R/Pharma logo

August 21, 22, and 23, 2019, Harvard University, Cambridge


About

The second annual R/Pharma conference will take place August 21, 22, and 23, 2019 at Harvard University, Cambridge, Massachusetts, USA.

Please note that R/Pharma 2019 is now full.

Thank you for the interest to attend R/Pharma 2019.

R/Pharma is deliberately a smaller event in terms of attendance in order to foster a more personal experience for attendees. Moreover, R/Pharma is a participant-driven gathering where the attendees are involved in running and organizing the meeting - a Contributor Attended Gathering. Our goal is to bring together the pharma community around open source R and attendance is driven by participation.

Please use the chat button (blue circle in lower left of screen) to let us know if you would like to be added to the wait-list.

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.

By design, R / Pharma is deliberately a smaller conference in terms of attendance in order to encourage maximum opportunities for direct interaction with speakers. The location will be the Center for Government and International Studies in the Tsai Auditorium at Harvard University and capped at 150 attendees. As of now, we are planning to make the gathering a free event. Invitations are firstly based on committee membership and advisory support, speaker acceptance, academic/student and diversity attendance.

Our entire event is a community-lead effort and 100% volunteer run. The event is vendor neutral and very much an academic conference. Harvard has been very helpful in hosting the event.

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.

2019 Organising Committee

The organising committee focuses on the logistics of running this conference. The content of this conference is shaped by dozens of Pharma industry colleagues in a community effort, led by John Sims and Bella Feng.

Harvey Lieberman Sanofi
Phil Bowsher RStudio
James Black Roche/Genentech
Edward Lauzier Merck
Elena Rantou FDA
Melvin Munsaka AbbVie
Eric Nantz Eli Lilly
Paul Schuette FDA
Michael Blanks Beigene
Min Lee Amgen
Reinhold Koch Roche/Genentech
Paulo Bargo Janssen
Volha Tryputsen Janssen
Elizabeth Hess IQSS Harvard University
John Sims Pfizer (& Program Committee link)
Bella Fang KitePharma, A Gilead Company (& Program Committee link)
Michael Lawrence Roche/Genentech (& R Foundation link)

Keynotes

  • Garrett Grolemund

    Garrett Grolemund Reproducibility and the role of code in reproducible data science

    RStudio Github

    Garrett Grolemund is the co-author of R for Data Science and R Markdown: The Definitive Guide, as well as the author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as both an educator and advocate of data science with R.

  • Paul Schuette

    Paul Schuette Simulations, and Complex Innovative Trial Designs

    FDA Blog on R use at the FDA

    Scientific Computing Coordinator for the Office of Biostatistics. Paul serves as subject matter expert for Scientific and Statistical Computing, manages scientific workstations, acquisition and deployment of software, and with additional projects dealing with statistical methodology appropriate for pregnancy registries and clinical trials.

  • Marianna Foos

    Marianna Foos Breaking the Speed Limit: How R Gets Faster

    Bluebird Bio Blog

    Scientific developer specializing in removing roadblocks to data access, with diverse experience independently moving projects forward with a focus on implementation details. Enthusiastic about empowering downstream analysis consumers with training, support and documentation.

  • Aedin Culhane

    Aedin Culhane Multi-modal data integration

    Harvard Lab website

    Computational Biologist at Dana-Farber Cancer Institue, Harvard School of Public Health. Her lab maintains ~6 Bioconductor packages.

Workshops

  • Joe Cheng

    Joe Cheng Shiny Reproducibility

    RStudio Github

    Joe is the Chief Technology Officer and Shiny team leader at RStudio.

  • Max Kuhn

    Max Kuhn Machine Learning

    RStudio Github

    Max is a Software Engineer at RStudio. He is the author or maintainer of several R packages for predictive modeling including caret, AppliedPredictiveModeling, Cubist, C50 and SparseLDA. He routinely teaches classes in predictive modeling at Predictive Analytics World and UseR! and his publications include work on neuroscience biomarkers, drug discovery, molecular diagnostics and response surface methodology.

  • Carson Sievert

    Carson Sievert Plotly

    Sievert Consulting LLC Website

    Carson is a freelance data scientist, well known as the maintainer of the plotly R package on CRAN.

  • Leon Eyrich Jessen

    Leon Eyrich Jessen Artificial neural networks in R with Keras and TensorFlow

    Technical University of Denmark Github

    Leon is an Assistant Professor in the Immunoinformatics and Machine Learning Group (Morten Nielsen Lab) at the Section for Bioinformatics at Technical University of Denmark. I apply advanced machine learning methods to model molecular interactions in the human immune system.

  • Andy Nicholls

    Andy Nicholls R Validation Hub (past, current and future state)

    GSK R validation hub website

    The R-Consortium in June 2018 awarded funding to create an online repository for R package validation in accordance with regulatory standards. Since the main hurdle for widespread use of R in late phase trials is ensuring adequate validation documentation, we are now focused on designing a framework which will specify a set of requirements, including metadata and examples of tests, which together would form evidence of the quality of an R package.

  • Will Landau

    Will Landau Machine learning workflow management with drake

    Eli Lilly drake website

    Machine learning workflows can be difficult to manage. A single round of computation can take several hours to complete, and routine updates to the code and data tend to invalidate hard-earned results. You can enhance the maintainability, hygiene, speed, scale, and reproducibility of such projects with the drake R package. drake resolves the dependency structure of your analysis pipeline, skips tasks that are already up to date, executes the rest with optional distributed computing, and organizes the output so you rarely have to think about data files. This talk demonstrates a deep learning project with drake-powered automation.

Schedule

DRAFT schedule - speakers, order and rooms are subject to change.

R/Pharma 2019 schedule
Room Title Speaker
2019-08-21 - Wednesday
8:10 AM - 8:40 AM Concourse Registration at CGIS South
8:40 AM - 10:10 AM S050 Shiny Reproducibility Joe Cheng
8:40 AM - 10:10 AM S250 R Validation Hub (past, current and future state) Andy Nicholls
8:40 AM - 10:10 AM S030 Artificial neural networks in R with Keras and TensorFlow Leon Eyrich Jessen
10:10 AM - 10:30 AM Concourse Break
10:30 AM - 12:30 PM S050 Shiny Reproducibility Joe Cheng
10:30 AM - 12:30 PM S250 R Validation Hub (past, current and future state) Andy Nicholls
10:30 AM - 12:30 PM S030 Artificial neural networks in R with Keras and TensorFlow Leon Eyrich Jessen
12:30 PM - 1:30 PM Concourse Lunch
1:30 PM - 3:00 PM S050 Machine learning Max Kuhn
1:30 PM - 3:00 PM S250 plottly Carson Sievert
1:30 PM - 3:00 PM S030 Machine learning workflow management with drake Will Landau
3:00 PM - 3:20 PM Concourse Break
3:20 PM - 5:20 PM S050 Machine learning Max Kuhn
3:20 PM - 5:20 PM S250 plottly Carson Sievert
3:20 PM - 5:20 PM S030 Machine learning workflow management with drake Will Landau
6:00 PM - 9:30 PM By invitation Pre-Conference Dinner for Speakers
2019-08-22 - Thursday
8:10 AM - 9:00 AM Concourse Registration at CGIS South
8:15 AM - 8:45 AM TBC Package Management Devin Pastoor
8:15 AM - 8:45 AM TBC R Education in Pharma Paulo Bargo and Satish Murthy
8:15 AM - 8:45 AM TBC R and Python Interoperability Sean Lopp
9:00 AM - 9:15 AM Auditorium Opening Remarks Merce Crosas, Chief Data Science and Technology Officer, IQSS
9:15 AM - 10:00 AM Auditorium Reproducibility and the role of code in reproducible data science Garrett Grolemund
10:00 AM - 10:20 AM Auditorium Using R for Generic Drug Evaluation and SABE R-package for Assessing Bioequivalence of Topical Dermatological Products Elena Rantou
10:20 AM - 10:30 AM Auditorium How to win friends and influence people: Efficiency, Reproducibility, and Scalability with R Project templates and parameterized R Markdown Leigh Alexander
10:30 AM - 10:50 AM Auditorium Teaching an old dog new tricks: modernizing gsDesign Keaven Anderson
10:50 AM - 11:10 AM Concourse Break
11:10 AM - 11:30 AM Auditorium nlmixr: an R package for population PKPD modeling Mirjam Trame
11:30 AM - 11:40 AM Auditorium Creating and reviving Shiny apps with {golem} Eric Nantz
11:40 AM - 12:00 PM Auditorium Exploratory Graphics (xGx): Promoting the purposeful exploration of PKPD data Alison Margolskee
12:00 PM - 12:10 PM Auditorium Interactive Visualization of Standardized CDISC-SEND-Formatted Toxicology Study Data Using R Shiny Kevin Snyder
12:10 PM - 12:30 PM Auditorium Using RStudio.Cloud to advance R proficiency: a crowdsourcing training experience Paulo Bargo
12:30 PM - 1:30 PM Concourse Lunch
1:30 PM - 1:50 PM Auditorium Updates on Analyzing Clinical Trials Data with R Adrian Waddell
1:50 PM - 2:00 PM Auditorium R Packages for Analyzing Clinical Trials Data with R Focusing on Safety And Early Efficacy Nina Qi
2:00 PM - 2:20 PM Auditorium Package management Devin Pastoor
2:20 PM - 2:30 PM Auditorium Shinytized R Markdown: A Potent OTC Alternative to 1,3,7‐Trimethylxanthine & Currently Indicated for NDA Document Generation, Among Others Mark Rothe
2:30 PM - 2:50 PM Auditorium Collaborating at scale: managing an enterprise analytical computing ecosystem Rena Yang
2:50 PM - 3:00 PM Auditorium Embrace R in Pharma - building internal R community and establishing fit-for-purpose R pilots Ning Leng
3:00 PM - 3:20 PM Auditorium Re-envisioning Clinical Content Delivery in the Open Source World Doug Kelkhoff
3:20 PM - 3:30 PM Auditorium The use of R for improved reproducibility of biomarker detection in liquid biopsies Vivian Zhuang
3:30 PM - 3:50 PM Concourse Break
3:50 PM - 4:35 PM Auditorium Breaking the Speed Limit: How R Gets Faster Marianna Foos
4:35 PM - 4:45 PM Auditorium Leveraging multiple R tools to make effective pediatric dosing decisions Jeannine Fisher
4:45 PM - 5:05 PM Auditorium Using Machine Learning and Interactive Graphics to Find New Cancer Targets David Cooper
5:05 PM - 5:15 PM Auditorium Machine learning workflow management with drake Will Landau
5:15 PM - 5:35 PM Auditorium An R package for Data Science and "Deep Visualization" of a complex clinical database David James
6:00 PM - 7:30 PM Cambridge Innovation Center Conference Reception (Cambridge Innovation Center, 245 Main Street, Cambridge MA)
2019-08-23 - Friday
8:10 AM - 9:00 AM Concourse Registration at CGIS South
8:15 AM - 8:45 AM TBC Shiny for Early Drug Discovery Research Gordon Turner
8:15 AM - 8:45 AM TBC Shiny in Production Kelly O'Briant
8:15 AM - 8:45 AM TBC SAS & R Bella Feng & Nate Mockler
9:00 AM - 9:15 AM Auditorium Opening Remarks Xiao-Li Meng, Professor of Statistics and Founding Editor in Chief of the Harvard Data Science Review
9:15 AM - 10:00 AM Auditorium Multi-modal data integration Aedin Culhane
10:00 AM - 10:20 AM Auditorium Your Missing Step in Reproducible R Programming: Continuous Deployment Chase Clark
10:20 AM - 10:30 AM Auditorium From playing in the backyard to designing one: Shiny transforms study designs, data analyses and statistical thinking of oncology in vivo group at Janssen Volha Tryputsen
10:30 AM - 10:50 AM Auditorium ModViz POP: R-Shiny Based PK/PD Interface for Empowering Teams to Perform Real-Time Simulations Pavan Vaddady
10:50 AM - 11:10 AM Concourse Break
11:10 AM - 11:30 AM Auditorium Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration Becca Krouse
11:30 AM - 11:40 AM Auditorium It's Not What's on the Outside, but It's What's on the Back-end That Matters: The World Beyond CSV Files Marcus Adams
11:40 AM - 12:00 PM Auditorium Improve installation sequences for R package cohorts Juliane Manitz
12:00 PM - 12:10 PM Auditorium Evaluating the performance of advanced causal inference methods applied to healthcare claims data Jessica Myers Franklin
12:10 PM - 12:30 PM Auditorium Tidysq for Working with Biological Sequence Data in ML Driven Epitope Prediction in Cancer Immunotherapy Leon Eyrich Jessen
12:30 PM - 1:30 PM Concourse Lunch
1:30 PM - 1:50 PM Auditorium This one is not like the others: Applicability Domain methods in R Max Kuhn
1:50 PM - 2:00 PM Auditorium Accelerating Chemistry Research through the Integration of Data Science with High-Throughput Experimentation Jason Stevens
2:00 PM - 2:20 PM Auditorium Reproducible shiny apps with shinymeta Carson Sievert
2:20 PM - 2:30 PM Auditorium Shiny apps for accelerating early drug discovery research Gordon Turner
2:30 PM - 2:40 PM Concourse Break - stretch your legs!
2:40 PM - 3:00 PM Auditorium Using R to foster the communication with non-statisticians on Bayesian dose escalation models Marianna Grinberg
3:00 PM - 3:10 PM Auditorium Prediction of maternal-fetal exposures of CYP450-metabolized drugs using physiologic pharmacokinetic modeling implemented in R and mrgsolve. Madeleine S. Gastonguay
3:10 PM - 3:30 PM Auditorium Making Better Decisions Andy Nicholls
3:30 PM - 3:40 PM Auditorium From CDISC to TLFs, using R to support Pharmacokinetic Analyses Jessica Higgins
3:40 PM - 4:00 PM Concourse Break
4:00 PM - 4:45 PM Auditorium Simulations, and Complex Innovative Trial Designs Paul Schuette
4:45 PM - 4:55 PM Auditorium Validation Framework for Assay Processing Pipelines Ellis Hughes
4:55 PM - 5:15 PM Auditorium Shiny in Production: Building bridges from data science to IT Kelly O'Briant
5:15 PM - 5:25 PM Auditorium Identifying progression-free survival in Veterans with Diffuse Large B-Cell Lymphoma using electronic healthcare records Debbie Morreall
5:25 PM - 5:45 PM Auditorium Democratizing Natural Language Processing with I2E and R Shiny Abhik Seal
5:45 PM - 8:00 PM Beat Brew Hall: https://www.beatbrewhall.com/ Drinks Offsite

Location

Programs

Please click an image below to view the program for R/Pharma conferences.

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