SAS Takes Lifecycle View of Patient Safety Data



Loading...

By Ann Neuer

Sept. 3, 2008 | The pharmaceutical industry and regulatory agencies are sharpening their focus on patient safety through intense efforts to improve the way safety data are collected, analyzed and interpreted. And there is a long way to go, says Jason Burke, global director of the health and life sciences market segments at SAS. “Today, most organizations do separate analyses for drugs before and after approval. This is a challenge because it may not be obvious how the lifecycle of a drug looks when safety analyses are conducted using separate pre- and post-approval processes and systems,” Burke explains.

A comprehensive lifecycle view of the safety performance of a drug is what is needed to provide a more repeatable, standardized, and auditable approach for exploring safety signals. The FDA is steering the market in this direction with the release of various guidances intended to improve how the agency disseminates safety information, how adverse events are to be reported, and how reviewers are to conduct the clinical safety reviews for the new drug application (NDA) and biologics license application (BLA) review processes. There is also the Sentinel Initiative, launched by the FDA in May to develop a national strategy for monitoring medical product safety, a nod to the emerging science of safety.

“The agency is driving toward getting a better understanding of the comprehensive view of what safety looks like over the entire history of the drug,” Burke says.

With all this headwind, SAS is on board with its just-released SAS for Patient Safety, a comprehensive solution designed to help users comply with recent FDA guidances by offering advanced analytics for signal detection and pharmacovigilance. The solution consists of a collection of SAS software that is implemented in conjunction with consulting services. It offers capabilities such as standardized safety reporting that leverages standards from the Clinical Data Interchange Standards Consortium (CDISC) and FDA guidances, visualization capabilities that enable researchers to understand patient safety data, and automated signal detection of published as well as SAS-developed signal detection algorithms. “The intent is to remove the need to manually implement commonly used safety algorithms by rolling them into the solution,” Burke comments.

An important feature of SAS for Patient Safety is that it allows for data aggregation and data integration, to enable standardization and to bring together information from disparate sources into a consistent repository. According to Burke, pharmaceutical companies typically rely on transactional safety systems within silos to produce periodic reports. “This siloed approach creates challenges for companies in terms of aggregating information from many sources, cleaning the data, and using standardized structures to report them,” he says.

The technology behind the integration capability is the newly launched SAS Clinical Data Integration server, a platform that defines and automates processes for aggregating clinical data through the use of standards such as those of CDISC. “With this platform, SAS can provide a bridge across whatever sources of safety information a pharmaceutical company might be using to create a 360-degree view of the profile of the drug. We created SAS for Patient Safety in response to what we have seen as a sea change in the industry focusing on safety,” Burke says.

Related articles:

McClellan Envisions Lifecycle Approach to Drug Surveillance

Safety of Drugs Is, Indeed, a Lifecycle Exercise

 

 

 

           

 

Click here to login and leave a comment.  

0 Comments

Add Comment

Text Only 2000 character limit

Page 1 of 1

White Papers & Special Reports

sapiosciences
The Workflow Driven Lab
Sponsored by Sapio Sciences

Many companies have recognized that their internal business units operate as a set of business processes. These business processes are also called workflows. Modern Laboratories are highly suitable to this workflow driven approach. In fact, the lab environments successful operation is predicated on the successful definition and adherence to workflows. It could be said that a modern  laboratory is an advanced process implementing construct. It is important that laboratory management software mirrors the process driven nature of the lab thereby increasing automation, shortening learning curves, improving data quality and increasing lab throughput.

  • The modern laboratory is an advanced workflow implementing construct
  • Laboratory Management Software solutions should fully embrace and mirror this process driven approach
  • Effective information management of workflow processes with a LIMS results in increased automation, reduced training curves, better data quality and increased lab throughput


panasas
Curing Life Sciences Data Management Challenges with Scalable Storage
Sponsored by Panasas

High performance storage systems are a given to meet today’s life sciences R&D computational challenges. But with the explosive growth in data produced by next-gen lab equipment, scalability and long-term data management issues must also be addressed. Read this paper to learn:

  • Why new lab equipment will impact R&D workflows
  • How to avoid the hidden costs of long-term data management
  • What approach you should take to accommodate today’s data while having the flexibility to scale to meet future demands.


Quantum
StorNext 4.0: Technical Product Brief
Sponsored by Quantum

 
Proven in the world’s most data intensive industries, Quantum StorNext is a scalable, high-performance file system which allows data sharing across Linux, Mac, Unix, and Windows operating systems and manages data in enterprise storage environments. In this Technical Brief you'll learn:

  • How a high-performing file system can accelerate your business
  • How to simplify your data management
  • How a tiered storage approach can save you money


Life Science Webcasts & Podcasts

Predict or Perish! Shaping the Practices of Clinical Trials
Decisionview webinarSponsored by:  DecisionView

Predictive Analytics are a key differentiator in running your clinical trials successfully through 2010 and beyond. They will help you to optimize your patient enrollment, reduce your clinical operations costs and minimize your financial liability in the clinical supply chain. In this session, you will:
• Learn what predictive analytics are and what they are not
• Understand why you need predictive analytics to run your clinical trials, and
• Explore how predictive analytics will shape the future of clinical trials

Download Now. 

 



More Podcasts

Job Openings

The University of Washington Department of Genome Sciences is seeking a LINUX SYSTEMS ENGINEERING MANAGER to lead a team in a diverse scientific computing environment that includes multiple HPC systems, petascale storage, and custom application servers. Apply online at UW Hires for req number 61505.  http://www.washington.edu/admin/hr/jobs/

Loading...

For reprints and/or copyright permission, please contact The YGS Group, 3650 West Market Street, York, PA;

(717) 505-9701 ext. 125, or via email to Ashley.Zander@theYGSgroup.com.