The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
A recent article published by Cytel authors Samadhan Ghubade, Sharayu Paranjpe, Kushagra Gupta, Anil Gore and colleague Krishna Asvalayan in the journal Current Science, tackles the topic of adverse drug reactions (ADRs) – a matter of great concern in drug research. The authors focused their research on drugs which had been either banned or withdrawn due to a serious problem of ADRs and applied quantitative modeling techniques to see if a systematic pattern of safety signals could be detected within the ADR count data. In this blog, the publication’s authors share their thoughts on the goals, takeaways and next steps for the research and we also link to the full article.
Signal management is one of the most audited pharmacovigilance processes. It also generates one of the highest findings from audits. The ability of Marketing Authorisation Holders (MAHs) to make a robust signal management system that is fully audit/inspection ready sometimes falls short of expectations. Happily, technology can be used to make the process more scientific and rigorous.
Technology in the signal management process can be divided into two categories. The first one is the front end i.e. what platform (.Net/JAVA) is being used to develop the system. The second is the back end i.e. what programs/software (R, Python, SAS) are used to process the data. In this blog, we will focus on the second category and discuss how R specifically can help improve the signal management process.