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Kara Woo posit::conf(2023) R not only in production

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How can the strengths of R, and the people who use it, influence the organization as a whole?

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Meet Angela

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Vancomycin can treat MRSA

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There’s no one dose that works for everyone

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We use pharmacological models + patient’s unique characteristics to recommend the optimal dose

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Patient data, lab results, past doses

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Patient data, lab results, past doses Recommended dose

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R is core to our product

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R is core to fulfilling our mission

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ETL

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• REST API • Data processing pipeline • Analyses and new models • Model validation • Regulatory reporting • New product prototypes • …

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{ "firstName": "First name", "lastName": "Last name", "dob": "Date of birth", "changeMyPassword": "Change my password", "logout": "Logout", ... } { "firstName": "Vorname", "lastName": "Nachname", "dob": "Geburtsdatum", "changeMyPassword": "Ändere mein Passwort", "logout": "Ausloggen", ... }

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{ "firstName": "First name", "lastName": "Last name", "dob": "Date of birth", "changeMyPassword": "Change my password", "logout": "Logout", ... }

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{ "firstName": "First name", "lastName": "Last name", "dob": "Date of birth", "age": "Age", "changeMyPassword": "Change my password", "logout": "Logout", ... } 👀

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{ "firstName": "First name", "lastName": "Last name", "dob": "Date of birth", "age": "Age", "changeMyPassword": "Change my password", "logout": "Logout", ... } { "firstName": "Vorname", "lastName": "Nachname", "dob": "Geburtsdatum", "changeMyPassword": "Ändere mein Passwort", "logout": "Ausloggen", ... } 👀

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{ "firstName": "First name", "lastName": "Last name", "dob": "Date of birth", "age": "Age", "changeMyPassword": "Change my password", "logout": "Logout", ... } { "firstName": "Vorname", "lastName": "Nachname", "dob": "Geburtsdatum", "age": "Alter", "changeMyPassword": "Ändere mein Passwort", "logout": "Ausloggen", ... } 👀

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The mindset of R as a first class language empowers us to solve problems.

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We can do this in R!

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💡 Idea

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💡 Idea “It works on my machine”

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💡 Idea “It works on my machine” ? Final product ? ?

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💡 Idea “It works on my machine” ? Final product ? ?

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Reliability Deployability

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We need to detect kidney injury accurately, all the time.

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Elevated creatinine suggests kidney damage Easy, right? • Data gaps • Out of order data • Data in di ff erent units • Missing baseline • Non-numeric data • Data entry errors

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test_that("AKI stage is calculated correctly", { result <- calc_aki_stage( scr = c(0.7, 1.0), t = c(0, 24), egfr = c(60, 40) ) expect_equal(result$stage, "stage 1") })

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test_that("AKI stage is calculated correctly", { result <- calc_aki_stage( scr = c(0.7, 1.0), t = c(0, 24), egfr = c(60, 40) ) expect_equal(result$stage, "stage 1") })

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test_that("AKI stage is calculated correctly", { result <- calc_aki_stage( scr = c(0.7, 1.0), t = c(0, 24), egfr = c(60, 40) ) expect_equal(result$stage, "stage 1") })

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test_that("AKI stage is calculated correctly", { result <- calc_aki_stage( scr = c(0.7, 1.0), t = c(0, 24), egfr = c(60, 40) ) expect_equal(result$stage, "stage 1") })

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test_that("stage correct: 0.3 mg/dl rise", { # ... }) test_that("stage correct: 1.5x baseline rise", { # ... }) test_that("sorts times correctly", { # ... }) test_that("handles non-numeric inputs", { # ... }) test_that("handles only 1 observation", { # ... })

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Jenny Bryan “If you use software that lacks automated tests, you are the tests.”

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Get latest code Build the R package Run the tests Continuous integration

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5d01863 Add function to detect AKI ✅ a28vf11 Rewrite AKI function to improve performance ❌ 682hcKa Fix handling of missing data ✅

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Continuous integration • Find bugs quickly • Be lazy free up time for more important work • Make sure the code continues to behave as intended

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💡 Idea “It works on my machine” ? Final product Testing Continuous Integration

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💡 Idea “It works on my machine” Docker Final product Testing Continuous Integration

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R R packages your code Docker

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FROM rstudio/plumber:v1.1.0 RUN Rscript -e "install.packages('clinPK')" COPY . /myproject WORKDIR /myproject ENTRYPOINT ["Rscript", "entrypoint.R"] Dockerfile

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FROM rstudio/plumber:v1.1.0 RUN Rscript -e "install.packages('clinPK')" COPY . /myproject WORKDIR /myproject ENTRYPOINT ["Rscript", "entrypoint.R"] Dockerfile

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FROM rstudio/plumber:v1.1.0 RUN Rscript -e "install.packages('clinPK')" COPY . /myproject WORKDIR /myproject ENTRYPOINT ["Rscript", "entrypoint.R"] Dockerfile

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FROM rstudio/plumber:v1.1.0 RUN Rscript -e "install.packages('clinPK')" COPY . /myproject WORKDIR /myproject ENTRYPOINT ["Rscript", "entrypoint.R"] Dockerfile

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FROM rstudio/plumber:v1.1.0 RUN Rscript -e "install.packages('clinPK')" COPY . /myproject WORKDIR /myproject ENTRYPOINT ["Rscript", "entrypoint.R"] Dockerfile

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FROM rstudio/plumber:v1.1.0 RUN Rscript -e "install.packages('clinPK')" COPY . /myproject WORKDIR /myproject ENTRYPOINT ["Rscript", "entrypoint.R"] Dockerfile https://github.com/karawoo/dockerdemo

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Image: Royyan Razka, Noun Project

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Get latest code Build the 
 R package Run the tests Continuous integration

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Get latest code Build the docker image Run the tests Continuous integration

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💡 Idea “It works on my machine” Docker Final product Testing Continuous Integration

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We are motivated to answer questions

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Database query was too slow

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Database query was too slow Added an index to the database

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Database query was too slow Added an index to the database Data processing pipeline was too slow

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Database query was too slow Added an index to the database Data processing pipeline was too slow Removed the index

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If you can’t make changes because you’re afraid of breaking something, it’s already broken.

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We can visualize and communicate our findings

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Tests test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... })

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Tests test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) test_that("...", { # ... }) become data

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We are used to dealing with uncertainty

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Motivated to answer questions Skilled at visualizing and communicating results Able to handle uncertainty

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Using R throughout the stack = doing science throughout the stack

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pos.it/slido-keynote