Agenda · innovation enterprise summits gsa 2016 new orleans


Is there a more efficient alternative to Hadoop that can deliver the same level of performance whilst dramatically lowering the organisational expenses and operational needs of a Big Data & Data Science initiative? Enterprise firms across the world are today using tools primarily from the Hadoop ecosystem for meeting their Data Science needs. gas up asheville They are powerful, capable and new. But, as anyone who has used these systems will tell you, they also come with significant operational overhead. We took a different path in our quest to find a solution that is inexpensive, has minimal administrative needs, simple to use and yet deliver superior performance to any contemporary solution for analysing Rx (Prescriptions), Claims and other medical datasets. The innovative solution has been widely recognised as the fastest data mining platform in Pharma and VCs from NYC to London have begun a new initiative to bring the platform to the broader Pharma market. electricity bill cost This talk will highlight the platform that we use and how you too can leverage them in optimising your organisations Big Data capabilities.

The rise and proliferation of Real World Evidence (RWE) in the Life Sciences – particularly in the Clinical and Commercial arenas – have given rise to massive opportunities in therapeutic innovation. However, the potential for a paradigm shift in the development cycle has been stymied by the logistical challenges of managing, modeling, and analyzing petabytes of complex data. gas finder map For healthcare organizations seeking to pioneer the therapeutic landscape, effective use of RWE can lead to massive gains in clinical trial efficiency through better site selection, targeted geolocation of patient cohorts, and efficient patient recruitment. In this highly informative presentation, Dr. electricity merit badge worksheet answers Josh Ransom, Head of Clinical Products for SHYFT Analytics and industry Subject Matter Expert, will address five data and analytics challenges commonly encountered throughout the development and go-to-market journey. He will also offer strategies to overcome these challenges through the tactical and actionable use of RWE, arming therapeutic innovators with a playbook to streamline processes, maximize investments, and impact patients’ lives.

Sequencing of transcribed RNA molecules (RNA-seq) has been used wildly for studying cell transcriptomes in bulk or at the single-cell level and is becoming the de facto technology for investigating gene expression level changes in various biological conditions, on the time course, and under drug treatments. static electricity images Furthermore, RNA-Seq data helped identify fusion genes that are related to certain cancers. Differential gene expression before and after drug treatments provides insights to mechanism of action, pharmacodynamics of the drugs, and safety concerns. electricity usage calculator spreadsheet Because each RNA-seq run generates tens to hundreds of millions of short reads with size ranging from 50bp-200bp, a tool that deciphers these short reads to an integrated and digestible analysis report is in high demand. QuickRNASeq is an application for large-scale RNA-seq data analysis and real-time interactive visualization of complex data sets. This application automates the use of several of the best open-source tools to efficiently generate the user-friendly, easy-to-share, and ready-to-publish report. Here, we outline the steps required to implement QuickRNASeq in user’s own environment, as well as demonstrate some basic yet powerful utilities of the advanced interactive visualization modules in the report.

: Insightful¬ analyses of Research & Development (R&D) data, such as, clinical trial, biomarker lab results, and patient Real World Data (RWD), are essential for every successful biopharmaceutical company to determine the efficacy and safety of their products. electricity bill saudi electricity company The integration and analyses of these data are typically labor intensive, time consuming and require specialized biostatistician or IT programming skills. Working with several innovative biopharma companies, Cambridge Semantics has pioneered the development of the Digital Patient Health Smart Data Lake using clinical trial, safety / PharmacoVilgence (PV), and Electronic Medical Record (EMR) based RWD data. The creation of the Digital Patient Health Smart Data Lake provides an integrated, harmonized, knowledge-graph driven data platform to discover new and important insights contained in patient data. The solution provides a robust set of advanced analytic capabilities for Data Scientist and Clinicians to develop and share new advanced analytics without incurring slow data integration penalties.