Recent regulatory shifts have critical implications for how biosimilar developers generate and prioritise information. Read ICON’s latest article in PharmTech Magazine, to learn what these changes mean for data collect...
ICON experts frequently author or contribute to industry trade press.
Filter media
Filter media articles by either clicking within the ‘Category’ drop-down list, or begin typing which will automatically match to the nearest available category. Note - not all categories will display results if selecting a particular year.
-
What Biotech and Pharma need to consider about decentralised trials
Discuss key considerations when implementing decentralised clinical trials, in addition to the success factors that lead to more patient-centric trials and increased patient recruitment, engagement and retention.
-
The surge of digital health technologies modernising clinical research
Dr. Isaac R. Rodriguez-Chavez outlines the key considerations when developing digital health technologies.
-
Cell and gene therapy specific market authorisation guidances
Brandon Fletcher, Principal, Cell and Gene Therapy, offers his insights on the key changes in regulatory guidance documents released by the US Food and Drug Agency.
-
Improving early phase oncology clinical trial design using Bayesian-based BOIN and BOP2 designs
Tim Clark, VP Drug Development Solutions, Martin Lachs, VP Project Management Oncology & Cell Therapeutics and Alan Phillips, Sr. Director Biostatistics, offer insights on selecting and implementing the appropriate model-based or model-assisted design for early phase oncology trials.
-
ICON reveals record €2.28bn business win in Q1
Steve Cutler is quoted in this article on the record earnings ICON achieved in the first quarter of 2022 despite the ongoing disruption from the war in Ukraine.
-
Precision medicine
Ewa Kleczyk, Vice President, Advanced & Custom Analytics, offers her insights on the use of precision medicine in clinical trials.
-
The silent problem: Machine learning model failure - How to diagnose and fix ailing machine learning models
This article considers the current issues around the applicability of Machine Learning Models.
Bennett, M. Balusu, J., Hayes, K., & Klecyzk, E. J., The Silent Problem- Machine Learning Model Failure - How to Diagnose and Fix Ailing Machine Learning Models. Cornell University ArxIV. doi: 10.48550/arXiv.2204.10227
-
Equipping our people leaders to drive an inclusive organisation
Mary O’Reilly and Nikki O’Hanlon discuss the vital role that people leaders play in driving diversity and inclusion within an organisation.
-
Defining quality tolerance limits and key risk indicators that detect risks in a timely manner
In this article, Gillian Pilbrow, along with multiple other SMEs from other organisations, discuss effective risk control through the earliest possible risk detection practices.
-
