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Pig Journal Volume: 56
Publication date: November 2005

Refereed Section

PHARMACOKINETIC, PHARMACODYNAMIC AND CLINICAL CORRELATIONS RELATING TO THE THERAPY OF LAWSONIA INTRACELLULARIS INFECTIONS, THE CAUSE OF PORCINE PROLIFERATIVE ENTEROPATHY ('ILEITIS') IN THE PIG
D.G.S. Burch

Abstract
Porcine proliferative enteropathy, commonly referred to as 'ileitis,' caused by Lawsonia intracellularis, is a common and widespread intestinal infection of pigs. In its acute form, it can cause mortality in finishing pigs and young breeding stock and in its chronic form, depression and unevenness of growth in growers and finishers.
In the United Kingdom, 67% of antimicrobials are delivered via the feed and at least a similar proportion is administered to pigs. Several important families of antibiotics are used to treat and prevent ileitis, including the tetracyclines, macrolides, lincosamides and pleuromutilins. Surprisingly, there is little published information on the pharmacokinetics of these products in the intestines of pigs and especially in the ileum.
The purpose of this paper was to establish a baseline model for antibiotic concentrations that are likely to be achieved in the ileal contents. These could then be related to the pharmacodynamic activity of the antibiotics, in particular to the intracellular minimum inhibitory concentrations (MICs) against L. intracellularis, which were established in the 1990s and correlate these with clinical studies. Pharmacokinetic/pharmacodynamic relationship analysis is a powerful tool, not only to predict dose rates and intervals, but also, as in this case, how antimicrobials are likely to work against target pathogenic bacteria and treat infectious disease.
In the paper, the ileal contents concentration (ICCs) for a number of antibiotics are estimated, but deficiencies in the determination of the intracellular MICs are highlighted. The ICCs do appear to correlate with the inhibitory activity of the antibiotics against L. intracellularis in the intracellular cell culture system, but due to the deficiencies in the data, more precise correlations cannot be mad

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