AI-Powered RoB Assessment: An Overview Risk of bias (RoB) assessment sits at the core of trustworthy systematic reviews. It determines how much confidence decision-makers can place in the studies that inform guidelines, policy, and clinical practice. For years, this work has relied on trained human reviewers applying structured tools such as the Cochrane RoB 2…

Overview A conversational AI literature review changes where the hardest translation in evidence synthesis happens: the move from a clinical question to a database query a reviewer must defend. Evidence teams in life sciences rarely fail for lack of information. They fail because the volume of information has outgrown the methods used to search it.…

AI in Real-World Evidence: Why the Evidence Base Moved Outside the Trial AI in Real-World Evidence (RWE) has moved from pilot project to operating requirement because regulators, payers, and medical affairs teams now ask questions that randomized controlled trials (RCTs) were never designed to answer. How does a therapy perform in patients over 75 with…

Overview Real-World Data (RWD) to Real-World Evidence (RWE) conversion stands at the center of modern life-sciences decision-making. Randomized controlled trials remain essential for establishing causality under controlled conditions, yet they leave gaps in understanding how treatments perform across diverse patients, care settings, and longer time horizons. RWD, drawn from electronic health records, claims, registries, wearables,…