Data Science

Jeanina (Nina) Worden

Director, Statistical Programming

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Agenda

Managing Expectations

Managing Data Security

Managing the People & Processes

Managing to Change

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Expectations

Four key departmental goals:

Compliant system/platform

Content security

Global access

Integrated environment for all users

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Highlights

Life Science Analytic Framework (LSAF)

Cloud-based SAS environment

Built to be compliant with regulatory requirements

Integrated analytic tools

Integrated library of CDISC standards

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LSAF Dashboard

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Compliance

LSAF IS a compliant system because:

Two-level system access

Account locking after failed attempts

Audit log records user activities

Redundant backups maintained by SAS

Robust change controls followed by SAS

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Performance Testing

Processing speed (in seconds) using a 440,000 record dataset

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Program Server LSAFSimple SET 0.7020 0.4297PROC SQL query (with MEAN) 0.6550 0.3915PROC FREQ 0.4830 0.6455PROC LOGISTIC 8.2840 4.4321

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Access Requirements

Granular access controls

Familiar SAS environment

Built in management and audit tools

SAS maintenance relieves in-house IT needs

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Controlling Access

Santen controls access by controlling account settings:

Creating user accounts appropriate to their function or task to be performed

Controlling access to the files contained on the system

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User Access

Santen has differing types of users based on their roles:

Programmers/Analysts

Data managers

Data “users” (i.e. executives, scientists)

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User Access

Different types of users based on their employment:

FTEs

Contractors located at the Santen office

CRO partners

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Group Accounts

Defined needs for each type of user

User “groups” provide consistency

Exceptions applied individually

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FTEs Only

Programming Group

Privileges

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Access Privileges

Can the user download out of LSAF?

Will the user be allowed to change the Data Standards?

Should the user be able to lock/unlock accounts?

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Content AccessContent differences also exist

Types of content includes:

Ongoing study files

Archived study files

Ad hoc/testing data

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Content AccessContent access is not automatic

Access can be controlled at different levels:

Study level

Subfolder level

File level

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Study Level

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Subfolder/File Level

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Access history

Account creation and access modifications are logged

Audit history used as documentation for regulatory agencies

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Going GlobalKey considerations in building the global

team

Efficient resourcing

Effective communication

Standard processes

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Where We Were

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Global ResourcesSingle work environment

Increase our team in a cost efficient manner

Full utilization of current resources

Capitalize on lower cost market

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US-based programmers

Japan-based programmers

New programmers

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Where We Are Now

296 8 18!

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Global Resources

Increase productivity by capitalizing on the differing time zones

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US

JapanChina

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Global Communication

Communication is the primary challenge

Study communication:

Single-source “living” documents

Task status

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Global Communication

Common study documents

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Monitoring Progress

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Global Libraries

Single environment = consistency

Global folders or libraries:

Best practice/guidance documents

Data standard implementation guides

Training templates

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Global Libraries

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Global Standards

Standards = efficiency

CDISC mapping documents

Standard programs

Dataset programs

Utility programs

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Global Libraries

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Change

Change is dependent on the starting point

Changes for Santen

UNIX environment

Jobs (Batch execution)

Working with files between areas

Storage management

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Change - Jobs

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Change - Jobs

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Dependencies are accounted for and are access based, not user based

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Change – Working with files

Check-in - Adding files

Checkout/Moving

Versioning

Tracks changes

Ability to revert to previous

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Change – Working with Files

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Copy = no change

Check-in/Checkout = changes allowed

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Change - Versioning

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Guidance needed for when to version, “type” definitions and utilizing the comment field

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Change – Versioning (Access)

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Note: You cannot compare versions

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Change - Storage Management

Storage understanding and management is key

Storage allocation between development and production areas

Each version stored

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Change - Storage ManagementDo’s

Check-out only what is needed

Delete unneeded files often

Do Not’s

Create “archived” folders

Duplicate files in multiple places

SAS can provide reports with offenders!

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Future Change

Value of data

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0

20

40

60

80

100

1 2 3 4 5 6 7 8 9

Study

Repository

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Future Change

Potential to build therapeutic data repository

Add value to data beyond submission usage

Cluster analysis for marketing targets

Preferred site locations

Defining better studies

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Summary

Account options provide wide access and granular security

The centralized work environment allows increased, efficient use of global resources

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SummaryChanges do occur but can be managed

and have the potential to add value

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Questions?

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Thank you to SAS for giving me the opportunity to present this topic!

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Thank You!

Jeanina (Nina) WordenDirector, Statistical Programming6400 Hollis Emeryville, CA 94608jeanina.worden@santen.com

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