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Xbiom 3.0 SaaS SuiteSmart Transformation

Machine Learning and AI augmented transformation of Clinical and Biomarker Data for semantically harmonized access

PhUSE Connect 2018

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Agenda

Ø Xbiom SaaS Suite

üModular, on the cloud, software as a service covering clinical and biomarker data for research insights or regulatory

Ø Xbiom Smart Transformation

üArtificial intelligence and machine learning augmented transformation of raw as-collected data from data lakes into standardized, usable, accessible, searchable repositories

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Xbiom© Suite for Research & Regulatory in Clinical & Nonclinical

Insights: Nonclinical

Roche, FDA & CTP

Insights: Clinical And Biomarker

Bayer

Xbiom™ built on

Orchestra™ Platform

MySEND – Free Downloadable Desktop tool

Regulatory: NonclinicalRoche, Bayer, Sanofi, Ipsen, Eisai, DaiIchi

Sankyo

Regulatory: Clinical

Ipsen

Smart Transformation

DataStandardization

SEND-ASSURE Services

Insights: Pre-clinical

Discovery

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Xbiom - Supporting the Research Cycle

Functional Markers

Omics

InformedConsent

RWD

Bio -samples

Digital Pathology

Think

Assess

Search

Find

View

Immersive,Interactive

PK/DMPKCDMS/EDC

Medical History

Registries

Nonclinical Toxicology

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Xbiom Suite - Data for Development and ResearchData Mapping Meta data store Data Exploitation

Metadata Governance

Xbiom Insights Clinical & Biomarker

Xbiom Insights Nonclinical

Xbiom Regulatory Clinical

Xbiom RegulatoryNonclinical

Taxonomy and Unit

Harmonization

SDEEDC/CDMS/CROs

Legacy Studies

Registries

Real World Data

Templates

Specify

Valid

atio

nSmart

Transformation

SaaS

SaaS

Standardized Data

UDM

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Xbiom Insight Process for Legacy and RWD

Study LifeCycle

Data Validation, Consistency Checks

Insights

Documentation Search

Curation and Smart Transformation

(Discovery)(Preclinical)Nonclinical

ClinicalBiomarkers

OMICs

Metadata and Terminology governance

Ontologies

metadata

VDRdata

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CURATION AND SMART TRANSFORMATION

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Curation and Smart Transformation

Ø Purpose

ü Curate by looking up Data Lake through Search

ü Transformation Facility to automatically identify re-usable data from raw,

legacy or incoming sources.

ü Conversion recommendations of selected data from batches of studies into

Structured/Standard format for searchable repository

Ø Benefits for Users

ü AI machine learning algorithms use Training sets (Data) & Terminology

Governance to recommend mappings

ü “Exception based decisions” for Data Managers to save time

ü Data Validation and QC dashboards to review Data Consistency, Data Formats

& Terminology issues

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Machine Learning Algorithms

Ø Artificial Neural Networks based Machine Learning Algorithms

Ø Pre-trained with Clinical, Non-Clinical and Biomarkers data, and continually learns based on user applied mapping and transformation decisions

Ø Recommendation algorithms for data mapping, transformation functions and data pivots.

Ø Recommendation algorithms for Terminology Normalization based on many industry standard databases – CDISC CT, MedDRA, WHODD, GeneInfo, UniProt, miRBase,…

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Transformation Facility – High level steps

Start

Create a Batch

Select,§ Source§ Studies§ Target Model§ Applicable CTs

Save & Initiate Process

Transformation

Dataset Transformations

Metadata Mappings

TerminologyNormalization

Normalization to External dictionaries

Additional Transformations

Validation and QC Check on

generated Outputs

View Output files

Validation

Preview in each stage

Store output files in destination

End

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XBIOM SMART CURATION DEMO

1. Metadata mappings (Direct, expression, transpose mappings)2. Preview of Mapping definitions3. Terminology normalization4. Output file

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