© 2014 PerkinElmer

HUMAN HEALTH • ENVIRONMENTAL HEALTH

Innovations in Clinical Analytics Accelerating Insights & Data-Driven Decisions

Mark Demesmaeker

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 Challenge: 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 Challenge: 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 Challenge: 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 Workflows 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 Workflows

Alerts Workflow Exploratory Workflow Line Listing Review

CRA Dashboard Central Monitor View Closed-Loop Monitoring

Holistic Data Provisioning

Study setup automation Extracts Management and Versioning SDTM Data Standardization

Study setup automation Data Source Identification Data Normalization

Advanced Analytics

Predictive risk modeling Adaptive monitoring Legacy data analysis and tolerance limits

Signal detection Time to event analysis Risk difference

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

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

Why Risk-Based Monitoring

• Traditional 100% SDV-based, scheduled monitoring approaches are costly and not effective in identifying issues with critical data and processes ◦ Mostly transcription errors are discovered ◦ Resources are not directed where they are most needed

• Risk-based monitoring shifts the focus from scheduled site visits to a targeted and adaptive monitoring and SDV approach, increasing patient safety and data quality while decreasing unnecessary resource costs

• RBM is recommended by regulatory bodies and the focus on RBM will increase with the upcoming GCP guidance, ICH E6 R2

• An effective RBM strategy should include a flexible, data-agnostic visualization platform, an integrated workflow solution, and advanced analytics to leverage the value of historical data assets in enhancing the monitoring strategy and trial design

…Members of TransCelerate have identified clinical

study execution as the initiative’s initial area of

focus. Five projects have been selected by the

group for funding and development, including:

development of a shared user interface for

investigator site portals, mutual recognition of study

site qualification and training, development of risk-

based site monitoring approach and standards,

development of clinical data standards, and

establishment of a comparator drug supply model.

RBM Overview

Risk Assessment

Categorization Tool (RACT)

ICH E6 R2- coming Nov 2016/early 2017

• Increased focus on Sponsor responsibilities for vendor oversight

• First mention of risk-based approach to quality in a GxP guidance (-> centralized Quality Risk Management (QRM) system)

• Focus on traceability in decision making and a metrics-based approach

• Need for tolerance limits for specific risk areas- what is the tolerated, systemic level of risk for a particular risk area

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

The Adaptive Risk Model: Beyond Visualization

Risk Trigger

Recommended Action

Action Follow-up

Action Impact Assessment

Risk Model Evaluation

Risk Model Adjustment

Site 104 is in the red category for the Protocol Deviations

KRI because while the count of minor violations is below

the average, there is a high proportion of major

violations.

A Site Visit has been recommended for the CRA based

on the Protocol Deviation Indicator. The CRA completes

the Action and adds Comments.

The Central Monitor is notified that the

Recommended Action has been

completed.

The Central Monitor can assess whether the

Action had an impact on the Protocol

Deviation Indicator.

The Central Monitor evaluates the Risk Model.

What is the historical correlation between:

o Visits at Site 104 and the Protocol

Deviation Indicator?

o Between Visits and other Key Risk

Indicators?

o Between Visits and the Protocol Deviation

Indicator across Sites?

Regression modeling and predictions based

on:

o Analysis of Indicators and other Indicators

o Analysis of Indicators and Actions

o Analysis of Indicators and Monitor

Comments

o Analysis against baseline and legacy

data

The Central Monitor adjusts Indicator Thresholds, KRI

Weightings, and Recommended Actions. The Risk

Model evolves based on monitoring impact and

adapts based on changing risk.

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

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

Key Framework Features

Persona-Driven Guided Workflows • 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

Secure Cloud Infrastructure • Multi-tenant and virtual private cloud options for secure, scalable architecture

Unified Framework • Single web application, modular clinical solutions to accelerate adoption

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

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

TIBCO Enterprise Runtime for R (TERR) allows you to code 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

Holistic Data Provisioning

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

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

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

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

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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

Thank You! mark.demesmaeker@perkinelmer.com