Why paperless lab is just the first step towards a smart lab

Why paperless lab is just the first

step towards a smart lab

Friedrich Hübner, Heiner Oberkampf

Slide 2

Outline

Introduction

Current Challenges with ELN data

What is Semantic Technology and how can it help?

A Vision for 21st Century Smart Labs

Reference Data Management

Slide 3

2015: global presence Founded: 1996 Aachen

Who we are

slide 4

OSTHUS Group

Connecting Data, People and Organizations

Onsite

Support

Lab

&

Data

Implementation

&

Integration

Business

Process Science

Installation

&

Roll-Out

Maintenance

&

Support

Requirements

Engineering

Cutting edge in R&D

Consulting, Solutions and

Services

Global Partner

for industry

Independent

from vendors and platforms

Hosted

Services

Digital Life Science Consulting Integrated Solutions Managed Services

Data Science Lab Informatics

Slide 5

Guiding Question

Do you already use an ELN?

Slide 6

Analytic Request Cycle

Scientist (plans and designs experiments,

generates samples,

creates analytic requests)

Lab Manager (assigns requests)

Analyst (prepares & performs tests,

creates results)

Slide 7

Screenshot HPLC Technik

Slide 8

Example structured data

Source: Perkin Elmer

Slide 9

Examples of unstructured data

Research Reports

Internal Papers

System Validation

Raw Device Data

Images

Video?

Slide 10

ELN related sytems

ELN

DWH

LIMS

Instruments

Inventory

Reporting tools

Slide 11

Guiding Question

What is your ELN Data used for?

Slide 12

Use of ELN

Simple documentation of performed experiments

Capturing and processing of measurement data

Import of result data from instruments

Compare measurements

Check consistency

Search and retrieval

Reporting & IP

Slide 13

Guiding Question

How structured is your ELN?

Slide 14

Value of ELN data

Documentation and IP

Answering scientific questions

Answering business questions

Multiple use within different scenarios

Slide 15

The Drug Discovery Life-Cycle

publications

organisms

substances

molecules

devices

linked ct

Drug Bank

drug side

effects

genes

proteins

pharmacology

social

media patient

reports

locations,

organizations

market

analysis

„Since I take medication X my

stomach feels better, however I

am always so tired.”

experiments

(pre-clinical ) clinical trials production

use of

medication

Slide 16

Roadmap

Code (Lists) Terms (Soil, Plant, etc.)

Controlled Vocabulary

(Agreed Upon Terms)

Taxonomy

(Hierarchy)

Thesaurus

(Preferred Labels, Synonyms, etc.) RDF Models

(Triples as Graphs)

OWL Ontologies

(RDF + Axioms)

Reasoning

(Rule-based Logics:

Discover New Patterns)

Ontologies and Reasoning add

Axioms and Advanced Logic

Slide 17

The 4V’s of Big Data

Normally the focus –

Big Data Analysis is

more than just size

Performance is

Critical to Success

Data complexity is

increasing – Model

complexity

Uncertainty abounds

– requires statistics

and probabilities

Majority of Big Data analytics

approaches treat these two V’s

Semantic

technologies provide

clear advantages

Mathematical

Clustering

Techniques

provide clear

advantages

Slide 18

Words, Terms and Concepts

isobutylphenylpropanoic acid

word

term = A compound of words

with a specific meaning in a

certain context.

concept = ”An abstract entity signifying a general characterizing idea or

universal which acts as a category for instances. The unit of semantics

(meaning), the node in some mental or knowledge organization system.”

[Obrst2010]

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Synonyms are …

different terms which represent the same concept:

TraumaDolgit Gel

IP82

Ibuprofen, Copper (2+) Salt

Calcium Salt Ibuprofen

Ibuprofen, Sodium Salt

Ibuprofen-Zinc

Magnesium Salt Ibuprofen

isobutylphenylpropanoic acid

IP-82

Ibuprofen, Zinc Salt

Motrin

Benzeneacetic acid, alpha-methyl-4-(2-methylpropyl)-

Ibumetin

Ibuprofen I.V. Solution

Potassium Salt Ibuprofen

Rufen

alpha-Methyl-4-(2-methylpropyl)benzeneacetic Acid

Trauma Dolgit Gel

Nuprin

Brufen

…

Sources: MeSH Thesaurus, ChEBI Ontology

Slide 20

Abbreviation example

• Has its origins in philosophy - generally understood as

the abstract study of meaning

• Distinguished from syntax – which is the rules-based

grammar of a language

“Washington”

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How can we express meaning?

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Textual Description

Ibuprofen, from isobutylphenylpropanoic acid, is a

nonsteroidal anti-inflammatory drug (NSAID) used for treating

pain, fever, and inflammation. This includes painful menstrual

periods, migraines, and rheumatoid arthritis. About 60% of

people improve with any given NSAID, and it is recommended

that if one does not work then another should be tried. It may

also be used to close a patent ductus arteriosus in a premature

baby. It can be used by mouth or intravenously. It typically

begins working within an hour.

Common side effects includes heartburn and a rash. Compared

to other NSAIDs it may have fewer side effects such as

gastrointestinal bleeding. It increases the risk of heart failure,

kidney failure, and liver failure…

Source: https://en.wikipedia.org/wiki/Ibuprofen

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Textual Description

Ibuprofen, from isobutylphenylpropanoic acid, is a

nonsteroidal anti-inflammatory drug (NSAID) used for treating

pain, fever, and inflammation. This includes painful menstrual

periods, migraines, and rheumatoid arthritis. About 60% of

people improve with any given NSAID, and it is recommended

that if one does not work then another should be tried. It may

also be used to close a patent ductus arteriosus in a premature

baby. It can be used by mouth or intravenously. It typically

begins working within an hour.

Common side effects includes heartburn and a rash. Compared

to other NSAIDs it may have fewer side effects such as

gastrointestinal bleeding. It increases the risk of heart failure,

kidney failure, and liver failure…

Source: https://en.wikipedia.org/wiki/Ibuprofen

Slide 24

Triple

subject predicate object

HPLC is-a liquid chromatography

ibuprofen is-a nonsteroidal anti-inflammatory drug

ibuprofen treats pain

predicate subject object

Slide 25

Semantic Networks

A simple, non-formal way to express the meaning of a concept

through relations (links) to other concepts.

antipyretics

C13H18O2

rash

symptom

pain

cyclooxygenase 2

treats

is-a

broader

has-formula

trade name

may-has-side-effect

is-a

medication

ibuproxam

narrower

ibuprofen

inhibitor-of

Motrin

Slide 26

Taxonomies and Ontologies

Opportunity: • Many existing taxonomies available

• Company-specific adaptations: additional classes, synonyms, relations etc.

Insect

Sucking Insect

Leaf Miner

has pest

Slide 27

Information Retrieval

Efficient semantic search

antipyretics

C13H18O2

rash

symptom

pain

cyclooxygenase 2

treats

is-a

broader

has-formula

trade name

may-has-side-effect

is-a

medication

ibuproxam

narrower

ibuprofen

inhibitor-of

Motrin

Slide 28

Why Semantics Matters for Data Analytics

Big Data approaches require proper metadata

and terminologies to integrate information well

Relationships matter in the data

Understanding perspective (context) is crucial for

success in today’s world

Semantics provides better data models/schemas

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Smart Labs for the 21st Century

Smart labs in the future will

provide the enterprise with:

Integrated Data – common

reference data structures

(vocabularies)

Sharable Data – easier interaction

across teams and business units

Scalability – Big data applications

that can be highly elastic

Conceptual Representations –

context and perspective are

captured

Advanced Analytics – complex &

automated problem-solving

capabilities

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Reference Data Management: ensure a common

language between your applications

ELN

DWH

LIMS

Instruments Inventory

Reporting tools

Reference Data Service

• provides shared vocabulary

• provides synonyms

• provides mapping

• …

Slide 31

References and more information

OSTHUS Webinar

(https://www.youtube.com/watch?v=Drm3r3BVkxE)

Allotrope Foundation

(http://www.allotrope.org/)

SmartLab 2016

(https://www.youtube.com/watch?v=maA1nQEedos)

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Thank you for your attention!

Heiner Oberkampf Tel.: +49 241-94314-490 Fax: +49 241-94314-19 Email: heiner.oberkampf@osthus.com Web: www.osthus.com

Friedrich Hübner Tel.: +49 241-94314-476 Fax: +49 241-94314-19 Email: friedrich.huebner@osthus.com Web: www.osthus.com