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: 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.
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Media article: The decentralisation of clinical trials is a key catalyst for innovation in artificial intelligence
Michael Philips considers the impact of decentralised clinical trials on innovation in AI.
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Media article: Will big tech dominate healthcare in the years ahead?
Louisa Roberts, VP of Corporate Development and Partnerships, considers the benefits of partnerships with tech companies.
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Media article: The path to smarter digital health
Michael Phillips and Kevin Rooney discuss the use of artificial intelligence for the purposes of automation in digital health and pharma.
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Media article: Data Science: transforming the future of clinical trials
Machine learning and artificial intelligence have the potential to add much value to a clinical trial by facilitating informed decision-making, reducing the time to complete the trial, and the overall drug development process.
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Media article: AI in Life Sciences – Covid pushes AI driven clinical trials and drug manufacturing into the limelight
In analyzing clinical trials and drug manufacturing, it is apparent that adoption of AI and machine learning technology holds astonishing potential to improve the healthcare sector.
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Media article: Role of data in revolutionising the CRO industry
Tom O’Leary, chief information officer (CIO) of ICON, highlights how data is already revolutionising the CRO industry and the steps that still need to be taken to better match patients with targeted therapies and improve health outcomes.
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Media article: Keeping it Real: Challenges and Benefits of Integrating AI and Machine Learning into Pharma R&D
AI and machine learning has been put into a position to transform the pharma landscape.
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.