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The INTO Statement in PROC SQL to Create Macro Variables

Clinical Programming Team

A member of the Quanticate Programming team writes about their opinions of the INTO statement in PROC SQL.

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Topics: Clinical Programming, SAS Programming, Large Datasets, SAS Macros, PROC SQL

Preparing for Big Data in Pharma

Nick Burch


 

Today, the Pharmaceutical industry, like many, has its feet in both camps when it comes to Big Data. Some parts of the industry, such as genomics and drug discovery, were early adopters and today couldn't imagine life without Big Data technologies and approaches. Others are pushing their current approaches to near their limits, and are beginning to consider "what's next?"

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Topics: Clinical Data Storage, Large Datasets, Big Data

Nick Burch Discusses Big Data in Clinical Trials [Video]

Nick Burch

Nick Burch, CTO at Quanticate discussed Big Data in Clinical Trials at the 4th Annual Clinical Data Integration and Management conference this year in Princeton, NJ. His presentation is titled: 'The Myth of the Big Data Silver Bullet - Why Requirements Still Matter'

Abstract

We've all heard the hype - Big Data will solve all your storage, processing and analytic problems effortlessly! Some moving beyond the buzzwords find things really do work well, but others rapidly run into issues. The difference usually isn't the technologies or the vendors per-se, but their appropriateness to the requirements, which aren't always clear up-front.

Big Data, and the related area of NoSQL, are actually a broad range of technologies, solutions and approaches, with varying levels of overlap. Sadly it's not just enough to pick "a" Big Data solution, it needs to be the right one for your requirements. In this talk, we'll first do a whistle-stop tour of the different broad areas and approaches of the Big Data space. Then, we'll look at how Quanticate selected and built our Big Data platform for clinical data, driven by the needs and requirements. We won't tell you what Big Data platform you yourself need, but instead try to help you with the questions you need to answer to derive your own requirements and approach, from which your successful Big Data in clinical trials solution can emerge!

 

Big Data in Clinical Trials Video 

 

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Topics: Clinical Trials, Clinical Data Storage, FDA, Clinical Study Design, Large Datasets, CRO Efficiency, Visualization, Accessible Data, Mobile Device, Big Data, Drug Development, Technology Trends

Using the Statistical Programming Language R in the Pharma Industry

Statistical Consultancy Team

The statistical programming language R is often underrated within the Pharmaceutical Industry. Often the default is to pay for expensive software when R could be a viable option. R is freely available and runs on almost all operating systems including Unix, MacOS, and Microsoft Windows.

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Topics: Statistical Programming, Programming R, Large Datasets, Visualization

Using Microsoft Excel to write SAS code in Clinical Trials

Clinical Programming Team

Often when we write SAS code in the pharmaceutical industry, there is a high level of repetition. This guide explains ways of writing repetitive SAS code using Excel that will reduce the overall time to write the code and make large scale amendments easier and quicker.

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Topics: Clinical Programming, SAS Programming, Large Datasets, SAS Datasets

How to Deal with Large SAS Datasets in Clinical Trials

Clinical Programming Team

This slideshow focuses on the problems faced when working with large SAS datasets and ways to resolve these problems.

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Topics: Clinical Data Storage, Clinical Programming, SAS Programming, Large Datasets, SAS Datasets

Clinical SAS Programming – Working Efficiently with Large Datasets

Clinical Programming Team

Issues of Large Datasets

Numerous SAS® programmers experience problems when working with large SAS® datasets that have millions of rows, hundreds of columns and are close to the size of a gigabyte or even more.

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Topics: Statistical Programming, Clinical Programming, SAS Programming, Large Datasets

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