Aardvark released exploratory data from its stopped Phase 3 HERO trial in Prader-Willi syndrome after FDA lifted the hold, and plans a redesigned Phase 3.
|Articles|October 27, 2011
Cmed Technology Announced the Launch of Timaeus Guided Trial Builder
Advertisement
A new survey of 55 large pharmaceutical companies, small biotechs, CROs and non-profit organizations indicates the current industry trial build process takes too long.(1) All respondents indicated the trial build process typically takes weeks or months to complete; no organization indicated an average trial build time shorter than two weeks. The next most common complaints were that the build process: requires too much technical knowledge; is too complicated; does not sufficiently comply with standards; and requires too much work to ensure quality control.
"BioPharmaceutical and research companies want eClinical technology to let them manage more trials with greater speed, higher quality and without increasing resources," said Cmed CEO Dr. David Connelly. "The survey data confirms that the traditional industry trial build tools—after years of trying—do not satisfy these needs. Timaeus Guided Trial Builder addresses the goal of the quick, easy and validated electronic trial with a different approach."
Central to GTB is the Maximal Re-use Template (MRT) approach, which encompass all the common factors and best practices across a sponsor's portfolio and places them in one large validated "super page." MRTs enable rapid build of complete trials without any need of technical programming knowledge. They automatically ensure adherence to standards and seamlessly validate the trial during the build process, eliminating the need for manual quality control (QC) and hand-offs between teams. Adding Guided Trial Builder to Timaeus' on-demand deployment capabilities allows study teams to start new trials and perform mid-trial updates without downtime or site interruption.
Advertisement
Related to this article
Clinical trials capture data faster than ever, but the real bottleneck is the distance between data capture and a decision teams can trust.
In today’s ACT Brief, we examine why the future of AI in trials is a trusted orchestration system rather than a single model, how coordinators rate eSource-enabled workflows, and what a bipartisan bill proposes for reusable trial networks.
The Faster Clinical Trials Act would create an FDA Center for Clinical Trial Innovation and aims to cut trial costs and enrollment time by at least 30%.
Standardized measurement across five oncology centers found that clinical research coordinators rated eSource-enabled workflows positively (Overall Mean Satisfaction 5.79 of 7), with reduced manual entry and electronic data transfer earning strong marks, while perceived reduction in sponsor and monitor queries lagged as the one domain below threshold.
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, describes the industry’s trajectory toward a unified intelligence orchestration environment—and explains why the future isn’t one model that knows everything, but a trusted system that brings the right evidence to the right human decision.
In today’s ACT Brief, we examine how sites can avoid both fear-driven and overly aggressive AI adoption, why community-based research needs sustained financial investment, and why patient access matters more than organizational size.
Pacing obesity trial enrollment, anchoring eligibility to stable real-world therapies, and building site and physician relationships improve retention and data quality more than aggressive recruitment or restrictive exclusion criteria do.
Advertisement
Advertisement
Trending on Applied Clinical Trials Online
1
Building Standardized Evidence for eSource-Enabled Clinical Trials: Multi-Site Validation of a Clinical Research Coordinator Satisfaction Methodology
2
Bipartisan Bill Would Build Reusable Clinical Trial Networks, With a Focus on Rare Disease
3
Where the Industry Is Headed as Clinical, Operational, and Real-World Data Connect
4
Where AI Governance in Clinical Development Falls Short
5