As regulatory requirements increase for drug safety, pharmaceutical, biologic, and medical device companies must now search and access more data than ever before. So how do you find specific data within the growing amount of structured and unstructured data inside your company’s disparate systems and databases?

On Tuesday, May 22 at 1:00 p.m. EDT, d-Wise Technologies, Inc. will answer this question during its hour-long webinar about Reveal®, the only enterprise search tool specifically designed for the clinical environment. Register now.

Enterprise Search for Clinical Trial Data? Specialization Makes a Difference 

It’s this simple – and critical. Can your clinical teams quickly and easily find the data they need -- when they need it?

All search tools attempt to solve an exponentially growing problem – data overload. If you work to advance clinical trials for pharmaceuticals, biologics and medical devices, you know this problem is particularly challenging. You are awash in data from increasingly complex clinical trial protocols, requirements issued by various levels of government and different governments, as well as mergers and acquisitions. 

Implementing the right enterprise search product will significantly reduce the time and effort your company presently spends on finding data, particularly at critical periods in the drug or device development process. 

Most enterprise search tools have been designed to perform horizontally across many data-heavy industries, such as finance, customer support, etc. However, the problem with these tools is that one size does not necessarily fit all. Each of these industries present different data challenges particular to their needs. 

Last year was record setting for new drug approvals, with 39 new drug and biological products approved in the U.S., the highest number in 16 years. The prediction is for even more approvals in 2013. 

Part of this optimism comes from the formation of TransCelerate BioPharma Inc. In September 2012, ten of the world’s leading pharmaceutical companies came together to form this non-profit organization, with the goal of accelerating the development of new medicines. Last month, it was announced that six more pharma companies have joined the group. (See the full list of members below.)

 “There’s never been anything like this to take on these big challenges,” said Garry Neil, the interim chief executive at the time of the launch in an article announcing the inititaitive in the New York Times.¹ TransCelerate members have identified five initial collaborative projects they believe will help them bring new drugs to market faster. All are aimed at making clinical trials more efficient.  

d-Wise Technologies Inc., a clinical optimization and technology leader and SAS Alliance Partner and CDISC Platinum member/Registered Solutions Provider based in Raleigh-Durham, NC is proud to be a Bronze Sponsor at this year's event in Chicago.

Four of d-Wise's Senior Life Science Consultants will be presenting at this year's event on the following industry topics and case studies:

• “The Implementation of a Statistical Computing Environment within a Life Science Sponsor organization” presented by Gary Cozzolino, Senior Life Sciences Consultant d-Wise.

• “Therapy Lessons Learned that Empower Programmers”  presented by Shelley Dunn, Life Science Consultant d-Wise.

• “Managing Metadata and Process Parameters” and a discussion on program optimization and parameter management through the use of metadata, presented by Mike Molter, Senior Life Sciences Consultant d-Wise.

• "The PHUSE/FDA Computational Science Working Groups: A Collaboration Breaking Down the Walls between FDA and Industry"
  presented by Chris Decker, VP Life Sciences Practice d-Wise Technologies, Inc.
  

d-Wise Sponsors PhUSE - Single Day Event-Durham 

PhUSE Raleigh-Durham SDE - Thursday, April 18th
Duke Clinical Research Institute - Durham, North Carolina

This event will focus on issues related to ADaM implementation. Since the ADaM standard is flexible and is closely associated with best practices with respect to management of metadata and interpretation of traceability, ADaM implementation poses unique challenges.

Attendees can expect to gain insight in how other organizations are approaching their implementation of ADaM and how particular challenges have been solved. Implementing standards within an organization is much more than creating a spreadsheet and entering some metadata, and this is even more evident when defining analysis data standards (ADaM). These standards include so many moving parts, including the data, variables, derivations, and complex statistical methods, all of which need to be captured within a well-defined framework.

Clinical Data Standards

An advancement in the fight against Parkinson’s disease (PD) was recently reported. The discovery was due to new clinical data standards. The standards allowed for a better way to store, and transfer clinical trial data for Parkinson's disease as well as allow researchers to combine and test data from multiple studies, streamline the efficiencies of new clinical trials, and assess the development of new drugs and treatments.

“The inclusion of biomarkers as well as clinical scales in the PD standard will assist with much needed standardization in future clinical studies.”

- Dr. Ken Marek, Institute of Neurodegenerative Disorders
Coalition for Accelerating Standards and Therapies (CFAST) Announces a Resource for Parkinson’s Disease Clinical Development

Overview of Reveal Enterprise Clinical Search Software

Reveal, in its current incarnation, does several things “out of the box” that are very difficult for horizontal search products to do:

• Reveal understands how to access the data within SAS datasets and index that data.  A large amount of clinical trial data is held within SAS datasets and it is extremely difficult for horizontal search products to access this data.
• A lot of clinical trial data is held within a Clinical Data Repository (CDR). A CDR is a system that is validated and 21 CFR Part 11 compliant. Data cannot be accessed from a CDR as simply as accessing a normal file system since it is a very controlled environment. Reveal knows how to interface with the popular CDR systems (with a growth path to support others) and extract data out of these systems to be indexed.
• Reveal has robust metadata search capabilities which allow an end user to perform clinically relevant searches without Reveal having to truly understand clinical terms.  For example, Reveal will pick up all assigned attributes to a SAS dataset or other file type held within a CDR (for example “Phase” may be such an attribute or property).  You can then perform a metadata search related to this metadata term (again such as “Phase”).  Other Enterprise Search products have much more modest metadata search capabilities.
• Reveal is designed to process structured (i.e. tabular) data from the start. It also supports indexing unstructured data as the horizontal search products do, but Reveal has special capabilities to search tabular data. For example, Reveal can search for a term within a specified column.

The FDA/PhUSE collaboration was created to provide high-quality quantitative analysis of information on product safety, effectiveness and quality. The core infrastructure for FDA's scientific community will help support ongoing efforts in pre-market development, modernization of drug review, post-market safety and drug quality. Key projects within the FDA's Computational Science Center are in areas of developing data standards and expanding the use of electronic review tools.

SAS® Drug Development is well known as a compliant, hosted repository for storing SAS data and running programs in a secure and audited environment. What is not well known is that SAS Drug Development provides an Application Programming Interface(API) for extending this environment to be more relevant to the way people do business. 

This blog post elaborates on the 3-Big Data solutions from SAS®. d-Wise Technologies can guide you through an assessment process to determine if Big Data is for you, and if it is, we can use our SAS implementation expertise to get you up and running rapidly.

When used in the context of using SAS technologies, the term "big data" means one of two things: handling large volumes of data and performing statistical analysis in near real time, or distributing a large processing problem over multiple servers. SAS offers a grid solution for the latter and two solutions for former: In-Database and In-Memory. Here is a brief description of each to help you decide which solution is best for your organization.

The In-Database solution means handing off computing work to the underlying DBMS and returning summarized results. SAS provides direct support for a half-dozen SASBase procedures. In addition, the solution supports custom UDFs for scoring acceleration and statistical procedures. In short, SAS passes the guts of the procedures to the DBMS in the form of complex SQL queries and the DBMS returns the result sets to SAS for further processing.