ORDER FROM CHAOS— WHERE
BIG DATA AND ANALYTICS ARE
HEADING, AND HOW LIFE
SCIENCES CAN PREPARE FOR THE
TRANSFORMATIONAL TIDAL WAVE
In this article from EY, the authors offer
an excellent overview of the five major
trends we're seeing in life sciences—
Disruptive consumer technology,
personalized medicine, analytics, maturing
capabilities of cloud computing, and
healthcare cost reductions—and how these
trends can lead to more patient-centric
medicine. The authors ask "Patient-
centricity and enterprise transformation
powered by big data-driven advanced
analytics is a reality. Is your organization
ready?"
* Read more here:
http://www.ey.com/Publication/vwLUAssets/
EY-OrderFromChaos/$FILE/EY-
OrderFromChaos.pdf
HOW GOOGLE'S USING BIG DATA
AND MACHINE-LEARNING TO AID
DRUG DISCOVERY
Here, Paul Sawyers from VentureBeat
briefly explains how the internet giant
Google is working to expedite the
discovery of drugs through their deep
learning model.
* Read more here:
http://venturebeat.com/2015/03/03/how-
googles-using-big-data-and-machine-
learning-to-discover-new-drugs
EVERYTHING YOU NEED TO KNOW
ABOUT DEEP LEARNING AND
NEURAL NETWORKS
"Often coined machine learning or
neural networking, deep learning involves
'training' a computational model so it can
decipher natural language..." Have no idea
what deep learning is? This article in
Techworld by Margi Murphy explains it in
a straight-forward, reader-friendly way.
* Read more here:
http://www.techworld.com/big-data/why-
does-google-need-deep-neural-network-
deep-learning-3623340/
GOOGLE'S NEXT BIG IDEA: MINING
DATA TO PREVENT DISEASE
In an article published by STAT, Charles
Piller interviews Dr. Jessica Mega, who left
Harvard Medical School to become medical
director of Google Life Sciences. In the
interview, Dr. Mega describes the
groundbreaking clinical trials that used
genetic and molecular signals of disease to
study customized treatments for heart
patients. She is now leading Google's life
sciences initiative to analyze genomic,
molecular, and imaging big data from
10,000 volunteers "to figure out what it
means to be healthy—the so-called
baseline study."
* Read more here:
https://www.statnews.com/2015/12/02/googl
e-doctor-jessica-mega/
FOUR COMPANIES USING DEEP
LEARNING FOR DRUG DISCOVERY
This article posted on Nanalyze.com
describes how the companies TwoXAR,
Atomwise, Insilico Medicine, and Berg
Health are using deep learning technology
to discover new drug compounds. A
prediction of their success is provided.
* Read more here:
http://www.nanalyze.com/2016/01/4-
companies-using-deep-learning-for-drug-
discovery/
ARTIFICIAL INTELLIGENCE VS.
DEEP LEARNING VS. BIG DATA
Confused by all the new technology
nomenclature? Newbies in drug
development should definitely
familiarize themselves with the terms
defined in this article, because you'll be
hearing and reading a lot about them in
the media and at medical conferences.
In this article
* Read more here:
http://www.nanalyze.com/2015/12/artific
ial-intelligence-vs-deep-learning-vs-big-
data/
DATA SHARING: AN OPEN MIND
ON OPEN DATA
The move to make scientific findings
transparent can be a major boon to
research, but it can be tricky to
embrace the change. This article by
Virginia Gewin in Nature does a great
job describing the data sharing
movement and what it means to junior
researchers.
* Read more here:
http://www.nature.com/nature/journal/v
529/n7584/full/nj7584-117a.html
GENTLE INTRODUCTION TO
PREDICTIVE MODELING
Just as the title of this article
suggests, Jason Brownlee provides a
beautifully simple step-by-step
introduction to predictive modeling--a
concept that is all part of deep
learning/big data movement in drug
development.
* Read more here:
http://machinelearningmastery.com/gen
tle-introduction-to-predictive-modeling/
Hot Topics in Drug Development [April 2016]
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