Patient recruitment remains a significant challenge for pharma companies conducting clinical trials. If all potential participants were aware of clinical trials, convincing patients to participate in them would still be a challenge. But that task becomes significantly more difficult when a large percentage of the population does not even know such trials exist.
Since the late nineteenth century, it has been well-known that individuals can vary widely in their responses to the same medication. Yet, accurately predicting and addressing the effects of that variability during drug development has continued to bedevil researchers, drug sponsors, and regulators.
Imagine for a moment you are your favorite superhero, charged with the task of saving the whole world from villains such as the Joker, Lex Luthor, Doctor Doom, and the Green Goblin. You would not be very effective — or much of a superhero, for that matter — if you only took one of them out while letting the others roam free. In the same way, as an industry, we cannot effectively tackle the issue of delays in the execution of Clinical Trial Agreements (CTAs) by only addressing one or two of the “villains” contributing to this industrywide problem.
Located between the United States and Central America, Mexico’s geography and Spanish language put it in an ideal position to act as a gateway to Latin American pharmaceutical markets. With an estimated size of $10 billion in 2016, the country’s pharmaceutical market ranked twelfth globally, lagging behind only Brazil as the second biggest market in Latin America. Mexico has a stable economy, and although it is classified as upper-middle income, it also offers lower costs than other countries.
With the quality of data captured throughout a trial playing a crucial role for the success or failure of a study, clinical data management (CDM) is a key element of any research program. During a study lifecycle, data managers will deal with data from many sources such as MRI scans, ECG, lab data, as well as eCOA – all of which are equally important.
This paper isolates three specific areas that warrant close attention for app developers, clinical trials sponsors and CROs designing trials powered with mHealth app tools: technology considerations, data considerations and regulatory considerations. These areas are vital to developing a compliant trial that generates meaningful data for clinical development using mHealth sources.
Post-approval research studies are becoming increasingly large and complex in the clinical research landscape. These programs are often massive in scope, engaging thousands of physicians and tens of thousands of patients. Unfortunately, post-approval operational strategies have not kept pace with the needs and demands of post-approval (Phase IV) research.
Understanding patient reported outcomes (PROs) in oncology clinical trials enables researchers to develop more effective treatments for patients battling this illness. But if it isn't easy for patients to report their health data, they won't - so it must be accessible for them.
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It has now been several decades since EDC was first introduced as a tool for data management in clinical trials. In that time, boosted by continuous developments and enhancements, the technology has grown from a somewhat esoteric alternative to paper to a standard considered essential throughout most of the industry. Without thorough and comprehensive training and support resources, though, it will be a challenge for today’s EDC users to fully benefit from the capabilities the technology has developed over the years. While the best EDC systems are defined by simplicity and intuitiveness, they still offer an intricate array of functionalities that require a certain level of instruction in order to access.
Medical research has seen a great deal of high-profile philanthropic investment in recent years. Last year, for example, tech billionaire Sean Parker made a $250 million donation to further the development of immunotherapy. More recently, the Chan Zuckerberg Biohub has made headlines by announcing plans to invest $3 billion in new research over the next 10 years. The investment is part of the Biohub’s ambitious goal of curing all disease by the end of the century. It will be directed toward a wide array of medical solutions including new drugs, vaccines, and diagnostic tests - and the first round of grant recipients has already been chosen.
Amid the AIDS epidemic during the late 80’s, Dr Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, found himself at a crossroads. As a long-time proponent of the traditional “research to approval” drug development model, involving randomized clinical trials and lengthy regulatory reviews, Fauci was faced with the realization that this traditional approach would be of little benefit to AIDS patients without the luxury of time. Something had to be done. But what?
On Friday, 31 March 2017 the EMA released the revised Module V- Risk Management Systems (Rev 2) of Good Pharmacovigilance Practice (GVP) (EMA/838713/2011 Rev 2) accompanied by a revised Guidance on the format of the risk management plan (RMP) in the EU – in integrated format (EMA/PRAC/613102/2015 Rev.2).
Clinical project managers are expected to make smarter decisions on intelligence derived from clinical trial data and sponsors/CROs are looking for ways to incorporate Business Intelligence into the eClinical systems they are using to empower oversight — turning raw trial data into actionable information.