Big Data and How It Is Being Used to Transform the Pharmaceutical Business Model

Big Data and How It Is

Being Used to Transform

the Pharmaceutical

Business Model

A Special Extended Symposium for the

2015 National Biotechnology Conference

Brian R Moyer and Atul Butte,

Co-Moderators

The AAPS NBC and

NBC Program Committee

Welcomes Everyone to a New Topic of High

Value to our Biotechnology Conference:

WHAT IS ……“BIG DATA”?

THIS EXAMPLE MAY HELP…..

Ants are very simple creatures.

They can recognize a dozen or so pheromones and can sense where these scents are more intense. They also can tell the difference between meeting two ants in a minute and 200 ants.

That, however, is about the extent of their individual communication abilities. But if we observe 10,000 of them in a colony, we see a "swarm logic" emerge. The colony is continually adjusting the number of ants foraging for food,

based on the number of mouths to feed, how much food is stored already in the nest, how much food is available in the vicinity, and whether other

colonies are out there competing for resources. Yet, no ant understands any of this.

The DEFINITION

“

are difficult (or impossible) to manage with traditional software and/or hardware; nor can they be easily managed with traditional or common data management tools and methods

(1).

Big data in healthcare is overwhelming not only because of its volume but also because of the diversity of data types and the speed at which it must be managed (1)……Big Data engages electronic datasets so large and complex that they are difficult (or impossible) to manage with traditional software and hardware. …………Big Data is overwhelming not only because of its volume, but also because of the diversity of data types and the speed in which it must be managed. Volume, Velocity, and Variety—often referred to as the three V’s of Big Data — capture the true meaning of Big Data.”

Abstracted from a Review: Wullianallur Raghupathi and Viju Raghupathi

Big data analytics in healthcare: promise and potential

In, Health Information Science and Systems 2014, 2:3 http://www.hissjournal.com/content/2/1/3 1. Frost & Sullivan: Drowning in Big Data? Reducing Information Technology Complexities

and Costs for Healthcare Organizations.

http://www.emc.com/collateral/analyst-reports/frost-sullivan-reducing-information-technology-complexities-ar.pdf

BIG DATA AND WHAT IT MEANS TO

BIOTECHNOLOGY

• Recent figures estimate the number of “Big Data” jobs will grow to 4.4

million, with 1.9 million of these jobs to locate in the United States.

• Jobs in Biotech: Many of these jobs will be directly related to

biotechnology platform development and applications off those

platforms.

• New Structures for Everyday Data: Big Data will require intricate

algorithms and the crafting stories out of the massive amounts of data

that today’s pharmaceutical companies are generating every day.

• Disjoined Data - “Connect the Dots”: Data scientists will be

challenged to make sense of enormous data arrays and will be

challenged to design uniquely structured data using cross-platform

experiences

BIG DATA AND WHAT IT MEANS TO

BIOTECHNOLOGY

Continued……

• Optimize the Data: Optimizing platform outcomes will be done to

satisfy customer/investor interests, foster new creative product

designs, and refine models of disease

• Make Sense of the Data: Interpretations of statistical analyses will

generate new pharmaceutical ventures and products, and ultimately

create solutions to many of the deadly diseases and health issues we

still face.

The Big Data Symposia Agenda

• 8 AM – 8:10 Welcome to the Workshop

• Brian R. Moyer, NBC Program Committee/ 2016 NBC Chair-Elect

• 8:10 - 8:35 Keynote Introduction to the Role of Big Data in Pharma:

• Tamara Dull, SAS

• Panel 1: Big Data Platforms (8:40 to 10:45 AM)

• 8:40 – 9:10 Personal Genomics: Mike Snyder, Stanford Univ.

• 9:10 – 9:40 Public Data: Atul Butte, UCSF

• 9:40 – 10:10 High Performance Databases: Enakshi Singh, SAP

• 10:10 – 10:40 Cloud Computing for Biomedicine: Ketan Paranjape, Intel

• 10:40 – 10:50 BREAK

• Panel 2: Big Data Applications (10:50 – 1 PM)

• 10:50 – 11:20 Microbiome: David Hanzel, Metabiomics

• 11:20 – 11:50 Pharmacogenomics: Gunaretnam Rajagopal, Janssen

• 11:50 - 12:20 Circulating DNA: Iwijn De Vlaminck, Cornell Univ.

• 12:20 - 12:50 Cloud Genomics: David Shaywitz, DNANexus

• 12:50 - 1:00 Closing Remarks: Atul Butte, UCSF and

Keynote Introduction

to the Role of Big Data in Pharma:

An applied conceptual architecture of big data analytics