AI can turn complex protocols into first-pass budget inputs, letting sponsors start budgeting sooner while budget builders shift from data entry to review.
|Articles|June 21, 2018
IQVIA Launches Virtual Research Solutions
Advertisement
IQVIA announced the launch of Virtual Research Solutions, a new suite of technology-led study options offering advances in patient-centric trial design and execution. Powered by the IQVIA CORE™, the Virtual Research Solutions brings together information assets, analytics, technologies, and critical domain expertise to design and execute trials and late-phase studies with people in mind.
Read the full release
Advertisement
Related to this article
Trialbee CEO Matt Walz explores the current impact of AI in delivering practical gains in clinical development and reflects on its future potential, where enrollment predictability may be the biggest prize of all.
In this video interview, Carole Berini, PhD, of Ontada, explains how validated proxies for variables like ECOG performance status can recover not just sample size but the representativeness of hard-to-reach patient populations in real-world oncology studies.
A biomarker test now decides who enters a precision medicine trial, yet results often go unused and assays are not ready when screening opens.
In today's ACT Brief, we examine proportionate analysis frequency in RBQM, how to build trust into real-world evidence foundations for cancer trials, and how rare disease developers monetize regulatory success.
Real-time RBQM requires proportionate analysis frequency matched to data arrival and issue criticality, not continuous reanalysis, because signal churn from over-frequent runs creates alert fatigue and operational noise that obscures meaningful deterioration.
In this video interview, Saamir Pasha and Carole Berini, PhD, of Ontada, explain how building trust into the data foundation—through source lineage, standardization, and reconciliation—is what makes reliable real-world evidence generation in oncology possible.
In today's ACT Brief, we examine how AI surfaces design flaws before enrollment, why site training readiness depends on learning science, and the priorities defining next-generation weight-loss therapies.
Advertisement
Advertisement
Trending on Applied Clinical Trials Online
1
Real-Time Data, Right-Time Decisions: Rethinking Analysis Frequency in RBQM
2
AI and Patient Recruitment: Can Predictive Promise Drive True Transformation?
3
FDA Releases Transparency Roadmap Outlining Disclosure Priorities Across Drug Development and Regulatory Review
4
How Routine Lab Markers Can Stand In for Missing Functional Status Data
5