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.
|Articles|April 20, 2015
SAS, Optum Offer Cloud-Based Health Analytics Platform
The shift from volume- to performance-based payment is propelling life sciences companies to seek concrete data and medical evidence – both to understand patient care and to demonstrate the effectiveness, safety and value of drug therapies.
Advertisement
The shift from volume- to performance-based payment is propelling life sciences companies to seek concrete data and medical evidence – both to understand patient care and to demonstrate the effectiveness, safety and value of drug therapies. To help life sciences clients better manage, analyze and share data, business analytics company
The new service features de-identified integrated claims and clinical data about everyday patients receiving health care, including prescriptions and labs – data from the real world, not just trials. For the new platform, Optum, a leading information and technology-enabled health services business and part of United HealthCare, is the first collaborator and will contribute health care expertise, analytics and vast stores of clinical data to the SAS® data warehousing platform.
Read the full release.
Advertisement
Related to this article
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.
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, argues that CROs must act as orchestrators rather than aggregators—and that the real test of any AI ecosystem is whether it reduces sponsor coordination burden or just hands it back to them.
Syneos Health and Optum outline a joint model for trial planning, recruitment and site access, with no financial terms or timelines disclosed.
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
Where the Industry Is Headed as Clinical, Operational, and Real-World Data Connect
3
Where AI Governance in Clinical Development Falls Short
4
Bipartisan Bill Would Build Reusable Clinical Trial Networks, With a Focus on Rare Disease
5