In March 2019 I had the opportunity to interview Jennifer Newman, Global Project Leader, Regulatory Affairs/Clinical Operations for Celldex Therapeutics. Newman was once part of the largest implementation of risk-based monitoring (RBM) and was able to share insights from her experience.
As part of our ongoing series detailing an approach for the rapid assessment and prototyping of digital and other clinical trial technologies, we introduce here the use of artificial intelligence (AI) and machine learning (ML) to optimize clinical study design and execution.
Clinical research is sometimes viewed as a box-checking exercise, where we run fairly cut-and-dried randomized, placebo-controlled studies based on long-established protocols. But things are actually changing very rapidly in the world of clinical development, which is by far the largest part of pharma R&D spending. We are on the threshold of a transformation that will allow us to dramatically accelerate the acquisition of useful knowledge, get new medicines to patients sooner, and expand their usage to new indications more quickly.
Three decades ago when I entered the profession of clinical research, our workplace equipment extended to typewriters, white-out, mimeographs, hand-written documents, rubber erasers, pens, label makers, and fax and copy machines. Rows of massive, locked, fire-proof filing cabinets storing millions of papers for a nationally funded research program lined record rooms, hallways, and every spare corner of the offices. Most of us felt rewarded when we could use a typewriter with a correction key despite one’s typing skills being firmly judged by the illegible mistakes in the carbon copies.
This white paper focuses on defining and expanding the definition of study startup, an element of clinical trials that is gaining attention because it offers the greatest opportunity to improve quality while compressing clinical trial timelines.
The cloud has made anywhere/anytime, centralized monitoring (adaptive-on-site and off-site) of all risk-related trial factors a seamless reality. Looking ahead, the cloud can integrate centralized monitoring, risk management measures, and predictive analytics. It can also create risk repositories, to keep trial costs in check and optimize better quality results for life saving therapies.
As pharmacovigilance adopts next-generation technology by leveraging artificial intelligence (AI) and the cloud, new possibilities are opening up for knowledge generation – and thus value – from the data collected and processed. This paper looks at three important developments around drug safety data and their analysis and how industry is prepared for them.
Just as patients have a stronger voice in today’s healthcare marketplace, that voice should resonate earlier in the drug development process. By adopting a patient-centric approach during protocol design and in day-to-day study management, sponsors can expect improved patient enrollment and retention, as well as a cleaner study with definitive outcomes.
Welcome to Clinical Leader, the premier online community that helps streamline clinical research by connecting trial sponsors and cutting edge service providers. Clinical Leader is part of the Life Science Connect media group. The vision of Life Science Leader and Life Science Connect is to help facilitate connections and foster collaborations in pharmaceutical and medical device development to find ways to get more life-saving and life-improving therapies to market. Connect, Collaborate, Contribute.
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When you’re diagnosed with cancer, diabetes, an autoimmune disorder, chronic pain, a neurological condition such as Alzheimer’s disease, or another illness, having the safest, most effective medicine is paramount. Knowing a promising therapy is “in the pipeline” doesn’t bring you a whole lot of comfort. You want access to the most advanced medicines now.
More than two years have passed since the 21st Century Cures Act was signed into law in December 2016. According to the FDA, the Cures Act is designed to help accelerate medical product development and bring new innovation and advances to patients who need them faster and more efficiently.
At Janssen, patients are at the center of everything we do. And we’re constantly working to improve their experience.
US Food and Drug Administration (FDA) requirements specify that packaging and distribution systems must protect the agent from contamination and damage. In distributing cryogenically frozen advanced therapies, this includes protection from temperature shock.
Competition is fierce between large pharmaceutical and biotechnology companies that are investing in the biosimilar market, and it is expected that the number of biosimilars being developed will continue to increase dramatically as more biologics come off patent. Recent experience in biosimilar clinical trials shows that strategic planning and a few simple tactics can increase return on investment and expedite time to market for biosimilars.
Adaptive design trials offer the potential to change this industry statistic and dramatically increase the ability of pharmaceutical companies to successfully bring more effective treatments to the market. Companies that adopt a comprehensive adaptive design strategy across their product pipeline will make better development decisions and ultimately bring effective products to the market more quickly.
Due to the increasing pace of innovation and blurring boundaries between pharma and device products have led to new drug-device combination products and the need for updated regulatory guidances, the EMA published a Q&A document detailing information for products that need both the drug and the device components to function.
In September 2018, FDA issued a new draft Guidance for Industry on Adaptive Designs for Clinical Trials of Drugs and Biologics. This guidance replaces the previously published 2010 draft guidance. Here, we summarize the differences between the two documents and highlight any significant new elements introduced in the most recent material. Of note, the 2018 guidance is more compact and streamlined than its 2010 predecessor, also evident by a fewer number of total pages (36 vs. 50 in the 2010 version).
