Shannon Bell

Dr. Shannon Bell is a seasoned computational biologist with over 20 years of experience in data analysis and integration which includes the development of models and data to support new approach methodologies (NAMs) for chemical safety evaluations and predictive biology. As Director of the Environmental Informatics Program at RTI International, she leads interdisciplinary teams of modelers, informaticians, and toxicologists in developing innovative tools and workflows that transform complex, multi-dimensional datasets into actionable insights for research, regulatory applications, and human health.

Dr. Bell's teams address the growing challenge of integrating diverse data streams—ranging from omics and cheminformatics to biological systems modeling—to better understand how chemicals interact with biological systems. By leveraging pathway-based approaches, such as the Adverse Outcome Pathway (AOP) framework, her work ensures that workflows are consistent, comparable, and computable. This research is essential for predicting system-level responses to chemical exposures and improving data-driven chemical safety assessments, while also advancing our understanding of disease progression and human health outcomes.

Her expertise spans key areas such as physiologically based pharmacokinetic (PBPK) modeling and in vitro to in vivo extrapolation (IVIVE). Dr. Bell and her team use advanced modeling and machine learning techniques to answer complex research questions across species, including plants, animals, and humans. Their work drives predictive biology, product development, and risk prioritization, providing stakeholders with user-friendly tools to navigate the evolving landscape of chemical assessment and public health.

Dr. Bell’s current research focuses on improving data accessibility and developing bespoke solutions that support data-driven decision-making in chemical safety and human health. By collaborating with subject matter experts and enriching data through knowledge organization systems and innovative search strategies, she unlocks valuable insights across disciplines. Whether pioneering new computational tools or refining existing models, Dr. Bell’s work bridges the gap between data complexity and practical, impactful outcomes for human and environmental health.