|Articles|January 1, 2011

Applied Clinical Trials-01-01-2011
Volume 20
Issue 1

Applied Clinical Trials Digital Edition - January 2011

SITES : Reducing the Challenges of Study Coordination Workload Measurement Instrument for Cancer Trials RECRUITMENT : African Americans in Clinical Trials Also in this issue : 2011, A Challenge for the Biomedical Research Community?, Joint Manifesto Tries to Address Vicious Cycle, Discontent with IRBs, R&D Success Rate Continues to Fall

External Link - article-821533.pdf

Articles in this issue

almost 16 years ago

Article

Obesity Wins One, but Rest of Field Uncertain

almost 16 years ago

Article

Site Coordinators: An Untapped Resource

almost 16 years ago

Article

EFGCP to Establish Changes in GCP Training

almost 16 years ago

Article

African Americans in Clinical Trials

almost 16 years ago

Article

The New Year Brings Same Old Battles

almost 16 years ago

Article

Workload Measurement Instrument

almost 16 years ago

Article

Frustration with IRB Bureaucracy & Despotism

almost 16 years ago

Article

Collaborative Staffing Model

almost 16 years ago

Article

Business and News Update January 2011

almost 16 years ago

Article

Deteriorating Quality in Global Trials

Stay current in clinical research with Applied Clinical Trials, providing expert insights, regulatory updates, and practical strategies for successful clinical trial design and execution.

Related to this article

October 12th, 2026

What a Practical Roadmap for FDA and EMA Quality Frameworks Actually Looks Like

In this video interview, Saamir Pasha and Carole Berini, PhD, of Ontada, describe what operationalizing regulatory-grade quality frameworks requires—and why fit-for-purpose evidence generation is a transparency and documentation discipline, not just a data cleanliness exercise.

Manual protocol translation slows study budgets. AI-enabled automation can shorten the path to negotiations while shifting budget builders to review. Credit: Stock.Adobe.com/7IMJAGO

October 9th, 2026

Start Study Budgets Sooner With AI-Enabled Protocol Translation

AI can turn complex protocols into first-pass budget inputs, letting sponsors start budgeting sooner while budget builders shift from data entry to review.

October 9th, 2026

AI and Patient Recruitment: Can Predictive Promise Drive True Transformation?

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.

October 9th, 2026

How Routine Lab Markers Can Stand In for Missing Functional Status Data

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.

Structured data, early assay validation, and broader testing access can move trial matching from retrospective to proactive. Credit: Stock.Adobe.com/wladimir1804.

October 9th, 2026

The Test Is the Ticket: Building Smarter Pathways to Clinical Trial Participation

A biomarker test now decides who enters a precision medicine trial, yet results often go unused and assays are not ready when screening opens.

October 9th, 2026

ACT Brief: RBQM Analysis Frequency, Building Trust in Oncology Data, and Rare Pediatric PRV Monetization

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.

© Murrstock - © Murrstock - stock.adobe.com

October 8th, 2026

Real-Time Data, Right-Time Decisions: Rethinking Analysis Frequency in RBQM

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.

October 8th, 2026

What It Takes to Harmonize AI Across Fragmented Oncology Health Systems

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.