Jeffrey S. Barrett, Kalpana Vijayakumar, Sundararajan Vijayakumar, Dimple Patel, Mahesh Narayan, Bhuvana Jayaraman, Erin Cummings, Steven Douglas Laboratory for Applied PK/PD, Division of Clinical Pharmacology, The Children’s Hospital of Philadelphia, PA Managing Disparate Data Generated from Translational Research Activities: iClinical Implementation to Support Data Integration and Sharing for the IPCP BACKGROUNDDESIGN AND METHODS OBJECTIVES  To effectively capture IPCP translational data, protocols and define the framework for comprehensive data collection.  Enforce metadata and dictionary standards right at the source and/or allow them to be mapped between systems  Route the data for review and approval and notify data consumers and project team alike  Standardize the data and results to enable meta-analysis across studies  Provide analysis ready datasets and track results from analysis.  The IPCP-iClinical web interface will serve as a common platform to bring translational research data across projects from different institutions and streamlines the data capture process and efficiently stores research data for public data sharing, analysis and reporting.  Centralized data and document storage, automated routing for review, correction and approval, capture interim data status, export raw data and import analytical results, gate access to entire study or sub-domain of study while limiting user operations on such data.  iClinical thus promotes collaborative study engagement both within the organization and external collaborators, including project sponsors such as the NIH and gated access to the broader research community.  The solution is easily accessible over the web and provides secure and encrypted access for both internal users and external sponsors, collaborators and the NIH.  Sharing data is an essential part of current multidisciplinary research program supported by the NIH and has defined the need for integrated data solutions for many academic medical research programs.  The Integrated Preclinical Clinical Program (IPCP) is an NIH grant mechanism that supports preclinical to clinical investigations for the discovery and development of new therapeutics targets for HIV infection.  The program consists of three cores with four inter-related projects. Core A serves as an administrative core. Core B provides HIV antiretroviral drug susceptibility and drug Interactions. Core C provides biostatistics and pharmacology. The four projects to identify neurokinin-1 receptor (NK1- R) antagonist for HIV therapy are recognized by number.  Project 1 investigates the mechanisms involved in the NK-1R substance P (SP) preferring receptor, antagonist-mediated anti-HIV activity in human immune cells.  Project 2 investigates the anti-viral, molecular and cellular immunologic mechanisms.  Project 3 investigates the SIV disease progression, effects of SP level, and neurophysiologic and neurobehavioral studies in Rhesus.  Project 4 investigates the safety, viral suppressive potential, pharmacokinetics in HIV-infected individuals and immune modulatory effects of treatment with aprepitant.  The program generates a large number of translational data from all four projects including basic science, PK/PD, safety and efficacy, laboratory, protocol, and in vitro/in vivo data in addition to reports and documents obtained from these experiments.  To comply with NIH data sharing requirements, an integrated data environment, iClinical, has been developed as a web-based tool to provide secure data storage, data sharing, analysis, and reporting capabilities. Pilot data from IPCP Projects 1 & 2 are analyzed in iClinical and accessible via the web. iClinical is an integrated data solution that can accommodate in-vitro, in-vivo and human clinical trial data at multiple levels of granularity and organization. Figure 1 shows the various component tiers. Figure 2 shows the summary of IPCP project data flow diagram into iClinical System and shows the modules for input of new data to pull together loosely coupled study data or supportive experimental data, and results from mathematical data analysis and predictive modeling. Figure 1: iClinical Component Tiers The system integrates and cross-links data from the above streams and making them available for drill down analysis within a study, meta-analysis across studies, data summarization and generation of tables and listings for reports. Data imported into iClinical is defined by association with corresponding data items in the central data dictionary. This allows users the ability to map multiple user defined dictionaries into one central dictionary or to external standards such as the CDISC. Benefits include the ability to define derived columns, unit standardization, enforcement of allowed values, translation of data coding tables into allowed values and most importantly enabling meta-analysis across studies and predictive results. The data that is mapped into the dictionaries can then be summarized and viewed via any number of canned reporting templates or one created on the fly. DESIGN AND METHODS Preparing the data files is as simple as preparing data in ASCII comma separated value (.csv) or MS Excel file. The uploaded files are captured as-is with appropriate date/time stamps, data ownership and versioning as well as parsed into the central data mart for easy searching. Access to data within iClinical is password protected and made available for browsing, updating, reporting, exporting or importing based on the roles granted to each user. iClinical is accessible via the web in a secure encrypted session fully compliant with the Code of Federal Regulations, 21-CFR-11. Figure 2: IPCP-iClinical Overview Using iClinical RESULTS Figure 3. User’s have an option to filter by dataset with variable of interest and stratify plot types on available subgroups. Figure 4. Shows the plots by selected drug and subgroups. * Various views of the IPCP data in iClinical system RESULTS CONCLUSIONS