Strong collaboration critical as trial development advances.
The emergence of AI-powered simulants in improving study efficiency.
eTMF-blockchain technology offers a myriad of application benefits to data quality and integrity while ensuring compliance to ethical standards.
Decentralized trials provide promise for lowering barriers in participation, but industry must continue to be proactive in patient centricity.
Evidence from a Phase III cancer trial points to notable advances in data-transfer tech.
Optimizing feasibility through increased data collection.
The diversified sources of the somatic cells call for additional oversight to prevent the introduction, transmission, and spread of communicable disease.
Study uncovers insights on the impact on safety, patient enrollment/retention, and compliance.
Gabi Hanna, MD highlights the need for an effective therapy for acute pancreatitis.
With an increasing amount of diverse data that must now be collected and analyzed, the industry is faced with increasingly complex studies that present new challenges in data management.
Study seeks to understand how different forms of data meet the needs of researchers.
Webinar Date/Time: Wed, Oct 30, 2024 11:00 AM EDT
Findings from the most recent Biopharma Confidence Index show that the pandemic has substantially influenced biopharma executives’ expectations in key areas like artificial intelligence/machine learning and real-world evidence.
Explore how natural language processing and social graph techniques help to tackle the challenge of patient and investigator recruitment and raise the success rate of clinical trials.
Patient-first trial design, based around the tenets of adaptability and personalization, has emerged as a key solution to increase diversity and improve trial outcomes for all.
Changing the expectations of the feasibility study can improve the process.
Hidden costs have industry searching for ways to not only identify quality issues, but completely eliminate them from the start.
Developing a strategic approach for labs that can identify and tackle global health challenges.
A representative sample patient population that accurately reflects the overall population is vital to establish the safety and efficacy of a drug.
Identifying areas of burden and steps supply chain operators can take to alleviate them.
Industry must take steps in preserving data for use after the war.
Identifying the ‘significant six’ areas of clinical study conduct to mitigate risk.
For antibody drug conjugates to reach their full potential, developers should focus on addressing current challenges such as safety and efficacy.
Recent research is showing medical treatment for pregnant women often relies on clinical data from non-pregnant female patient populations.
Fully-integrated, component-based CDMS offers flexibility, customization, and efficiency.
Outlining the five critical hurdles faced by clinical teams conducting studies in these nations amid quarantine and other restrictions.
The many different shapes and sizes of vendors requires a thoughtful process for selection.
Explore how natural language processing and social graph techniques help to tackle the challenge of patient and investigator recruitment and raise the success rate of clinical trials.
Laboratory services organization focuses on easing patient and site burden with improved collection device.