Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants

Authors: Isabel Chien, Wessel P Bruinsma, Javier Gonzalez, Richard E. Turner

ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We evaluate SAFE-T on a thorough set of synthetic scenarios (Sec. 5.1), differing subgroup distributions (Sec. 5.2), and sample size variations (Sec. 5.3). In Sec. 5.4, we apply SAFE-T to a new adaptive setting, demonstrating possible future extensions.
Researcher Affiliation Collaboration 1University of Cambridge, Cambridge, UK 2Microsoft Research AI for Science 3Microsoft Research.
Pseudocode Yes We first discuss important components of SAFE-T and then detail the algorithm in Section 3.2, with pseudocode in Algorithm 1.
Open Source Code No The paper does not provide any explicit statements about open-source code availability or links to a code repository for the methodology described.
Open Datasets No The paper uses 'synthetic scenarios' which are constructed by the authors based on literature, but no concrete access information (link, DOI, repository, or formal citation to a public dataset) is provided for these scenarios.
Dataset Splits No The paper does not specify explicit training, validation, or test dataset splits (e.g., percentages or sample counts) for the synthetic scenarios used in the experiments.
Hardware Specification No The paper does not provide specific hardware details (e.g., GPU/CPU models, memory, or cloud instance types) used for running the experiments.
Software Dependencies No The paper mentions software like 'Py MC' and 'GPy Torch' for implementation but does not provide specific version numbers for these or other software dependencies.
Experiment Setup Yes We define νT = 0.2 for the safety constraint and νE = 0.2 (needed when UCB efficacy optimization is used)... Both the toxicity and efficacy GPs use constant mean functions (we set mean = 0.3 for toxicity and mean = 0.1 for efficacy) and the stationary radial basis function kernel (RBF kernel) as the covariance function (we set length scale = 4 for toxicity and length scale = 2 for efficacy). We also set the matrix A, with Q rows and S columns, which is composed of the coefficients a(i) s of the LMC model to 1.0 0 0.2 0.2 0 1.0.