Himanshu Pandya
Director, Clinical Data Sciences @Arcus Biosciences
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WORK HISTORY
Director, Clinical Data Sciences @Arcus Biosciences
CA, US
EDUCATION
Fairleigh Dickinson University
MS, Computer Science
Vishwakarma Institute Of Technology
BS, Mechanical Engineering
St. Xavier's High School
High School
SKILLS
ABOUT HIMANSHU PANDYA
I am a senior Data Science and Statistical Programming leader with 25 years of end-to-end clinical development experience (Phase I–IV) across Pharma, Biotech, and CRO environments, supporting both traditional clinical trials and emerging real-world data strategies.My career spans more than 20 FDA and global regulatory submissions, including NDA, BLA, and Advisory Committee (AdCom) preparations, with hands-on expertise navigating FDA, EMA, PMDA, and Health Canada requirements under aggressive timelines. I bring deep operational and strategic experience in CDISC-compliant SDTM and ADaM development, Define.xml, ISS/ISE, CSRs, DSMB reports, and integrated safety and efficacy analyses.I have worked extensively across multiple therapeutic areas - Oncology: Lung, GI, Pancreatic, Renal, ThyroidNeurology: Alzheimer’s, MS, Parkinson’sRare/Orphan Diseases: Fabry, Pompe, Gaucher, MPS IMusculoskeletal: OsteoarthritisInfectious Diseases: HIVBeyond execution, I specialize in modernizing clinical analytics and programming organizations. I have led and mentored global SAS teams in adopting open-source technologies (R, Python), driving efficiency, reproducibility, and innovation across both CSR and non-CSR deliverables. My experience includes leading development of R packages, R Shiny applications, and enterprise dashboards using Power BI, Spotfire, and Tableau.As an AI practitioner, I apply machine learning (supervised and unsupervised) techniques to RCT, RWD, biobank, and public datasets to uncover safety signals, patient subgroups, and data patterns. I also work with NLP and transformer-based models (BERT, BART, LLaMA, GPT, NER) for sentiment analysis, risk classification, text summarization, and medical information extraction—bridging clinical science, regulatory needs, and advanced analytics.I am particularly passionate about connecting regulatory rigor with emerging AI technologies, helping organizations adopt innovation responsibly while remaining inspection-ready and submission-focused.
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