{
  "_id": "6ac91931de46216d5edd9977",
  "Package": "pmxTools",
  "Type": "Package",
  "Title": "Pharmacometric and Pharmacokinetic Toolkit",
  "Version": "1.6.0.9000",
  "Authors@R": "c(person(\"Justin\", \"Wilkins\", email = \"justin.wilkins@occams.com\", role = c(\"aut\", \"cre\", \"cph\"), comment=c(ORCID=\"0000-0002-7099-9396\")),\nperson(\"Bill\", \"Denney\", email=\"wdenney@humanpredictions.com\", role=\"aut\", comment=c(ORCID=\"0000-0002-5759-428X\")),\nperson(\"Rik\", \"Schoemaker\", email=\"rik.schoemaker@occams.com\", role=\"aut\"),\nperson(\"Satyaprakash\", \"Nayak\", email=\"sn248@cornell.edu\", role=\"ctb\"),\nperson(\"Leonid\", \"Gibiansky\", email=\"lgibiansky@quantpharm.com\", role=\"ctb\"),\nperson(\"Andrew\", \"Hooker\", email=\"Andrew.Hooker@farmbio.uu.se\", role=\"ctb\"),\nperson(\"E. Niclas\", \"Jonsson\", email=\"niclas.jonsson@pharmetheus.com\", role=\"ctb\"),\nperson(\"Mats O.\", \"Karlsson\", email=\"mats.karlsson@farmbio.uu.se\", role=\"ctb\"),\nperson(\"John\", \"Johnson\", email=\"johndjohnson@gmail.com\", role=\"ctb\"))",
  "Maintainer": "Justin Wilkins <justin.wilkins@occams.com>",
  "Contact": "Justin Wilkins <justin.wilkins@occams.com>",
  "Description": "Pharmacometric tools for common data analytical tasks;\nclosed-form solutions for calculating concentrations at given\ntimes after dosing based on compartmental PK models\n(1-compartment, 2-compartment and 3-compartment, covering\ninfusions, zero- and first-order absorption, and lag times,\nafter single doses and at steady state, per Bertrand & Mentre\n(2008)\n<https://web.archive.org/web/20231002021707/https://www.facm.ucl.ac.be/cooperation/Vietnam/WBI-Vietnam-October-2011/Modelling/Monolix32_PKPD_library.pdf>);\nparametric simulation from NONMEM-generated parameter estimates\nand other output; and parsing, tabulating and plotting results\ngenerated by Perl-speaks-NONMEM (PsN).",
  "License": "GPL-2",
  "URL": "https://github.com/kestrel99/pmxTools,\nhttps://kestrel99.github.io/pmxTools/",
  "BugReports": "https://github.com/kestrel99/pmxTools/issues",
  "Roxygen": "list(markdown = TRUE)",
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  "Repository": "https://kestrel99.r-universe.dev",
  "Date/Publication": "2026-10-09 15:41:35 UTC",
  "RemoteUrl": "https://github.com/kestrel99/pmxtools",
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  "Packaged": {
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    "User": "root"
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  "Author": "Justin Wilkins [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-7099-9396>),\nBill Denney [aut] (ORCID: <https://orcid.org/0000-0002-5759-428X>),\nRik Schoemaker [aut],\nSatyaprakash Nayak [ctb],\nLeonid Gibiansky [ctb],\nAndrew Hooker [ctb],\nE. Niclas Jonsson [ctb],\nMats O. Karlsson [ctb],\nJohn Johnson [ctb]",
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  "_expires": "2027-01-17T16:41:18.000Z",
  "_created": "2026-10-09T16:29:58.000Z",
  "_published": "2026-10-09T16:41:20.852Z",
  "_buildurl": "https://github.com/r-universe/kestrel99/actions/runs/37959063362",
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    "committer": "Justin Wilkins <justin.wilkins@occams.com>",
    "message": "Merge branch 'nhanes-vignette': NHANES vignette and resampling as default method\n",
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  "_tags": [
    {
      "name": "v1.6",
      "date": "2026-10-07"
    }
  ],
  "_topics": [
    "nonmem",
    "pharmacokinetics",
    "simulation"
  ],
  "_stars": 37,
  "_contributors": [
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  "_pkgdown": "https://kestrel99.github.io/pmxTools/",
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
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    "extra/NEWS.txt",
    "extra/pmxTools.html",
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    "extra/readme.md"
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  "_homeurl": "https://github.com/kestrel99/pmxtools",
  "_realowner": "kestrel99",
  "_cranurl": true,
  "_releases": [
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      "date": "2018-03-14"
    },
    {
      "version": "0.1.1",
      "date": "2019-03-11"
    },
    {
      "version": "0.1.3",
      "date": "2019-10-28"
    },
    {
      "version": "1.0",
      "date": "2020-01-10"
    },
    {
      "version": "1.2.1",
      "date": "2020-08-26"
    },
    {
      "version": "1.2.3",
      "date": "2022-04-06"
    },
    {
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      "date": "2023-02-21"
    },
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      "date": "2025-08-25"
    },
    {
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      "date": "2026-10-07"
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  ],
  "_exports": [
    "blq_log_trans",
    "blq_trans",
    "breaks_blq_general",
    "calc_derived",
    "calc_derived_1cpt",
    "calc_derived_2cpt",
    "calc_derived_3cpt",
    "calc_sd_1cmt",
    "calc_sd_1cmt_linear_bolus",
    "calc_sd_1cmt_linear_infusion",
    "calc_sd_1cmt_linear_oral_0",
    "calc_sd_1cmt_linear_oral_0_lag",
    "calc_sd_1cmt_linear_oral_1",
    "calc_sd_1cmt_linear_oral_1_lag",
    "calc_sd_2cmt",
    "calc_sd_2cmt_linear_bolus",
    "calc_sd_2cmt_linear_infusion",
    "calc_sd_2cmt_linear_oral_0",
    "calc_sd_2cmt_linear_oral_0_lag",
    "calc_sd_2cmt_linear_oral_1",
    "calc_sd_2cmt_linear_oral_1_lag",
    "calc_sd_3cmt",
    "calc_sd_3cmt_linear_bolus",
    "calc_sd_3cmt_linear_infusion",
    "calc_sd_3cmt_linear_oral_0",
    "calc_sd_3cmt_linear_oral_0_lag",
    "calc_sd_3cmt_linear_oral_1",
    "calc_sd_3cmt_linear_oral_1_lag",
    "calc_ss_1cmt",
    "calc_ss_1cmt_linear_bolus",
    "calc_ss_1cmt_linear_infusion",
    "calc_ss_1cmt_linear_oral_0",
    "calc_ss_1cmt_linear_oral_0_lag",
    "calc_ss_1cmt_linear_oral_1",
    "calc_ss_1cmt_linear_oral_1_lag",
    "calc_ss_2cmt",
    "calc_ss_2cmt_linear_bolus",
    "calc_ss_2cmt_linear_infusion",
    "calc_ss_2cmt_linear_oral_0",
    "calc_ss_2cmt_linear_oral_0_lag",
    "calc_ss_2cmt_linear_oral_1",
    "calc_ss_2cmt_linear_oral_1_lag",
    "calc_ss_3cmt",
    "calc_ss_3cmt_linear_bolus",
    "calc_ss_3cmt_linear_infusion",
    "calc_ss_3cmt_linear_oral_0",
    "calc_ss_3cmt_linear_oral_0_lag",
    "calc_ss_3cmt_linear_oral_1",
    "calc_ss_3cmt_linear_oral_1_lag",
    "compare_nhanes",
    "count_na",
    "cut_quantile",
    "datamap",
    "dgr_table",
    "estimate_lloq",
    "fmt_signif",
    "ftrans_blq_linear",
    "ftrans_blq_log",
    "gcv",
    "gcv_convert",
    "get_auc",
    "get_est_table",
    "get_omega",
    "get_probinfo",
    "get_shrinkage",
    "get_sigma",
    "get_theta",
    "gm",
    "itrans_blq_linear",
    "itrans_blq_log",
    "label_blq",
    "pcv",
    "pk_curve",
    "plot_dist",
    "plot_nhanes",
    "plot_nmprogress",
    "plot_scm",
    "read_nm",
    "read_nm_all",
    "read_nm_multi_table",
    "read_nm_std_ext",
    "read_nmcov",
    "read_nmext",
    "read_nmtables",
    "read_scm",
    "rnm",
    "sample_nhanes",
    "sample_omega",
    "sample_sigma",
    "sample_uncert",
    "table_rtf"
  ],
  "_datasets": [
    {
      "name": "nhanes_peds",
      "title": "NHANES pediatric body weight and height reference data",
      "object": "nhanes_peds",
      "class": [
        "data.frame"
      ],
      "fields": [
        "CYCLE",
        "SEQN",
        "AGE_MONTHS",
        "AGE",
        "SEX",
        "WT",
        "HT",
        "MEC_WT"
      ],
      "rows": 11230,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "blq_trans",
      "title": "A transform for ggplot2 with data that may be below the lower limit of quantification",
      "concept": [
        "BLQ Transformation"
      ],
      "topics": [
        "blq_log_trans",
        "blq_trans"
      ]
    },
    {
      "page": "breaks_blq_general",
      "title": "Generate breaks for measurements below the limit of quantification",
      "concept": [
        "BLQ Transformation"
      ],
      "topics": [
        "breaks_blq_general"
      ]
    },
    {
      "page": "calc_derived",
      "title": "Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment linear model.",
      "topics": [
        "calc_derived",
        "calc_derived_1cpt",
        "calc_derived_2cpt",
        "calc_derived_3cpt"
      ]
    },
    {
      "page": "calc_sd_1cmt",
      "title": "Calculate C(t) for a 1-compartment linear model",
      "topics": [
        "calc_sd_1cmt",
        "calc_sd_1cmt_linear_bolus",
        "calc_sd_1cmt_linear_infusion",
        "calc_sd_1cmt_linear_oral_0",
        "calc_sd_1cmt_linear_oral_0_lag",
        "calc_sd_1cmt_linear_oral_1",
        "calc_sd_1cmt_linear_oral_1_lag"
      ]
    },
    {
      "page": "calc_sd_2cmt",
      "title": "Calculate C(t) for a 2-compartment linear model",
      "topics": [
        "calc_sd_2cmt",
        "calc_sd_2cmt_linear_bolus",
        "calc_sd_2cmt_linear_infusion",
        "calc_sd_2cmt_linear_oral_0",
        "calc_sd_2cmt_linear_oral_0_lag",
        "calc_sd_2cmt_linear_oral_1",
        "calc_sd_2cmt_linear_oral_1_lag"
      ]
    },
    {
      "page": "calc_sd_3cmt",
      "title": "Calculate C(t) for a 3-compartment linear model",
      "topics": [
        "calc_sd_3cmt",
        "calc_sd_3cmt_linear_bolus",
        "calc_sd_3cmt_linear_infusion",
        "calc_sd_3cmt_linear_oral_0",
        "calc_sd_3cmt_linear_oral_0_lag",
        "calc_sd_3cmt_linear_oral_1",
        "calc_sd_3cmt_linear_oral_1_lag"
      ]
    },
    {
      "page": "calc_ss_1cmt",
      "title": "Calculate C(t) for a 1-compartment linear model at steady-state",
      "topics": [
        "calc_ss_1cmt",
        "calc_ss_1cmt_linear_bolus",
        "calc_ss_1cmt_linear_infusion",
        "calc_ss_1cmt_linear_oral_0",
        "calc_ss_1cmt_linear_oral_0_lag",
        "calc_ss_1cmt_linear_oral_1",
        "calc_ss_1cmt_linear_oral_1_lag"
      ]
    },
    {
      "page": "calc_ss_2cmt",
      "title": "Calculate C(t) for a 2-compartment linear model at steady-state",
      "topics": [
        "calc_ss_2cmt",
        "calc_ss_2cmt_linear_bolus",
        "calc_ss_2cmt_linear_infusion",
        "calc_ss_2cmt_linear_oral_0",
        "calc_ss_2cmt_linear_oral_0_lag",
        "calc_ss_2cmt_linear_oral_1",
        "calc_ss_2cmt_linear_oral_1_lag"
      ]
    },
    {
      "page": "calc_ss_3cmt",
      "title": "Calculate C(t) for a 3-compartment linear model at steady-state",
      "topics": [
        "calc_ss_3cmt",
        "calc_ss_3cmt_linear_bolus",
        "calc_ss_3cmt_linear_infusion",
        "calc_ss_3cmt_linear_oral_0",
        "calc_ss_3cmt_linear_oral_0_lag",
        "calc_ss_3cmt_linear_oral_1",
        "calc_ss_3cmt_linear_oral_1_lag"
      ]
    },
    {
      "page": "compare_nhanes",
      "title": "Compare a simulated pediatric population with NHANES",
      "topics": [
        "compare_nhanes"
      ]
    },
    {
      "page": "count_na",
      "title": "Count the number of NA values in a vector.",
      "topics": [
        "count_na"
      ]
    },
    {
      "page": "cut_quantile",
      "title": "Create quantile-based bins for continuous variables",
      "topics": [
        "cut_quantile"
      ]
    },
    {
      "page": "datamap",
      "title": "Create a data map showing individual dosing and observation records over time",
      "topics": [
        "datamap"
      ]
    },
    {
      "page": "dgr_table",
      "title": "Generate a summary table of descriptive data for every individual in a dataset suitable for tabulation in a report.",
      "topics": [
        "dgr_table"
      ]
    },
    {
      "page": "estimate_lloq",
      "title": "Estimate the lower limit of quantification (LLOQ) from a vector",
      "concept": [
        "BLQ Transformation"
      ],
      "topics": [
        "estimate_lloq"
      ]
    },
    {
      "page": "fmt_signif",
      "title": "Format a number with the correct number of significant digits and trailing zeroes.",
      "topics": [
        "fmt_signif"
      ]
    },
    {
      "page": "ftrans_blq_linear",
      "title": "Forward transformation for linear BLQ data",
      "concept": [
        "BLQ Transformation"
      ],
      "topics": [
        "ftrans_blq_linear",
        "ftrans_blq_log"
      ]
    },
    {
      "page": "gcv",
      "title": "Calculate a geometric coefficient of variation.",
      "topics": [
        "gcv"
      ]
    },
    {
      "page": "gcv_convert",
      "title": "Convert geometric variance or standard deviation to a geometric coefficient of variation",
      "topics": [
        "gcv_convert"
      ]
    },
    {
      "page": "get_auc",
      "title": "Calculate the area under the curve (AUC) for each subject over the time interval for dependent variables ('dv') using the trapezoidal rule.",
      "topics": [
        "get_auc"
      ]
    },
    {
      "page": "get_est_table",
      "title": "Create a table of model parameter estimates from a NONMEM output object.",
      "topics": [
        "get_est_table"
      ]
    },
    {
      "page": "get_omega",
      "title": "Extract variability parameter estimates from a NONMEM output object.",
      "topics": [
        "get_omega"
      ]
    },
    {
      "page": "get_probinfo",
      "title": "Extract problem and estimation information from a NONMEM output object.",
      "topics": [
        "get_probinfo"
      ]
    },
    {
      "page": "get_shrinkage",
      "title": "Extract shrinkage estimates from a NONMEM output object.",
      "topics": [
        "get_shrinkage"
      ]
    },
    {
      "page": "get_sigma",
      "title": "Extract residual variability parameter estimates from a NONMEM output object.",
      "topics": [
        "get_sigma"
      ]
    },
    {
      "page": "get_theta",
      "title": "Extract structural model parameter estimates and associated information from a NONMEM output object.",
      "topics": [
        "get_theta"
      ]
    },
    {
      "page": "gm",
      "title": "Calculate geometric mean",
      "topics": [
        "gm"
      ]
    },
    {
      "page": "itrans_blq_linear",
      "title": "Inverse transformation for linear BLQ data",
      "concept": [
        "BLQ Transformation"
      ],
      "topics": [
        "itrans_blq_linear",
        "itrans_blq_log"
      ]
    },
    {
      "page": "label_blq",
      "title": "Label axes with censoring labels for BLQ",
      "concept": [
        "BLQ Transformation"
      ],
      "topics": [
        "label_blq"
      ]
    },
    {
      "page": "nhanes_peds",
      "title": "NHANES pediatric body weight and height reference data",
      "topics": [
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