The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
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 this blog, Alla Muchnik, Senior Clinical Data Manager at Cytel, discusses how specialist CROs can add value and streamline processes by providing oversight of data management services delivered by another CRO. This model helps to fulfill essential regulatory obligations for biopharma companies who may lack their own internal oversight resources.
In this blog, Jonathan Pritchard, Director Business Development at Cytel, draws on his experience in commercial, clinical and technology roles within the biopharmaceutical industry and shares his insights on the primary considerations for sponsors when implementing an ePRO solution.
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.