Johnson & Johnson’s Open Source Journey in R

Tadeusz Lewandowski joined the pharmaceutical industry in 2001, as a statistical programmer in CRO, in 2008 joined Roche, worked as a Lead programmer in oncology; since 2016 led a group of statistical programming data analytics - working on AA, ML projects, and software development, in 2019 co-initiated the NEST project a business lead, in 2021, started a chapter of Pan-pharma code collaboration lead. In 2022, Tadeusz joined Johnson & Johnson as a Data Engineering Head and Open-Source group.

Mark Bynens is Director and Scientific Computing Operations (SCO) Head within Statistics & Decision Sciences (SDS), Global Development, Janssen R&D. In this role, he, together with his team, is responsible and accountable for amongst other: change management, project management and end-to-end management of software applications for statistical evaluation or for business processes, education in-classroom and e-learning, knowledge sharing, software/application acquisition and high-performance computing for intensive data evaluation, simulations, and statistical research. He is one of the main authors of the SCE White Paper and is an R-Consortium ISC member.

Nicholas Masel is the Open-Source Solutions Lead within Clinical & Statistical Programming at Johnson & Johnson. He is focused on leading the transition of J&J’s Statistical Programming group from an SAS-based environment and workflow to one supporting SAS, R, and Python. He is an active member and contributor to several external organizations, including PHUSE, the pharmaverse, and TransCelerate. He also contributes to a handful of packages specific to the pharmaceutical industry, including logrx, envsetup, datasetJSON, and tidytlg.

Mr. Sumesh Kalappurakal is the Senior Director, Technology Solutions for Clinical and Statistical Programming at Johnson & Johnson Innovative Medicine. He has been with the company since 2005 and has led a Medical Affairs programming team for twelve years. In his current role, Mr. Kalappurakal and his team are dedicated to developing technology solutions using open-source platforms, particularly R and Python. They establish methodologies, standards, and web applications to fulfill the portfolio requirements of clinical and statistical programming functions. Additionally, the team employs advanced automation techniques that utilize Natural Language Processing (NLP), Artificial Intelligence/Machine Learning (AI/ML), and Robotic Process Automation (RPA) to improve efficiency in clinical trial operations.

Phil is the Director of Healthcare and Life Sciences at Posit. His work focuses on innovation in the pharmaceutical industry, with an emphasis on interactive web applications, reproducible research and open-source education. He is interested in the use of R with applications in drug development and is a contributor to conferences promoting science through open data and software. He has experience at a number of technology and consulting corporations working in data science teams and delivering innovative data products. Phil has over 10 years’ experience implementing analytical programs, specializing in interactive web application initiatives and reporting needs for life science companies.