By Jen Lamppa PhD – Clinical trials have a diversity problem. Despite years of effort, the participants in many studies still fail to reflect the true demographics of the populations they aim to serve. The consequences are profound: limited applicability of results, missed insights, and health inequities that persist across generations.
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By Hilary Marston MD MPH & Kevin Bugin PhD – Breakthroughs in science and technology are advancing innovation in more areas of medicine, providing novel treatment options for patients. The scientific community has a deepening understanding of disease and human biology, and of the enormous potential afforded through new technologies.
By Wendy Morahan – Despite the critical nature of clinical trials in pharmaceutical research and development, trial stakeholders often struggle with managing scattered data across locations, systems and applications.
By Harsha K Rajasimha – AI is heralding a new era in drug development, promising groundbreaking solutions to longstanding challenges. Traditional clinical trials are often plagued by manual processes, leading to prolonged timelines and soaring costs.
By Hiren Thakkar – Inadequate ethnic diversity in clinical trials, tight eligibility criteria, delayed or missing prescription recommendations for certain communities, and access gaps affecting global health are all hot topics in academia, business, and government.
By Emily Newton – Like many other industries, the medical sector is ramping up its AI adoption. This technology has shown significant potential in many use cases, particularly clinical trials, but some concerns remain. As more organizations use AI in medical research, more ethical questions emerge.
By Gunnar Esiason – I have cystic fibrosis (CF), a rare genetic condition that was historically known as a childhood disease. Today, CF is anything but that, and it’s due in large part to my community’s willingness to rally around clinical trial programs.
By Scott Gray – Patients suffering from chronic illness are often eager to participate in clinical trials with the hopes of finding a more effective treatment for themselves and others with their condition. This is especially true in the case of rare diseases, as these trials are often seen as a patient’s only opportunity for treatment.
By Ben van der Schaaf & Ben Enejo – Much has been written about the application of Artificial Intelligence and Machine Learning (AI/ML) in clinical development, and at first glance it is an obvious area of focus. Successful use of AI/ML capability requires vast amounts of data, and there have been….