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Comprehend Systems Grabs $8.4M in Series A

2013-07-11
PALO ALTO, CA, Comprehend Systems has partnered with Sequoia Capital and raised $8.4 million in Series A funding to support further development and expansion of its cloud-based clinical data insights software.
Driven by industry demand to better manage clinical trials, Comprehend Systems, Inc. has partnered with Sequoia Capital and raised $8.4 million in Series A funding to support further development and expansion of its cloud-based clinical data insights software. The round was led by Sequoia with additional support from Aaron Levie, Nils Johnson, Zod Nazem, Zorba Lieberman and the Life Science Angel Network, among others. Warren Hogarth will represent Sequoia on Comprehend's board of directors.

Since its founding in 2010, Comprehend Systems has been making it easier to bring drugs to market by improving the way clinical research sponsors access and analyze data. The company will use the funding to continue development of its cloud-based insights platform, Comprehend Clinical(TM), which pulls together clinical and operational data from different systems, making it easy for executives, study mangers, clinicians and others to track and analyze studies.

'Clinical trials are increasing in complexity but the tools to manage and analyze the data are outdated,' said Warren Hogarth, partner at Sequoia Capital. 'Comprehend's simple and tailored approach provides real-time insights and facilitates collaboration that helps researchers make more informed decisions about their data, save time and money, and bring a drug to market faster. '

Earlier this year, the company delivered the industry's first quick-access solution for clinical- and operational-data insights through the launch of its online, self-service portal. Designed to remove lengthy procurement and integration processes, this online portal enables sponsors to quickly sign-up to cost-effectively analyze study data for critical decision-making in a matter of days. Last month, Comprehend Systems further expanded its reach in the clinical-research space with a partnership with Merge Healthcare's eClinical Solutions division, enabling Merge's customer base to gain end-to-end critical insights - without the need for costly programming, data warehousing or business intelligence (BI) tools.

'The pharma and biotech industries continue to struggle to maximize the capabilities of modern technologies in a data-driven world. Contract Research Organizations and sponsors need innovative, real-time, cost-effective ways to review their data and make smarter decisions,' said Rick Morrison, CEO of Comprehend Systems. 'As we move into our next stage of growth, we will continue to address these challenges through powerful and user-friendly tools that provide meaningful, actionable insights.'

offers cloud-based clinical data insights tools that improve the way clinical researchers access, understand, explore and analyze data. Designed specifically for life sciences, Comprehend Clinical (TM) enables data managers, monitors and clinical operations executives to identify broad operational and clinical trends across trials and also easily drill down and report on a wide range of factors, including safety issues, regulatory requirements and opportunities for critical time and cost savings. Comprehend Systems was founded in 2010 in Palo Alto by a team of entrepreneurs with decades of combined experience in clinical research and software development.

About Sequoia Capital Sequoia Capital helps founders turn imaginative ideas into enduring companies. As the 'Entrepreneurs Behind the Entrepreneurs,' the Sequoia team has worked closely with legendary founders such as Steve Jobs of Apple, Larry Ellison of Oracle, Len Bosack and Sandy Lerner of Cisco, David Filo and Jerry Yang of Yahoo!, Max Levchin, Elon Musk and Peter Thiel of PayPal, Sergey Brin and Larry Page of Google, Steve Chen and Chad Hurley of YouTube, and Reid Hoffman and Jeff Weiner of LinkedIn. Sequoia is now helping the next generation of innovators build the lasting companies of tomorrow.
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