and was presented at OOW 2019 in San Francisco and

featured on Forbes.com

Next Steps

• PoV being extended and implemented initially within ICBF

• Industry conversations ongoing

Thank you for listening

#WeBreedInnovation

Documents

Technology Innovations Driving Transformation in Regulatory · Validated Data - Pharmaceuticals “without complete, accurate, reliable, or retrievable raw data about the HPLC system’s