Trials that address multiple questions simultaneously using a master protocol can be operationally complicated. These complexities can be managed, even in studies used to support a marketing application.
Key takeaways from a survey of 250 oncology patients measuring COVID-19’s impact on patient willingness to participate in clinical trials.
Distinguishing CAR-T and CPI approaches and the clinical trial challenges and complexities associated with each.
2020 Tufts CSDD study examines relationship between investigative site personnel diversity and study participant diversity.
Alleviating sponsor and investigator concerns around sharing of remote-assessment data in accordance with GCP and GDPR standards.
Eliminating barriers to engage underrepresented populations.
By integrating real-world data more deeply into the process of clinical research, life sciences stakeholders can open up new possibilities for therapeutic development and the evidence-based treatment of hematologic cancers.
Reliable internet connection an integral part of movement to DCTs.
A look at the future of clinical trial laboratory testing amid the emerging use of new devices at the point of care.
Strong collaboration critical as trial development advances.
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.
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.
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.
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.
Fully-integrated, component-based CDMS offers flexibility, customization, and efficiency.