Innovations in Clinical
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1 Innovations in Clinical Accelerating Insights & Data-Driven Decisions Masha Hoffey Director, Clinical Analytics 15 September 2016 HUMAN HEALTH ENVIRONMENTAL HEALTH 2014 PerkinElmer
2 Contents Introduction Innovating to accelerate insights: Workflow, Advanced Analytics, Data Provisioning Innovation Spotlight: CDR Guided workflow, SDTM standardization Innovation Spotlight: RBM Closed-loop integrated monitoring workflow, leveraging legacy data Innovation Roadmap: Clinical Application Framework Single framework, modular solutions
3 Safe Harbor Statement This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements. 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 Introduction Accelerate Insights with PerkinElmer Innovations in Clinical Analytics
5 Spotfire in Clinical Development Clinical/Medical Data Review Clinical Operations Health Outcomes & RWE Safety and PV Risk-Based Monitoring
6 The Workflow Problem: Where is the Actionable Data? How do find the analysis I need? How do I know the data is current and actionable? How do I navigate the analysis to find the data points I m looking for? How do I act on the data?
7 The Analytics Problem: The Need for Faster, Smarter Data-Driven Decisions Competitive pressure for: Smarter decisions: pervasive advanced analytics beyond the data science community Faster decisions: both human and automated Need for agile analytics: Data questions and answers change rapidly Analytics must be adaptive
8 The Data Problem: There s More to Data Insights than Analytics Clinical Analytics Can studies be set up automatically? Are the data sets compatible? Can they be standardized? Can they be integrated? Can I look across historical snapshots of data? Can I perform analysis across multiple studies? How quickly can I access the data?
9 Clinical Innovation Focus Areas Persona-Driven Guided Workflow Integrated role-based insights to reduce drug development duration Curated analytics experience to streamline root-cause analysis Immediate access to actionable data for faster data-driven decisions Advanced Analytics TERR for advanced statistics and predictive modeling Legacy data analysis to unlock value of legacy data assets Alignment with TIBCO Roadmap for fastest analytics innovation Holistic Data Provisioning Ability to normalize and standardize clinical data Manage data extracts Easily provision data for analytics from multiple data sources
10 Innovation Spotlight: CDR & RBM Clinical and Medical Data Review Persona-Driven Guided Workflow Alerts Workflow Exploratory Workflow Line Listing Review Advanced Analytics Signal detection Time to response analysis Survival analysis Holistic Data Provisioning Risk-Based Monitoring CRA Dashboard Central Monitor View Closed-Loop Monitoring Predictive risk views Adaptive monitoring Legacy data analysis and tolerance limits Study setup automation Extracts Management and Versioning SDTM Data Standardization Study setup automation Data Source Identification Data Normalization
11 Clinical Data Review Alerts Workflow Option, Extract Management, Data Standardization
12 Clinical Data Review Provides access to a 360 degree view into Patient Demographics, Adverse Events, Labs, Vitals/ECG results and other safety domains Increases agility by allowing interactive exploration of unexpected trends & hidden relationships Enables rapid medical review of clinical data through intuitive navigation of population and subject-level data Provides fast and accurate data quality assessment through fraud detection and visibility into data quality issues Facilitates process improvement by allowing early identification of study issues and dimension-free data exploration Navigate population-level and domain-level views Select sub-populations for analysis Easily navigate to subject-level data with Patient Profile
13 Workflow Configuration: Alerts-Driven and Exploratory Workflows Reduce drug development duration Streamline root-cause analysis Save costs by identifying issues early Explore trends in population-level data to select a sub-population for analysis or follow configurable therapeutic-area Alerts directly to the Patient Profiles of relevant subjects View all alerts or filter based on status or timeline
14 Line Listing Review and Queries Mark records as read or reviewed Raise queries about specific data points Mark records directly in analysis for accelerated data-driven decisions Access review history audit trail for 21 CFR part 11 compliance and meet validation requirements Access full review history and audit trail
15 Advanced Analytics: Enhance Clinical Data Review with Advanced Analytics Built in R TIBCO Enterprise Runtime for R (TERR) allows you to code n opensource R directly in Spotfire with many built-in analytics methods and supported R packages Embed advanced analytics directly into the analysis to extend advanced data insights beyond the data science community Smarter data insights with advanced analytics, including: Relative Risk Time to Response Analysis Survival Analysis Time to AE Analysis
16 Automate Study Setup, Manage Data Extracts, Expedite Data Standardization Reduce cycle time and medical monitoring costs with study setup automation Enable CRO oversight and leverage historical data with historical analysis across data snapshots PerkinElmer Data Services Study setup automation PerkinElmer Signals TM Perspectives Merging and versioning of study data extracts to enable historical analysis Reduce cycle time to analysis with expedited SDTM standardization PerkinElmer Signals TM Perspectives SDTM data standardization for study pooling and cross-study analysis
17 Risk-Based Monitoring Closed-loop Monitoring Workflow, Adaptive Monitoring, and Data Normalization
18 Risk-Based Monitoring Simplifies Risk-Based Monitoring with intuitive dashboard displays Enables flexibility by providing a vendor and data-agnostic solution designed to work with multiple clinical data sources Supports adaptive design and adaptive monitoring through modeling of KRI algorithms, thresholds, weightings, and recommended actions Provides risk model assessment and feedback loop through timeline analysis, geographic views, and regression modeling Leverages historical data assets through the analysis of legacy data to establish tolerance limits for risk categories Dashboard view into TransCelerate-aligned Risk Indicators, Category-Level Indicators, and Overall Site Indicators Timeline view to assess the impact of recommended actions on risk signals Geographic view of indicators and risk levels for resource management and root-cause assessment
19 Persona-Driven Views Simplify RBM through role-based guided workflows, users only see what they need Reduce monitoring cycle time through fastest access to actionable data The CRA is able to view and investigate risk Indicators for assigned sites The Central Monitor is able to navigate the overall risk model and drill down to site-level details
20 Closed-Loop Monitoring Save time by following up on recommended actions directly in the analysis Use the feedback loop to learn what is working and easily adjust recommended actions Optimize trial design and QbD by leveraging historical data on recommended actions CRA updates status and comments for recommended actions Status is automatically updated Action status can be reviewed and actions modeled according to impact assessment
21 Advanced Analytics: Unlock the Value of Historical Data Assets Apply out-of-the box regression analysis, advanced statistics, historical analysis and predictive modeling to: Regression modeling and advanced statistics offer a feedback loop on the historical performance of the risk model Apply adaptive monitoring, adjusting risk model in response to data Derive statistically meaningful tolerance limits for risk categories (an ICH E6 R2 requirement) Assess site feasibility Improve trial design Adjust KRI algorithms, weightings, thresholds, and recommended actions based on risk model assessment
22 Data Normalization and Provisioning Enable cross-study analysis and study pooling by expediting the normalization of source data Lower cost of ownership and reliance on IT with Signals TM Perspectives, providing a lightweight, virtual alternative to traditional warehousing Reduce time to analytics insights by provisioning data to analytics without impacting source system performance Discover joins between data sources to explore the full picture view of risk across multiple clinical source systems, trackers, etc.
23 Clinical Application Framework Looking Ahead: Combining Workflow, Holistic Data Provisioning, and Advanced Analytics
24 PerkinElmer Clinical Application Framework: One Stop Shop for Clinical Data insights
25 Streamlined Workflow, Curated Analytics With PerkinElmer s new Clinical Application Framework: Convenience: single, hosted web application for all clinical analytics modules Process Efficiency: intuitive analytics workflows tailored to user role Cost Savings: agile and automatic data normalization and provisioning Smart Insights: built-in advanced and predictive analytics Faster Decisions: direct access to actionable data, closed-loop workflow Quality by Design: leverage data to enhance trial design, site selection, analytics workflows Security and Compliance: secure cloud infrastructure, 21 CFR part 11 compliance Persona-Driven Workflow Automatic study setup and data normalization TIBCO Spotfire visualizations, enhanced with advanced analytics Actionable Data Insights
26 RWE Clinical Workflow Modules RBM Medical Review Clinical Application Framework Conceptual Roadmap Medical Monitor Workflow Workflow Configuration Audit Trail Cloud infrastructure Cohort Builder Data Source Discovery Audit Trail CRA Dashboard Threshold Modeler Data Manager Workflow Biostatistics Workflow Patient Narratives Recommended Actions Action Logging Tolerance Limit Definition Automatic Study Setup and Data Provisioning Advanced Analytics and Statistical Modeling This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements.
27 Analytics Workflow: Before Separate analysis file for every study and analytics use case Data mapping is configured on a per-study and per-analysis basis Retention of audit trail requires custom functionality User administration and security management handled in separate interface This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements.
28 Analytics Workflow: PerkinElmer Clinical Application Framework Single web application for all clinical analytics solution modules Single interface for user management and definition of system roles Full audit trail and centralized system administration This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements.
29 Analytics Workflow: Before Workflow based on tab navigation in Spotfire User needs to know how to filter and mark data Ability to mark records or raise queries requires custom functionality Multiple visualizations and analyses can be difficult to navigate This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements.
30 Analytics Workflow: PerkinElmer Clinical Application Framework Guided analytics experience based on user roles and permissions Persona-driven views and workflows Simplified, intuitive filtering and curated visualizations Full power and flexibility of Spotfire analytics Out-of-the-box ability to mark records, raise queries, and send notifications This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements.
31 Automatic Study Provisioning and Mapping: PerkinElmer Clinical Application Framework Automatic study setup and data provisioning Easily configure data upload frequency Adjust field mapping to analysis standard This document shows current intentions regarding product features, behavior, schedules and support; these intentions may change without notice as we respond to customer requirements.
32 Thank You
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