• The Time is Right to Disrupt Clinical Cancer Trials and Accelerate Innovation

    Clinical Research News | As we prepare for a new decade, marked at its start by the astonishingly speedy development of a vaccine for COVID-19, clinical trial sponsors have the opportunity to disrupt the traditional drug development process like never before by using real-world data.

    Aug 18, 2021

  • Predicting Patient Response In COVID-19 Drug Trials

    Clinical Research News | Based on cellular-level insights from previous COVID-19 clinical trials, mathematical modelers at the University of Waterloo (Ontario) have simulated how the body deals with the virus as a starting point for predicting how patients will respond to new experimental vaccines and treatments—including those targeting variants of concern. While this is a generic model meant to reflect an “average human being,” it can be customized to more precisely forecast drug effectiveness in individuals according to variables such as their gender, age, and comorbid conditions.

    Aug 16, 2021

  • An Application Now Rests with the FDA: How to Manage the Review Process

    Clinical Research News | What is happening inside the FDA and the Center for Drug Evaluation and Research (CDER) statisticians in the review of the drug/device application? We look at what data are analyzed, the integrated review process, and labeling and post-approval evaluation.

    Aug 13, 2021

  • Ovarian Cancer Chip Model Reveals Drug Repurposing Opportunities

    Clinical Research News | A novel organ-on-a-chip model of ovarian cancer has been used to showcase the sinister activities of tumors, including use of circulating platelets to fuel their growth and undermine treatment with chemotherapeutic drugs. The model also demonstrated the potential of an anti-platelet drug, currently in clinical trials for a different condition: to fight back.

    Aug 11, 2021

  • What You Don’t know, Will Hurt You: Overcoming “Missingness” in Healthcare Data

    Clinical Research News | Most data sets—especially in healthcare—are missing data and, therefore, may not sufficiently representative to support the broader conclusions being drawn about groups of patients. Missing values is a problem that data scientists refer to as “missingness.” Even if data isn’t specifically missing, often the quality of the data is so poor that it is unusable and functionally considered missing. This missingness often leads directly to poor analytics outcomes.

    Aug 6, 2021

  • Follow the Money: Clinical Trial Platforms, Improving Diversity in Trials

    Clinical Research News | Novartis and PCORI both invest in eliminating racial disparity in clinical research, 4G gets a big growth equity investment for randomization and trial supply management, ObvioHealth seeks to integrate the EHR for clinical trial design, and more.

    Aug 5, 2021

  • Parexel Acquisition, Medable Expands to Europe, NSF Funds for RWE Outcomes

    Clinical Research News | Parexel acquired by private equity business, American Heart Association seeks genomic diversity, partnerships for Flywheel and HealthMyne as well as Marken and THREAD.

    Aug 3, 2021

  • Patient-Centric Focus, Awareness, Technology Can Fix Pharma’s Lack of Progress on Trial Diversity

    Clinical Research News | Conversations of diversity in clinical trials has been just talk for a long time. It’s great that study results are being reported with demographic data about race and ethnicity, but it’s still up to the individual pharma company whether it wants to report diversity or not. This is not the path toward meaningful change.

    Jul 30, 2021

  • Machine Learning Can Predict If COVID-19 Trials Will Succeed

    Clinical Research News | A pair of computer scientists at Florida Atlantic University have come up with a machine learning approach to predict the likelihood of a clinical trial being terminated down the road and attribute factors contributing to study termination or success. When applied to the flurry of COVID-19 trials launched since early last year it performs particularly well.

    Jul 29, 2021

  • Data Privacy And Patient-Centeredness Driving Technology Adoption

    Clinical Research News | The potential of artificial intelligence (AI), internet-connected devices, wearables, and cloud computing to disrupt traditional clinical trials was explored during a presentation on patient-centered endpoints at the recent DIA 2021 Global Annual Meeting. The common goal is to make studies more palatable for participants, improving their engagement and retention, and to help pick up the pace and cost of making new medicines.

    Jul 26, 2021

  • 5 Reasons Why a Decentralized Method Works for Clinical Trials

    Clinical Research News | With sponsors like IQVIA, Pfizer, and GSK joining the Decentralized Trials & Research Alliance and the FDA giving decentralization its nod of approval, it’s safe to say the clinical research industry will continue to embrace decentralized trials.

    Jul 23, 2021

  • Building Trust In Real-World Evidence

    Clinical Research News | Lessons learned to date about the growing use of real-world evidence (RWE), including emerging approaches to improve study design and the measurement of treatment effects, were highlighted during a presentation by regulatory and pharmacoepidemiology (PE) experts at the recent DIA 2021 Global Annual Meeting. The wide-ranging conversation touched on everything from the regulatory context in which RWE is being used and whether clinical questions can be reliably addressed to the quality of real-world data (RWD) sources and more rigorous methodological approaches that might be adopted to help ensure confidence in study findings.

    Jul 21, 2021

  • Overcoming Barriers To Using Artificial Intelligence In Clinical Research

    Clinical Research News | Current and potential uses of artificial intelligence (AI) and automation in clinical research, and ways to overcome common barriers, were discussed by a panel of industry experts at the recent DIA 2021 Global Annual Meeting. Two multi-stakeholder communities of practice groups now meet regularly to explore ways to leverage AI and machine learning (ML), one focused on improving trial quality and cycle times and the other producing high-quality protocols and reducing risks before the start of a study.

    Jul 20, 2021