Recently, DataArt and Microsoft partnered to host a webinar, "The Role of AI in Clinical Trials”, to discuss how this innovative technology can save time and money in clinical trials. The panel of experts included:
- Gene Buckley, Senior Director for Customer Success for Health and Life Sciences, Microsoft
- Andrey Sorokin, AI Expert and Solution Architect for Healthcare and Life Science Practice, DataArt
- Daniel Peikarz, Senior Vice President, Head of Healthcare and Life Science Practice, DataArt
In this article, we summarized the key insights from their discussion.
Implementing AI Solutions Just Got Easier
Just a few years ago, building and implementing AI tools was a time-consuming and expensive process. Businesses had to hire a team of engineers to customize AI models to their needs and provide operational support, with no guarantee of success. For example, in 2017, IBM's Watson attempted to create a clinical decision support tool using AI at a cost of 62 million dollars, but the project failed.
Today, AI tools are much more accessible and user-friendly. Thanks to advancements in natural language processing, RAG (retrieval augmented generation), and prompt engineering, we can now interact with large language models simply by asking questions in plain English and receiving answers.
These developments offer new opportunities in the clinical trial industry. While traditionally, clinical trials have been time-consuming, costly, and complex, the latest advancements in AI tools make the process much more efficient by reducing costs and improving the accuracy and speed of data analysis.
Addressing Data Privacy Concerns
As AI becomes more powerful and widespread, data privacy concerns are one of the hot topics raised within the clinical trial industry, given the sensitive data used during these trials. The main concerns focus on whether cloud providers can access the clinical data uploaded and if this data will be used to train AI models.
Using Azure Cloud for data ensures customer security and privacy. Microsoft’s commitment to comply with strict privacy standards in handling sensitive medical information helps the company maintain trust among Azure Cloud users.
Achieving Regulatory Compliance with Ease
Remaining compliant poses an ongoing challenge for clinical trial businesses, as they need to adhere to numerous regulations and reference documents. AI can be used to accelerate clinical trials, significantly reducing the time required to get from the design phase to the regulatory submission. For example, AI can analyze past research and local regulations to generate sections of a trial protocol. Another example is an annotation of protocol documents: AI tools can automate the extraction of eligibility criteria and cut preparation time in half.
Maximizing Success in Patient Recruitment
Patient recruitment is one of the most difficult and time-consuming parts of clinical trials. With over 80% of clinical trials failing to meet their patient enrolment timelines, the need for efficient recruitment strategies is more critical than ever.
Simplifying Data Processing
Processing a large volume of data is arguably the biggest challenge for companies involved in clinical trials. Cloud technologies, such as Microsoft Azure, ease this challenge as they allow processing data from thousands of sources and analyzing it in real-time. AI tools can further help businesses standardize patient data and provide insights.
DataArt’s AI Use Cases in Clinical Trials
- Recommendation System for Clinical Trials.
DataArt solved the expensive and time-consuming issue of distributing patient quotas across hospitals and countries by using advanced algorithms and an automated process. - GenAI-Powered ICF Processing Solution.
DataArt created an innovative Generative AI solution that automates the population workflow for Informed Consent Forms (ICFs), solving the client's problems with manual filling and related inefficiencies. - Matching Cancer Patients with Clinical Trials.
Using advanced NLP methods and human expertise, DataArt developed a model that speeds up the process of finding a personalized clinical trial for a specific patient.
Learn More about DataArt’s AI Expertise in Clinical Trials
DataArt and Microsoft
DataArt has been a Microsoft partner for over 20 years, equipped with the expertise in Microsoft tools necessary to enhance the effectiveness of clinical trials with AI. By leveraging AI capabilities within Microsoft's ecosystem, DataArt can streamline participant recruitment, optimize trial designs, improve data analysis, and contribute to faster and more accurate outcomes in medical research.
Learn More about DataArt's Services on Microsoft Azure
Final Thoughts and Next Steps
AI has a transformative impact on clinical trials, particularly in areas such as compliance, patient recruitment, and regulatory submissions. As it continues to advance, the collaboration between industry experts and technology providers promises to drive significant improvements in efficiency, accuracy, patient safety, and the overall clinical trial experience.
To see the full webinar and get more insights on AI in clinical trials, request the recording here.
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