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PhUSE SDE09Nov2017

DATA VISUALIZATION STRATEGIES FOR ANOMALY DETECTION

Agenda

- Introduction

- Defining the Challenge

- Data Anomaly Use Cases

- Working Group 3 Plan

- Call for Action

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Introduction

- Transformative

- Interactive data visualizations

- Incorporating unsupervised anomaly detection

- Early detection and action

WHY IS IT IMPORTANT?

3Image Credit: Steffen Ruefer https://www.r-bloggers.com/outlier-detection-with-mahalanobis-distance/

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Data Anomaly Case 1

DATA QUALITY

Labs– XULN: Data Error

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Other Data Anomaly Use Cases

SIGNAL DETECTION

• Safety Trend across patient groups within a study• Data aggregated across studies for a given compound compared to norm

FRAUD DETECTION• Distribution of Assessment Dates – By Site• Event time to time event reported• Distribution of Measurements

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Working Group 3

- Identify and recommend best practices for systematic approach to detecting anomalies

- Planning

- Literature Review is ongoing- SME Guest Speakers Q4 2017 /Q1 2018- White Paper Comparison of Available Tools Q2 2018

DELIVERABLE GOAL AND PLANS

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Call for Action – Join Us

NEW MEMBERS ARE WELCOME!

Paul Schuette FDAElena Rantou FDAMitch Cooper Eli Lilly and CompanyJasmine Sen BayerMichael Rubison CapishBhaskar Dutta Astra Zeneca

Eric Herbel Integrated Clinical SystemsHeather Stevens Covance

Please contact Lauren White [email protected] to join.

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