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PerkinElmer Signals™ Turning Data Science into Reality with Spotfire Dan Weaver and Seungtaek Lee October 4, 2016

PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

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Page 1: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

PerkinElmer Signalstrade Turning Data Science into Reality with Spotfire

Dan Weaver and Seungtaek Lee

October 4 2016

2

Safe Harbor Statement

bull This document shows current intentions regarding product features

behavior schedules and support these intentions may change without

notice as we respond to customer requirements

bull Any unreleased products services or features referenced herein are

not currently available and may not be delivered on time or at all

Customers who purchase PerkinElmer informatics applications should

make their purchase decisions based upon products features and

services that are currently available

4

Big Data Challenges in Life Science

Transactional Systems Data Silos Discovery amp Access Restrictions

Isolation

Distributed Research Models Limited Sharing and Collaboration

Collaboration

On-premise Data Centers Expensive and Complex

Infrastructure Patients Assays Tissues

Organisms Proteins Genes

Variety

100000s of samples 100s of GB per day per Experiment

Volume

Structured vs Unstructured Data How to make Sense of the Data

Complexity

5

Cloud-based data store and analytics platform designed

for todayrsquos and tomorrowrsquos life science needs Enabling

user experience around TIBCO Spotfire supports wide

range of data processing workflows and applications

PerkinElmer Signalstrade

Domain-specific entity model and ontologies

Machine learning for data normalization and mapping

Signals App Store with scientific applications

Intelligent

Big data technology foundation - Spark amp HDFS

Cloud-scale elastic SaaS deployment

Automated workflows with Automation Services

Scalable

User friendly scientific applications in TIBCO Spotfire

User-driven self-service access to all relevant data

Collaboration within and across the firewall

Enabling

Introducing PerkinElmer Signalstrade

7

PerkinElmerrsquos Vision of Translational Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Stratified Patient Population Patient Population

8

From Translational Medicine to Personalized Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Precise diagnosis

Targeted Therapy

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 2: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

2

Safe Harbor Statement

bull This document shows current intentions regarding product features

behavior schedules and support these intentions may change without

notice as we respond to customer requirements

bull Any unreleased products services or features referenced herein are

not currently available and may not be delivered on time or at all

Customers who purchase PerkinElmer informatics applications should

make their purchase decisions based upon products features and

services that are currently available

4

Big Data Challenges in Life Science

Transactional Systems Data Silos Discovery amp Access Restrictions

Isolation

Distributed Research Models Limited Sharing and Collaboration

Collaboration

On-premise Data Centers Expensive and Complex

Infrastructure Patients Assays Tissues

Organisms Proteins Genes

Variety

100000s of samples 100s of GB per day per Experiment

Volume

Structured vs Unstructured Data How to make Sense of the Data

Complexity

5

Cloud-based data store and analytics platform designed

for todayrsquos and tomorrowrsquos life science needs Enabling

user experience around TIBCO Spotfire supports wide

range of data processing workflows and applications

PerkinElmer Signalstrade

Domain-specific entity model and ontologies

Machine learning for data normalization and mapping

Signals App Store with scientific applications

Intelligent

Big data technology foundation - Spark amp HDFS

Cloud-scale elastic SaaS deployment

Automated workflows with Automation Services

Scalable

User friendly scientific applications in TIBCO Spotfire

User-driven self-service access to all relevant data

Collaboration within and across the firewall

Enabling

Introducing PerkinElmer Signalstrade

7

PerkinElmerrsquos Vision of Translational Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Stratified Patient Population Patient Population

8

From Translational Medicine to Personalized Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Precise diagnosis

Targeted Therapy

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 3: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

4

Big Data Challenges in Life Science

Transactional Systems Data Silos Discovery amp Access Restrictions

Isolation

Distributed Research Models Limited Sharing and Collaboration

Collaboration

On-premise Data Centers Expensive and Complex

Infrastructure Patients Assays Tissues

Organisms Proteins Genes

Variety

100000s of samples 100s of GB per day per Experiment

Volume

Structured vs Unstructured Data How to make Sense of the Data

Complexity

5

Cloud-based data store and analytics platform designed

for todayrsquos and tomorrowrsquos life science needs Enabling

user experience around TIBCO Spotfire supports wide

range of data processing workflows and applications

PerkinElmer Signalstrade

Domain-specific entity model and ontologies

Machine learning for data normalization and mapping

Signals App Store with scientific applications

Intelligent

Big data technology foundation - Spark amp HDFS

Cloud-scale elastic SaaS deployment

Automated workflows with Automation Services

Scalable

User friendly scientific applications in TIBCO Spotfire

User-driven self-service access to all relevant data

Collaboration within and across the firewall

Enabling

Introducing PerkinElmer Signalstrade

7

PerkinElmerrsquos Vision of Translational Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Stratified Patient Population Patient Population

8

From Translational Medicine to Personalized Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Precise diagnosis

Targeted Therapy

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 4: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

5

Cloud-based data store and analytics platform designed

for todayrsquos and tomorrowrsquos life science needs Enabling

user experience around TIBCO Spotfire supports wide

range of data processing workflows and applications

PerkinElmer Signalstrade

Domain-specific entity model and ontologies

Machine learning for data normalization and mapping

Signals App Store with scientific applications

Intelligent

Big data technology foundation - Spark amp HDFS

Cloud-scale elastic SaaS deployment

Automated workflows with Automation Services

Scalable

User friendly scientific applications in TIBCO Spotfire

User-driven self-service access to all relevant data

Collaboration within and across the firewall

Enabling

Introducing PerkinElmer Signalstrade

7

PerkinElmerrsquos Vision of Translational Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Stratified Patient Population Patient Population

8

From Translational Medicine to Personalized Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Precise diagnosis

Targeted Therapy

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 5: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

7

PerkinElmerrsquos Vision of Translational Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Stratified Patient Population Patient Population

8

From Translational Medicine to Personalized Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Precise diagnosis

Targeted Therapy

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 6: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

8

From Translational Medicine to Personalized Medicine

Multiplex ELISA

NGS

GEA

Quantitative

Pathology

IHC

Fusion CNV

Getting the right drug to the right patient at the right time

Precise diagnosis

Targeted Therapy

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 7: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

9

Translational Medicine Workflows

Raw Data

Select Processed

Data

QAQC

Results

Review Secondary

Analysis Select Clinical

Subject amp Samples

Secondary

Analysis

Data

Processing

Select Secondary

Results

Perform Integrated

Analysis

Bioinformatician Data Scientist

Focuses on single experiment

and starts with an instrument run

Translational Scientist

Starts with a scientific hypothesis

and scientific Entities

PerkinElmer Signals Annotated Raw Data

Annotated Processed Data

Derived Data

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 8: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

Translational Video

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 9: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

PerkinElmer Signals for Screening How Big Data Becomes Breakthrough Data

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 10: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

Screening Video

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 11: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

Extensible and configurable analytics applications to

TIBCO Spotfire The Signals Apps Store for Screening

supports users to create configurable screening data

analytics workflows for a wide range of applications

Signals App Store for Screening

Configurable and extensible apps can be combined to

protocols protocols can be saved and shared between

users extension and configuration with custom apps

Flexible

Protocols can be run interactive or fully automated

using Automation Services reporting apps for fully

integrated workflows

Automated

Intrinsic domain model awareness enables apps to

configure themselves and guide user through input

parameters selection

Intelligent

PerkinElmer Signalstrade for Screening

Data Import and

Aggregation

Spotfire Templates

High Content Profiler

Curve Fitting

SAR

Real-time Analytics

Alerts Reports

Publish Collaborate

Automated Workflow

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 12: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

Spotfire for Your Instrumentshellip

Plate Readers

Quantitative

Pathology Flow Cytometry

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 13: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

SciStream

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 14: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

16

Fingerprint ndash food and beverage profile

bull Food signaturefingerprint

bull Food fraud detection

bull Adulterated beverages

bull MSMS LC GC NIR etc

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 15: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

18

Fingerprint ndash gene expression signatureprofile

J Biomol Screen 2016 Oct21(9)989-97 doi 1011771087057116658646 Epub 2016 Jul 26 Severyn B1 Nguyen T2 Altman MD3 Li

L2 Nagashima K4 Naumov GN2 Sathyanarayanan S2 Cook E5 Morris E2 Ferrer M5 Arthur B5 Benita Y6 Watters J6 Loboda A6 Hermes

J5 Gilliland DG2 Cleary MA7 Carroll PM2 Strack P2 Tudor M5 Andersen JN2

Conclusion Multiplex gene expression readouts are more labor- and

resource-intensive than other assays commonly used in

drug discovery and HTS however in some instances they

may provide the only means of quantifying a phenotype of

interest This can be because a single readout (reporter gene

protein expressionmodification) may not capture all possible

responses of a model or because a univariate readout

may not have a sufficient assay window for screening In

cases where mRNA levels can be translated into relevant

biological readouts expression screening enables the

interrogation

of complex networks by small molecules and hits

identified from such GE-HTS efforts may yield important

new insights Indeed the ability of the present assay system

to identify RAS-MAPK targeting compounds together

with other recent gene signaturendashbased proof-of-concept

studies1718 suggests that these chemical genomic screens

will be able to play a unique role in drug discovery

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 16: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

19

Fingerprint ndash cellular phenotype

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 17: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

20

HCS usage is stillhellip quite Low Content

20

Shantanu Singh Anne E Carpenter amp Auguste Genovesio

Journal of Biomolecular Screening 19 611-613 (June 2014)

doi101038nrd3480 httpjbxsagepubcomcontent195640

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 18: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

21

High Content Profiler for HCSHTS

bull Multivariate Statistics

Normalization

QCOutlier detection

Feature selection

Hit selection amp stratification

bull Guided Spotfire Workflows

Cell and well level analysis

Automated standardized analysis

Highly interactive visualization

Scientifically validated

bull Image Rendering

Hypothesis testing

Result validation

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 19: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

23

System Components

These intentions may change without notice as we respond to customer requirements

HCS HTS 3rd Party ImageData Analysis Software

Matlab ImageJ CellProfiler etc

SIGNALS for SCREENING Analysis persistence and management of data generated by the instruments Columbus and Spotfire Apps and Protocols

COLUMBUS

OMERO 5x

Manage image transfer

and analysis from

instrument to the cloud

HPC IMAGE ANALYSIS

Columbus leverages

compute clusters for

scalable image analysis

Spotfire App Store

Interactive front-end for

protocol development

analysis and automation

SIGNALS PLATFORM

Built to support diverse screening platforms with domain models archiving permissions etc

SEARCH AND ADVANCED SCREENING ANALYTICS

Advanced search and cross assayscreen analytics

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 20: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

26

Takeaways ndash PerkinElmer Signalstrade

bull Life science data generation outpaces perception capabilities

bull Need to bring Big Data technologies to life science

bull Distributed research models require collaborative informatics

bull PerkinElmer Signalstrade for agile cloud-scale data management

bull Signals App Store for flexibility and automation in TIBCO Spotfire

bull Addressing business problems with intelligent scientific applications

Thank You

Page 21: PerkinElmer Signals™ · 2016-10-07 · Cloud-scale, elastic SaaS deployment Automated workflows with Automation Services Scalable User friendly scientific applications in TIBCO

Thank You