The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
By Nicolas Rouillé and Eric Henniger
The right design and the right data ultimately leads to the right decisions, so obtaining fit-for-purpose data, collected based on what your protocol is looking for is vital. However, there are several data pressure points facing oncology drug developers that need specialized expertise and processes to handle. In this blog, we run through some key aspects to consider to smooth your data collection and analysis.
The Cytel team made its annual trip to the PSI (Statisticians in the Pharmaceutical Industry) conference 2nd to 5th June. Taking place in London, UK, the theme of this year's meeting was Data-driven decision-making in medical research. As ever, the discussions both within the official conference agenda and during the networking breaks were engaging and productive.
In this blog, we share some of the particular highlights from the sessions that our team attended. We look forward to participating again in 2020 when the conference will return to Europe.
This article was originally published as part of a series by pharmaphorum in association with Cytel and is reproduced with their permission. Scott Harris, a four-time biotech Chief Medical Officer, and principal at Middleburg Consultants, a pharmaceutical consulting organization, told pharmaphorum’s Richard Staines that using novel adaptive or seamless clinical trial models can help to cut development costs. In doing so they can reduce the risks of trial failure that can spell the end for those biotech companies without the deep pockets of big pharma behind them.
In case you haven’t noticed, the traditional three-phase clinical development process is changing. While big late-stage trials are still pretty common, it’s also no longer a surprise to see sponsors refer to phase 1/2 trials, or phase 2/3, indicating that a smaller trial can be progressed to the next phase if an interim data readout supports further evaluation.
This is known as a “seamless” trial as the boundaries between each development stage have become less defined, and there are other options too.
Middleburg Consultants’ Scott Harris is a proponent of this new way of working and has personal experience of the approach after using it to steer a gastroenterology drug through the approval process.
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.