“Integrated Biomedical and Clinical Research Informatics for

CCEB

J. Richard Landis, PhDRobert M. Curley, MSGregg Fromell, MD

Center for Clinical Epidemiology and Biostatistics (CCEB)Office of Human Research (OHR)

University of Pennsylvania School of MedicinePhiladelphia, PA 19104-6021

“Integrated Biomedical and ClinicalResearch Informatics for Translational

Medicine and Therapeutics”

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http://cceb.med.upenn.edu/main/index.html

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http://www.med.upenn.edu/ohr

The Office of Human Research (OHR) seeks to promote human researchfor the advancement of healthcare while ensuring the highest level ofresearch participant safety and facilitating the highest quality research by:

• Realizing the best research standards through adherence to University and government research policies and regulations• Supporting investigators and research teams through process improvement, innovative technologies, and education and training initiatives• Propagating best operational practices to maximize the efficiencies of research activities• Collaborating with University organizations involved with human research

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• NIH increasingly promotes translational collaborationsamong basic science and clinical research programs

• SCCORs, PPGs, U01s illustrate interplay of translationalscience, requiring data integration across the entireresearch enterprise (basic, translational, clinical)

• Biostatistics -- fundamental challenge at the dataanalytic stage, incorporating data elements from allsources into comprehensive risk and/or efficacy models

• Data management systems -- typically isolated, notinter-operable -- inadequate to support biomedicalresearch informatics needs at Research Enterprise level

Introduction

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• Successful conduct of clinical and translational sciencerequires biomedical and clinical research informaticsi) methods, ii) tools, and iii) fully integratedinformatics highway

•• Integrative Informatics --Integrative Informatics -- despite considerableprogress in specialized areas of bioinformatics toharness complex genomics, proteomics and lipidomicsdata structures, the challenges associated withsupporting an integrated (biomedical, clinical research,and health system informatics) clinical and translationalscience research enterprise are formidable

Introduction (cont’d)

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•• Data IntegrationData Integration -- most foundationalchallenge is the need for an integrated datainfrastructure spanning fully the genotype andphenotype (i.e., molecular and clinical attributes)of research subjects and patients

•• Individual Data RecordIndividual Data Record -- relevant data fromthe basic science, translational, clinical research,and health care domains need to be fullyintegrated at the individual data record, in orderto produce “personalized medicine” models

Challenges

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• Motivating example -- consider how thewithdrawal of Vioxx and Bextra (due torecognition that they confer a small, butabsolute incremental cardiovascular risk)presents a problem for celebrex and new cox-2inhibitors, such as prexige (lumiracoxib)and arcoxia (etoricoxib)

• Wish to harvest recognized efficacy, but alsomanage the overall increased absolute risk

Challenges (cont’d)

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•Translational researchers want access tomultiple data enterprises to producerefined estimates of risk and efficacy atthe individual patient level

•Data are required from the …- Basic Science Research Enterprise,- Clinical Research Enterprise, and- Clinical (Health Care) Enterprise


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Basic Science Research Enterprise:• phenotypic data collected in model systems –

e.g., zebrafish, in which the coxs have beengenetically manipulated, or in which COXmutations have been detected, or in micetreated with cox-2 inhibitors, in whichCOX-2 or COX-1 have been manipulated(knocked out, knocked down, globally orselectively, or over-expressed) may informhuman genomic association patterns


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Basic Science Research Enterprise (cont’d):• cellular imaging data from model systems in

which COX-2 has been manipulated (deleted,over-expressed of knocked down) may alsocontribute insights

• lipidomic analyses of the consequences of COXmanipulation in cells, tissues from mice, fish orpeople in body fluids may provide insights intoclinical applications


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Clinical Research Enterprise:• individual data from randomized trials and / or

observational studies relating to CV events, GItoxicity and concomitant therapy;

• Patient samples for analysis of drug levels andbiomarkers of response / risk;

• individual response data, such as efficacy and/orblood pressure data;

• more detailed studies of drug response in smallnumbers of patients within GCRC setting.


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Patient-specific Risk / Efficacy Models-- goal of personalized medicine is the daywhen each potential patient could say …

"this is the particular drug thatworks specifically

for me"!


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• Disease-specific data integration efforts haveled to narrow-scope tools utilizing centralizedand highly specific data warehouses

•• Data IntegrationData Integration – to be transformational,clinical and translational medicine researchneeds comprehensive disease-independent,enterprise-wide data integration and analysisapproaches, in order to achieve personalizedmedicine goals


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Breadth of this undertaking necessitates …• a federated data acquisition, storage and

analysis strategy

• an enterprise-wide commitment and investmentin a comprehensive vision

• a complex technology base with interoperabledata standards and systems

• talented, multi-disciplinary personnel dedicatedto realizing this vision


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This talk will promote a vision for a transformedenterprise-wide informatics framework for theconduct of clinical and translational science …

• a centralized computational architecture andresearch data facility

• an integrated biomedical and clinical researchinformatics toolkit

• an integrated biomedical informatics highwaywith connectivity among all data repositories

Vision

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Multi-disciplinary team of facultyinvestigators and technology leaders

- biostatistics,- bioinformatics,- biomedical/clinical research informatics,- computer science, and- computational biology.

Vision: A New Center for BiomedicalInformatics in Translation (BIIT)

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BIIT will provide …..• new informatics connectivity between CHOP

and PENN, permitting enterprises to attaincommitment to data interoperability,integration, and sharing between institutions;

• provide comprehensive research informaticssupport for the biostatistical methods andstatistical genetics research computing anddata analyses required for enterprise-wideclinical and translational science.

Vision: Center for BiomedicalInformatics in Translation (BIIT)

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Integrated Biomedical and Clinical Research InformaticsIntegrated Biomedical and Clinical Research Informaticsfor Translational Medicine and Therapeuticsfor Translational Medicine and Therapeutics

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BIIT will provide …• a PENN Center for Clinical Research Informatics –

an enterprise-wide organization formed to coordinateclinical research informatics standards, tools and theconduct of clinical research studies; enhancedcoordination and connectivity between clinical, clinicalresearch, and basic research units and groups withinCHOP, leveraging its ongoing efforts in informatics;

• a PENN Research Data Center – a consolidatedfacility for biomedical and clinical research informaticsresources, with coordinated, centralized IT resourcesand services;

Vision: Center for BiomedicalInformatics in Translation (BIIT)

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Integrated Biomedical and Clinical Research InformaticsIntegrated Biomedical and Clinical Research Informaticsfor Translational Medicine and Therapeuticsfor Translational Medicine and Therapeutics

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Vision: Industry Partnerships

Oracle Corporation and Penn CTSA –– Oracle Clinical (OC) Trials Applications

… a comprehensive clinical data management solution Remote Data Capture (RDC) Thesaurus Management System (TMS) Adverse Event Reporting System (AERS)

– Health Care Transaction Base (HTB) … a platform for integration, development, and

operation of healthcare applications.

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• Oracle Clinical (OC) -- standardization and control of datadefinitions and data usage across a large-scale clinicalresearch enterprise, ensuring that data elements aredefined, managed, and interpreted consistently

• OC -- integrated suite of applications (Oracle Clinical TrialApplications) supporting clinical research process

-- Remote Data Capture (RDC) - enter and managedata from the investigative site

-- Thesaurus Management System (TMS) - classify terms against medical dictionaries

-- Adverse Event Reporting System (AERS) - manageand report safety data


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• Site participation requires effort such as budgeting, trackingenrollment, scheduling and conducting patient visits, and managingpayments. Data may be in disparate systems such as spreadsheets,making it difficult to get a view of trials underway, exposed the siteto inaccuracies, and leading to delays as information is reconciledthat can affect the conduct of the trial and willingness of the sitesto participate in future trials.

• Sponsors, CROs, and sites need tools to manage site information.• Oracle offers an application for tracking trial administrative and

financial data - SiteMinder for sites or TrialMinder for sponsorsand CROs. It includes: (i) site personnel and contact information,(ii) site events such as visits, (iii) management of patientscheduling and visits, (iv) Contracts and budgeting, (v) Paymentsdue and owed, and (vi) Generating and tracking documents.


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• Data Integration Models – at the health careenterprise, driven by the business-orientation andcompelling business needs for integratedinformation.

• Lessons learned can be extended to Research.

• An example of a mature Health Care Enterprisesolution that could be applicable to research isOracle HealthCare Transaction Base (HTB)


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• HTB -- platform for integration, development, andoperation of healthcare applications

• A comprehensive data repository and standards-basedinformation model, coupled with integrated services fordata normalization, customer-defined security andauditing, and business process / workflow.

• Supports meaningful data consolidation and genuineinter-operability among different systems.

• HTB offers a clinical infrastructure based on industryinformation standards– HL7 version 3 ReferenceInformation Model (RIM)


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Pharma Partners and Penn CTSA -a Regional Research

Information Organization (RRIO)


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•• Regional Health Information OrganizationsRegional Health Information Organizations((RHIOsRHIOs) are developing to share data) are developing to share data

•• Regional Research Information OrganizationsRegional Research Information Organizations(RRIO) could be formed for a similar purpose,(RRIO) could be formed for a similar purpose,e.g., GSK and Penne.g., GSK and Penn

•• Clusters of Clusters of RRIOsRRIOs could form the basis for the could form the basis for theNIH Roadmap NIH Roadmap ‘‘National Electronic ClinicalNational Electronic ClinicalTrial and Research NetworkTrial and Research Network’’ (NECTAR) (NECTAR)


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GSK and RRIOGSK and RRIO

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•Tomorrow’s ‘translational knowledge’ isdeveloping and accumulating today in thefoundational form of information and data.

•This information will be converted toknowledge via a ‘data organization andanalysis partnership’ between Clinicians,Investigators, Biostatisticians, andInformaticians.

Conclusions

Documents

“Integrated Biomedical and Clinical Research Informatics for