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Make name of the package hyperlinked in pkgdown
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@ramiromagno
ramiromagno committed Jul 31, 2024
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14 changes: 7 additions & 7 deletions README.Rmd
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Expand Up @@ -21,7 +21,7 @@ knitr::opts_chunk$set(

An EDC and Data Standard agnostic solution that enables the pharmaceutical
programming community to develop SDTM datasets in R. The reusable algorithms
concept in `{sdtm.oak}` provides a framework for modular programming and also
concept in ``{sdtm.oak}`` provides a framework for modular programming and also
can automate SDTM creation based on the standard SDTM spec.

## Installation
Expand All @@ -32,7 +32,7 @@ The package is available from CRAN and can be installed with:
install.packages("sdtm.oak")
```

You can install the development version of `{sdtm.oak}` from [GitHub](https://github.com/pharmaverse/sdtm.oak/) with:
You can install the development version of ``{sdtm.oak}`` from [GitHub](https://github.com/pharmaverse/sdtm.oak/) with:

``` r
# install.packages("remotes")
Expand All @@ -48,14 +48,14 @@ remotes::install_github("pharmaverse/sdtm.oak")
Due to the differences in raw data structures and data collection standards, it may seem impossible to develop a common approach for programming SDTM datasets.

## GOAL
{sdtm.oak} aims to address this issue by providing an EDC-agnostic, standards-agnostic solution. It is an open-source R package that offers a framework for the modular programming of SDTM in R. With future releases; it will also strive to automate the creation of SDTM datasets based on the metadata-driven approach using standard SDTM specifications.
`{sdtm.oak}` aims to address this issue by providing an EDC-agnostic, standards-agnostic solution. It is an open-source R package that offers a framework for the modular programming of SDTM in R. With future releases; it will also strive to automate the creation of SDTM datasets based on the metadata-driven approach using standard SDTM specifications.

## Scope
Our goal is to use {sdtm.oak} to program most of the domains specified in SDTMIG (Study Data Tabulation Model Implementation Guide: Human Clinical Trials) and SDTMIG-AP (Study Data Tabulation Model Implementation Guide: Associated Persons). This R package is based on the core concept of `algorithms`, implemented as functions capable of carrying out the SDTM mappings for any domains listed in the CDISC SDTMIG and across different versions of SDTM IGs. The design of these functions allows users to specify a raw dataset and a variable name(s) as parameters, making it EDC (Electronic Data Capture) agnostic. As long as the raw dataset and variable name(s) exist, {sdtm.oak} will execute the SDTM mapping using the selected function. It's important to note that {sdtm.oak} may not handle sponsor-specific details related to managing metadata for LAB tests, unit conversions, and coding information, as many companies have unique business processes. With subsequent releases, strive to automate SDTM creation using a metadata-driven approach based on a standard SDTM specification format.
Our goal is to use `{sdtm.oak}` to program most of the domains specified in SDTMIG (Study Data Tabulation Model Implementation Guide: Human Clinical Trials) and SDTMIG-AP (Study Data Tabulation Model Implementation Guide: Associated Persons). This R package is based on the core concept of `algorithms`, implemented as functions capable of carrying out the SDTM mappings for any domains listed in the CDISC SDTMIG and across different versions of SDTM IGs. The design of these functions allows users to specify a raw dataset and a variable name(s) as parameters, making it EDC (Electronic Data Capture) agnostic. As long as the raw dataset and variable name(s) exist, `{sdtm.oak}` will execute the SDTM mapping using the selected function. It's important to note that `{sdtm.oak}` may not handle sponsor-specific details related to managing metadata for LAB tests, unit conversions, and coding information, as many companies have unique business processes. With subsequent releases, strive to automate SDTM creation using a metadata-driven approach based on a standard SDTM specification format.

## Road Map

This Release: The V0.1 release of {sdtm.oak} users can create the majority of the SDTM domains. Domains that are NOT in scope for the V0.1 release are DM, Trial Design Domains, SV, SE, RELREC, Associated Person domains, and EPOCH Variable across all domains.
This Release: The V0.1 release of `{sdtm.oak}` users can create the majority of the SDTM domains. Domains that are NOT in scope for the V0.1 release are DM, Trial Design Domains, SV, SE, RELREC, Associated Person domains, and EPOCH Variable across all domains.

Subsequent Releases:
We are planning to develop the below features in the subsequent releases.\
Expand All @@ -72,14 +72,14 @@ We are planning to develop the below features in the subsequent releases.\

## Feedback

We ask users to follow the mentioned approach and try {sdtm.oak} to map any SDTM domains supported in this release. Users can also utilize the test data in the package to become familiar with the concepts before attempting on their own data. Please get in touch with us using one of the recommended approaches listed below:
We ask users to follow the mentioned approach and try `{sdtm.oak}` to map any SDTM domains supported in this release. Users can also utilize the test data in the package to become familiar with the concepts before attempting on their own data. Please get in touch with us using one of the recommended approaches listed below:

- [Slack](https://oakgarden.slack.com/)
- [GitHub](https://github.com/pharmaverse/sdtm.oak/issues)

## Acknowledgments

We thank the contributors and authors of the package. We also thank the CDISC COSA for sponsoring the {sdtm.oak}. Additionally, we would like to sincerely thank the volunteers from Roche, Pfizer, GSK, Vertex, and Merck for their valuable input as integral members of the CDISC COSA - OAK leadership team.
We thank the contributors and authors of the package. We also thank the CDISC COSA for sponsoring the `{sdtm.oak}`. Additionally, we would like to sincerely thank the volunteers from Roche, Pfizer, GSK, Vertex, and Merck for their valuable input as integral members of the CDISC COSA - OAK leadership team.



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20 changes: 10 additions & 10 deletions README.md
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Expand Up @@ -46,7 +46,7 @@ programming SDTM datasets.

## GOAL

{sdtm.oak} aims to address this issue by providing an EDC-agnostic,
`{sdtm.oak}` aims to address this issue by providing an EDC-agnostic,
standards-agnostic solution. It is an open-source R package that offers
a framework for the modular programming of SDTM in R. With future
releases; it will also strive to automate the creation of SDTM datasets
Expand All @@ -55,7 +55,7 @@ specifications.

## Scope

Our goal is to use {sdtm.oak} to program most of the domains specified
Our goal is to use `{sdtm.oak}` to program most of the domains specified
in SDTMIG (Study Data Tabulation Model Implementation Guide: Human
Clinical Trials) and SDTMIG-AP (Study Data Tabulation Model
Implementation Guide: Associated Persons). This R package is based on
Expand All @@ -64,17 +64,17 @@ carrying out the SDTM mappings for any domains listed in the CDISC
SDTMIG and across different versions of SDTM IGs. The design of these
functions allows users to specify a raw dataset and a variable name(s)
as parameters, making it EDC (Electronic Data Capture) agnostic. As long
as the raw dataset and variable name(s) exist, {sdtm.oak} will execute
as the raw dataset and variable name(s) exist, `{sdtm.oak}` will execute
the SDTM mapping using the selected function. It’s important to note
that {sdtm.oak} may not handle sponsor-specific details related to
that `{sdtm.oak}` may not handle sponsor-specific details related to
managing metadata for LAB tests, unit conversions, and coding
information, as many companies have unique business processes. With
subsequent releases, strive to automate SDTM creation using a
metadata-driven approach based on a standard SDTM specification format.

## Road Map

This Release: The V0.1 release of {sdtm.oak} users can create the
This Release: The V0.1 release of `{sdtm.oak}` users can create the
majority of the SDTM domains. Domains that are NOT in scope for the V0.1
release are DM, Trial Design Domains, SV, SE, RELREC, Associated Person
domains, and EPOCH Variable across all domains.
Expand Down Expand Up @@ -102,9 +102,9 @@ specification.

## Feedback

We ask users to follow the mentioned approach and try {sdtm.oak} to map
any SDTM domains supported in this release. Users can also utilize the
test data in the package to become familiar with the concepts before
We ask users to follow the mentioned approach and try `{sdtm.oak}` to
map any SDTM domains supported in this release. Users can also utilize
the test data in the package to become familiar with the concepts before
attempting on their own data. Please get in touch with us using one of
the recommended approaches listed below:

Expand All @@ -114,7 +114,7 @@ the recommended approaches listed below:
## Acknowledgments

We thank the contributors and authors of the package. We also thank the
CDISC COSA for sponsoring the {sdtm.oak}. Additionally, we would like to
sincerely thank the volunteers from Roche, Pfizer, GSK, Vertex, and
CDISC COSA for sponsoring the `{sdtm.oak}`. Additionally, we would like
to sincerely thank the volunteers from Roche, Pfizer, GSK, Vertex, and
Merck for their valuable input as integral members of the CDISC COSA -
OAK leadership team.

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