The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Generating high-quality clinical data is a vital but challenging task in modern drug development. Unfortunately, in the current era of ‘big data’ and global clinical operations, spanning multiple sites and digital systems, protecting the quality of clinical data has become harder than ever.
Planning your data strategy is, therefore, crucial to ensure a high-quality evidence package and increase the chances of successful clinical development. However, as we discuss in our new eBook, planning a data strategy is a complex process involving various considerations that require significant amounts of time and expertise to fully address.
Read our eBook for expert insights on planning a data strategy that can help overcome key challenges in clinical development and boost your success.
In this blog, we discuss the many data-related challenges commonly faced in clinical development and how to implement a fail-safe data strategy that can overcome these challenges, bringing effective new therapies to patients.
It is widely acknowledged among drug developers that one of their most important assets is the data generated during clinical trials. Hence, it is no surprise that many companies plan and execute a strategy to protect the quality of the clinical data they produce. It is, however, easy to underestimate just how much time and expertise you need to address the numerous and complex considerations involved in the planning process.
Unlock top tactics and tips on how to plan a rock-solid data strategy to minimize risk and boost clinical success in our latest eBook.
If you are keen to find out how to optimize your clinical data strategy, read on to discover five of the top tips outlined in our eBook from specialists working in the Strategic Consulting, Clinical Research Services, and Data Management teams. Their global reach ensures top insights from every corner of the world.
In clinical development, a high-quality evidence package is a prerequisite for a new therapy to gain approval from regulators and other key decision-makers. As such, the quality of your clinical data is one of the key factors determining whether an effective new therapy reaches patients.
Implementing a data strategy can help to protect the quality of your evidence package. However, many companies start planning their strategy quite late in the development process, which makes it difficult to address (sufficiently address) the complex considerations involved. As we explore in our new eBook, a data strategy planned well in advance of starting Phase 1 and following the industry’s best practices can help you reduce risk, expedite clinical development, and successfully achieve your business objectives.
Download the new eBook, “Are you Harnessing the Power of your Clinical Data?” to find out how to optimize your data strategy to advance clinical development.
In our previous blog, we talked about the value of planning a data strategy for the entire duration of your program (i.e., a ‘program-wide’ strategy). However, it is also important to plan for specific phases of clinical development, because they each have unique challenges. Below we discuss the major challenges commonly encountered in Phase 1 and Phase 2 studies, and the tactics you can use to resolve them. An upcoming article will engage with challenges in Phase 3 and post-market.
In the quest for clinical success, we all strive for evidence packages of the highest quality. If the clinical data is strong, then a promising new therapy is more likely to obtain approval from key stakeholders, such as regulators and payers . As a result, you’ll get the chance to develop a therapy that will help many patients (and you will likely gain returns on your investments). As we discuss in our new eBook on data strategy planning, a carefully planned data strategy can help mitigate risks to your programs and enable you to successfully achieve your goals.
Discover how to plan a data strategy that enhances your clinical programs and enables new therapies to reach patients in our new eBook.
In the high-stakes environment of clinical development, it is never too early to start protecting your valuable data assets with a first-rate strategy. So, keep reading to learn which planning approach to use, who should be involved, when it is best to start, and why it is well worth going to all the effort.
In clinical development, data is the vital ‘foundation’ that supports your programs. To successfully bring a promising new therapy to patients, the quality of your evidence must be strong enough to gain approval from key decision-makers, including regulators, payers, and health technology assessment (HTA) agencies.
So, how can you strengthen the quality of your clinical evidence package? A key solution is to optimize your data strategy. As we discuss in our new eBook on data strategy planning, making just a few small changes to your planning approach can strengthen your ‘foundation’ and generate various benefits that enhance and expedite clinical development.
Download our free eBook to find out how to optimize your data strategy to boost success in clinical development.
Cytel Inc. and Axio Research joined forces in June 2019, expanding our ability to solve the most complex analytical challenges for the life sciences industry. Cytel offers a full range of clinical data management services delivered by advanced analytics experts with global reach.
In this blog, we talk to Ronald Dumpit, who is based in Bremerton, Washington to find out more about his career path, current role at Axio and his interests outside of work.
PhUSE EU Connect 2019 was held in the beautiful city of Amsterdam between the 10th and 13th of November. This clinical data science conference comprised 19 Streams, including 150 papers, 24 posters and 3 engaging data scientists as keynote speakers. The event was well attended and had several interesting and innovative presentations. Caroline Terrill, Associate Director of Statistical Programming at Cytel UK, conducted a session “No Place Like Home: Managing Remote Programmers Remotely” and stood out as the winner in the Personnel Management category. Based on 5 years' experience of managing remote programmers, Caroline’s paper gives guidance on issues to be considered and traps to be avoided if you are managing people who work remotely.
In this blog, we share the presentations from our Statistical Programmers and summarize some of the sessions that our team members attended.
In association with Statisticians in the Pharmaceutical Industry (PSI) , UCB and Cytel hosted a symposium on September 11, 2019 at UCB’s offices in Slough, Berkshire. The primary agenda was to educate the audience on Artificial Intelligence (AI) approaches and their impact on clinical development.
With recent advances in AI, it is important for quantitative scientists to keep up to date with the most recent methods and be involved in guiding their application to the most pressing analytical challenges. This one-day event covered cutting edge examples of how data science and statistical sciences are intersecting, and its relevance to our attendees.
“Artificial Intelligence and associated methodology is becoming increasingly important to the Pharma Industry and its technical foundation in statistical theory means that PSI is naturally keen to promote good practice through its membership and established Industry links. PSI is proud to have set up a Special Interest Group in this field and is keen to broaden its links and membership.”
- PSI Data Science special interest group
In this blog, we share some of the key takeaways from the symposium. If you are interested in attending similar sessions, you can check Cytel’s list of upcoming events here.
At the 2019 Challenges in Rare Diseases Clinical Trials Symposium and East training, Cytel partnered with Alexion to bring together expertise from academia and industry. David Kerr, Director of DMC Services at AXIO, was among the notable speakers and his talk “Data Monitoring Committees – Behind Closed Doors” covered general considerations and options that the DMC has when reviewing the data presentations during their closed sessions. He presented four specific case studies that highlighted the data provided to the DMC from meeting to meeting and discussed how the DMC arrived at their recommendations for each meeting. We had the opportunity to sit down with David and speak about Data Monitoring Committees, understand their proceedings and talk about his presentation at the symposium.