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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Media article: AI’s transformative role in drug discovery and development
In the Irish Times Life Sciences and Stem supplement, ICON’s CIO Tom O’Leary discussed AI is transforming drug development across a range of specific use cases, from discovery to clinical trials and post-marketing.
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Media article: How AI can manage the risks and costs of postmarketing requirements
Postmarketing requirements (PMRs) for drug development are commonly required to gather data on a product’s longer-term safety, efficacy and optimal use. Carefully applied AI and machine learning offers the potential for better management of PMRs.
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Media article: Us and it
This article delves into how AI is transforming clinical trials by improving efficiency, accelerating timelines, and enhancing decisions across the clinical development process.
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Blog: 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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Blog: Unlocking quality in machine translation: The impact of ISO 18587 certification on clinical research
ISO 18587 certification provides guidelines for ensuring high-quality translations through the process of human post-editing of machine translation output.
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Media article: Streamlining bioprocesses with automation
In this article from BioPharm International, Ronan Fox, Senior Vice President, IT R&D, provides commentary on the evolving role of automation in biopharmaceutical development.
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Blog: 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 & machine learning (ML) strategies for drug development on investing in and deploying connected sensors to reduce costs & improve patient outcomes.
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Blog: 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.
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.