# Introduction

## Objectives

The purpose of this document is to introduce you how to use the MOSAICbioacc application. This application is based on the R software1 and especially the rjags library (version 4.10)2 andthe jagsUI library (version 1.5.1)3, to estimate parameters of Toxico-Kinetic (TK) models under a Bayesian framework. MOSAICbioacc is developed as an R-Shiny interface (version 1.6.0)4. If you want to be kept informed, please email us: sandrine.charles@univ-lyon1.fr.

## Context

The MOSAICbioacc application is a turn-key web tool providing bioaccumulation metrics (BCF/BMF/BSAF) from a TK model fitted to accumulation and depuration data. It is designed to fulfill the requirements of regulators when examining applications for market authorization of active substances.

Toxico-Kinetic/Toxico-Dynamic (TKTD) models are used to describe and predict the toxicity and the effects of chemical substances on individual traits based on experimental data. The TK part describes the relationship between the exposure medium and the organism, considering various processes such as ADME (accumulation, depuration, metabolization and excretion)5. Regulation No 283/2013 (EU)6 defines the data requirements for active substances of plant protection products in marketing authorization applications. In particular, a bioaccumulation study on fish is required following OECD guideline 3057. Achieved in agreement with EFSA’s scientific opinion on good modeling practices8,9, this ready-to-use on-line service allows to easily estimate BCF/BMF/BSAF as required in a regulatory framework, accounting for bioaccumulation of parent compounds and their metabolites through biotransformation. MOSAICbioacc does not expect any input besides the accumulation-depuration data sets according to exposure concentrations. The service automatically fits the TK model, initially defined from the appropriately user data and optimizes the estimation of its parameters. Then, the service provides the corresponding bioaccumulation metrics, as well as all goodness-of-fit criteria required to carefully check the reliability of the results10. All calculations are based on the JAGS software and its companion R packages rjags2,11 and jagsUI3.

## Installation

If you use the web interface (https://mosaic.univ-lyon1.fr/bioacc), you don’t need to install anything.

However, if you want to run the R script (downloadable from the application) by yourself, you need to install:

Here is an example of the R code to install the required packages:

if(is.element('rjags', installed.packages()[,1]) == FALSE)
{install.packages('rjags')}

if(is.element('jagsUI', installed.packages()[,1]) == FALSE)
{install.packages('jagsUI')}

if(is.element('tidyverse', installed.packages()[,1]) == FALSE)
{install.packages('tidyverse')}

if(is.element('gridExtra', installed.packages()[,1]) == FALSE)
{install.packages('gridExtra')}

if(is.element('ggmcmc', installed.packages()[,1]) == FALSE)
{install.packages('ggmcmc')}

if(is.element('GGally', installed.packages()[,1]) == FALSE)
{install.packages('GGally')}

if(is.element('stringr', installed.packages()[,1]) == FALSE)
{install.packages('stringr')}

if(is.element('DT', installed.packages()[,1]) == FALSE)
{install.packages('DT')}

When using MOSAICbioacc, the first step is to upload input data (Fig. 1.1):

## 1.1 Format

You can upload your own data (click on “Browse”) by taking care about the format specification of your file. MOSAICbioacc expects to receive data as a .txt file or a .csv file (comma, semicolon or tabular separator). Each line of the table corresponds to a time point for a given replicate and a given exposure concentration of the contaminant. The table must contain the four following columns, with exact header names (Table 1.1):

• “time”: the time point of the measurement at the exposure concentration;
• “expw,” “exps,” “expf,” “exppw”: the concentration of the contaminant in the exposure medium (expw: water, exps: sediment, expf: food, exppw: pore water);
• “replicate”: a number or a string that is unique for each replicate;
• “conc”: the concentration measurements of the contaminant within the organism.

According to your data, further columns can be added in the file:

• “concm$$\ell$$”: the concentration measurements of metabolite $$\ell$$ from the parent compound within the organism (e.g. concm1, concm2, …). Please note that only metabolites of phase I (deriving directly from the parent compound) in the metabolization process are considered;
• “growth”: the growth measurements (e.g. weight, size) of the organisms.

Then be careful to the units:

• The time points must be in hours, minutes, days or weeks;
• The exposure concentration in the medium must be in $$\mu$$$$g.mL^{-1}$$ or in $$\mu g.g^{-1}$$;
• The numbering of replicates is dimensionless;
• The concentration measurements (parent compound and metabolite(s)) within the organisms must be in $$\mu$$$$g.g^{-1}$$;
• The growth measurements must be in g, mg, cm, mm or other.
time conc expw replicate
0 0.000 0.0044 2
3 0.225 0.0044 2
7 0.355 0.0044 2
14 0.553 0.0044 2
21 0.658 0.0044 2
28 0.785 0.0044 2

Once the upload is complete, you have to manually select the corresponding separator, the appropriate time unit and the duration of the accumulation phase.

## 1.2 Example data

Instead of using your own data, you can try MOSAICbioacc from several example files that are provided. Three data sets use a simple TK model (one exposure route and one elimination process), whereas two data sets consider a more complex TK model, accounting for metabolization and growth (Fig. 1.2).

Please note that more data are, the more the TK model is complex, and the more the calculations take time. Thus, we indicated the approximative mean time calculation for each example data sets (Fig.1.2).

## 1.3 Visualization of the data

In case you upload a data set with several exposure concentrations, select the one for which you want to see the results. We propose two types of visualization to check if the file has correctly been uploaded: as a table or a plot (Fig. 1.3 and 1.4).