Ndoh Penn
Biostatistician · Clinical Data Scientist
Profile

Biostatistician with 5+ years in pharmaceutical clinical development, clinical assay statistics, and translational research. Experienced in longitudinal and repeated-measures models, time-to-event methods, Bayesian methods, and high-dimensional biomarker data. Strong R and SAS programmer; CDISC SDTM/ADaM expertise; R Shiny developer. Open-source enthusiast and developer of R packages for regulated analytical workflows.

Experience
Open-Source Development
ReproStats · Belgium
  • Designed and built four R packages covering tamper-evident audit logging, row-level data provenance, CDISC-compliant exclusion tracking, and Bayesian prior elicitation.
  • Two packages published on CRAN (reproducr, bayprior); two in submission/active development (regulog, lineager).
  • Built IQ/OQ/PQ qualification suites for regulog covering 21 CFR Part 11 §11.10, §11.100, §11.200 and EU Annex 11 Clauses 9 and 11.
Statistician – FSP
Enovalife · GSK · Brussels, Belgium

Vx Clinical Assay Statistics · Jul 2023 – Mar 2025

  • Led statistical design, analysis, and interpretation of clinical assay experiments supporting vaccine immunogenicity programmes.
  • Provided statistical expertise across assay development, validation, and lifecycle management including performance characterisation for pharmacodynamic and predictive endpoints.
  • Developed and executed statistical analysis plans.
  • Championed R adoption; designed and deployed R Shiny dashboards and analysis tools to enhance reproducibility, traceability, and reporting.

Vx Preclinical & Research Statistics · May 2022 – Jul 2023

  • Performed analysis of preclinical data supporting translational research questions.
  • Designed and implemented statistical analysis plans; conducted QC and compiled analysis reports.
  • Participated in cross-functional planning meetings on statistical methodology and experimental design.
Statistician – Health Data Scientist
INSERM · Bordeaux, France
  • Wrote and maintained statistical analysis plans for high-dimensional survival data studies incorporating biomarker endpoints.
  • Implemented advanced methods: time-to-event models, penalised regression, and machine learning-based prediction models.
  • Co-authored research communications.
Epidemiologist
Cameroon Society of Epidemiology (CaSE) · Yaoundé, Cameroon
  • Designed data collection tools; supervised vaccine programme epidemiological investigations and public health surveillance.
Education
DegreeInstitutionYear
M.Sc. Public Health Data ScienceUniversity of Bordeaux, France2019 – 2020
M.Sc. Applied Statistics & BiostatisticsHasselt University, Belgium2016 – 2019
M.Sc. EpidemiologyUniversity of Buea, Cameroon2013 – 2015
B.Sc. MicrobiologyUniversity of Buea, Cameroon2010 – 2013
Certifications
  • Advanced Certificate in Practical Applications of Bayesian Statistics in Clinical Trials · London School of Business & Research · Oct 2025 – Mar 2026
  • ICH Good Clinical Practice E6 (R2)
  • SAS Programming 2: Data Manipulation Techniques
  • SAS Macro Language · SAS Programming for R Users
  • SDTM001 – CDISC SDTM Implementation
Languages
EnglishFluent
FrenchAdvanced
DutchBasic
Technical Skills

Statistical methods: Mixed models, survival analysis, Bayesian methods, penalised regression, high-dimensional data analysis, biomarker statistics, time-series methods

Programming: R (advanced), R Shiny, SAS (advanced), Python (intermediate), Git, SQL

Standards & frameworks: CDISC SDTM/ADaM, 21 CFR Part 11, EU Annex 11, ICH E9(R1), GCP E6(R2)

R ecosystem: R Shiny & package development, testthat, pkgdown, devtools, Quarto, dplyr, ggplot2, haven, Rmarkdown