rpact (R package) 

 Accommodates the design, monitoring, and analysis of APE designs with binary, continuous, and survival outcomes as well as simulations.

esDesign (R package)

Facilitates the design of APE trials for various outcomes in the context of two subpopulations. It offers options for early stopping for either futility or efficacy as well as opportunity to increase sample sizes after an interim analysis based on conditional power in certain subpopulations showing results that are viewed as promising. See details of underpinning methods.  

GSED (R package) 

Allows the design of APE designs using group sequential methods using survival, binary, and continuous outcomes. Evaluates the selection of subgroups at interim analyses and estimates point and interval estimates. See details of underpinning methods. 

asd (R package)

Seamless adaptive trial with co-primary analyses in a prespecified subgroup and the full population. It allows an interim analysis using an early outcome (adaptation outcomes) that can be different from the primary outcome to decide on whether to proceed with both full and subpopulations, the subpopulation only or the full population, using a predefined selection rule. Also allows the use of different methods to control the familywise error rate. Simulations require data for the early and final primary outcomes, the correlation between the final and the early outcomes, and subpopulation prevalence. See details for underpinning methods with examples (Link 1; Link 2).
 

ASSISTant (R package)

Facilitates the design of a 3-stage APE trial using group sequential methods such as DEFUSE trial. See details for underpinning methods.

AdaptiveDesignOptimizer (R package)

Offers the design and simulation of APE trials with a binary, survival, and continuous outcome. Allows two prespecified subpopulations and full population.
 

FACTS

Adaptive design simulator that also facilitates the design and implementation APE trials using Bayesian methods.

East: ENRICH (module)

Facilitates the design, monitoring, and analysis of APE trials with sample size re-estimation for survival outcomes using the promising zone concept and combination test methods.

ADDPLAN: PE (module)

Facilitates the simulation and analysis of APE designs allowing for sample size re-estimation and early stopping for efficacy or futility using adaptive group sequential methods.

There is existing FDA guidance on adaptive trials ¹ and also on enrichment strategies in clinical trials ² which researchers may wish to read. Most importantly, researchers are encouraged to engage regulators at the planning stage when considering an APE trial such as via scientific advice meetings. 

1. FDA. Adaptive designs for clinical trials of drugs and biologics guidance for industry. 2019. Accessed February 5, 2020.
2. FDA. Enrichment strategies for clinical trials to support determination of effectiveness of human drugs and biological products guidance for industry. 2019. Accessed February 4, 2021.