New publication in Drug Discovery Today

Transitioning to open-source statistical software allows the pharmaceutical industry to rapidly adopt and scale methodological innovations required for complex clinical trials, while ensuring transparency for key stakeholders. The shift enhances efficiency by reducing redundant costs of maintaining proprietary analysis pipelines, and shares the burden of software development, testing, validation, and maintenance across organisations.

The transition to open-source faces several challenges. A major challenge involves philosophical resistance rooted in the industry's reliance on proprietary software, due to validation, certification, and regulatory issues. Technical and resource hurdles also present challenges, particularly the lack of software-engineering skills among classically trained statisticians and statistical programmers, and concerns regarding the long-term sustainability and reliability of community-driven tools.

The way forward involves strategic shifts toward sustainable software-engineering practices and collaboration across organisations. Four key pillars contribute to success: professionalising research software engineers and upskilling statisticians, overcoming organisational barriers and scepticism, enhancing the collaborative ecosystem, and standardising quality and maintenance. Open-source has proven it can fit rigorous pharmaceutical and regulatory processes, with successful submissions by Roche and Novo Nordisk, and successful pilot projects by the R Submissions Working Group.