Artificial Intelligence: Healthcare’s Gateway to the Future
The implementation of Artificial Intelligence (AI) in the nations’ healthcare ecosystem offers unique opportunities to improve health care delivery, its efficiency, and patient outcomes but has potentially significant challenges
As the technical sophistication of AI continues to evolve, many pharma companies will likely partner with- or acquire- external vendors to leverage AI tech to focus research efforts more efficiently and bring products to market more quickly, competitively, and effectively
Together, AI may ease administrative/ repetitive burdens, improve analysis of big data for improved decision making and ultimately improve “customer” service for the key stakeholders in HC
Outline the Evolution of AI and ML and How They are Revolutionizing The Clinical Research Ecosystem
Employ AI and machine learning tools to extract more value from clinical trial data
Partner with external vendors to leverage AI tech and focus research efforts more efficiently, bring products to market more quickly, competitively, and effectively
Understand how AI can change every stage of clinical trials, from finding a trial to enrollment to medication adherence
Improve the Clinical Trial Lifecycle by Leveraging Artificial Intelligence and Machine Learning to Reduce Time to Market
Discover how AI algorithms, combined with adequate digital infrastructure, can enable continuous streams of clinical trial data to be cleaned, aggregated, coded, stored, and managed to lead to faster, safer, and significantly less expensive clinical trials
Learn the practical uses of artificial intelligence (AI) and Machine Learning in running clinical trials has the potential to optimize the process at different stages with the intent of reducing the time overall
Demonstrate how AI, particularly deep learning (DL), machine learning (ML) and natural language processing (NLP), combined with an effective digital infrastructure, has the potential to improve drug approval rates, reduce development costs and deliver medications to patients faster
Understand The Impact Of Digital Transformation In Clinical Trials To Improve Safety And Enhance Clinical Trial Protocols
Discuss the adoption of digital transformation and what it means for the clinical development landscape?
Examine AI and its current and potential role in clinical research
Share examples of how life sciences companies are reducing the cost and time required to process clinical-trial data through smart automation, improved efficiency, and less need for rework.
Leverage Artificial Intelligence And Machine Learning To The Analysis Of Clinical Trials: Deriving Further Insight
Explore the potential of AI-enabled insights from historical clinical trial data to make more informed decisions at the beginning of the clinical trial and planning lifecycle
Learn how tools such as eCOA, wearable sensors, and mobile medical devices that allow you to collect data more frequently benefit from using advanced AI and ML to glean insights that can help study teams quickly
Hear best practices utilizing AI and ML to analyze large datasets and bring new drugs to market faster
What challenges do clinical data management systems currently face?
