© 2014 PerkinElmer

HUMAN HEALTH • ENVIRONMENTAL HEALTH

Innovations in Clinical Accelerating Insights & Data-Driven Decisions

Masha Hoffey Director, Clinical Analytics

15 September 2016

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

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.

Introduction Accelerate Insights with PerkinElmer Innovations in Clinical Analytics

Clinical/Medical Data Review

Safety and PV Risk-Based Monitoring

Clinical Operations

Spotfire in Clinical Development

Health Outcomes & RWE

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?

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

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?

• …

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

Clinical and Medical Data Review Risk-Based Monitoring

Innovation Spotlight: CDR & RBM

Persona-Driven Guided Workflow

Holistic Data Provisioning

Alerts Workflow Exploratory Workflow Line Listing Review

CRA Dashboard Central Monitor View Closed-Loop Monitoring

Study setup automation Extracts Management and Versioning SDTM Data Standardization

Study setup automation Data Source Identification Data Normalization

Advanced Analytics

Predictive risk views Adaptive monitoring Legacy data analysis and tolerance limits

Signal detection Time to response analysis Survival analysis

Clinical Data Review Alerts Workflow Option, Extract Management, Data Standardization

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

Workflow Configuration: Alerts-Driven and Exploratory Workflows

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

Reduce drug development duration

Streamline root-cause analysis Save costs by identifying issues early

View all alerts or filter based on status or timeline

Line Listing Review and Queries

Mark records as “read” or “reviewed”

Raise queries about specific data points

Access full review history and audit trail

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

Advanced Analytics: Enhance Clinical Data Review with Advanced Analytics Built in R

TIBCO Enterprise Runtime for R (TERR) allows you to code n open-source 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

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”

Reduce cycle time to analysis with

expedited SDTM standardization

Merging and versioning of study data extracts to enable historical analysis

SDTM data standardization for study pooling and cross-study analysis

Study setup automation

PerkinElmer Data Services

PerkinElmer SignalsTM

Perspectives

PerkinElmer SignalsTM

Perspectives

Risk-Based Monitoring Closed-loop Monitoring Workflow, Adaptive Monitoring, and Data Normalization

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

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

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

Advanced Analytics: Unlock the Value of Historical Data Assets

Regression modeling and advanced statistics offer a feedback loop on the historical performance of the risk model

Adjust KRI algorithms, weightings, thresholds, and recommended actions based on risk model assessment

Apply out-of-the box regression analysis, advanced statistics, historical analysis and predictive modeling to: 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

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 SignalsTM 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.

Clinical Application Framework Looking Ahead: Combining Workflow, Holistic Data Provisioning, and Advanced Analytics

PerkinElmer Clinical Application Framework: “One Stop Shop” for Clinical Data insights

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

Clinical Application Framework Conceptual Roadmap

This document shows current intentions regarding product features, behavior, schedules and support;

these intentions may change without notice as we respond to customer requirements.

1.0 2.0 1.5

Medical Monitor Workflow Workflow Configuration

Patient Narratives

Med

ical

Rev

iew

R

BM

Data Manager Workflow Biostatistics Workflow

RW

E Clin

ical

Wo

rkfl

ow

Mo

du

les

Automatic Study Setup and Data Provisioning

Advanced Analytics and Statistical Modeling

Audit Trail Cloud infrastructure

Audit Trail CRA Dashboard Threshold Modeler Recommended Actions

Action Logging Tolerance Limit Definition Cohort Builder

Data Source Discovery

Analytics Workflow: Before

This document shows current intentions regarding product features, behavior, schedules and support;

these intentions may change without notice as we respond to customer requirements.

Separate analysis file for every study and analytics use case

Retention of audit trail requires custom functionality User administration and security

management handled in separate interface

Data mapping is configured on a per-study and per-analysis basis

Analytics Workflow: PerkinElmer Clinical Application Framework

Single web application for all clinical analytics solution modules

This document shows current intentions regarding product features, behavior, schedules and support;

these intentions may change without notice as we respond to customer requirements.

Full audit trail and centralized system administration

Single interface for user management and definition of system roles

Analytics Workflow: Before

This document shows current intentions regarding product features, behavior, schedules and support;

these intentions may change without notice as we respond to customer requirements.

Ability to mark records or raise queries requires custom functionality

Workflow based on tab navigation in Spotfire User needs to know how to filter and mark data

Multiple visualizations and analyses can be difficult to navigate

Analytics Workflow: PerkinElmer Clinical Application Framework

This document shows current intentions regarding product features, behavior, schedules and support;

these intentions may change without notice as we respond to customer requirements.

Full power and flexibility of Spotfire analytics

Guided analytics experience based on user roles and permissions

Persona-driven views and workflows

Out-of-the-box ability to mark records, raise queries, and send notifications

Simplified, intuitive filtering and curated visualizations

Automatic Study Provisioning and Mapping: PerkinElmer Clinical Application Framework

This document shows current intentions regarding product features, behavior, schedules and support;

these intentions may change without notice as we respond to customer requirements.

Automatic study setup and data provisioning

Easily configure data upload frequency

Adjust field mapping to analysis standard

Thank You