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Digital Endpoint Development for Remote Monitoring

Exploring the digital endpoint development process with a case-study
Measuring what matters; identifying and addressing needs. Dealing with concerns around development, validation, regulatory concerns
Putting endpoints to use via deployment in clinical trials

Senior Data Scientist, Early Clinical Development

Pfizer

Extracting AI-Driven Insights from Unstructured Trial Protocol Data

Using AI to evaluate the demographic population and trial operational performance trade offs of exclusion of non-safety required chronic conditions in the eligibility criteria
Benchmarking and differentiating between Schedule of Assessment(SoA) procedures relative to different time periods and peer groups to drive greater operational efficiency

Principal Data Scientist

Genentech

Using Machine Learning Fairness to Help Assess and Design More Representative Clinical Trials

Assessing representativeness of randomized clinical trials using ML fairness metrics and surveillance data
Using these metrics to assess and monitor representativeness of clinical trials
New tools for designing representative and more efficient single and multi-site trials

Professor of Mathematical Sciences

Rensselaer Polytechnic Institute

Using Machine Learning Fairness to Help Assess and Design More Representative Clinical Trials

Assessing representativeness of randomized clinical trials using ML fairness metrics and surveillance data
Using these metrics to assess and monitor representativeness of clinical trials
New tools for designing representative and more efficient single and multi-site trials

Professor of Mathematical Sciences

Rensselaer Polytechnic Institute

Leveraging AI for Adaptive Clinical Trial Design

Opportunities for improving efficiency of clinical research and development
Combining information technology, statistics, and data science to address challenging problems in drug development
Integrated scientific learning approach

Senior Director, Statistical Scientist

Novartis

Democratizing Data at Novartis Through Clinical Trial Data Access: Lessons Learned from Building the Data42 Program

Addressing the technical, cultural and policy hurdles that traditionally impede the broad access and usage of clinical trial data
Layout a blueprint for companies to accelerate their progress in a patient-first manner
Developing a framework to automatically approval clinical trial data requests
Exploring the impact this has had on Novartis and the broader industry