TECHNOLOGYLIKE NEVER BEFORE
EBDC Dresden7. October 2014
The Need forBIG DATAProcessing
Petra StrengSolution Manager SAP SEIndustry Business Unit Life Sciences
Markus TempelGlobal LeadBig Data Analytics Services Practice
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SAP Use Cases- Customer Projects- Partner Projects
Big Data PlatformInsight into suitableIT Architecture andinnovation platform
The NeedFor Big DataArchitectures
Agenda
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Growing Data Volumes in Diverse Healthcare Systems
PubMedbiomedical articledatabase23+ Mil. articles
Clinical trialsCurrently more than 30,000recruiting on ClinicalTrials.gov
Cancer patient records160,000 atNCT Heidelberg
Clinical informationmanagement systemsOften more than 50 GB
Human proteome160 Mil. data points (2.4 GB) per sample3.7 TB raw proteome data onProteomicsDB.org
Prescription data1.5 Bil. records from 10,000 doctorsand 10 Mil. Patients (100 GB)
Human genome/biological data800 MB per full genome15 PB+ in databases of leading institutes
Medical imaging dataScan of a single organ in 1screates 10GB of raw data
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Big Data Challenges – Oncology as an example
1 million human genomesfully sequenced by end of2013, and 5 million by 2014
BIG
DATA
As many as 20 drivermutations possible fora single cancer cell
About 400 protein-coding genes showedsomatic mutationsdriving tumor growth
Causal mutations aredifferent from patientto patient, and evolveover time
9 days for theanalysis of a patient’ssequencing data
EmbraceComplexity
15 millionnew cancer
patients eachyear
Human genome:800 MB per full genome,15 PB+ in databases ofleading institutes
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Business Development – What Does It TakeFor Big Data Analysis in Life Sciences?
Money
Dietmar Hopp,SAP Co-Founder,invested 1 bil Euroin biotech
InnovationNew players in R&D:
Hasso Plattner,SAP Co-Founder,invented a revolutionaryplatform geared for Big Data
EnvironmentWhat is the required legal and socio-economicframework to foster collaboration and adoption
of new innovations?
EBDC
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What is SAP doing in nature?How Life Sciences Research and IT Technology can benefit each other
92 % coverage of thehuman proteome
www.proteomicsdb.org
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Proteomics DatabaseDedicated to expedite the identification of the human proteome andits use across the scientific community
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Proteome-based Cancer ResearchDedicated to identify early cancer signals (“fingerprints”) toderive at diagnostic tests via protein mass spectroscopy signals
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Award WinningPersonalized Medicine
The White House Honors SAP, Stanford and NCT
SAP received special recognition from the US White Housetogether with the Stanford School of Medicine and theNational Center for Tumor Diseases (NCT Heidelberg) tohelp accelerate the Human Genome Project’s therapeuticpromise of personalized medicine
http://www.forbes.com/sites/sap/2013/11/14/the-white-house-honors-sap-stanford-and-nct/
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National Center for Tumor Diseases (NCT)Gain Insight into Cancer Research
• Interface for real-timeanalyses of clinical data:Various sources of structured(tumor documentation, medicalrecords, clinical trials) andunstructured (doctor letters,treatment guidelines, trialreports, publications) nature.
• Medical records from 150,000patients and 3,600,000interactions, and a selection ofdoctor letters from 120 doctors
“In future we want everyone comingfor a diagnosis to go through an SAPHANA scan just as they have anMRI/Ultrasound scan today.”Professor von Kalle, NCT Heidelberg
Screenshot: A search for lung carcinoma patients
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Genomics: SAP and StanfordGenome analysis in real-time of 1000 genome data
Dr. Carlos D. Bustamante
Analyze genome wide patterns ofvariation within and between species toaddress fundamental questions in biology,anthropology, and medicine: implicationsfor global health and disease
"We have been thrilled to work with SAP and HPI on a collaboration to accelerate DNAsequence analysis. In our pilot projects, we are seeing dramatic speedups in computingon human genome variation data from many samples. We are dreaming of what will soonbe possible as we integrate phenotype, genomics, proteomics, and exposome data toempower complex trait mapping using millions of health records.”
- Professor Carlos D. Bustamante at the Stanford University School of Medicine
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Plant Genomics: SAP & University of British ColumbiaMatch geno- and phenotypes
Dr. Loren Riesberg
Integrates high-throughput genomicmethods, bioinformatics, ecologicalexperiments & evolutionary theory tostudy the origin & evolution of species,domesticated plants & weeds.
Project goals:
Complete pre-variant analysis pipeline for sunflower genome data &benchmark against existing tools
Develop post-variant analysis algorithms & visualizations
Predictive analysis – using HANA-R integrations & SAP’s existingpredictive tools
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Real Life Evidence through Remote Patient EngagementCapture medical device data to drive lifestyle change through insight
Patient stratification Analyze outcomeRemote monitoring
Paired a mobile technology application withthe following features:
Logging and setting goalsAlerts and remindersVital parameter trackingPrescription orderingInsurance reimbursement agreement
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Transforming Healthcare with SAP TechnologyNational Rural Health Mission in India
Initially it took MKI two days to find differences in genomedata between cancer patients and healthy peoplePlanned to enroll
270 millionschool children
across India
Currently
> 60 000children enrolled
A pilot program for 270 million school children to start alifetime of data collection, using mobile tablets for dataentry and cloud storage for all health data.
Goal: Determine the need for medical support, preventepidemics, and provide analysis capabilities to aid in theunderstanding of health trends across the population.
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Partner Engagement for Genome Analysis
Initially it took MKI two days to find differences in genomedata between cancer patients and healthy people
.“Our solution is to incorporate SAP HANA along with Hadoop and R tocreate a single real-time big data platform. Data mining will be handledby R and assisted by HANA. Data pre-processing prior to data analysisand high-speed storage will be managed by Hadoop. With this we havefound a way to shorten the genome analysis time from several daysdown to only 20 minutes.”Yukihisa Kato, CTO and Director of MITSUI KNOWLEDGE INDUSTRY
216xfaster by
reducing genomeanalysis from
several days toonly 20 minutes
408,000xfaster than traditionaldisk-based systems in
a technical PoC
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Partner Engagement for Treatment Decision Support
Initially it took MKI two days to find differences in genomedata between cancer patients and healthy people
300x faster
An exomeanalysis nowonly requires3 minutes!
With TreatmentMAP™ MolecularHealth has created a state ofthe art result report providing
Actionable treatment options,
Details on each of the treatment options as well as
Drug-drug interactions to ensure effective treatment
Molecular Health handles the complete process:Sample collection
Sequencing genetic tests,
Deep-level analysis run against the current medical research
Summary recommendations and result report
75%of the time drug
therapies areineffective, because
every patient’s canceris different, unique to
his/her geneticmakeup.
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17Confidential© 2014 SAP AG or an SAP affiliate company. All rights reserved.
Research&Development Manufacturing/SupplyChain Sales&MarketingResearch&Development Manufacturing/SupplyChain Sales&Marketing
InnovationMgmt
InnovationMgmt
Uncover value.Create breakthroughs.Experience simplicity.
GenomicAnalyzerGenomicAnalyzer ProteomicsProteomics
ClinicalData
Warehouse
ClinicalData
Warehouse
ConnectedHealth
ConnectedHealthContinuous
ProcessVerification
ContinuousProcess
Verification
Track&
Trace
Track&
Trace
ClinicalTrial
SupplyMgmt
ClinicalTrial
SupplyMgmt
CareCircles
CareCircles
VirtualPatientsVirtual
Patients
TreatmentMAP
TreatmentMAPPredictive
Maintenance
PredictiveMaintenanc
e
Examples of SAP and Partner Solutions and Customer Projects based on HANAExamples of SAP and Partner Solutions and Customer Projects based on HANA
IDMPIDMPPharmaco-vigilance
SignalDetection
Pharmaco-vigilance
SignalDetection
PopulationHealth
PopulationHealth
Industry4.0
Industry4.0
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18Confidential© 2014 SAP AG or an SAP affiliate company. All rights reserved.
SAP HANA Database Technologyas basis for our bioinformatics work
Bulk loadFast insertion of largegenomic datasets or
other relevantdatasets
T
Text Retrievaland Extraction
Search doctor’s notes,diagnoses,
etc.(unstructured data)
SQL interface oncolumns & rowsEasily connect
with other tools(e.g. Rstudio)
SQL
LightweightCompression
Fit big data in mainmemory while
allowing fast retrieval
Multi-core/parallelization
Speedup of relevantqueries acrossmany nodes
On-the-flyextensibility
Adapting to new formatrequirements without
going offline (e.g.changing VCF files)
+++
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BIGDATA Portfolio
Key Components of a World Class Big Data Portfolio
SAP is making a significant investment to lead the market and is going BIG with BIGDATA:www.sapbigdata.com
BIG DATAPLATFORM
In-Memory Platform
Analytics Database
Hadoop
Event Processing
Data Services
Accelerate how you acquire,analyze and act
on Big Data insights
BIG DATAANALYTICS
Predictive Analytics
Visualization
Text Analysis
Business Intelligence
Unleash the power of BigData with collective insight
across your business
BIG DATAAPPLICATIONS
Business Applications
Custom Applications
Adopt new business modelsand revenue streams with
applications that deliver BigData insights
BIG DATASERVICES
Full Offering:Discover, Plan,Realize, Run
Data Science Experts:Predicting your businessbetter than you can
Achieve tangible results fromyour Big Data initiatives withservices that apply advanceddata science to your business
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SAP HANA PlatformMore than just a database
Any AppsAny App ServerAny Apps
Any App Server
JSONR Open ConnectivityMDXSQL
SAP HANA Platform for Healthcare – industry specific extensions of SAP HANA.Providing breakthrough capabilities for healthcare and life sciences applications
from SAP and its partners, while reducing time-to-value and TCO.
Supports any Device
Other AppsLocationsReal-timeHADOOPMachineUnstructuredTransaction
SAP HANA PlatformSQL, SQLScript, JavaScriptSQL, SQLScript, JavaScript
Integration ServicesIntegration Services
SpatialSpatial
Business FunctionLibrary
Business FunctionLibrary
SearchSearch Text MiningText Mining
PredictiveAnalysis Library
PredictiveAnalysis Library
DatabaseServicesDatabaseServices
Stored Procedure & Data ModelsStored Procedure & Data Models
Planning EnginePlanning Engine Rules EngineRules Engine
Application & UIServices
Application & UIServices
Omics EngineOmics Engine
Healthcare Integration ServicesHealthcare Integration Services
SAP Healthcare and LifeScience Applications
SAP Healthcare and LifeScience Applications
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ActAnalyzeAcquire
Effectively, rapidly andefficiently acquire andconsolidate massiveamounts of diverse andarbitrary data
Real-time response timeregardless of datavolume or data locationmanage and integratemassive volumes of data
Achieve real results toget the insights you needwith a variety of meansalone or in combination
SAP HANA: Unprecedented hyper-performance achieved throughdeep synergies between software and hardware innovations
++
++
++
++++
PAA
Acquire, Analyze and Act on BIGDATA
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BIGDATA augments traditional analytics …
Adding BIGDATA technologies enables analytics solutions…to include more types of datato consume higher volumes of information.to process more information in less timeto maintain a higher quality of analysisto offer an improved user experience.to allow users to explore all data beyond DWH models
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R Data Mining Language Support• Native installer included• ~12 R algorithms included• 3,500+ R Model library and growing• Custom R, JAVA, etc.
Rich Pre-Built Modelling Functionality• Automatic Data Preparation• Classification• Regression• Anomaly Detection• Attribute Importance• Association Rules• Clustering• Feature extraction
• Direct access to Advanced Visualizations• Superset solution includes SAP Visual Intelligence library• Stunning visualizations
Advanced Visualization
MultiLanguageSupport• EN, DE, ES,
PO, FR, JP, IT
Integration• Native integration with SAP HANA• Leverage existing BOBJ universes• Publish actionable results to mobile & BI clients
Ease of Use• Drag & drop data selection, preparation, processing• Easy sharing /collaboration of findings• Built for business analysts
SAP Predictive Analysis
Automated Approach tosolvingpredictive problems• Rapid development of
predictive models• Focused on predictive functions
not algorithms• Ability to deliver large amounts
of models quickly
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BENEFITTINGFROM SAP HANA
COMBINEmassive amount of data fromall available sources
SEGMENTATIONof very large data sets
PREDICTIVEpower to identify risks forpatient’s health or company’sfinancial performance early on
REAL-TIMEanalysis of very large data set ofgenome or proteome data, orders,invoices, financial transitions,medical records, doctor letters ormedical publications
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