Career progression is rarely linear, and there is no single path to leadership. In our latest blog, Sinéad McKeon discusses what drove her move from the lab bench to project management. She reflects on the capabilities...
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Filter blogs 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.
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Managing AI model biases in AI-enabled SaMDs
Medical device developers using AI in software as a medical device must avoid AI biases to optimise their SaMDs and limit health disparity perpetuation.
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Understanding FDA regulations for AI in SaMD
Despite an increase in AI-enabled medical devices receiving FDA approval there is no distinct regulatory route. Learn about FDA guidance on AI in SaMD.
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Mitigating data disruptions in open claims datasets
Healthcare data now makes up 30% of global data and is growing rapidly. While this offers life sciences firms more insights, it also brings disruptions—from new data sources to cyberattacks—that can either enhance or hinder analytics.
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Reimagining clinical programming: the strategic role of R in modern trials
This blog explores how adopting R is transforming clinical programming by meeting growing complexity, tighter timelines, and the need for transparency, positioning it as a catalyst for innovation across pharma and biotech.
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The future of clinical trials: Why patient-centric outcome measures matter
In recent years, clinical trials have shifted toward a more holistic, patient-centred model. This approach values patients as experts in their own conditions, offering critical insight into whether treatments truly address their needs and priorities. But how do researchers determine which measures reflect what truly matter to patients?
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Implementing digital health technologies for patient-centred trials
DHT adoption is growing as a way to de-risk clinical trials. But effective use of these technologies requires a structured approach to mitigate risks and maximise value. This blog and accompanying webinar provide a step-by-step guide to success with DHTs.
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A partnered perspective on the 2025 Medidata NEXT conference
ICON sponsored and presented at the 2025 Medidata NEXT conference in London, unveiling our Clinical Data Studio integration and discussing innovations in clinical data science and support efficient trials. Read key insights here.
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How COAs and DHTs offer deep insights into patient experiences and treatment effects
A conversation with Sonia Bothorel, Managing Director, Mapi Research Trust and Outcome Measures Solutions.
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Why using COAs and DHTs together is the future of clinical research
Though both COAs and DHTs are tools used to evaluate a treatment’s impact, they often exist in separate spheres, rarely integrated. We argue that combining these two approaches in the same study can help researchers gather better data and improve the likelihood of regulatory approval.
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Digital health: why evaluating human factors is essential
With the rapidly evolving technology, digital health is transforming healthcare, emerging as a promising solution to reduce rising healthcare costs and improve patient care.
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Digital health: managing cybersecurity risks
When developing a new digital health device, as well as maintaining an existing device, securing the device from cybersecurity attacks is critical.
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Utilising connected sensors to power diverse and equitable clinical trials
Our publication in Nature npj Digital Medicine outlines current evidence and a solution framework for diversity in research using digital health technologies.
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Enabling a new way to select fit-for-purpose COAs to simplify clinical protocols
While digital health technologies are one piece of the clinical protocol puzzle, holistic protocol design requires more breadth.
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Enhancing diversity in clinical trials with AI and human expertise
Explore how AI-enabled insights and data-driven site selection can play a key part in a multifaceted approach to diversity in clinical trials and benefit equity in healthcare by extension.
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The rise of precision outcome measures
Precision outcome measures are the means by which to evaluate a meaningful change on the exact outcome of interest, regardless of tool or instrument.
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Unlocking quality in machine translation: The impact of ISO 18587 certification on clinical research
ISO 18587 certification helps ensure consistency and quality in the post-editing process, fostering trust and confidence in machine-translated content across various industries and applications.
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Tested, tried and true: Why digital biomarkers are the AI & ML strategy pharma should prioritise
Rather than chasing generative AI, pharma executives can focus their AI and machine learning (ML) strategies for drug development on investing in and deploying connected sensors to reduce costs and improve patient outcomes.
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Outcome measures: Driving precision health strategies forward
ICON has been speaking, collaborating, and building with top pharma throughout the year to help them develop better drugs, faster, for patients. Here are a few observations from this year.
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The impact of AI on the evolution of machine translation
From its nascent stages to the sophisticated systems we employ today, machine translation has become an indispensable efficiency generating tool.
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How human-enabled AI is creating a new map for navigating site selection
Discover how AI transforms site selection in clinical research by leveraging data and human expertise through an ecosystem approach to optimise site ranking, patient enrolment, and study timelines.
