diff options
Diffstat (limited to 'vignettes/mkin.Rmd')
| -rw-r--r-- | vignettes/mkin.Rmd | 167 |
1 files changed, 167 insertions, 0 deletions
diff --git a/vignettes/mkin.Rmd b/vignettes/mkin.Rmd new file mode 100644 index 00000000..63d97c6b --- /dev/null +++ b/vignettes/mkin.Rmd @@ -0,0 +1,167 @@ +--- +title: mkin - Kinetic evaluation of chemical degradation data +author: Johannes Ranke +date: "`r Sys.Date()`" +output: + html_document: + toc: true + toc_float: true +bibliography: references.bib +vignette: > + %\VignetteEngine{knitr::rmarkdown} + %\VignetteIndexEntry{mkin - Kinetic evaluation of chemical degradation data} + \usepackage[utf8]{inputenc} +--- + +[Wissenschaftlicher Berater, Kronacher Str. 8, 79639 Grenzach-Wyhlen, Germany](http://www.jrwb.de)<br /> +[Privatdozent at the University of Bremen](http://chem.uft.uni-bremen.de/ranke) + +```{r, include = FALSE} +require(knitr) +opts_chunk$set(engine='R', tidy=FALSE) +``` + +# 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 `R` add-on package `mkin` [@pkg: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. + +# Background + +Many approaches are possible regarding the evaluation of chemical degradation +data. + +The now deprecated `kinfit` package [@pkg:kinfit] in `R` [@rcore2016] +implements the approach recommended in the kinetics report provided by the +FOrum for Co-ordination of pesticide fate models and their USe [@FOCUS2006; +FOCUSkinetics2014] for simple data series for one parent compound in one +compartment. + +The `mkin` package [@pkg:mkin] extends this approach to data series with +transformation products, commonly termed metabolites, and to more than one +compartment. It is also possible to include back reactions, so equilibrium +reactions and equilibrium partitioning can be specified, although this +oftentimes leads to an overparameterisation of the model. + +When mkin was first published, the most commonly used tools for +fitting more complex kinetic degradation models to experimental data were +KinGUI [@schaefer2007], a MATLAB based tool with a graphical user +interface that was specifically tailored to the task and included some output +as proposed by the FOCUS Kinetics Workgroup, and ModelMaker, a general purpose +compartment based tool providing infrastructure for fitting dynamic simulation +models based on differential equations to data. + +The code was first uploaded to the BerliOS platform. When this was taken down, +the version control history was imported into the R-Forge site, where the code +is still mirrored today (see *e.g.* +[the initial commit on 11 May 2010](http://cgit.jrwb.de/mkin/commit/?id=30cbb4092f6d2d3beff5800603374a0d009ad770). + +At that time, the R package `FME` (Flexible Modelling Environment) +[@soetaert2010] was already available, and provided a good basis for +developing a package specifically tailored to the task. The remaining challenge +was to make it as easy as possible for the users (including the author of this +vignette) to specify the system of differential equations and to include the +output requested by the FOCUS guidance, such as the relative standard deviation +that has to be assumed for the residuals, such that the $\chi^2$ +goodness-of-fit test as defined by the FOCUS kinetics workgroup would pass +using an significance level $\alpha$ of 0.05. + +Also, mkin introduced using analytical solutions for parent only kinetics for +improved optimization speed. Later, Eigenvalue based solutions were +introduced to mkin for the case of linear differential equations (*i.e.* +where the FOMC or DFOP models were not used for the parent compound), greatly +improving the optimization speed for these cases. + +The possibility to specify back-reactions and a biphasic model (SFORB) for +metabolites were present in mkin from the very beginning. + +## Derived software tools + +Soon after the publication of mkin, two derived tools were published, namely +KinGUII (available from Bayer Crop Science) and CAKE (commissioned to Tessella +by Syngenta), which added a graphical user interface (GUI), and added fitting by +iteratively reweighted least squares (IRLS) and characterisation of likely +parameter distributions by Markov Chain Monte Carlo (MCMC) sampling. + +CAKE focuses on a smooth use experience, sacrificing some flexibility in the model +definition, originally allowing only two primary metabolites in parallel. +The current version 3.2 of CAKE release in March 2016 uses a basic scheme for +up to six metabolites in a flexible arrangement. + +KinGUI offers quite an even more flexible widget for specifying complex kinetic +models. Back-reactions (non-instanteneous equilibria) were not present in the +first version of KinGUII, and only simple first-order models could be specified +for transformation products. Later, starting from KinGUII version 2.1 published in ), +back-reactions and biphasic modelling of metabolites were also available in +KinGUII. + +A further graphical user interface (GUI) that has recently been brought to a decent +degree of maturity is the browser based GUI named `gmkin`. Please see its +[documentation page](http://kinfit.r-forge.r-project.org/gmkin_static) and +[manual](http://kinfit.r-forge.r-project.org/gmkin_static/vignettes/gmkin_manual.html) +for further information. + +## Recent developments + +Currently (June 2016), the main features available in `mkin` which are +not present in KinGUII or CAKE, are the speed increase by using compiled code when +a compiler is present, parallel model fitting on multicore machines using the +`mmkin` function, and the estimation of parameter confidence intervals based on +transformed parameters. These are explained in more detail below. + +# Internal parameter transformations + +For rate constants, the log +transformation is used, as proposed by Bates and Watts [-@bates1988, p. 77, +149]. Approximate intervals are constructed for the transformed rate +constants [compare @bates1988, p. 135], *i.e.* for their logarithms. +Confidence intervals for the rate constants are then obtained using the +appropriate backtransformation using the exponential function. + +In the first version of `mkin` allowing for specifying models using +formation fractions, a home-made reparameterisation was used in order to ensure +that the sum of formation fractions would not exceed unity. + +This method is still used in the current version of KinGUII (v2.1 from April +2014), with a modification that allows for fixing the pathway to sink to zero. +CAKE uses penalties in the objective function in order to enforce this +constraint. + +In 2012, an alternative reparameterisation of the formation fractions was +proposed together with René Lehmann \citep{ranke2012}, based on isometric +logratio transformation (ILR). The aim was to improve the validity of the +linear approximation of the objective function during the parameter +estimation procedure as well as in the subsequent calculation of parameter +confidence intervals. + +In the first attempt at providing improved parameter confidence intervals +introduced to \Rpackage{mkin} in 2013, confidence intervals obtained from +FME on the transformed parameters were simply all backtransformed one by one +to yield asymetric confidence intervals for the backtransformed parameters. + +However, while there is a 1:1 relation between the rate constants in the model +and the transformed parameters fitted in the model, the parameters obtained by the +isometric logratio transformation are calculated from the set of formation +fractions that quantify the paths to each of the compounds formed from a +specific parent compound, and no such 1:1 relation exists. + +Therefore, parameter confidence intervals for formation fractions obtained with +this method only appear valid for the case of a single transformation product, where +only one formation fraction is to be estimated, directly corresponding to one +component of the ilr transformed parameter. + +The confidence intervals obtained by backtransformation for the cases where a +1:1 relation between transformed and original parameter exist are considered by +the author of this vignette to be more accurate than those obtained using a +re-estimation of the Hessian matrix after backtransformation, as implemented +in the FME package. + + +# References + +<!-- vim: set foldmethod=syntax: --> |