Cytel Blog

 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.

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.

Nand Kishore Rawat is a Director and Head, Early Phase Biostatistics based in the King of Prussia, PA Cytel office. We recently spoke with Nand for the Cytel podcast to gain his thoughts on the unique aspects of Phase 1 development and where innovative approaches supported by thorough planning can meet these challenges head-on.  Read on for key insights or listen to the podcast. 

We have written on the blog in the past about the value that a statistical consultant can bring to your team, and to the overall clinical development process. Statistical consultants can be instrumental to the success of your development program, providing a variety of input from creating innovative trial designs that improve information quality and efficiency, to supporting regulatory interactions.

By Esha Senchaudhuri

An important trend in clinical development involves integrating strategic pharmacometric analysis with program level decision-making, to make the most use of available data. This can occur in various forms, from leveraging preclinical data for go-no-go decision making [1], to the need for improved comparative effectiveness frameworks [2].

Here we have five reasons why you should consider utilizing model-based meta-analyses ( MBMAs)  for your program or portfolio development.

PSI is a global member organization dedicated to leading and promoting best practice and industry initiatives for statisticians in the biopharmaceutical industry. The PSI annual conference is going from strength to strength, attracting increasing numbers of delegates from Europe and beyond. With the 2018 conference taking place in Amsterdam in only a month’s time, we took the opportunity to sit down with Lucy Rowell, Senior Principal Statistical Scientist at Roche and the Conference Chair, to learn more about this year’s venue, themes, and new hot topics, along with insights on Lucy’s vision for the future of the PSI organization. We look forward to seeing you in The Netherlands! 

By Esha Senchaudhuri

In response to its R&D productivity from 2005 – 2010, AstraZeneca took the initiative in 2011 to implement what it has called the 5R Framework to strengthen its capabilities. In a Perspectives article from Nature Reviews Drug Discovery [1], Paul Morgan and his team provided complex details about the success of this framework from the perspective of every stage of drug development. Between 2005 and 2010, AstraZeneca was behind industry averages in every phase of clinical development except Phase 1.  After the implementation of 5R, AstraZeneca success rates improved substantially. Indeed, it was announced by IDEA Pharma in March 2018 that AstraZeneca had topped its 2018 innovation index.  Here we examine to what Morgan et al, attribute AstraZeneca’s  success.