Global spending on clinical trials is expected to reach $68.9 billion per year by 2025 with the average phase 1 asset taking 10.5 years to reach regulatory approval. As the industry faces demands to innovate faster and reduce costs, having access to high-quality data is critical to designing trials that can reach these goals.
The key to improving trial design is access to high-quality clinical data. However, the majority of data available to trial collaborators is inconsistent, messy and stored in a variety of locations and formats. In many cases, life science consulting services provide the first step at collecting, analyzing and structuring this data. Fortunately, A.I. is revolutionizing how the industry can approach this data, enabling clinical investigators, trial managers and coordinators to gain new value from internal and external data that can positively influence recruitment strategies, drug target efficacy and overall trial design.
This webinar will explore:
- The role of data in trial design and trial success rates.
- No code visualization tools for exploring meta-analysis that inform phase 2/phase 3 trial design and drug efficacy and safety
- How AI is improving these analytics capabilities. Most notably, the use of Large Language Models to improve trial analysis and design.
- New ways for visualizing and analyzing clinical outcome data with flexible, no code web applications.
