Industry Trends

Loading...

Clinical Research
Off-shoring: A Country Attractiveness Index for Clinical Trials

By Mark P. Mathieu
For many years, pharmaceutical companies have been off-shoring manufacturing operations to lower-cost countries. Healthy margins and strong risk aversion have afforded pharmaceutical companies the luxury of staying close to home, for all but manufacturing activities. As financial pressures increase, pharmaceutical executives are finding that going offshore is not only less risky than it once was, but also too attractive to ignore.  Read More



IBM’s Sunny Forecast for Clinical Cloud Computing



Loading...

By Deb Borfitz

June 1, 2009 | An increasing number of the top life science companies are considering a switch from the outright acquisition and customization of e-clinical technologies to establishing and accessing “clinical clouds.” Indeed, it may be the only sensible way to access needed software and information as they engage in more collaborations, alliances, and partnerships to weather the “perfect storm of unprecedented challenges” bearing down on their collective bottom line, says Paul Papas, the Americas life sciences leader for IBM Global Business Services.

Paul_Papas
Paul Papas
Historically, most large pharmaceutical firms have run fully integrated vertical business models, doing all they can in-house and “choosing to selectively outsource where appropriate,” says Stuart Henderson, IBM’s Americas life sciences research and development leader. But many are moving to a network business model where they share risks, rewards, financing, and resources with a portfolio of partners to, among other things, develop and commercialize drugs. As companies do less within their four walls and seek to reduce the time and cost of clinical development, the demand for hosted, fully integrated, end-to-end clinical solutions will rise because sharing an integrated platform is cheaper, less time consuming, and more supportive of a networked business model than the alternative.

The enabler of all this is cloud computing, an Internet-based model wherein a broad range of applications can be tapped from just about anywhere. Users needn’t know anything about the technology infrastructure in the cloud that supports them. They pay cloud computing service providers like IBM and Amazon only for the resources they need and use.

“Building a smarter clinical cloud will enable collaboration, transparency, and access to real-time information wherever it is created,” says Papas. According to IBM, a “smarter” clinical cloud consists of ten core capabilities: multi-tenant security, file sharing, data sharing, help and support, collaboration, analytics, compliance, clinical application suite, process integration and orchestration, and infrastructure.

Clinical cloud computing is certainly more economical for companies than buying  licenses for separate electronic data capture (EDC), clinical trial management (CTM), and information management systems, integrating them internally, and then redundantly paying for the same services whenever they use a clinical research organization, says Henderson.

The FDA already trusts external servers when clinical trial data is sent by email from labs to investigators and from investigators to sponsors, says FDA spokesperson Crystal Rice. But if the data is archived using cloud computing, sponsors will have to convince the agency that there are adequate “write protection” safeguards to prevent tampering. The FDA would be particularly interested in data security measures if the cloud computing service provider has other “sensitive users” such as insurance companies and banks. “The agency might [also want to] check for assurance that investigator records correspond with the data in the cloud repository.”

IBM predicts that life science companies will “flip” to buying technology in a cloud-provisioned way within no more than three to five years. “The situation will be less about which products they use to do EDC or CTM,” says Papas. “The majority of talented clinical IT resources now focused on operational efforts will instead be focused on the science of analytics.”

So what will companies do with the millions of dollars of technology they have already invested in? “There are multiple options and much depends on the investment lifecycle for each clinical application for each client,” says Papas. “IBM’s approach is to enable a phasing to cloud computing where a client uses a combination of their in-house applications and the applications available as part of the cloud solution.”

The move to cloud computing will essentially force companies to agree not just on how they will collect and exchange clinical data, but also how they will manage and warehouse it, says Henderson. “What companies increasingly agree on is that the differentiation they bring is not in the applications they use to execute studies, but the study design, the assets being progressed through the pipeline, and their relationships with clinical investigators.”

When done right, Papas says, a clinical cloud will facilitate company-specific variations via configuration rather than customization. “Companies will have to realize and accept that most customizations are costly and do not provide differentiation.”

Click here to log in.

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.