{
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  "Package": "ncappc",
  "Title": "NCA Calculations and Population Model Diagnosis",
  "Version": "1.0.0.9000",
  "Authors@R": "c(\nperson(\"Chayan\", \"Acharya\", role = \"aut\"),\nperson(\"Gulbeyaz Y.\", \"Turkyilmaz\", role = \"aut\"),\nperson(\"Siv\", \"Jonsson\", role = \"aut\"),\nperson(\"Mats O.\", \"Karlsson\", role = \"aut\"),\nperson(\"Andrew C.\",\"Hooker\", email=\"andrew.hooker@uu.se\",\nrole=c(\"aut\",\"cre\"),\ncomment=c(ORCID = \"0000-0002-2676-5912\")\n))",
  "Description": "A flexible tool that can perform (i) traditional\nnon-compartmental analysis (NCA) and (ii) Simulation-based\nposterior predictive checks for population pharmacokinetic (PK)\nand/or pharmacodynamic (PKPD) models using NCA metrics. The\nmethods are described in Acharya et al. (2016)\n<doi:10.1016/j.cmpb.2016.01.013>.",
  "License": "GPL-3",
  "VignetteBuilder": "knitr",
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  "Encoding": "UTF-8",
  "URL": "https://github.com/UUPharmacometrics/ncappc,\nhttps://uupharmacometrics.github.io/ncappc/",
  "BugReports": "https://github.com/UUPharmacometrics/ncappc/issues",
  "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libx11-dev",
  "Repository": "https://uupharmacometrics.r-universe.dev",
  "Date/Publication": "2025-04-25 15:10:38 UTC",
  "RemoteUrl": "https://github.com/uupharmacometrics/ncappc",
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  "Packaged": {
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    "User": "root"
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  "Author": "Chayan Acharya [aut],\nGulbeyaz Y. Turkyilmaz [aut],\nSiv Jonsson [aut],\nMats O. Karlsson [aut],\nAndrew C. Hooker [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-2676-5912>)",
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  "_published": "2026-05-24T08:19:36.776Z",
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      "date": "2015-03-04"
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    },
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    "calc.stat",
    "dv.plot",
    "est.nca",
    "histobs.plot",
    "histpop.plot",
    "nca.check.obs",
    "nca.check.sim",
    "nca.deviation.plot",
    "nca.ind.data",
    "nca.npde",
    "nca.npde.plot",
    "nca.pde.deviation.outlier",
    "nca.read.sim",
    "ncappc",
    "out.digits",
    "read_nm_table"
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  "_help": [
    {
      "page": "calc.stat",
      "title": "Calculates a set of statistics for a given array of numbers.",
      "topics": [
        "calc.stat"
      ]
    },
    {
      "page": "dv.plot",
      "title": "Plots drug plasma concentration vs time data",
      "topics": [
        "dv.plot"
      ]
    },
    {
      "page": "est.nca",
      "title": "Estimate individual NCA metrics.",
      "topics": [
        "est.nca"
      ]
    },
    {
      "page": "histobs.plot",
      "title": "Plots histogram of selected set of NCA metrics.",
      "topics": [
        "histobs.plot"
      ]
    },
    {
      "page": "histpop.plot",
      "title": "Plots population histogram of the NCA metrics selected for model diagnosis.",
      "topics": [
        "histpop.plot"
      ]
    },
    {
      "page": "nca_ind_data",
      "title": "Prepare individual PK data",
      "topics": [
        "nca_ind_data"
      ]
    },
    {
      "page": "nca.check.obs",
      "title": "Check observed data",
      "topics": [
        "nca.check.obs"
      ]
    },
    {
      "page": "nca.check.sim",
      "title": "Check simulated data",
      "topics": [
        "nca.check.sim"
      ]
    },
    {
      "page": "nca.deviation.plot",
      "title": "Plot individual deviation of NCA metrics estimated from observed and simulated data",
      "topics": [
        "nca.deviation.plot"
      ]
    },
    {
      "page": "nca.ind.data",
      "title": "Prepare individual PK data",
      "topics": [
        "nca.ind.data"
      ]
    },
    {
      "page": "nca.npde",
      "title": "Calculates individual normalized prediction distribution errors (NPDE) from PDE data.",
      "topics": [
        "nca.npde"
      ]
    },
    {
      "page": "nca.npde.plot",
      "title": "Plots population histogram of the NCA metrics selected for model diagnosis.",
      "topics": [
        "nca.npde.plot"
      ]
    },
    {
      "page": "nca.pde.deviation.outlier",
      "title": "Calculates individual prediction distribution errors (PDE) and scaled deviation of NCA metrics estimated from observed and simulated data. Identifies outlier to population PK model.",
      "topics": [
        "nca.pde.deviation.outlier"
      ]
    },
    {
      "page": "nca.read.sim",
      "title": "Check observed data",
      "topics": [
        "nca.read.sim"
      ]
    },
    {
      "page": "ncappc",
      "title": "Performs NCA calculations and population PK model diagnosis.",
      "topics": [
        "ncappc"
      ]
    },
    {
      "page": "out.digits",
      "title": "output value with correct digits and trailing zero",
      "topics": [
        "out.digits"
      ]
    },
    {
      "page": "read_nm_table",
      "title": "Read NONMEM table files produced.",
      "topics": [
        "read_nm_table"
      ]
    }
  ],
  "_readme": "https://github.com/uupharmacometrics/ncappc/raw/HEAD/README.md",
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      "source": "ncappc-vignette.Rmd",
      "filename": "ncappc-vignette.html",
      "title": "Introduction to the ncappc package",
      "author": "Chayan Acharya, Andrew C. Hooker, Siv Jönsson, Mats O. Karlsson",
      "engine": "knitr::rmarkdown",
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        "Graphical output",
        "[Individual level] Concentration vs. time profile",
        "[Population level] Histogram of the selected NCA metrics estimated from the observed data",
        "[Population level] Histogram of the simulated population means of the NCA metrics",
        "[Individual level] Deviation of the simulated NCA metrics from the observed value",
        "[Individual level] Distribution of the simulated NCA metrics for the outliers}",
        "[Population level] Histogram of the NPDE values of the NCA metrics within a given population group",
        "[Population level] Forest plot for the NPDE type analysis",
        "[Individual level] NPDE values of the NCA metrics for each individual"
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