PhD Biostatistician & FDA Clinical Trial Expert

Specialties & Experience of this Expert Witness

Additional Information

Lei Li, PhD, is a biostatistician, statistical expert consultant, and former FDA/CDRH statistical reviewer with extensive experience in regulatory statistics, real-world evidence (RWE), medical device submissions, pharmaceutical development, clinical trials, and quantitative model evaluation. He is currently supporting two active expert consulting matters involving statistical evidence review, regulatory and clinical data interpretation, assessment of quantitative methods, and evaluation of model assumptions, uncertainty, and data reliability. At FDA/CDRH, Dr. Li evaluated statistical components of 510(k), PMA, and other medical device submissions; assessed safety and effectiveness evidence; reviewed RWE and post-market studies; and advised on complex statistical issues for regulatory decision-making. His FDA work included evaluation of study design adequacy, endpoint justification, sample-size rationale, bias and confounding, missing data robustness, and interpretation of clinical performance metrics under regulatory standards. In industry, Dr. Li served as Statistical Project Leader at Sanofi and Principal Biostatistician at Edwards Lifesciences, supporting global clinical and regulatory programs across rare diseases, inflammatory diseases, vaccines, oncology, cardiovascular medicine, and medical devices. He has designed and analyzed Phase I-III clinical trials, post-market studies, device performance evaluations, and observational RWE studies. His work has supported INDs, BLAs, 510(k) submissions, PMAs, protocols, SAPs, interim monitoring, and regulatory agency interactions. Dr. Li specializes in clinical trial methodology and advanced statistical inference, including Bayesian and group-sequential designs, adaptive and platform trials, blinded sample-size re-estimation, survival and time-to-event analysis, longitudinal and mixed-effects modeling, multiplicity control, AE/SAE analysis, missing data methods, sensitivity analyses, and tipping point analyses. He also evaluates study integrity, randomization imbalance, protocol deviations, subgroup analyses, data quality, and robustness issues relevant to litigation and regulatory review. Dr. Li provides expert consultation on statistical causation and inference, study design flaws and bias, reanalysis of clinical trial and RWE evidence, medical device safety and performance statistics, vaccine effectiveness and immunogenicity analysis, statistical robustness and sensitivity analyses, data integrity, protocol compliance, FDA regulatory expectations, and quantitative damages or predicted-loss calculations where statistical modeling and uncertainty assessment are at issue. Dr. Li holds a PhD in Statistics from George Mason University and has published peer-reviewed research in biostatistics, statistical inference, robust estimation, divergence-based methods, sequential design, and clinical trial theory. He also works in artificial intelligence and machine-learning model validation, including predictive-model validation, algorithm performance assessment, robustness evaluation, fairness assessment, uncertainty quantification, and validation of clinical prediction models for regulatory and legal use cases. Dr. Li is experienced in communicating complex statistical concepts to attorneys, clinicians, regulators, and non-technical audiences. His combined background in FDA regulatory statistics, clinical trial methodology, medical devices, pharmaceutical development, RWE, quantitative modeling, and AI/ML validation makes him well positioned to support consulting expert and testifying expert engagements involving statistical, regulatory, clinical, and quantitative evidence.