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How Eliminating Data Silos Will Democratize Pharma R&D

In this special guest feature, Gunjan Bhardwaj, Founder and CEO of Innoplexus, discusses how data silos in pharma prevent the latest advancements in machine learning and data analytics from operating at their full potential, how AI and blockchain are transforming incentives in data sharing practices to promote greater transparency, and how companies can leverage open data to drive innovation and lower drug prices.

AI for Pharma R&D – Creating Anti-cancer Drugs Faster, Reducing Process from Years to Days

The costs and process of developing anti-cancer drugs has been an extreme challenge for decades. Today one company, AccutarBio, is harnessing the power of AI to accelerate drug discovery and reform the current “hit-to-lead” drug discovery scheme. The company recently received $15 million in funding (including money from Chinese AI/facial recognition company YITU) and is now partnering with Amgen.

HIMSS 2018: Perspectives on Health Industry use of AI and Machine Learning

The 2018 Healthcare Information and Management Systems Society (HIMSS) Conference & Exhibition, March 5–9, 2018 in Las Vegas, is a big deal for IT related themes centered around the health information industry. We put together a number of compelling commentaries below from a short list of important health information industry vendors. The the focus of the perspectives align with insideBIGDATA’s primary areas of big data, data science, machine learning, AI and deep learning. Enjoy the comments and the conference!

Lexalytics® Radically Simplifies Market Research and Voice of Customer Programs for the Pharmaceutical Industry

Lexalytics®, a leader in cloud and on-prem text analytics solutions, announced the availability of the Pharmaceutical Industry Pack, created to meet the specific needs of market research, social media marketing, customer experience management (CEM) and voice of the customer (VOC) professionals working in the pharmaceutical industry.

Deep Learning Applied to Drug Discovery and Repurposing

In a recently accepted manuscript titled “Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data”, scientists from Insilico Medicine, Inc located at the Emerging Technology Centers at Johns Hopkins University in collaboration with Datalytic Solutions and Mind Research Network presented a novel approach applying deep neural networks (DNNs) to predict pharmacologic properties of many drugs.

Big Data Capacity and Performance Supports Genome Analytics

When Stanislav Dusko Ehrlich – a world expert in microbiology and a pioneer of metagenomics – and his team set out to create their next generation biotech research platform, they needed a technology solution to support their stringent capacity and performance requirements for big data analytics.

Interview: Datameer Brings End-to-End Data Analytic Solutions Built on Hadoop

“Datameer is all about providing a self-service, end-to-end experience for big data analytics on Hadoop. From data integration to analytics to visualization, we are wizard-led, point-and-click. Most recently we announced our Smart Analytics module, which allows business users to use data mining algorithms through a drag and drop UI. These new capabilities complement what data scientists are doing and enable business analysts to take advantage of advanced algorithms without involving IT.”

Challenges and Solutions for Genomics in the Age of Big Data

Leading researchers in data science and genomics are recommending strategies to help genomic scientists better manage, share, analyze and archive massive research and clinical data sets in an effort to ensure that the big data explosion results in better health outcomes and faster research discoveries.

Global CEO Initiative on Alzheimer’s Disease Announces a Big Data Challenge

Challenge to be first in a series to crowdsource Alzheimer’s data for new disease insights .

Leveraging High Quality Data to Discover Drugs

The IP & Science Business of Thomson Reuters has announced a strategic initiative with NuMedii. The companies will leverage high-quality data, knowledge and predictive technologies to identify therapeutic candidates with the greatest probability for clinical success.