- Tackling the issue of underutilized “failed” clinical trial data.
- What lessons can be learned from “failed” clinical trial data and how can these data better inform future clinical studies?
Eric Sarpong
Director, Real-World Data Analytics
Merck
- Automating highly manual processing tasks, translating and digitizing safety case processing and adverse drug reaction documents to make them more usable
- Discuss how optical character recognition (OCR), NLP and deep neural networks are being used to format this data
- Ultimately leading to faster assessment of subject, site and study risks
- Using AI to systematically evaluate the effect of different eligibility criteria on cancer trial populations and outcomes with real-world data
- Ultimately identifying a wider and more accurate pool of patients that could potentially benefit from treatments
- Facilitating the design of more inclusive trials while maintaining safeguards for patient safety
Vishwa Kolla
Associate Director, Advanced Analytics
Takeda
- This session provides the unique opportunity to listen to, and engage with, innovative start-up and middle market companies that are accelerating the integration of AI into clinical trials
- Six companies will take to the stage to deliver quick fire presentations about the work they are carrying out to enhance clinical trials
- Effectively applying deep learning methods to medical image segmentation and medical time series analysis
- Refining AI imaging studies via consistent selection of clinically meaningful endpoints such as survival, symptoms, and need for treatment models into the realm of statistical inference – particularly for prediction heterogenous treatment effects
- Understanding the promise and limitations of causal AI
Kevin Brown
Associate Director of Data Science
Bristol Myers Squibb
- Highlighting the challenges for clinical trial design in areas where robust clinical trial data is lacking
- Leveraging real-world data (RWD) to inform QSP disease progression models
- Demonstrating how the QSP-RWD modeling framework was used to establish a target value for early go/no-go decision making
Lyndsey Meyer
Principal Scientist
Pfizer
- Demonstrating the value of centralized-cloud management for the initial concept evaluation phase, development of the protocol, conducting and monitoring research, and intervening to make adjustments to the protocol
- Implementing cloud-based methods for protected clinical trial data sharing
Darshan Mahendral
Director of Engineering, R&D Data Platform
GSK
- Generating clinical evidence using digitally simulated ‘predicted outcomes’
- Fully harnessing the power of simulation in each phase of the trial and utilizing AI tools to implement knowledge gained from real-world data
Tina Morrison
Director, Office of Regulatory Science and Innovation
FDA