The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
With only two weeks left for this fabulous year to end, we would like to thank all our blog subscribers and new readers for following and appreciating the Cytel blog. This year, we collaborated with several experts from both within and outside the company to bring to you a range of interesting topics including real-world evidence, AI, challenges in rare diseases, patient-reported outcomes, data management, and our popular series “The Good Data Submission Doctor” and “Career Perspectives”. In this blog, we share with you the top 5 Cytel blogs that resonated most with our community in 2019.
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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.
In place of collecting data from patients recruited for a trial who have been assigned to the control or standard-of-care arm, an external control creates a comparator arm using either real-world data-sets such as electronic health records or previous clinical trials. The external control offers a practical, effective way to leverage real-world evidence and has been applied in regulatory approvals. In this blog, we share an illustrative example of how we can help customers in this emerging area of interest.
The term biomarker signature describes the behavior of a set of biomarkers that define a signature to maximize the prediction performance. We examine the behavior of specific biomarkers as a set that consistently fluctuate together to maximize the accuracy on predicting the disease-related outcome.
How we apply a biomarker signature depends on the prediction problem. A prognostic biomarker signature is used to predict the disease progression, a risk biomarker signature is used to identify sets of subjects that are likely to develop a disease, and a predictive biomarker signature is used to determine the patients that are likely to respond to a particular treatment. Predictive biomarker signatures are used often in oncology to stratify patients with a specific cancer into sub-populations and develop targeted therapies for the diseased population subtypes defined by the biomarker signature.
In this blog, we share an example project that our data science team has worked on supporting this work. The case study forms part of a new ebook 'Innovative Data Science and Real-World Analytics Approaches in Practice' and we are also delighted to provide the link for download as part of the article.
Nowadays, it’s difficult to pick up a mainstream newspaper or read an industry publication without seeing reference to Artificial Intelligence or AI and progress towards innovations like autonomous vehicles, or customer behavior prediction. For the biopharma industries specifically, AI represents an opportunity to avert the R&D productivity crisis with paradigm-shifting applications such as in-silico drug design, prediction of trial risks and big data analytics.
However, with every opportunity, there are risks and challenges, and in this blog, I will discuss how pharma needs to address the opacity of AI to ensure trust and credibility with all stakeholders.
In honor of Rare Disease Day 2019 we share a new Cytel podcast featuring Cytel Strategic Consultant Ursula Garczarek discussing how innovative statistical approaches can overcome challenges in rare disease development. Below, you can access the podcast and a summary of some of Ursula's key insights from working in rare diseases and interacting with regulatory agencies for complex and innovative designs.
In 2018, Cytel ran a qualitative survey among biostatisticians and programmers on trends in data science and perceptions about the goals, barriers and future of the field in the biopharma and life science industry. Our analysis and report revealed a range of insights from the respondents including :
Lack of shared understanding of what data science represents with less than 1 in 7 of all respondents suggesting a definition of data science.
Clear trend of investment in data science across organizational types with three-quarters of all respondents saying their organizations had a dedicated data science department.
An opportunity for improved clinical trial design by using data science techniques was recognized by the majority of respondents. In addition, respondents across all functions perceive the key opportunity for data science to be in maximizing the value of real-world data.
In a recently published discussion on The Effective Statistician podcast ( a weekly podcast produced in association with PSI) Ursula Garczarek, Associate Director Strategic Consulting at Cytel sat down with hosts Alexander Schacht and Benjamin Piske to discuss where the biopharma and life science industries are headed with the application of data science.