% $Id: mkin.Rnw 66 2010-09-03 08:50:26Z jranke $ %%\VignetteIndexEntry{Routines for fitting kinetic models with one or more state variables to chemical degradation data} %%VignetteDepends{FME} %%\usepackage{Sweave} \documentclass[12pt,a4paper]{article} \usepackage{a4wide} %%\usepackage[lists,heads]{endfloat} \input{header} \hypersetup{ pdftitle = {mkin - Routines for fitting kinetic models with one or more state variables to chemical degradation data}, pdfsubject = {Manuscript}, pdfauthor = {Johannes Ranke}, colorlinks = {true}, linkcolor = {blue}, citecolor = {blue}, urlcolor = {red}, hyperindex = {true}, linktocpage = {true}, } \SweaveOpts{engine=R, eps=FALSE, keep.source = TRUE} <>= options(prompt = "R> ") options(SweaveHooks = list( cex = function() par(cex.lab = 1.3, cex.axis = 1.3))) @ \begin{document} \title{mkin -\\ Routines for fitting kinetic models with one or more state variables to chemical degradation data} \author{\textbf{Johannes Ranke} \\[0.5cm] %EndAName Eurofins Regulatory AG\\ Weidenweg 15, CH--4310 Rheinfelden, Switzerland\\[0.5cm] and\\[0.5cm] University of Bremen\\ } \maketitle \begin{abstract} In the regulatory evaluation of chemical substances like plant protection products (pesticides), biocides and other chemicals, degradation data play an important role. For the evaluation of pesticide degradation experiments, detailed guidance has been developed, based on nonlinear optimisation. The \RR{} add-on package \Rpackage{mkin} implements fitting some of the models recommended in this guidance from within R and calculates some statistical measures for data series within one or more compartments, for parent and metabolites. \end{abstract} \thispagestyle{empty} \setcounter{page}{0} \clearpage \tableofcontents \textbf{Key words}: Kinetics, FOCUS, nonlinear optimisation \section{Introduction} \label{intro} Many approaches are possible regarding the evaluation of chemical degradation data. The \Rpackage{kinfit} package \citep{pkg:kinfit} in \RR{} \citep{rcore2012} implements the approach recommended in the kinetics report provided by the FOrum for Co-ordination of pesticide fate models and their USe \citep{FOCUS2006, FOCUSkinetics2011} for simple data series for one parent compound in one compartment. The \Rpackage{mkin} package \citep{pkg:mkin} extends this approach to data series with metabolites and more than one compartment and includes the possibility for back reactions. \section{Example} \label{exam} In the following, requirements for data formatting are explained. Then the procedure for fitting the four kinetic models recommended by the FOCUS group to an example dataset for parent only given in the FOCUS kinetics report is illustrated. The explanations are kept rather verbose in order to lower the barrier for \RR{} newcomers. \subsection{Data format} The following listing shows example dataset C from the FOCUS kinetics report as distributed with the \Rpackage{mkin} package <>= library("mkin") FOCUS_2006_C @ Note that the data needs to be in the format of a data frame containing a variable \Robject{name} specifying the observed variable, indicating the compound name and, if applicable, the compartment, a variable \Robject{time} containing sampling times, and a numeric variable \Robject{value} specifying the observed value of the variable. If a further variable \Robject{error} is present, this will be used to give different weights to the data points (the higher the error, the lower the weight, see the help page of the \Robject{modCost} function of the \Rpackage{FME} package \citep{soetaert10}). Replicate measurements are not recorded in extra columns but simply appended, leading to multiple occurrences of the sampling times \Robject{time}. Small to medium size dataset can be conveniently entered directly as \RR{} code as shown in the following listing <>= example_data <- data.frame( name = rep("parent", 9), time = c(0, 1, 3, 7, 14, 28, 63, 91, 119), value = c(85.1, 57.9, 29.9, 14.6, 9.7, 6.6, 4, 3.9, 0.6) ) @ \subsection{Model definition} The next task is to define the model to be fitted to the data. In order to facilitate this task, a convenience function \Robject{mkinmod} is available. <>= SFO <- mkinmod(parent = list(type = "SFO")) SFORB <- mkinmod(parent = list(type = "SFORB")) SFO_SFO <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO")) SFORB_SFO <- mkinmod( parent = list(type = "SFORB", to = "m1", sink = TRUE), m1 = list(type = "SFO")) @ The model definitions given above define sets of linear first-order ordinary differential equations. In these cases, a coefficient matrix is also returned. Other models that include time on the right-hand side of the differential equation are the first-order multi-compartment (FOMC) model and the Hockey-Stick (HS) model. At present, these models can only be used only for the parent compound. \subsection{Fitting the model} Then the model parameters should be fitted to the data. The function \Robject{mkinfit} internally creates a cost function using \Robject{modCost} from the \Rpackage{FME} package and then produces a fit using \Robject{modFit} from the same package. In cases of linear first-order differential equations, the solution used for calculating the cost function is based on the fundamental system of the coefficient matrix, as proposed by \citet{bates88}. <>= SFO.fit <- mkinfit(SFO, FOCUS_2006_C) summary(SFO.fit) SFORB.fit <- mkinfit(SFORB, FOCUS_2006_C) summary(SFORB.fit) SFO_SFO.fit <- mkinfit(SFO_SFO, FOCUS_2006_D, plot=TRUE) summary(SFO_SFO.fit, data=FALSE) SFORB_SFO.fit <- mkinfit(SFORB_SFO, FOCUS_2006_D, plot=TRUE) summary(SFORB_SFO.fit, data=FALSE) @ \section{Acknowledgements} This package would not have been written without me being introduced to regulatory fate modelling of pesticides by Adrian Gurney during my time at Harlan Laboratories Ltd (formerly RCC Ltd). Parts of the package were written during my employment at Harlan. \bibliographystyle{plainnat} \bibliography{references} \end{document} % vim: set foldmethod=syntax: