AI Insights
Artificial Intelligence (AI) technology, combined with big data, hold the potential to solve many key clinical trial challenges.
Big Data and AI technologies are complimentary as AI can help to synthesize and analyse ever-expanding data.
AI-powered capabilities, including data integration and interpretation, pattern recognition and evolutionary modelling, are essential to gather, normalise, analyse and harness the growing masses of data that fuel modern therapy development. Indeed, AI and advanced analytics were viewed as the digital technology with the most potential to improve clinical R&D productivity in our Digital Disruption in Biopharma industry survey.
AI has many potential applications in clinical trials both near- and long-term. AI technologies make possible innovations that are fundamental for transforming clinical trials, such as seamlessly combining phase I and II of clinical trials, developing novel patient-centered endpoints, and collecting and analysing Real World Data.
Applying AI to manage the risks and costs of postmarketing requirements
Our award-winning Cassandra AI system harnesses real world data on drugs and data obtained from the US FDA and EMA postmarketing requirements databases to accurately forecast whether postmarketing studies will be necessary.
Advancements in AI for site selection
Learn how ICON is using human-enabled AI to efficiently integrate, interrogate and interpret large datasets from diverse sources and gain valuable insights for site selection in both expected and unexpected ways.
The impact of artificial intelligence on outcomes based contracting
In the United States outcomes-based contracting (OBC) has long been proposed as a measure to reward innovation, based on actual performance of treatments and interventions in patient populations. However, the perceived and actual challenges in implementation have prevented many innovative contracts from leaving the drafting table.
Recently, the potential use of artificial intelligence (AI) to predict suitable outcomes for patients to mitigate potential challenges has been discussed. Read our whitepaper for insights on the latest trends and challenges.
How AI and other digital technologies will transform R&D productivity enough to restore ROI
In our recent white paper 'Digital Disruption in Biopharma' almost 80% of survey respondents were using, or planning to use, AI technologies.
Two thirds of industry executives surveyed were bullish on the potential of AI to increase productivity by 26 percent or more. 22% of respondents were expecting a 51% to 99% improvement, whilst 5.5 percent were expecting an improvement of 100% or more.
AI webinars
Artificial Intelligence at ICON
Artificial intelligence (AI) is a general term for software that mimics human cognition or perception. Rapid progress in AI is transforming many industries with considerable impact, including clinical trials.
Watch the recording.
Advancements in AI for optimal clinical trial site identification: Turning Big Data into actionable intel
Despite advancing technologies, clinical trials still struggle to meet patient enrolment goals. Slow enrolment directly impacts schedule and budget, with each day of delay carrying cripplingly high costs.
Watch the recording.
The future of pharmacovigilance: Exploring automation and AI in literature surveillance
In this webinar, industry experts explore the future of Pharmacovigilance and offer key insights on the critical role of literature surveillance in the pharmaceutical and biotech sectors, and how automation is revolutionising the process.
Watch the recording.
AI at ICON
Our portfolio of award-winning AI solutions are designed to accelerate trial timelines, improve data accuracy, optimise resource management, and ensure compliance — all while maintaining the highest ethical standards.
AI and clinical trials blogs and media contributions
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Blog: 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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Media article: Human-enabled AI driving enhancements in clinical trial site selection
In this piece from Clinical Trial Vanguard, Travis Caudill, Vice President, Feasibility, Site Identification & Clinical Informatics explores the improvements in site selection that human-enabled AI is delivering.
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Blog: 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.
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Blog: The rise and role of AI in medical imaging
Discover how AI is revolutionising medical imaging and clinical trials, enhancing efficiency, accuracy, and patient outcomes through innovative applications in oncology, cardiology and more.
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Blog: How AI could transform literature surveillance for pharmacovigilance
In pharmacovigilance AI could be used to detect adverse events sooner, offering benefits for patients and researchers.
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Media article: Outsourcing analytical testing: AI could transform analytical labs
In this article from Drug Development & Delivery, Suzanne Jansen, Head of QC Laboratory, discusses the importance of faster data turnaround within the analytical lab to facilitate adaptive dosing decisions that will benefit all stages of clinical trials.
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Media article: AI has the power to revolutionise drug discovery and design
In this article, Gerard Quinn, VP of IT Innovation and Informatics provides insight on how artificial intelligence can support the drug development process.
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Media article: Automation in Clinical Trials
This article will explore how clinical trials have become more complex with more moving parts, along with the requirements for technology specific automation.
The power of AI to transform clinical trials
The AI transformation of clinical trials starts with protocol development, reducing or replacing outcome assessments that may be more responsive to change than traditional methods and utilising remote connected technologies that reduce the need for patients to travel long distances for sites visits.
Data-driven protocols and strategies powered by advanced AI algorithms processing data collected from mobile sensors and apps, electronic medical and administrative records, and other sources have the potential to reduce trial costs. They achieve this by improving data quality, increasing patient compliance & retention, and identifying treatment efficacy more efficiently and reliably than ever before.
Panel: Digital R&D: AI - the reckoning?
Andrew Garrett, Executive Vice President Scientific Operations, ICON, joins Badhri Srinivasan, Head, Global Development Operations, Novartis and other panelists debating where will AI add value to pharma, and the complexities of implementation, the issues of data collection, quality and the need for scale. Moderator: Sarah Neville, Global Pharmaceuticals Editor, Financial Times. Recorded late November 2019 at the Financial Times Global Pharmaceutical and Biotechnology conference in London.
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Leveraging voice-assistant technology in clinical trials
In addition to the rise in mobile and wearable solutions, AI powered digital voice assistants are becoming ubiquitous, with every smartphone today now shipping with either Siri or Google Assistant, while smart speakers like the Amazon Echo with Alexa and Google Home are becoming the hubs for smart homes.
Voice assistant technologies provide an opportunity to create a different level of engagement and interaction with patients in comparison to regular apps and web pages. ICON have developed a proof-of-concept application operating on the Amazon Echo platform that leverages a Voice Assistant to deliver a patient-reported outcome instrument and collect patient responses.