{ "_id": "6a169380acfb0bcc41d7984f", "Package": "escalation", "Type": "Package", "Title": "A Modular Approach to Dose-Finding Clinical Trials", "Version": "0.2.3", "Date": "2025-10-08", "Authors@R": "c(\nperson(\"Kristian\", \"Brock\",\nemail = \"kristian.brock@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-3921-0166\")\n),\nperson(\"Daniel\", \"Slade\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-6063-1283\")\n),\nperson(\"Michael\", \"Sweeting\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0003-0980-8965\")\n),\nperson(\"Conor\", \"Norris\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0009-0009-8850-0811\")\n),\nperson(\"Bharat\", \"Bhushan\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0009-0001-5271-7113\")\n)\n)", "Maintainer": "Kristian Brock ", "Description": "Methods for working with dose-finding clinical trials. We\nprovide implementations of many dose-finding clinical trial\ndesigns, including the continual reassessment method (CRM) by\nO'Quigley et al. (1990) , the toxicity\nprobability interval (TPI) design by Ji et al. (2007)\n, the modified TPI (mTPI) design\nby Ji et al. (2010) , the\nBayesian optimal interval design (BOIN) by Liu & Yuan (2015)\n, EffTox by Thall & Cook (2004)\n; the design of Wages &\nTait (2015) , and the 3+3\ndescribed by Korn et al. (1994) .\nAll designs are implemented with a common interface. We also\noffer optional additional classes to tailor the behaviour of\nall designs, including avoiding skipping doses, stopping after\nn patients have been treated at the recommended dose, stopping\nwhen a toxicity condition is met, or demanding that n patients\nare treated before stopping is allowed. By daisy-chaining\ntogether these classes using the pipe operator from 'magrittr',\nit is simple to tailor the behaviour of a dose-finding design\nso it behaves how the trialist wants. Having provided a\nflexible interface for specifying designs, we then provide\nfunctions to run simulations and calculate dose-paths for\nfuture cohorts of patients.", "License": "GPL (>=3)", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "URL": "https://brockk.github.io/escalation/,\nhttps://github.com/brockk/escalation", "BugReports": "https://github.com/brockk/escalation/issues", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libuv1-dev\nlibxml2-dev libx11-dev", "Repository": "https://brockk.r-universe.dev", "Date/Publication": "2025-10-08 13:39:24 UTC", "RemoteUrl": "https://github.com/brockk/escalation", "RemoteRef": "HEAD", "RemoteSha": "add4557aba9c0a124f1f27b4cef7202078b7540c", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-27 06:38:50 UTC", "User": "root" }, "Author": "Kristian Brock [aut, cre] (ORCID:\n),\nDaniel Slade [aut] (ORCID: ),\nMichael Sweeting [aut] (ORCID: ),\nConor Norris [ctb] (ORCID: ),\nBharat Bhushan [ctb] (ORCID: )", "MD5sum": "ad824a4955bafceae7c608b1402ee47c", "_user": "brockk", "_type": "src", "_file": "escalation_0.2.3.tar.gz", "_fileid": "d27379858be075af420309b0acfd9cd593fbc7deb6036ec0972d1a685a610fc9", "_filesize": 1688496, "_sha256": "d27379858be075af420309b0acfd9cd593fbc7deb6036ec0972d1a685a610fc9", "_created": "2026-05-27T06:38:50.000Z", "_published": "2026-05-27T06:47:28.864Z", "_distro": "noble", "_jobs": [ { "job": 78021731808, "time": 442, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7233690541" }, { "job": 78021731812, "time": 429, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7233687517" }, { "job": 78021731841, "time": 264, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7233640969" }, { "job": 78021731921, "time": 281, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7233644036" }, { "job": 78020887079, "time": 395, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7233575109" }, { "job": 78021731795, "time": 148, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7233614408" }, { "job": 78021731855, "time": 461, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7233695790" }, { "job": 78021731828, "time": 464, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7233696911" }, { "job": 78021731806, "time": 454, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7233694672" } ], "_buildurl": "https://github.com/r-universe/brockk/actions/runs/26494950176", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/brockk/escalation", "_commit": { "id": "add4557aba9c0a124f1f27b4cef7202078b7540c", "author": "Kristian Brock ", "committer": "GitHub ", "message": "Update test-coverage.yaml", "time": 1759930764 }, "_maintainer": { "name": "Kristian Brock", "email": "kristian.brock@gmail.com", "login": "brockk", "description": "I am a clinical trial statistician, with a research focus on efficient methods for early phase trials, especially Bayesian methods. I write in R, Python & Stan.", "uuid": 10177935, "orcid": "0000-0002-3921-0166" }, "_registered": true, "_dependencies": [ { "package": "magrittr", "role": "Depends" }, { "package": "dplyr", "role": "Imports" }, { "package": "tidyr", "version": ">= 1.0", "role": "Imports" }, { "package": "tidyselect", "role": "Imports" }, { "package": "stringr", "role": "Imports" }, { "package": "purrr", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "gtools", "role": "Imports" }, { "package": "dfcrm", "role": "Imports" }, { "package": "BOIN", "role": "Imports" }, { "package": "trialr", "version": ">= 0.1.5", "role": "Imports" }, { "package": "DiagrammeR", "role": "Imports" }, { "package": "RColorBrewer", "role": "Imports" }, { "package": "viridis", "role": "Imports" }, { "package": "binom", "role": "Imports" }, { "package": "R6", "role": "Imports" }, { "package": "mvtnorm", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "Iso", "role": "Imports" }, { "package": "testthat", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "covr", "role": "Suggests" } ], "_owner": "brockk", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-41", "n": 2 } ], "_tags": [], "_stars": 17, "_contributors": [ { "user": "brockk", "count": 127, "uuid": 10177935 }, { "user": "dsladeaz", "count": 5, "uuid": 134501244 }, { "user": "olivroy", "count": 1, "uuid": 52606734 } ], "_userbio": { "uuid": 10177935, "type": "user", "name": "Kristian Brock", "description": "I am a clinical trial statistician, with a research focus on efficient methods for early phase trials, especially Bayesian methods. I write in R, Python & Stan." }, "_downloads": { "count": 294, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/escalation" }, "_mentions": 1, "_devurl": "https://github.com/brockk/escalation", "_pkgdown": "https://brockk.github.io/escalation/", "_searchresults": 80, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/escalation.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/brockk/escalation", "_realowner": "brockk", "_cranurl": true, "_releases": [ { "version": "0.1.1", "date": "2020-03-08" }, { "version": "0.1.2", "date": "2020-04-14" }, { "version": "0.1.3", "date": "2020-05-13" }, { "version": "0.1.4", "date": "2020-10-18" }, { "version": "0.1.5", "date": "2023-05-29" }, { "version": "0.1.8", "date": "2024-02-23" }, { "version": "0.1.9", "date": "2024-05-22" }, { "version": "0.1.10", "date": "2024-06-27" }, { "version": "0.2.3", "date": "2025-10-08" } ], "_exports": [ "boin12_rds", "calculate_probabilities", "check_dose_selector_consistency", "cohort", "cohorts_of_n", "continue", "convergence_plot", "CorrelatedPatientSample", "crystallised_dose_paths", "demand_n_at_dose", "dont_skip_doses", "dose_admissible", "dose_escalation_table", "dose_indices", "dose_paths", "dose_paths_function", "dose_string_to_vector", "dose_strings", "dose_vector_to_string", "doses_given", "eff", "eff_at_dose", "eff_limit", "empiric_eff_rate", "empiric_tox_rate", "enforce_three_plus_three", "expand_last_dose_to_cohort", "fit", "follow_path", "get_boin", "get_boin_comb", "get_boin12", "get_dfcrm", "get_dfcrm_tite", "get_dose_combo_indices", "get_dose_paths", "get_empiric_crm_skeleton_weights", "get_mtpi", "get_mtpi2", "get_potential_outcomes", "get_random_selector", "get_three_plus_three", "get_tpi", "get_trialr_crm", "get_trialr_crm_tite", "get_trialr_efftox", "get_trialr_nbg", "get_trialr_nbg_tite", "get_wages_and_tait", "graph_paths", "is_randomising", "linear_follow_up_weight", "mean_prob_eff", "mean_prob_tox", "median_prob_eff", "median_prob_tox", "model_frame", "n_at_dose", "n_at_recommended_dose", "num_cohort_outcomes", "num_dose_path_nodes", "num_doses", "num_eff", "num_patients", "num_tox", "parse_phase1_2_outcomes", "parse_phase1_outcomes", "PatientSample", "phase1_2_outcomes_to_cohorts", "phase1_outcomes_to_cohorts", "prob_administer", "prob_eff_exceeds", "prob_eff_quantile", "prob_eff_samples", "prob_recommend", "prob_tox_exceeds", "prob_tox_quantile", "prob_tox_samples", "recommended_dose", "select_boin_comb_mtd", "select_boin_mtd", "select_boin12_obd", "select_dose_by_cibp", "select_mtpi_mtd", "select_mtpi2_mtd", "select_tpi_mtd", "selector", "selector_factory", "simulate_compare", "simulate_trials", "simulation_function", "simulations", "simulations_collection", "spread_paths", "stack_sims_vert", "stick_on_num_tox", "stop_at_n", "stop_when_n_at_dose", "stop_when_too_toxic", "stop_when_tox_ci_covered", "supports_sampling", "three_plus_three", "tox", "tox_at_dose", "tox_limit", "tox_target", "trial_duration", "try_rescue_dose", "unadmit_untested", "utility", "weight" ], "_help": [ { "page": "as_tibble.dose_paths", "title": "Cast 'dose_paths' object to 'tibble'.", "topics": [ "as_tibble.dose_paths" ] }, { "page": "as_tibble.selector", "title": "Cast 'dose_selector' object to 'tibble'.", "topics": [ "as_tibble.selector" ] }, { "page": "as_tibble.simulations_collection", "title": "Convert a simulations_collection to a tibble", "topics": [ "as_tibble.simulations_collection" ] }, { "page": "boin12_rds", "title": "Tabulate rank-based desirability scores for a BOIN12 trial", "topics": [ "boin12_rds" ] }, { "page": "calculate_probabilities", "title": "Calculate dose-path probabilities", "topics": [ "calculate_probabilities" ] }, { "page": "check_dose_selector_consistency", "title": "Check the consistency of a dose_selector instance", "topics": [ "check_dose_selector_consistency" ] }, { "page": "check_simulations_consistency", "title": "Check the consistency of a dose_selector instance", "topics": [ "check_simulations_consistency" ] }, { "page": "cohort", "title": "Cohort numbers of evaluated patients.", "topics": [ "cohort" ] }, { "page": "cohorts_of_n", "title": "Sample times between patient arrivals using the exponential distribution.", "topics": [ "cohorts_of_n" ] }, { "page": "combo_selector", "title": "Dose selector for combinations of treatments", "topics": [ "combo_selector" ] }, { "page": "continue", "title": "Should this dose-finding experiment continue?", "topics": [ "continue" ] }, { "page": "convergence_plot", "title": "Plot the convergence processes from a collection of simulations.", "topics": [ "convergence_plot" ] }, { "page": "CorrelatedPatientSample", "title": "A sample of patients that experience correlated events in simulations.", "topics": [ "CorrelatedPatientSample" ] }, { "page": "crystallised_dose_paths", "title": "Dose-paths with probabilities attached.", "topics": [ "crystallised_dose_paths" ] }, { "page": "demand_n_at_dose", "title": "Demand there are n patients at a dose before condisdering stopping.", "topics": [ "demand_n_at_dose" ] }, { "page": "dont_skip_doses", "title": "Prevent skipping of doses.", "topics": [ "dont_skip_doses" ] }, { "page": "dose_admissible", "title": "Is each dose admissible?", "topics": [ "dose_admissible" ] }, { "page": "dose_escalation_table", "title": "Plot a table of dose escalation vs de-escalation vs stop decisions", "topics": [ "dose_escalation_table" ] }, { "page": "dose_indices", "title": "Dose indices", "topics": [ "dose_indices" ] }, { "page": "dose_paths", "title": "Dose pathways", "topics": [ "dose_paths" ] }, { "page": "dose_paths_function", "title": "Get function for calculating dose pathways.", "topics": [ "dose_paths_function" ] }, { "page": "dose_string_to_vector", "title": "Go from a single multi-treatment dose string to a vector of dose-indices", "topics": [ "dose_string_to_vector" ] }, { "page": "dose_strings", "title": "Dose strings", "topics": [ "dose_strings" ] }, { "page": "dose_vector_to_string", "title": "Go from a single multi-treatment vector of dose-indices to a dose string", "topics": [ "dose_vector_to_string" ] }, { "page": "doses_given", "title": "Doses given to patients.", "topics": [ "doses_given", "doses_given.boin_comb_selector", "doses_given.simulations" ] }, { "page": "eff", "title": "Binary efficacy outcomes.", "topics": [ "eff" ] }, { "page": "eff_at_dose", "title": "Number of toxicities seen at each dose.", "topics": [ "eff_at_dose" ] }, { "page": "eff_limit", "title": "Efficacy rate limit", "topics": [ "eff_limit" ] }, { "page": "empiric_eff_rate", "title": "Observed efficacy rate at each dose.", "topics": [ "empiric_eff_rate" ] }, { "page": "empiric_tox_rate", "title": "Observed toxicity rate at each dose.", "topics": [ "empiric_tox_rate" ] }, { "page": "enforce_three_plus_three", "title": "Enforce that a trial path has followed the 3+3 method.", "topics": [ "enforce_three_plus_three" ] }, { "page": "expand_last_dose_to_cohort", "title": "Expand the cohort of the last given dose to at least n patients", "topics": [ "expand_last_dose_to_cohort" ] }, { "page": "fit", "title": "Fit a dose-finding model.", "topics": [ "fit" ] }, { "page": "follow_path", "title": "Follow a pre-determined dose administration path.", "topics": [ "follow_path" ] }, { "page": "get_boin", "title": "Get an object to fit the BOIN model using the BOIN package.", "topics": [ "get_boin" ] }, { "page": "get_boin_comb", "title": "Get an object to fit the BOIN COMB model using the BOIN package.", "topics": [ "get_boin_comb" ] }, { "page": "get_boin12", "title": "Get an object to fit the BOIN12 model for phase I/II dose-finding.", "topics": [ "get_boin12" ] }, { "page": "get_dfcrm", "title": "Get an object to fit the CRM model using the dfcrm package.", "topics": [ "get_dfcrm" ] }, { "page": "get_dfcrm_tite", "title": "Get an object to fit the TITE-CRM model using the dfcrm package.", "topics": [ "get_dfcrm_tite" ] }, { "page": "get_dose_combo_indices", "title": "Get all combinations of dose indices", "topics": [ "get_dose_combo_indices" ] }, { "page": "get_dose_paths", "title": "Calculate future dose paths.", "topics": [ "get_dose_paths" ] }, { "page": "get_empiric_crm_skeleton_weights", "title": "Get posterior model weights for several empiric CRM skeletons.", "topics": [ "get_empiric_crm_skeleton_weights" ] }, { "page": "get_mtpi", "title": "Get an object to fit the mTPI dose-finding model.", "topics": [ "get_mtpi" ] }, { "page": "get_mtpi2", "title": "Get an object to fit the mTPI-2 dose-finding model.", "topics": [ "get_mtpi2" ] }, { "page": "get_potential_outcomes", "title": "Get potential outcomes from a list of PatientSamples", "topics": [ "get_potential_outcomes" ] }, { "page": "get_random_selector", "title": "Get an object to fit a dose-selector that randomly selects doses.", "topics": [ "get_random_selector" ] }, { "page": "get_three_plus_three", "title": "Get an object to fit the 3+3 model.", "topics": [ "get_three_plus_three" ] }, { "page": "get_tpi", "title": "Get an object to fit the TPI dose-finding model.", "topics": [ "get_tpi" ] }, { "page": "get_trialr_crm", "title": "Get an object to fit the CRM model using the trialr package.", "topics": [ "get_trialr_crm" ] }, { "page": "get_trialr_crm_tite", "title": "Get an object to fit the TITE-CRM model using the trialr package.", "topics": [ "get_trialr_crm_tite" ] }, { "page": "get_trialr_efftox", "title": "Get an object to fit the EffTox model using the trialr package.", "topics": [ "get_trialr_efftox" ] }, { "page": "get_trialr_nbg", "title": "Get an object to fit the NBG dose-finding model using the trialr package.", "topics": [ "get_trialr_nbg" ] }, { "page": "get_trialr_nbg_tite", "title": "Get an object to fit a TITE version of the NBG dose-finding model using trialr", "topics": [ "get_trialr_nbg_tite" ] }, { "page": "get_wages_and_tait", "title": "Get an object to fit Wages & Tait's model for phase I/II dose-finding.", "topics": [ "get_wages_and_tait" ] }, { "page": "graph_paths", "title": "Visualise dose-paths as a graph", "topics": [ "graph_paths" ] }, { "page": "is_randomising", "title": "Is this selector currently randomly allocating doses?", "topics": [ "is_randomising" ] }, { "page": "linear_follow_up_weight", "title": "Weights for tolerance and toxicity events using linear function of time", "topics": [ "linear_follow_up_weight" ] }, { "page": "mean_prob_eff", "title": "Mean efficacy rate at each dose.", "topics": [ "mean_prob_eff" ] }, { "page": "mean_prob_tox", "title": "Mean toxicity rate at each dose.", "topics": [ "mean_prob_tox" ] }, { "page": "median_prob_eff", "title": "Median efficacy rate at each dose.", "topics": [ "median_prob_eff" ] }, { "page": "median_prob_tox", "title": "Median toxicity rate at each dose.", "topics": [ "median_prob_tox", "median_prob_tox.boin_comb_selector" ] }, { "page": "model_frame", "title": "Model data-frame.", "topics": [ "model_frame" ] }, { "page": "n_at_dose", "title": "Number of patients treated at each dose.", "topics": [ "n_at_dose" ] }, { "page": "n_at_recommended_dose", "title": "Number of patients treated at the recommended dose.", "topics": [ "n_at_recommended_dose" ] }, { "page": "num_cohort_outcomes", "title": "Number of different possible outcomes for a cohort of patients", "topics": [ "num_cohort_outcomes" ] }, { "page": "num_dose_path_nodes", "title": "Number of nodes in dose-paths analysis", "topics": [ "num_dose_path_nodes" ] }, { "page": "num_doses", "title": "Number of doses.", "topics": [ "num_doses" ] }, { "page": "num_eff", "title": "Total number of efficacies seen.", "topics": [ "num_eff" ] }, { "page": "num_patients", "title": "Number of patients evaluated.", "topics": [ "num_patients" ] }, { "page": "num_tox", "title": "Total number of toxicities seen.", "topics": [ "num_tox" ] }, { "page": "parse_phase1_2_outcomes", "title": "Parse a string of phase I/II dose-finding outcomes to vector notation.", "topics": [ "parse_phase1_2_outcomes" ] }, { "page": "parse_phase1_outcomes", "title": "Parse a string of phase I dose-finding outcomes to vector notation.", "topics": [ "parse_phase1_outcomes" ] }, { "page": "PatientSample", "title": "A sample of patients to use in simulations.", "topics": [ "PatientSample" ] }, { "page": "phase1_2_outcomes_to_cohorts", "title": "Break a phase I/II outcome string into a list of cohort parts.", "topics": [ "phase1_2_outcomes_to_cohorts" ] }, { "page": "phase1_outcomes_to_cohorts", "title": "Break a phase I outcome string into a list of cohort parts.", "topics": [ "phase1_outcomes_to_cohorts" ] }, { "page": "prob_administer", "title": "Percentage of patients treated at each dose.", "topics": [ "prob_administer" ] }, { "page": "prob_eff_quantile", "title": "Quantile of the efficacy rate at each dose.", "topics": [ "prob_eff_quantile" ] }, { "page": "prob_recommend", "title": "Probability of recommendation", "topics": [ "prob_recommend" ] }, { "page": "prob_tox_exceeds", "title": "Probability that the toxicity rate exceeds some threshold.", "topics": [ "prob_eff_exceeds", "prob_tox_exceeds", "prob_tox_exceeds.boin_comb_selector" ] }, { "page": "prob_tox_quantile", "title": "Quantile of the toxicity rate at each dose.", "topics": [ "prob_tox_quantile", "prob_tox_quantile.boin_comb_selector" ] }, { "page": "prob_tox_samples", "title": "Get samples of the probability of toxicity.", "topics": [ "prob_eff_samples", "prob_tox_samples" ] }, { "page": "recommended_dose", "title": "Recommended dose for next patient or cohort.", "topics": [ "recommended_dose", "recommended_dose.simulations" ] }, { "page": "select_boin_comb_mtd", "title": "Select dose by BOIN-COMB's MTD-choosing algorithm.", "topics": [ "select_boin_comb_mtd" ] }, { "page": "select_boin_mtd", "title": "Select dose by BOIN's MTD-choosing algorithm.", "topics": [ "select_boin_mtd" ] }, { "page": "select_boin12_obd", "title": "Select dose by BOIN12's OBD-choosing algorithm.", "topics": [ "select_boin12_obd" ] }, { "page": "select_dose_by_cibp", "title": "Select dose by the CIBP selection criterion.", "topics": [ "select_dose_by_cibp" ] }, { "page": "select_mtpi_mtd", "title": "Select dose by mTPI's MTD-choosing algorithm.", "topics": [ "select_mtpi_mtd" ] }, { "page": "select_mtpi2_mtd", "title": "Select dose by mTPI2's MTD-choosing algorithm.", "topics": [ "select_mtpi2_mtd" ] }, { "page": "select_tpi_mtd", "title": "Select dose by TPI's MTD-choosing algorithm.", "topics": [ "select_tpi_mtd" ] }, { "page": "selector", "title": "Dose selector.", "topics": [ "selector" ] }, { "page": "selector_factory", "title": "Dose selector factory.", "topics": [ "selector_factory" ] }, { "page": "simulate_compare", "title": "Simulate clinical trials for several designs using common patients.", "topics": [ "simulate_compare" ] }, { "page": "simulate_trials", "title": "Simulate clinical trials.", "topics": [ "simulate_trials" ] }, { "page": "simulation_function", "title": "Get function for simulating trials.", "topics": [ "simulation_function" ] }, { "page": "simulations", "title": "Simulated trials.", "topics": [ "simulations" ] }, { "page": "simulations_collection", "title": "Make an instance of type 'simulations_collection'", "topics": [ "simulations_collection" ] }, { "page": "spread_paths", "title": "Spread the information in dose_finding_paths object to a wide data.frame format.", "topics": [ "spread_paths" ] }, { "page": "stack_sims_vert", "title": "Stack 'simulations_collection' results vertically", "topics": [ "stack_sims_vert" ] }, { "page": "stick_on_num_tox", "title": "Stay at the current dose when num_tox of num_patients have experienced tox", "topics": [ "stick_on_num_tox" ] }, { "page": "stop_at_n", "title": "Stop when there are n patients in total.", "topics": 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