OHEJP-RaDAR-D-JRP3-2.1-Pharmacodynamics and transmission models

1. General introduction:
In the agricultural sector, antimicrobial drugs are widely used as curative or metaphylactic treatment in food producing animals. One side effect of these usages concerns the development of resistance among the commensal bacteria of animals, mainly within guts, and their potential spread between animals. Then, the resistant bacteria could spread in all the food chain, from the animal towards the food and finally towards the consumers intestines. The risk could be worrying when looking at the plasmid-mediated resistance, like Extended-spectrum β-lactamases (ESBL) for beta-lactamin/cephalosporin or mcr for colistin, due to the possibility that a resistant bacteria originating from animals could transmit its plasmid to human commensal bacteria or pathogen bacteria that are present within guts (Madec, et al., 2017; Nordmann, Poirel, 2016).
The link between antimicrobial drug (AMD) use and the development of antimicrobial resistance (AMR) in bacterial strains has been mainly studied in vitro experiments and sometimes modelled thanks to pharmacokinetics-pharmacodynamics (PKPD) approaches. Many within‐host models of antibiotic resistance are based on this pharmacokinetics/pharmacodynamics (PK/PD) approach as opposite to the between-host models, which are mainly epidemiological models. Within‐host models are useful for understanding bacteria dynamics and response to an AMD treatment, within a single individual (Tetteh, et al., 2020). PKPD models are a good basis to explore mechanistically the relationship between drug concentrations and the development/selection of resistant bacteria and may be extrapolated to in vivo situations (Nielsen, Friberg, 2013). However, there are only few PKPD models that describe the impact of AMD within the gut for several reasons: (i) these mechanisms occur in a complex environment (intestinal microbiota) with various interactions and external factors (ii) we face a lack of observed data to inform the PKPD model (need of longitudinal data); (iii) this could be time and computer-intensive.
Hence, the goal of this work was to refine and develop a “within-host PKPD model” (hereafter simplified as PKPD model) to assess and predict the impact of an AMD treatment (as an input of the model) on the emergence/selection of resistant bacteria within guts and excretion towards faeces (output of the model) for pig, at the individual level and population level (taking into account the inter-individual variability).