Chris Barnes
Vice President, Biometrics Pliant Therapeutics Inc.
Dr. Barnes received his PhD in Biostatistics from the University of Louisville with his research focusing on adaptive clinical trial designs including extensions of Simon 2-stage designs and novel multistage, randomized designs for binary responses. Dr. Barnes completed a fellowship at the James Graham Brown Cancer Center focusing on cancer bioinformatics. Dr Barnes joined Industry post his fellowship and has worked in multiple therapeutic areas across several companies with a primary focus in respiratory diseases including COPD, Asthma, and IPF. Dr. Barnes has contributed to the approval of multiple medicines in COPD and Asthma.
Seminars
Effective clinical trial design in IPF is constrained by patient scarcity, high costs, and the need for robust statistical methodology to drive confident decisionmaking. This workshop will bring together statistical experts, clinical researchers, and industry professionals to explore how innovative statistical approaches can optimize sample sizes, improve trial efficiency, and mitigate the risks of underpowered studies.
Key discussion points:
Balancing Statistical Rigor with Feasibility in Trial Design
- How can we determine the optimal sample size that maintains statistical power while reducing costs and recruitment timelines?
- What alternative statistical methodologies can be applied to small patient populations to maximize data reliability?
Mitigating the Risks of Small, Underpowered Studies
- Explore historical IPF trial failures due to inadequate proof-of-concept data and lessons learned
- How to design early-phase trials to better de-risk phase three studies while working within financial constraints
Addressing Data Integrity & Outlier Impact
- The role of extreme outliers in phase two datasets— when should they be excluded or accounted for?
- Statistical innovations for improving disease modelling, endpoint selection, and predictive power of early-phase studies
This workshop will provide practical insights into statistical frameworks that enhance the success of clinical trials in IPF, ensuring more efficient study designs that improve the likelihood of regulatory success and commercial viability.
