Clinical Trial Technology Editorial

  1. A Clinical Machine Learning Operations (MLOps) Maturity Framework For Biopharma 3/24/2026

    Pharma has invested substantially in machine learning applications, but investment in the operational infrastructure — the MLOps layer — has lagged. The time to build that infrastructure is now — not after your next trial fails.

  2. How Deep Learning Is Changing Clinical Trial Design, Execution, And Analysis In 2026 3/10/2026

    Deep learning is reshaping clinical trial design, execution, and analysis. Learn how to deploy it safely, measurably, and at scale with help from life sciences consultant and MIT industry advisor Partha Anbil.

  3. The Uncomfortable Conversation: AI And Data Use In Clinical Trials 3/2/2026

    AI is quietly transforming clinical trials at the site level, boosting efficiency while creating hidden risks for patient data, protocols, and sponsor intellectual property.

  4. When A Clinical Trial Surfaces In An AI Chat, What Happens Next? 3/2/2026

    AI is soon becoming the first interpreter of your clinical trial. Understand its implications for enrollment design, screening efficiency, and ultimately program predictability.

  5. Pick The Right PV Technology With Help From A Safety Data Management Expert 2/27/2026

    Otsuka's Head of U.S. GPV Safety Data Management Vikalp Khare shares how smart governance should inform pharmacovigilance (PV) technology choices.

  6. Enabling Cloud Computing In DCTs For Remote Data Capture, Monitoring, And More (Part 1) 2/25/2026

    Understand why cloud infrastructure is foundational to hybrid and decentralized trials and what critical trial activities it enables with reduced operational friction.

  7. Safe And Sustainable DCTs and Hybrid Trials (Part 2) 2/25/2026

    In part two of this series, learn practical cloud architectural patterns, governance structures, and operating mechanisms that allow sponsors to run hybrid and decentralized trials.

  8. Forget More Clinical Tech, We Need More Adoption 2/23/2026

    At SCOPE Summit, Craig Lipset shared a blunt assessment of clinical trial innovation: the tools exist, regulators are engaged, and digital approaches offer clear quality advantages — yet adoption remains the industry’s biggest hurdle. From evolving FDA inspection expectations to the normalization (and lingering misconceptions) of decentralized trials, Lipset argues progress will depend less on new technology and more on scaling what already works.

  9. Joe Dustin: Sites Are Driving Clinical Tech Evolution 2/20/2026

    At SCOPE Summit 2026, Joe Dustin shared why clinical trial sites are emerging as the next drivers of innovation. As sites digitize operations and push back against the burden of sponsor-mandated systems, new models like “bring your own technology” and seamless digital data flow aim to reduce duplication, speed startup, and improve both coordinator and patient experiences.

  10. AI Trial Matching Comes Of Age At City Of Hope 2/19/2026

    City of Hope has embedded an internally trained AI platform into oncology care and research workflows, helping clinicians summarize complex patient histories and match patients to clinical trials in real time. By reducing manual review and accelerating feasibility assessments across its national network, the system is improving trial access, easing clinician workload, and shifting more time back to patient care.