In this blog post, we’ll explore the top 45 R packages for clinical trials. In the realm of clinical research, the integration of R packages has become increasingly crucial for advancing data analysis and statistical methodologies. Join us as we explore the essential R packages that are revolutionizing the landscape of clinical trials, providing researchers with valuable tools for driving innovation and efficiency in the field of clinical research.
1. The accrualPlot Package
The accrualPlot package in R is a specialized tool designed to assist with the tracking and prediction of participant accrual in clinical trials. It’s an essential resource for researchers, statisticians, and clinical trial coordinators who need to monitor recruitment progress and forecast when a trial might reach its intended sample size.
For more information about the accrualPlot package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the accrualPlot package: Lukas Bütikofer <[email protected]>.
2. The BACCT Package
BACCT is a package in R that provides tools for Bayesian augment control to compare treatments in clinical trials. It includes functions for designing trials, estimating treatment effects, and conducting hypothesis tests.
For more information about the BACCT package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the BACCT package: Hongtao Zhang <[email protected]>.
3. The bayesCT Package
bayesCT is an R package that provides tools for Bayesian analysis of clinical trials. It includes functions for designing trials, monitoring trials, making interim decisions, and analyzing trial results.
For more information about the bayesCT package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the bayesCT package: Thevaa Chandereng <[email protected]>.
4. The BayesCTDesign Package
BayesCTDesign is an R package that provides tools for Bayesian design of clinical trials. It includes functions for specifying prior distributions, computing operating characteristics, and optimizing trial designs.
For more information about the BayesCTDesign package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the BayesCTDesign package: Barry Eggleston <[email protected]>.
5. The BOIN Package
BOIN stands for Bayesian Optimal INterval. This R package provides tools for designing and conducting phase I clinical trials using the Bayesian optimal interval design.
For more information about the BOIN package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the BOIN package: Ying Yuan <[email protected]>.
6. The brms.mmrm Package
brms.mmrm is an R package that extends the brms package to support mixed model repeated measures (MMRM) designs. MMRM designs are often used in clinical trials where measures are taken on the same subjects over time.
For more information about the brms.mmrm package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the brms.mmrm package: William Michael Landau <[email protected]>.
7. The c212 Package
c212 is an R package that provides a set of tools for conducting phase I and II clinical trials with adaptive designs. This includes functions for simulating trial outcomes, calculating optimal dose levels, and performing other tasks common in clinical trials.
For more information about the c212 package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the c212 package: Raymond Carragher <[email protected]>.
8. The clinDataReview Package
clinDataReview is an R package offering tools for reviewing clinical trial data. It provides functions to generate data review reports, perform data checks, and visualize data.
For more information about the clinDataReview package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the clinDataReview package: Laure Cougnaud <[email protected]>.
9. The clinfun Package
clinfun is an R package offering tools for performing common statistical tasks in clinical trials. It provides functions to compute sample sizes, perform interim analyses, and adjust p-values for multiplicity.
For more information about the clinfun package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the clinfun package: Venkatraman E. Seshan <[email protected]>.
10. The ClinicalTrialSummary Package
ClinicalTrialSummary is an R package offering tools for summarizing clinical trial data. It provides functions to compute summary statistics, create tables, and generate reports.
For more information about the ClinicalTrialSummary package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the ClinicalTrialSummary package: Daewoo Pak <[email protected]>.
11. The CTNote Package
CTNote is a package that provides functions for managing and analyzing clinical trials data. It includes features for importing data, cleaning and transforming data, performing statistical analyses, and generating reports.
For more information about the CTNote package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the CTNote package: Gabriel Odom <[email protected]>.
12. The ctrdata Package
Ctrdata is a package that provides functions for downloading and managing public data from clinical trials registered in the EU Clinical Trials Register (EUCTR) and the US ClinicalTrials.gov platforms.
For more information about the ctrdata package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the ctrdata package: Ralf Herold <[email protected]>.
13. The ctrialsgov Package
Ctrialsgov is a package that provides an interface to the ClinicalTrials.gov API, allowing users to download and analyze data from clinical trials registered in the US.
For more information about the ctrialsgov package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the ctrialsgov package: Taylor Arnold <[email protected]>.
14. The DesignCTPB Package
DesignCTPB stands for Designing Clinical Trials with Patient Burden. This package provides tools for designing clinical trials that take into account the burden on patients. This includes factors like the number and frequency of visits, the types of procedures involved, and the potential side effects of treatment. The package provides functions for modeling patient burden and for optimizing the trial design to minimize this burden.
For more information about the DesignCTPB package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the DesignCTPB package: Yitao Lu <[email protected]>.
15. The escalation Package
escalation is an R package that provides tools for designing dose escalation trials, which are used in the early phases of clinical drug development. It includes functions for defining trial parameters, simulating trial outcomes, and analyzing trial data.
For more information about the escalation package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the escalation package: Kristian Brock <[email protected]>.
16. The eudract Package
eudract is an R package that provides an interface to the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT). It includes functions for searching for clinical trials, retrieving trial information, and downloading trial data.
For more information about the eudract package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the eudract package: Simon Bond <[email protected]>.
17. The EurosarcBayes Package
EurosarcBayes is an R package that provides tools for Bayesian clinical trial design for rare cancers. It includes functions for specifying trial parameters, simulating trial outcomes, and analyzing trial data.
For more information about the EurosarcBayes package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the EurosarcBayes package: Peter Dutton <[email protected]>.
18. The ewoc Package
ewoc is an R package that provides tools for designing early-phase oncology clinical trials using the EffTox dose-finding design. It includes functions for defining trial parameters, simulating trial outcomes, and analyzing trial data.
For more information about the ewoc package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the ewoc package: Marcio A. Diniz <[email protected]>.
19. The fragility Package
fragility is an R package that provides tools for conducting fragility analysis in clinical research. It includes functions for fragility index calculation, result interpretation, and visualization.
For more information about the fragility package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the fragility package: Lifeng Lin <[email protected]>.
20. The grpseq Package
The grpseq package provides functions for group-sequential designs in clinical trials. This can be useful when designing clinical trials and planning interim analyses.
For more information about the grpseq package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the grpseq package: Lu Mao <[email protected]>.
21. The gsDesign Package
The gsDesign package provides functions for group sequential design in clinical trials. This can be useful when designing clinical trials and planning interim analyses.
For more information about the gsDesign package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the gsDesign package: Keaven Anderson <[email protected]>.
22. The hctrial Package
The hctrial package provides functions for designing and analyzing historical control trials. This can be beneficial when designing clinical trials and needing to incorporate historical control data.
For more information about the hctrial package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the hctrial package: Dominic Edelmann <[email protected]>.
23. The interim Package
The interim package provides tools for interim analysis and monitoring in clinical trials. It offers functions for calculating stopping boundaries, conducting group sequential analysis, and simulating trial outcomes.
For more information about the interim package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the interim package: Bastian Becker <[email protected]>.
24. The interimApp Package
The interimApp package is an app designed for scheduling interim analyses in clinical trials. It allows for interactive assessment of the timing of interim analyses, simulating recruitment and treatment/event phases of a clinical trial.
For more information about the interimApp package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the interimApp package: Bastian Becker <[email protected]>.
25. The Mediana Package
The Mediana package aids in clinical trial simulations and statistical analysis planning. It streamlines the process of analyzing clinical trials by providing a platform for statistical analysis in a reproducible manner.
For more information about the Mediana package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the Mediana package: Gautier Paux <[email protected]>.
26. The MedianaDesigner Package
The MedianaDesigner package is a complementary tool to Mediana, providing a user-friendly interface for the design of clinical trial simulation studies. It supports a wide range of designs and analysis methods, making the planning stage of clinical trials more efficient.
For more information about the MedianaDesigner package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the MedianaDesigner package: Alex Dmitrienko <[email protected]>.
27. The OneArmTTE Package
The OneArmTTE package in R is used for statistical analysis, offering functionalities for the design and analysis of time-to-event studies, particularly for a single-arm. This package is primarily useful in clinical trial scenarios, allowing us to analyze the time until an event occurs.
For more information about the OneArmTTE package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the OneArmTTE package: Heng Zhou <[email protected]>.
28. The ph2bye Package
The ph2bye package provides tools for designing Phase II clinical trials with binary endpoints. It uses Simon’s two-stage design and offers functions for sample size calculation, design evaluation, and interim/final analysis.
For more information about the ph2bye package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the ph2bye package: Yalin Zhu <[email protected]>.
29. The ph2mult Package
The ph2mult package is designed for Phase II clinical trials with multiple endpoints. It uses a multivariate normal model to analyze the multivariate response data and provides tools for sample size calculation and hypothesis testing.
For more information about the ph2mult package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the ph2mult package: Yalin Zhu <[email protected]>.
30. The Phase12Compare Package
The Phase12Compare package is a platform for comparing Phase I-II clinical trial designs. It provides users with the ability to generate operating characteristics and decision-theoretic quantities, enabling them to choose the most suitable design for their trial.
For more information about the Phase12Compare package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the Phase12Compare package: Andrew G Chapple <[email protected]>.
31. The randomizeR Package
The randomizeR package provides a user-friendly interface for designing and analyzing randomized controlled trials. It includes a variety of randomization procedures, making it a comprehensive tool for clinical researchers.
For more information about the randomizeR package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the randomizeR package: Ralf-Dieter Hilgers <[email protected]>.
32. The rpact Package
The rpact package is a tool for Adaptive Clinical Trial Design. It provides functions for design, analysis and simulation, making it easier to conduct complex, multistage clinical trials.
For more information about the rpact package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the rpact package: Friedrich Pahlke <[email protected]>.
33. The safetyCharts Package
The safetyCharts package is an R package that creates customizable, interactive data visualizations for safety data. It is particularly useful in clinical trials, where safety data needs to be visualized and analyzed in a comprehensive and efficient manner.
For more information about the safetyCharts package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the safetyCharts package: Jeremy Wildfire <[email protected]>.
34. The safetyData Package
The safetyData package is a companion to the safetyCharts package, providing clean, accessible, and standardized datasets for use with safetyCharts. It includes preprocessed clinical trial safety data, making it easier for researchers to visualize and analyze safety data.
For more information about the safetyData package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the safetyData package: Jeremy Wildfire <[email protected]>.
35. The safetyGraphics Package
The safetyGraphics package is designed for creating interactive graphics for safety data from clinical trials. It provides an easy way to create a wide range of charts, including timelines, scatterplots, and waterfall charts.
For more information about the safetyGraphics package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the safetyGraphics package: Jeremy Wildfire <[email protected]>.
36. The SampleSize4ClinicalTrials Package
The SampleSize4ClinicalTrials package in R offers functions to compute sample sizes for a variety of designs in clinical trials. This includes standard designs as well as more specific ones like cross-over designs, making it a comprehensive tool for clinical trial researchers.
For more information about the SampleSize4ClinicalTrials package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the SampleSize4ClinicalTrials package: Hongchao Qi <[email protected]>.
37. The seqmon Package
The seqmon package is designed to facilitate the monitoring of sequential trials in clinical research. It provides functions for adjusting stopping boundaries and assessing trial results, among other features, ensuring efficient and ethical operations of clinical trials.
For more information about the seqmon package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the seqmon package: Hui Zheng <[email protected]>.
38. The speff2trial Package
The speff2trial package is designed for conducting two-arm superiority trials in R. It provides functions for sample size calculation and power analysis, and it supports a variety of design and analysis methods, facilitating the planning and conduct of clinical trials.
For more information about the speff2trial package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the speff2trial package: Michal Juraska <[email protected]>.
39. The stepp Package
The stepp package in R stands for ‘Subpopulation Treatment Effect Pattern Plot (STEPP)’. It allows for the exploration of treatment effect patterns in subpopulations, useful in fields such as clinical trials and personalized medicine.
For more information about the stepp package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the stepp package: Wai-ki Yip <[email protected]>.
40. The subgroup Package
The subgroup package in R provides methods for subgroup discovery and analytics, particularly suited to clinical trial data and personalized medicine. This makes it an important tool in fields such as biostatistics and healthcare analytics.
For more information about the subgroup package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the subgroup package: I. Manjula Schou <[email protected]>.
41. The Surrogate Package
The Surrogate package provides tools for analyzing surrogate endpoints in clinical trials. This is often used in medical research to evaluate the effect of certain treatments.
For more information about the Surrogate package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the Surrogate package: Wim Van Der Elst <[email protected]>.
42. The tLagInterim Package
The tLagInterim package provides tools for time-lagged interim analyses in clinical trials. This package offers functions to estimate the sample size and statistical power for time-lagged interim analyses, offering a valuable tool for clinical trial design and analysis.
For more information about the tLagInterim package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the tLagInterim package: Shannon T. Holloway <[email protected]>.
43. The trialr Package
The trialr package in R is designed to offer Bayesian clinical trial designs for phase I/II oncology trials. It provides various models and methods for dose-response modeling and toxicity probability interval designs, improving the efficiency and effectiveness of clinical trials.
For more information about the trialr package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the trialr package: Kristian Brock <[email protected]>.
44. The TwoArmSurvSim Package
The `TwoArmSurvSim` package provides functions for simulating two-arm survival trials with time-to-event outcomes. Its a useful tool for planning and designing clinical trials, allowing researchers to model various scenarios and evaluate their potential impact.
For more information about the TwoArmSurvSim package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the TwoArmSurvSim package: Bo Zhang <[email protected]>.
45. The YPInterimTesting Package
The YPInterimTesting package offers functions to perform interim testing in clinical trials using a power prior. It helps in determining the effectiveness and safety of a treatment at an interim stage, providing valuable information for decision-making in clinical trials.
For more information about the YPInterimTesting package’s functionalities, you can review our comprehensive reference guide. To get started with the package, check out our beginner’s guide.
You can also contact the maintainer of the YPInterimTesting package: Daewoo Pak <[email protected]>.