From molecule to market:
Delivering on the promise ofreal-world data
Real-world data (RWD) is revolutionizing how biotech and pharmaceutical organizations develop, deliverand measure the effectiveness of medical treatments in the real-world. Yet, most organizations struggle totransform their large volumes of unstructured RWD into novel insights. Generating real-world evidence (RWE)
at scale requires a new approach to data and AI that can only be achieved with a modern data lakehouse.

What is real-world evidence?
Real-world evidence is generated from data collected outside of a traditional clinical trial. This data — called real-world
data — is gathered from sources like electronic medical records, claims, and wearable devices. These data sets provide
novel insights into the usage, and potential benefits or risks, of a drug.

Hospital
EHR’sPatientRegistries

BiomedicalImages

Wearables

Pharmacy
ClaimsREAL-WORLDDATA INSIGHTS

Opt-inGenomeRegistries

PrivatePayers andPlan Claims

Government
Health PlanClaims

SocialMedia

Real-world Evidence Use Cases

Regulatory
ApprovalDrug
SafetyTrial
DesignCoverage
Decisions

EarlyIntervention

Regulators see

Longitudinal RWE

Drug makers can use

Healthcare

Integrated riskhuge promise instudies can replace

RWE to improve thecompanies can use

reports built from

RWE to help

or supplement

design of clinical

RWE to develop

diverse sets ofaccelerate thevoluntary reporting

trials and fast-track

guidelines andRWD help identify

approval process

to provide real-time

the development of

support coveragepatients who arefor new

insight on efficacy

new therapies.

decisions.

at high risk fortreatments.

or adverse effects.

chronic conditions.

Databricks for Real-World Evidence

Real-world evidence at scale with the Databricks Lakehouse Platform
Bring together all of your real-world data into a single, open and collaborative platform, that supports all of your analytics
and AI workloads.

A L L YO U R R E A L-WO R L D DATA
EHR

Semi-structured

ClaimsSemi-structured

Imaging

Unstructured

Social media

Unstructured

Genomic
Disease registry

Structured
Semi-structured

Medical IoT

Unstructured

Provider notes

Unstructured

Billing and payments

R E L I A B L E , R E A L-T I M E
PROCESSINGA N A LY T I C S A N D A I C A PA B I L I T I E S
F O R E V E RY U S E C A S E

Regulatory Approvals
Drug Safety Monitoring

DATA L A K E H O U S E
Process, manage andquery all your data

Clinical Trial Design
Coverage Decisions
Early Intervention

Structured

Challenge

The Databricks Lakehouse Solution

Real-world data is messy

Ingest and curate all your real-world data

A major challenge in generating reliable evidence

Bring together all your structured and unstructured datafrom real-world data is transforming the data from its

in a single platform for data + AI. Databricks’ partner

raw unstructured form to a proper data model that issolutions make it easy to ingest unstructured real-world

optimized for longitudinal studies.

data (e.g. NLP for text) and standardize with the OMOP
common data model.

Real-world data is massive

Analyze real-world data at scale

Legacy on-premises data architectures are complex toCloud-native and built for speed, the Databricks

manage and costly to scale for today’s massive volumes of

Lakehouse Platform enables organizations to analyze

real-world data, including growth in imaging and genomics.

petabytes of real-world data in near real-time.

Regulatory standards are hard to meet

Build analytics you can trust

Most organizations have disconnected platforms for data

Track your data and machine learning models from source

science and data warehouses. This creates challenges

through results in a single, secure platform. This enables

when trying to build trust and reproducibility in real-world

reproducibility wherever your research teams are located.

evidence analytics.

Databricks for Real-World Evidence

Leading life sciences organizations innovate on Databricks
Centralized terabytes of real-world

Applied machine learning to 17M+

patient data (e.g. EHR, claims,

electronic health records to identifypurchased) on Databricks to

new treatment indications foraccelerate clinical trial recruitment

approved therapies while reducing

with advanced analytics.

data processing costs by 30%.

Get Started with Databricks’ Solution Accelerators
for Real-world Evidence
Our Solution Accelerators help your teams get started faster with prepackaged analytics templates that include
sample data, prebuilt code, and step-by-step instructions ready to go in a Databricks notebook.

OMOP and Propensity Score Matching
Automate the ingestion of real-world data into your lakehouse andstandardize with OMOP for observational analysis at scale.

Generate Oncology RWE with NLP
Extract insights from PDF pathology reports for use cases ranging frommeasuring disease progression to exploring optimal treatment pathways.

Detect Adverse Drug Events with NLP
Improve drug safety monitoring by extracting adverse drug events from healthtext data and building visualizations to show the frequency of correlations.

Databricks customers in Healthcare and Life Sciences

Questions? Learn more at dbricks.co/lifesciences and dbricks.co/healthcare© Databricks 2022. All rights reserved.