With encouragement from the U.S. Food and Drug Administration (FDA), using Patient Reported Outcomes (PRO) data to claim labeling became more and more popular. Well-defined and reliable PRO can be used to support a claim in medical product labeling.  It is found that there are an increasing number of regulatory submissions for new drugs to provide PRO data to support claims. DeMuro et al. (2013)  have reviewed drug approvals by both FDA and EMA for the years 2006–2010. They found that out of 75 drugs approved by the EMA, 35 (47%) had at least one PRO related claim approved by the EMA compared to 14 (19%) for the FDA.
At the present time, the regulatory and drug development communities are adapting to a rising trend in biosimilar development in a number of therapeutic areas.
The regulatory framework for biosimilars in the US is still evolving; the number of biosimilars approved by the FDA in 2015 was 1, this rose to 4 in 2016 and is set to increase in 2017. The FDA is developing and consulting on draft guidance documents that will shape future trials, and at this early stage there are a number of legal issues to be agreed around licencing conditions, such as the period of exclusivity and the applicability of the biosimilar to all approved indications of the reference product. To put this in context with the European landscape, biosimilars have been approved and used in the EU for over a decade without highlighting any major safety concerns. As of April 2017, there were 28 approved biosimilars in the EU on 11 different biologics. However, there are aspects of the emerging FDA guidance that will almost certainly be reflected in the evolution of trial designs in the future, for products aimed at the US market.
Where and when did
Pharmacovigilance begin? Medical remedies have been recognized by mankind for thousands of years, and so have their potential dangers, side effects, and benefits. During the 20th century there were some serious adverse events associated with medical products and drugs that resulted in pressure on governments, businesses to produce legalization and guidance, as well as the evolution of regulatory bodies to protect the safety of patients. This infographic identifies those significant milestones across the 20th century and into the modern era.
The ICH Guidelines for Good Clinical Practice (E6) has morphed into the international standard for clinical trial conduct since its inception twenty years ago. However, within that period, clinical research has changed dramatically and it is a credit to it’s authors that ICHGCP remains relevant today, with only one previous notable update seen in response to electronic data capture (EDC) technologies being widely utilized by the industry.
With a growing trend towards the use of risk based monitoring, and with new technologies available to support this alternative to traditional onsite monitoring, there remains inertia to implement this approach. Having discussed remote monitoring capabilities with industry peers, we have identified the root cause of this reluctance as an intrinsic fear of flouting regulatory compliance within the conduct of a clinical trial.
Far from being simply a summary of individual results, a comprehensive and detailed summary allows companies to make informed decisions. Producing comprehensive integrated summaries of safety and efficacy is a critical stage of the submission life cycle. These need to be designed and planned carefully in advance to ensure informed decision-making and effectiveness at the regulatory interface. A focus on the approval and whole lifecycle of the product, and not just the submission, will influence the quality and direction of the content. Traceability is key in all respects of the creation of information, from data that leads to knowledgeable decisions and the ultimate wisdom that forms the label of a product.
Today, mHealth, Mobile Health, Mobile Apps and Wearables are hot topics with consumers and regulators alike. We're also starting to see consumer-grade wearables and mHealth technologies creeping into clinical trials. We've written this blog for those looking to use this area more.
We've all heard the hype - Big Data will solve all your storage, processing and analytic problems effortlessly! Some moving beyond the buzzwords find things really do work well, but others rapidly run into issues. The difference usually isn't the technologies or the vendors per-se, but their appropriateness to the requirements, which aren't always clear up-front.
Big Data, and the related area of NoSQL, are actually a broad range of technologies, solutions and approaches, with varying levels of overlap. Sadly it's not just enough to pick "a" Big Data solution, it needs to be the right one for your requirements. In this talk, we'll first do a whistle-stop tour of the different broad areas and approaches of the Big Data space. Then, we'll look at how Quanticate selected and built our Big Data platform for clinical data, driven by the needs and requirements. We won't tell you what Big Data platform you yourself need, but instead try to help you with the questions you need to answer to derive your own requirements and approach, from which your successful Big Data in clinical trials solution can emerge!
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