Irvine, California, United States
Clinical significance-focused biostatistics and data science leader with over a decade of success in driving regulatory submission approvals and publications within the pharmaceutical and medical device space. Experienced with neuroscience, GI, cardiovascular, oncology, venous thromboembolism, and chronic limb-threatening ischemia therapeutic areas. Design and lead RCTs, IDEs, PMAs, PMCF/PMS/PMR through regulatory body discussions and clinical evidence generation. Provide statistical innovation in the areas of comparative effectiveness, treatment efficacy gap, and personalized medicine.
◆ Stryker acquired Inari on Feb 19, 2025 for 4.9B ◆ Lead biostatistics, statistical programming, and data management functions
◆ Being part of the patient journey and revolutionizing the venous thromboembolism field including Pulmonary Embolism and Deep Vein Thrombosis! ◆ Encourage player-coach mentality and provide both hands-on and management guidance for the Biostatistics and Programming team. ◆ Design clinical studies in both RWE and RCT settings; expertise in adaptive designs (e.g. group sequential, sample size re-estimation, Bayesian Goldilocks) and win ratio outcomes. ◆ Implement CDISC process for all clinical studies, including RCTs (PEERLESS I, PEERLESS II, DEFIANCE, PERSEVERE) and real world registries (FLASH, CLOUT, JCLOUT, FLAME, FLARE-FT2, REVIT, VISION, ARTIXASCEND, PROMISE I/II/III, CLARITI). ◆ Generate real world evidence with ad-hoc analyses for conferences and publications. Support HEOR reimbursement analyses. ◆ Apply advanced causal inference methodologies: propensity score models, match adjusted indirect comparisons, machine learning predictive analytics, survival analyses (RMST, time-varying Cox, etc.), Bayesian power priors and data borrowing.
◆ Led a team of 25, including internal direct reports and external vendors. ◆ Supported Germany reimbursement dossier submission for SMA. ◆ Supported HTA for Alzheimer’s disease. ◆ Simulate MRI scanning frequency and minimizing mean squared error for brain volume measurements. ◆ Design innovative analyses for Neurofilament Light (NfL) prognosis modeling and disease monitoring. ◆ Apply innovative methodologies; expertise in machine learning, marginal structure models, propensity scores matching, multiple imputation, network meta-analysis, treatment comparative effectiveness, and dynamic treatment regime
◆ Supported Worldwide Medical and part of the ReAl WorLd EvIdence StrateGy and ANalytics (ALIGN) team. ◆ Aided RWE research areas including clinical trial and real world efficacy gap, treatment comparative effectiveness, personalized medicine, drug adherence pattern, and etc. ◆ Contributed to innovative statistical method for the Real World Evidence group; expertise in predictive analytics and causal inference approaches. ◆ Supported Multilple Sclerosis Post Authorization Safety Study (PASS) in Europe and Phase IV studies internationally. ◆ Supported Spinal Muscular Atrophy (SMA) registry planning in Europe and PASS internationally. ◆ Led 6 cohorts (Rush Medical, Mayo Clinic, Framingham, VUmC, Memora, AIBL) in real world evidence initiative for Alzheimer’s disease to plan for post Aducanumab approval; supported responses to EMA and HTA questions. 1. Disease Progression: investigated natural disease progression for real world patients similar to clinical trial placebo arm. 2. Medical Cost and Caregiver Burden: designed cost estimation models for answering payer questions. 3. Incidence of Comordities and Medical Events: estimated incidence of comorbidities and medical events and identify factors that may be source of confounding.
◆ Drove analysis for Medical Affairs department manuscript publication and presentation in addition to answering ad-hoc data driven questions under Transcatheter Heart Valve business unit. ◆ Analyzed volume-outcome relationship for site's learning curve in implementing device; immediate impact to patient access across the country. ◆ Submitted three successful abstracts to the largest interventional cardiology conference, EuroPCR 2017; lead to fast-track publication to European Heart Journal. ◆ Implemented innovative methods in SAS and R to answer clinical questions driven by Principal Investigators in USA, Europe, and Japan; expertise in propensity score models, survival analysis, and predictive/machine learning analytics. ◆ Aided FDA submission process and strategically answered FDA questions.
◆ Supported Genomic Medicine to drive Precision Healthcare in clinical studies across various therapeutic areas. ◆ Applied machine learning approaches (supervised and unsupervised) for companion diagnostic submissions; predict disease outcome from biomarkers for clinical trial patients and identified “super-responder” group to drug treatment. ◆ Aided cross-functional departments by representing modeling and simulation working group on different clinical studies and improved efficiency of timelines by 1-2 weeks. ◆ Educated non-stats group on the importance of scientific driven approaches based on statistical methods and increased use of statistical evidence in 15% of projects.