Chen Hu

Responsibilities: - Support the launch of a new product by multiple RWE projects addressing clinical, regulatory, and payer decision needs. - Design and oversea study protocols and reports for post-hoc analyses of clinical trials, to contextualize meaningful treatment benefit for patient-centered clinical evaluation. - Engage in designing an externally controlled trial comparing treatment effectiveness versus real-world standard of care integrating trials and external registry data, to generate comparative effectiveness evidence for regulatory submissions. - Develop a comprehensive and accurate code library of disease-specific reference definitions (ICD, NDC, CPT, HCRU components), harmonized across databases and expert input to enable scalable future analytics. - Implement disease-staging algorithms on claims data to capture epidemiologic features and healthcare utilization of stage-specific populations, informing payer-facing decisions on target populations and care gaps. Achievements: - Accelerated product launch readiness by effectively delivering regulatory-grade study materials, streamlining analytic reference libraries and pipeline, and maintaining clear communication with product strategy leads. - Delivered rigorous target population sizing and recourse utilization profiling, with direct outputs subsequently used in health economic models for pricing. - Strengthened cross-functional collaboration across clinical, regulatory, medical affairs, and market access stakeholders. - Share concepts, methodologies, and best practice in trial-emulation, supporting broader team capability development.

* Responsibility highlights: Research focus; Methodological design; Systematic literature review; EHR data engineering; Pharmacoepidemiology; Multi-modal patient-reported outcomes; Analytical techniques; Machine learning phenotyping models; Association tests, meta-analyses, and causal inference (target trial emulation); Collaboration and communication.

TA of Molecular Epidemiology (Graduate Level): Lead discussions and critiques on research articles, and deliver comprehensive lectures on GWAS and Polygenic Risk Scores, enhancing student understanding, engagement, and critical thinking.

- Key projects: Biomarker development and evaluation; Comparative effectiveness study for drug repurposing; -Omics and bioinformatics for pathophysiology discovery; EHR, Claims and patient-reported outcomes; GWAS and PheWAS; Social determinants of health. - Research contribution: Advance clinical research on multiple sclerosis and related disorders (MSRD), employing appropriate epidemiological and biostatistical methods to design, execute and interpret epidemiology studies. - Collaborative leadership: Facilitate cross-functional collaborations with academic and industry experts; Deliver regular updates to ensure transparent and goal-oriented communication. - Mentorship: Provide guidance in epidemiological and statistical methods to clinical fellows. - Scientific writing: Author and co-author scientific papers; Assist with R01 grant writing.

Responsibilities: - Supported the development of a post-authorization safety study (PASS) for a product using 6 European disease registries, to monitor and compare long-term safety profiles in real-world settings across comparator treatments. - Designed and implemented a claims-based study investigating AE risk in RA patients across treatments, in response to information requests from the Japanese health authority. - Collaborated on development of an AI-powered tool to automatically extract AE information from published clinical trials, producing accurate and structured outputs without manual review. - Identified key limitations of existing safety surveillance tools (lack of data QC, inflexible AE specification, inaccurate incidence estimation under complex situations) and contributed to targeted improvements. Achievements: - Authored sections of the PASS protocol, including detailed data source descriptions for registry databases to be used, and valid MedDRA terms for defining infections and malignancies. - Discovered meaningful safety signals associated with RA treatments, forming the basis for a planned future manuscript. - Delivered a validated AI-based AE extraction tool achieving 97% accuracy, and successfully transferred the tool to external functional teams for broader deployment. - Upgraded existing safety surveillance tools to a more real-time, rapid, and flexible pipeline, adopted by colleagues to support preparedness ahead of internal review and safety meetings.

- Lead biostatistician: Direct data analyses across clinical and population research on neurological diseases; Plan, perform, visualize, and interpret statistical analyses; Provide expert statistical advice to postdoctoral clinical research fellows. - Key projects: Establish reference curves of biomarkers through GAMLSS models; Develop R Shiny App; Streamline data processing of clinical registries; Build parallel computing pipelines for MRI image segmentation; Perform Mendelian Randomization study; Conduct bioinformatic analyses (genomic, transcriptomics, and metabolomics); Clean and analyze high-dimensional digital health data; Perform functional time series models - Data coordination: Partner with clinical coordinators to facilitate data collection and follow-up. - Scientific communication: Engage in manuscript writing and findings presentation at major conferences.

TA of R programming (Undergraduate Level) Conducted weekly coding demonstrations and provided after-class support for debugging and project development, to promote practical and theoretical knowledge application.

- Safety and efficacy evaluation: Contribute to the post-marketing surveillance trial of Trulicity in China; Perform propensity score matching to optimize study design. - Protocol development: Assist with developing standard operating procedures and PRO questionnaires; Formulate statistical analysis plan to supplement the study protocol. - Panel discussion: Deliver an in-depth presentation on the design, assessment, and implementation of propensity score matching techniques; Lead a discussion of pros and cons among peers.

- Statistical consultation: Offer tailored statistical advice to researchers across academic backgrounds. - Statistical analyses: Perform survival analyses to evaluate effect of the metastatic bulk on clinical outcomes associated with anti-EGFR therapies in colorectal cancer.

Key Coursework: Epidemiology Methods, Causal Inference, Grant Writing, Pathophysiology of Environmental Disease, Molecular Epidemiology, Chronic Disease Epidemiology, Population Neuroscience

Key Coursework: Statistical Inference, Statistical Learning, Survival Analysis, Data Science Practicum, Statistical Methods for Medical Image Analysis, Advanced R

Key Coursework: Mathematical Analysis, Advanced Algebra, Stochastic Process, Differential Equation, Probability and Mathematical Statistics, Non-parametric statistics, Bayesian statistics, Python