Laboratory Informatics in the Digital Era

Michael Shanler

Research Vice President, Life Science R&D

Dynamic Recombination

What We’ll Discuss

1. Forces and technology trends impacting

all businesses in the “Digital Era”

2. CIO priorities

3. IT environment for Scientific Industries

4. How technology will enable laboratory

innovation transformation

Strategic Technology Trends & IT

CIO Priorities

Scientific Industries

Lab IT

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Forces Impacting All Businesses

We Are in the Beginning…

…of a Digital Renaissance

Massive Collaboration -

Cross-organization

Any X Connectivity –

device, platforms

Complexity Increases

Big Data & Analytics

Cloud Technology

Distributed Infrastructure

Technologies Supporting “The Nexus of Forces” Enable Business Transformation

The Collision of the Nexus of Forces andthe Internet of Things …

The Collision of the Nexus of Forces andthe Internet of Things …

2009: 1.6B personal devices + 1B “things” 2020: 7B personal devices + 30B “things”

… Has Spawned “Digital Business”

Digital Business Is the Creation of

New Business Designs by Blurring

the Digital and Physical Worlds.

Digital Business Is Specifically

Focused on Peer Exchange and

Communication Between:

Business (Including Process and

Information), People and Physical

Things as Equal Entities.

9

Of the PHYSICAL…

…with the DIGITAL

CONVERGENCE

Where nearly every asset, consumable, biologic, process, chemical, etc.

will have a data associated

What Can we Learn from Yelp about “Convergence”?

Monocle

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Gartner Strategic Technology Trends

Collection

of Devices,

Information,

Apps, Services

around individuals

Extract greater

meaning from a

rapidly expanding

set of sources

technology architectures and platforms must change

to support the world of digital and autonomous business enabled

by the digital mesh and smart machines

Top 10 Strategic

TechnologyTrends

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What Are the CIO Priorities?

Life Science IT Spending – Where’s the money going?

GrowRun Transform

Innovation

IT FTEs as % of Revenue

IT FTEs as % of Total Employees

= Reduced Internal Capabilities!

cross industry avg = 3.4%

cross industry avg = 4.8%!

How do I better understand what is happening in my test?

How do I improve the ROI of my Lab IT Systems?

How do I scale globally (or reduce costs of on-premises IT)?

How do I offer better remote capabilities for labs?

How do I better protect my data in shared environments?

“How can I leverage scientific data and insights more broadly?

How do we improve collaboration for experiments?

CIO Top Priorities Contextualized for Laboratory IT

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Meanwhile, What is the Lab IT Environment for Scientific industries?

The New Normal with Distributed R&D & Supply Chain

CompanyPAST FUTURE

External Partners Internal Capabilities

Internal

InnovationExternal Contract /

Transactional Innovation

Distributed Shared

Innovation

• Technology-based strategic partners to execute clinical development activities

• Increased collaboration, increased access

• Globalized infrastructures for sharing very complex R&D / Manuf. data

• Extreme agility required for clinical insights delivered via analytics

PRESENT

“Shadow IT” Dominates R&D Informatics

R&D Activities

Externalization…What does the Enterprise Really Know?

R&D “dark art”

Vendor Myths

Vaporware promises

Innovation on the Fringe

New Technology

Vision

BIG DATA

[Image Source: Shutterstock]

VELOCITY

COMPLEXITYVARIETY

VOLUME

Application Complexity: How Many Apps Do You Really Use? Need? Want?

21

Laboratory IT Application Trend

Customization Platform-strategy

Valu

e

SDMS

RequestELN 1

LIMS 2

LIMS 1

CDSELN 2

Pipeline

Inventory

Too many vendors (Rationalize Harmonize)

EDS

Lower Quality

Higher Costs

Lower Efficiency

Difficult Innovations

=

Vendor A

Vendor B

Vendor Z

Laboratory IT Application Trend

Customization Platform-strategy

Valu

e

SDMS

RequestELN 1

LIMS 2

LIMS 1

CDSELN 2

Pipeline

Inventory

EDS

Too many vendors (Rationalize Harmonize)

Vendor A

Vendor B

Vendor Z

Laboratory IT Application Trend

Customization Platform-strategy

Valu

e

SDMS

Request

LIMS 2

LIMS 1

CDSELN 2

Pipeline

InventoryELN 1

EDS

E-Lab Informatics Platform Strategy

Higher Quality

Lower Costs

Higher Efficiency

Easier Innovations

=

Lab Informatics Platform When adds value

Hyped Informatics Technology

Source: Gartner (FEB 2014)

ELN“3.0”

Enterprise LIMS “4.0”

Lab Informatics

Suites

QA/QC ELNBio ELN Chem ELN

Generic ELN

SaaS ELN

Cloud ELN

QM LIMS

Research LIMSELN-provided

by LIMSSaaS LIMS

Lots of “Bit Players.” Few Enterprise PartnersVendor Info

VendoreCLINICAL CDM IVRS IWRS eCOA ePRO CTMS Clinical

Data

Warehou

se

EDC PV

Monitorin

g

Safety / Adverse

Event Reporting

System

eSubmissi

on

Clinical

Site

Monitorin

g

Analytics

Product Names

Lab Informatics components categories as claimed by vendors

~ 80

“Lab

Informatics”

component

vendors

tracked

VERY FEW “ENTERPRISE” VENDORS

Most lack broad functionality.

Most lack execution

Most don’t have global coverage

Most are built on old architectures

Solution Suitability

A

B

C

D

E

F

G

H

I

J

K

L

Solution Suitability for R&D IT

Core Configuration Customization

Very Low Low Medium High Very High

Gartner, Inc (2015) $$’s $$$’s$’s

Yes, the capabilities Increase…..but….

the long term IT complexity, validation challenges & costs increase, too.

CORE CONFIGURE CUSTOMIZE

So…What to Do?

Lab Informatics experience has been a

giant, sticky mess.

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What does this mean for Laboratory IT?

How to understand the relationships?

Today’s Challenges Will Be Overcome Creating Significant Opportunities

The Inevitable.

But the type of cloud will need to be matched to workflow, needs,

risk aversion, etc.

By 2017, 80% of ELN* will underperform due to

changing R&D needs and unsustainable service

models, requiring replacement or overhauls.*process and data workflows

Gartner Prediction – ELN challenges

Predicts 2014: Manufacturer R&D Gets Smarter About Innovation in the Digitalized Era

02 December 2013 G00259030

By 2019, 30% of the top 100 life science R&D IT

organizations will have successfully moved big

data projects from proof of concept (POC) and

pilots into production.*process and data workflows

Gartner Prediction – Big Data Project Challenges

Predicts 2016: Digital Generates Business Value Opportunities in Life Science 02 December 2015 G00292201

By 2018, (only) 15% of manufacturers will use turnkey solutions to translate

scientific information into engineering-based new product development

(NPD) actions.

By 2019, the blurring of industry boundaries will drive 25% of major R&D

activities, enabling brand-new digital products and services.

By 2018, 90% of scientific R&D organizations will struggle entering the

"digital era," due to hurdles with legacy laboratory systems and unfamiliar

IoT environments.

Gartner Prediction – Multiples R&D Issues

Predicts 2016: The Rise of Digital R&D Without Borders

01 December 2015 G00291729

Business

People

Things

• Focus: Leverage new data sources and drive informed decisions

• Outcome: Newbusiness models leveraging new entities

Electronic

Digital

Paper

Era

The Digital Lab Journey Is Going to Be Wild

Now imagine a Yelp Monocle (AR) + Laboratory Performance

No Longer Is this Science Fiction

QR code recognition built into Process

With built in Compliance

Improved System of Record

..Leverage Laboratory Execution

Protocol & Consumables Information on Demand

..Record into ELN or LIMS

Location Services With Security + Authentication

Warm up the HPLC

before you arrive

Define Your Future

To make this work…

People(Scientist, Managers, Collaborators)

SystemsLaboratory and R&D Workflows; Informatics, S/W.

Internet-Connected ThingsLab Equipment, Labels, Sensors, Beacons, RFID,

Smart Phones, Wearables (Glasses, watches) Keycards, Tablets.

“smart” products

Dynamic processesContext, Analytics, ITCreative, Insightful

Connect Devices, Systems (point to point)

Collect observe and experiment (point to point)

Model & Simulate characterize products

Innovate systems

Transform

Increasing Laboratory IoT Maturity Requires Evolutionary Investment and New Skills

Different Ascendancy Phases of IoT

Prescriptive

Predictive

Descriptive

What is the Enteprise

value of IoT

Analytics?

Beacons, sensors, IoT Infrastructure

IoT Analytics and visualization, semantic enrichment

IoT, HPC, graph computing

IoT Autonomics, ML, rules engines

Diagnostic

“smart”, AI, VPAs, “Cognitive” IoT

(1) Incremental and layered technology

investments, (2) process changes and (3) new skills required

Level 1 Level 2 Level 3 Level 4 Level 5

Initial /

Unaware

Opportunistic /

Visible

Organized /

Proactive

Enterprise /

Business

Partnerships

Transformative

/ Business

Differentiation

IoTMaturity

What is required of IT, skills,

processes, technology?

Now…

….Imagine Your Lab of the Future…

Connect Devices, Systems (point to point)

Collect observe and experiment (point to point)

Model & Simulate characterize products

Innovate systems

Transform

Start with Imagining the Journey.

“ Tomorrow, Our scientists will be able to __________.”

Today

In 2 Yrs

In 5 Yrs

Going Digital Requires New Working Parts

How to select the right ones

to work together?

How to put these into motion?

How to manage hype and portfolios?Technology "Hype"

Systems of Record

Systems of Differentiation

Systems of Innovation

Pace Layer Approach

Maturity

From, "Hype Cycle for Life Sciences, 2014," 30 July 2014 (G00264354)

Image Source: Shutterstock

Can you execute

BiModal IT and

Manage it?

Which Technology

Bets?

Who Can Do it?

The future is unknown, but the technology precursors for big changes are here, today.

The ability to live with that uncertainty and then embrace it quickly will be a key success factor in the future.

Help the stakeholders visualize new business opportunities that are enabled by IT and technology.

Thank You

Supplemental

https://d0.awsstatic.com/whitepapers/compliance/Using_AWS_in_GxP_Systems.pdf

https://aws.amazon.com/compliance/gxp-part-11-annex-11/

mHealth Apps to capture analog data, remotely.

Even pull data from Analog,

Unconnected equipment