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August 21, 22, and 23, 2019 (Date TBC), Harvard University, Cambridge


About

The second annual R/Pharma conference is planned for August 21, 22, and 23, 2019 at Harvard University, Cambridge, Massachusetts, USA. A confirmation on this date will appear on this site as soon as the venue booking is confirmed.

Based on feedback, we have devoted a 3rd day to the conference agenda focused completely on R/Pharma workshops for attendees. More info will be available soon.

R/Pharma is an ISC working group (www.r-consortium.org/projects/isc-working-groups) under the R Consortium. The conference is envisioned as a relatively small, scientifically & industry oriented, collegial event focused on the use of R in the development of pharmaceuticals. The conference will cover topics including reproducible research, regulatory compliance and validation, safety monitoring, clinical trials, drug discovery, research & development, PK/PD/pharmacometrics, genomics, diagnostics, immunogenicity and more. All will be discussed within the context of using R as a primary tool within the drug development process. The conference will showcase the current use of R that is helping to drive biomedical research, drug discovery & development, and clinical initiatives. (Note that topics related to the use of R in hospitals/clinics for patient care by clinicians, doctors, and researchers will likely be the focus of the upcoming R/Medicine conference.)

The conference will be a single track conference consisting of keynotes from renowned industry practitioners to key R developers to leading academics, pre-conference workshops and full-length presentations as well as a number of shorter, highly-energetic lightning talks.

R/Pharma is dedicated to providing a harassment-free conference experience for everyone regardless of gender, sexual orientation, disability or any feature that distinguishes human beings. For more information, please see the R Consortium code of conduct.

2018 Keynotes

Last years keynote speakers below.

  • RStudio

    Max Kuhn Modeling in the tidyverse

    RStudio Twitter

    The tidyverse (tidyverse.org) is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures. The packages primarily consist of tools for data ingest, manipulation, and visualization. In the last year or so, Rstudio and others have been creating a set of packages focused on the modeling process. In this talk, we will introduce the tidyverse and illustrate these new tools whose goals are to: simplify the modeling process, encourage empirical validation and good methodology, and to enable a wider variety of approaches.

  • FDA

    Lilliam Rosario Modernizing the new drug regulatory program in FDA/CDER

    FDA Bio

    Lilliam will be presenting a perspective on what the office of computational science is doing to support regulatory review for safety assessments. She will explore the concept of collaborations and sharing to support process and transparency, along with a perspective with the use of R.

  • Roche/Genentech

    Michael Lawrence Enabling open-source analytics in the enterprise

    Roche/Genentech Twitter

    The open-source analytics community is driving innovation in precompetitive spaces like statistical methodology, reproducibility approaches, visualization techniques, and scaling strategies. The diverse and rapidly evolving ecosystem of open-source tools and standards stands in contrast with the disposition of the enterprise towards stability, standardization, and reliability. This talk will present the policies and frameworks we have developed at Genentech to enable internal scientists to responsibly leverage open-source tools and to participate in the community process through their own contributions.

  • RStudio

    Joe Cheng Using interactivity responsibly in pharma

    RStudio Twitter

    Shiny is a package for turning analyses written in R into interactive web applications. This capability has obvious applications in pharma, as it lets R users build interactive apps for their collaborators to explore models or results, or to automate workflows. However, the interactivity of Shiny apps is a double-edged sword, as it introduces challenges to the traceability and reproducibility of your analysis. To use interactive applications in pharma responsibly, these challenges must be addressed. In this talk, I'll look at some of the tools and techniques you can use in Shiny to deal with these challenges head-on.

Location

Harvard University, CGIS South, Cambridge Street, Cambridge, MA, USA. Cambridge, MA

Contact

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