Saama Launches Active Safety Analytics for Pharma (ASAP), Co-built With Gilead to Transform Safety Surveillance
ASAP Developed Using FDA-Recommended Active Safety Surveillance Approach
- First-of-its-kind cloud-based capability leverages RWD for pharmacovigilance
- Complements existing spontaneous safety surveillance capabilities
- Facilitates rapid response to regulatory requests and findings
CAMPBELL, Calif.–(BUSINESS WIRE)–#Gilead—Saama Technologies, Inc. (“Saama”), the #1 AI clinical analytics platform company, announced today the launch of the new Active Safety Analytics for Pharma (ASAP) product. ASAP is the first validated pharmacovigilance solution to leverage the U.S. Food and Drug Administration’s (FDA) Sentinel Common Data Model and the TreeScan methodology for detecting safety signals. ASAP was co-built with Gilead Sciences, a research-based biopharmaceutical company that discovers, develops and commercializes innovative medicines in areas of unmet medical need. Saama and Gilead partnered to develop ASAP, with scientific advice from the Reagan-Udall Foundation for the FDA, and accelerate the life sciences industry’s paradigm shift to adopt active safety analytics.
“ASAP offers a new standard for applying real word data (RWD), including claims and electronic medical record (EMR) data, to safety surveillance and pharmacovigilance,” said Suresh Katta, Founder and CEO of Saama Technologies. “ASAP was born of a collaboration between the great scientific minds of Gilead and the great engineering minds of Saama. Together we have created a new bar by which to monitor and evaluate safety through the post-approval phase of the drug development life cycle.”
ASAP, a new product within Saama’s award-winning Life Science Analytics Cloud, brings transformative capabilities to sponsors, who can now overcome the limits of existing passive or spontaneous safety surveillance approaches, and apply the same rigor to safety signal detection and analysis as the FDA. The TreeScan models were adopted to various study designs with scientific advice from Robertino Mera, M.D., Executive Director, Epidemiology, Gilead Sciences, and Judith Maro, Ph.D., Operations Lead of FDA Sentinel Operations Center, through a collaboration with the Reagan-Udall Foundation for the FDA.
“Gilead’s commitment to advances in pharmacoepidemiology is reflected in our partnership with Saama to create ASAP to push the boundaries of safety for new and existing medicines,” said Dr. Mera. “ASAP can effectively complement existing spontaneous safety surveillance capabilities to provide Biotech and CROs with a comprehensive safety surveillance framework that will help enable the next generation of life-changing medicines.”
“TreeScan is a robust signal identification method that is compatible with multiple study design options intended for longitudinal data. It evaluates thousands of potential adverse events by taking advantage of grouping similar clinical outcomes to increase statistical power while still controlling for multiple hypothesis testing,” said Dr. Maro. “ASAP couples TreeScan methodologies with extended review capabilities to provide a complete suite of signal identification tools for active surveillance.”
“ASAP builds upon the tools within the FDA’s Sentinel Initiative, a long-term program designed to build and implement a national electronic system using real world data for monitoring the safety of FDA-approved drugs and other medical products through active surveillance,” said Carla Rodriguez, Ph.D., Scientific Director of the Innovation in Medical Evidence Development and Surveillance (IMEDS) program at the Reagan-Udall Foundation for the FDA. “Saama’s vision for developing ASAP aligns with the FDA’s commitment to active safety surveillance.”
ASAP offers the life science industry the ability to:
- Identify and evaluate potential new and unsuspected safety concerns.
- Respond more effectively and efficiently to regulatory requests or potential findings through a cost-effective approach.
- Utilize data science, artificial intelligence (AI) and machine learning (ML) (future), and real world data (RWD) in all safety initiatives.
- Extend this real world evidence (RWE) platform to enterprise-wide data science initiatives that leverage claims, EMR, and genomic (future) data sets.
- Enhance capabilities to support observational trials and synthetic-arm trials.
Active safety surveillance will be the subject of a November 3 Xtalks webinar titled “Active Surveillance: A New Paradigm in Patient Safety.”
“Life science industry professionals in Pharmacovigilance, Epidemiology and Medical Affairs will find this webinar extremely valuable for understanding how they can harness the power of active safety surveillance in clinical development,” said Benzi Mathew, Vice President and Partner at Saama Technologies.
To learn more about ASAP visit https://www.saama.com/solutions/pharmacovigilance-epidemiology-sponsors/.
About Saama Technologies, Inc.
Saama is the #1 AI clinical analytics platform company, enabling the life sciences industry to conduct faster and safer clinical development and regulatory programs. Today, over 50 biotech companies use Saama’s award-winning Life Science Analytics Cloud (LSAC) platform on more than 1,500 studies, including many of the top 20 pharmaceutical companies. LSAC’s rich applications facilitate an unprecedented, authoritative oversight of comprehensive clinical research data, enabling companies to file New Drug Applications (NDAs) more efficiently and bring drugs to market faster. Discover more at www.saama.com and follow Saama @SaamaTechInc.
About Gilead Sciences
Gilead Sciences, Inc. is a research-based biopharmaceutical company that discovers, develops and commercializes innovative medicines in areas of unmet medical need. The company strives to transform and simplify care for people with life-threatening illnesses around the world. Gilead has operations in more than 35 countries worldwide, with headquarters in Foster City, California. For more information on Gilead Sciences, please visit the company’s website at www.gilead.com.
Gregory T. Simpson