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toxSummary is an R Shiny app to visualize and summarize repeat-dose toxicologystudy results. toxSummary app wrapped in R package (which is also calledtoxSummary) so app can be distributed easily.

Prior to initiation of clinical trials, repeat-dose toxicology studies areconducted in multiple species to support the safety of the active pharmaceuticalingredient (API) in the proposed clinical dosing regimen, route ofadministration, and duration of treatment. The primary metric used toextrapolate the safety of clinical dosage from repeat-dose toxicology studyresults is the safety margin, i.e. the ratio of no observable adverse effectlevel (NOAEL) from the toxicology study to the proposed clinical dose. Thisratio can be calculated by using allometric scaling to approximate theequivalent human dose from that used in the toxicology study based on the bodysurface area of the species employed or by comparing the empirically measuredmaximum plasma concentration (Cmax) or total plasma exposure (AUC) between thetoxicokinetic animal data and the human pharmacokinetic data, if available.Another important consideration in drug safety evaluation is the nature andseverity of the toxicities observed at doses above the NOAEL. As toxicitystudies of various durations are typically conducted in multiple species andpotentially via multiple routes of administration, it can be challenging toeffectively integrate all of this information. In collaboration with thePharmaceutical Users Software Exchange (PHUSE) Nonclinical Scripts Working Groupand with consultation from toxicologists at FDA, an open source R shinyapplication was developed to allow users to interactively visualize safetymargins and the severity of user-defined significant toxicities across studiesthroughout a drug development program in a single plot. The application canalso present this information in tabular form that can be exported in variousformats, e.g. CSV, Excel or Word files. These functionalities are designed tofacilitate holistic evaluation of the drug safety by generating graphical andtabular summaries of the full toxicological profile of an API.

Package can be installed from CRAN.

#install toxSummary packageinstall.packages("toxSummary")

Development version can be installed from GitHub.

# install devtools if already not installed install.packages("devtools")#install toxSummary packagedevtools::install_github('phuse-org/toxSummary')

library(toxSummary)toxSummary::toxSummary_app()

library(toxSummary)toxSummary::toxSummary_app(    database_path = "path/of/your/database.db",    studyid_file = "path/for/program_studyid_mapping.csv",    save_file_path = NULL)

When save_file_path set to NULL, files will be saved in current working directory.an example database can be found in GitHub repositorydatabase link

database_path = "path/of/your/database.db"
studyid_file = "path/for/program_studyid_mapping.csv"
Package does not contain database. Database is too big for a package.

Clone theGitHub repo and set repo asworking directory.If you don't have any database to connect and want to run app,only run this following code in R console.

pkgload::load_all(".")toxSummary::toxSummary_app()

To run the app with database connection follow this direction;set repo as working directory and open app.R file (or copy code given below)and run the code. if you connect to your database then change the path toyour files.otherwise this will connect to example database available in test_datadirectory.

pkgload::load_all(".")db_path <- "test_data/test_db.db"study_list_path <- "test_data/IND_with_studies_2.csv"toxSummary::toxSummary_app(    database_path = db_path,    studyid_file = study_list_path,    save_file_path = NULL)

This will open toxSummary app. The default/example database(in "test_data/test_db.db" directory) only contain few studies.

First create app.R file in the working directory.
Then copy the code from here and change the database and file paths.

 toxSummary::toxSummary_app(    database_path = "path/of/your/database.db",    studyid_file = "path/for/program_studyid_mapping.csv",    save_file_path = NULL,    where_to_run = "rsconnect")

Deploying Shiny app as package is little different.There is no publish button when you open app.R file in RStudio. Runningrsconnect::writeManifest() command in R console will createmanifest.json file. app then can be deployed on rsconnect running
rsconnect::deployApp() command in R console.

Keep in mind that when app running on server, app need to have access to thefiles given in database_path and studyid_file argument.

A demo app can be found heredemo app link

MIT LICENSE

Copyright (c) 2023 Food and Drug Administration (FDA)

Permission is hereby granted, free of charge, to any person obtaining a copyof this software and associated documentation files (the "Software"), to dealin the Software without restriction, including without limitation the rightsto use, copy, modify, merge, publish, distribute, sublicense, and/or sellcopies of the Software, and to permit persons to whom the Software isfurnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THEAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHERLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THESOFTWARE, ANY UPDATES TO THE SOFTWARE MADE BY CRAN, OR THE USE OROTHER DEALINGS IN THE SOFTWARE OR ANY UPDATED VERSION.

This package/shiny app reflects the views of the author and should not beconstrued to represent FDA’s views or policies.

Any examples or sample analyses in this package are for illustrative purposes only.

Nothing in these scripts is intended to guide the analytic process andany interpretations of data found as a result of using these scripts aresolely the responsibility of the user of the scripts and not the developers.All users are responsible for ensuring their own compliance with applicable laws,regulations, and agency guidance.