The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
At the Partnerships in Clinical Trials Conference in Barcelona in November 2018, Strategic Consultant Ursula Garczarek participated in a thought leadership stream tackling various developments in Real World Evidence, Pediatrics, Trial Design & Big Data. As well as participating in a panel discussion on innovations in clinical trial design, she was impressed by the contributions and innovations offered from other stakeholders across the healthcare landscape. One of these exceptional contributions came from from Galina Velikova, Professor of Psycho-social and Medical Oncology at the University of Leeds, and in this blog, we are thrilled to share an interview with Professor Velikova, in which she expands her discussion of the role of Patient Reported Outcomes (PROs) and Quality of Life Measures in trials and clinical practice.
No one plans to have a trial whose data collection needs rescuing. However, lagging enrollment rates, operational struggles, and diminished budgets can leave some trials in need of intervention. A great deal has been written about how to prevent the need for rescues (e.g., more investment in study planning and improved communication between stakeholders). Far less has been said about how to assemble a rescue team – the roles that need to be filled and the process of analysis that ensures the completion of a failing trial.
Quantitative pharmacology encompasses the many strategic advantages of using complex mathematical models to understand biochemical relationships that ultimately improve clinical decision-making. This includes pharmacometric modeling, familiar to those who have used pharmacokinetic/pharmacodynamic (PK/PD) modeling to improve dosage decisions, and the extension of such models to the performance of meta-analyses, the construction of decision rules, and other uses involving a broad array of cases. In this blog we summarize some key areas of opportunity.
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.
A 2018 publication in the Biometrical Journal by Cytel’s Cyrus Mehta, Lingyun Liu and Sam Hsiao, ‘Optimal Promising Zone Designs’ (1) marks a new milestone for adaptive sample size re-estimation. Inspired by insights from the team's work with a number of Cytel's strategic consulting clients, it presents an easy to implement and new iteration of the popular promising zone design. The basic principle? That any investment of sample size at an interim analysis should be contingent on a minimal acceptable return on the investment. This return is expressed in terms of guaranteed conditional power, By identifying a minimum rate of return upfront, the new design offers greater efficiency to clinical trial planners. Importantly, the design concept is both easy to communicate, and easily understood among statistical and clinical stakeholders alike.
In this blog, Cytel Co-Founder and Fellow of the American Statistical Association, Cyrus Mehta shares his insights with us on the goals and key takeaways of the publication, and how it adds to the growing toolkit of intuitive adaptive designs available to drug developers today. We also share full access to the publication itself.
Career Perspectives: Interview with Tina Checchio, Associate Director, Quantitative Pharmacology & Pharmacometrics
QPP remains at the heart of model based drug development. Short for Quantitative Pharmacology & Pharmacometrics, it refers to several types of quantitative modeling including meta-analysis, PK/PD, statistical modeling and the modeling of go-no-go decision rules. Cytel’s expert Quantitative Pharmacology and Pharmacometrics group delivers high quality solutions to help our customers get those decisions right.
In this blog we talk to Tina who lives in Stonington, Connecticut, to find out more about her career path, current role at Cytel, and her interests outside of work.