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Distribution, lipophilicity and tissue half-life as key factors in sulphonamide clearance from porcine tissues

Artur Burmańczuk

Artur Burmańczuk

Department of Pharmacology, Toxicology and Environmental Protection, University of Life Sciences in LublinLublin, Poland
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Burmańczuk, Artur
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Monika Osypiuk

Monika Osypiuk

Department of Pharmacology, Toxicology and Environmental Protection, University of Life Sciences in LublinLublin, Poland
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Osypiuk, Monika
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Bożena Polska

Bożena Polska

Department of Pharmacology, Toxicology and Environmental Protection, University of Life Sciences in LublinLublin, Poland
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Polska, Bożena
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Dominik Kunicki

Dominik Kunicki

Department of Pharmacology, Toxicology and Environmental Protection, University of Life Sciences in LublinLublin, Poland
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Kunicki, Dominik
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Marcin Kocik

Marcin Kocik

Private veterinary practiceTarnów, Poland
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Kocik, Marcin
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Karol Grzęda

Karol Grzęda

Private veterinary practicePuławy, Poland
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Grzęda, Karol
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Włodzimierz Markiewicz

Włodzimierz Markiewicz

Department of Pharmacology and Toxicology, Faculty of Veterinary Medicine, University of Warmia and MazuryOlsztyn, Poland
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Markiewicz, Włodzimierz
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Oktay Yilmaz

Oktay Yilmaz

Department of Obstetrics and Gynaecology, Faculty of Veterinary Medicine, Afyon Kocatepe University, ANS CampusAfyonkarahisar, Türkiye
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Yilmaz, Oktay
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Tomasz Grabowski

Tomasz Grabowski

Department of Inorganic Chemistry, Medical University of GdańskGdańsk, Poland
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Grabowski, Tomasz
  
Jan 30, 2025
Distribution, lipophilicity and tissue half-life as key factors in sulphonamide clearance from porcine tissues's Cover Image
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Published Online: Jan 30, 2025
Page range: 101 - 109
Received: Apr 25, 2024
Accepted: Jan 21, 2025
DOI: https://doi.org/10.2478/jvetres-2025-0002
Keywords
© 2025 Artur Burmańczuk et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1.

Total exposure to formulation A active substances (sulphathiazole, sulphamethazine and sulphadimethoxine). A – nonlinear semi-log fit of all observed concentrations (black line) with 99% confidence intervals (dashed lines). Circles represent arithmetic means in one tissue type based on observed concentrations of all active substances. B – variability of sulphathiazole, sulphamethazine and sulphadimethoxine observed concentrations per tissue. MRL – maximum residue limit; I – injection site; K – kidneys; L – liver; M – muscle; F – fat and skin. Bold ticks on the time axis represent the in B represent the start and finish of the designed 10-day withdrawal period
Total exposure to formulation A active substances (sulphathiazole, sulphamethazine and sulphadimethoxine). A – nonlinear semi-log fit of all observed concentrations (black line) with 99% confidence intervals (dashed lines). Circles represent arithmetic means in one tissue type based on observed concentrations of all active substances. B – variability of sulphathiazole, sulphamethazine and sulphadimethoxine observed concentrations per tissue. MRL – maximum residue limit; I – injection site; K – kidneys; L – liver; M – muscle; F – fat and skin. Bold ticks on the time axis represent the in B represent the start and finish of the designed 10-day withdrawal period

Fig. 2.

Total exposure to formulation B active substances (sulphathiazole, sulphamethazine and sulphacetamide). A – nonlinear semi-log fit of all observed concentrations (black line) with 99% confidence intervals (dashed lines). Circles represent arithmetic means in one tissue type based on observed concentrations of all active substances. B – variability of sulphathiazole, sulphamethazine, and sulphacetamide concentrations observed in different tissues. MRL – maximum residue limit; I – injection site; K – kidneys; L – liver; M – muscle; F – fat and skin. Bold ticks on the time axis in B represent the start and finish of the 10-day withdrawal period
Total exposure to formulation B active substances (sulphathiazole, sulphamethazine and sulphacetamide). A – nonlinear semi-log fit of all observed concentrations (black line) with 99% confidence intervals (dashed lines). Circles represent arithmetic means in one tissue type based on observed concentrations of all active substances. B – variability of sulphathiazole, sulphamethazine, and sulphacetamide concentrations observed in different tissues. MRL – maximum residue limit; I – injection site; K – kidneys; L – liver; M – muscle; F – fat and skin. Bold ticks on the time axis in B represent the start and finish of the 10-day withdrawal period

Performance data for the method detecting antibiotic residues in porcine tissues

Analyte Tissue LOD ng/g LOQ ng/g CCα ng/g CCβ ng/g Recovery % Intra-day precision % Inter-day precision %
Sulphadimethoxine Muscle 1.02 3.08 124.57 125.70 74.56 3.49 4.12
Liver 1.17 3.54 128.60 129.50 96.23 3.21 4.56
Kidney 1.25 3.78 103.78 105.70 74.78 3.52 5.18
Fat and skin 0.90 2.73 119.96 120.44 77.34 3.02 5.96
Sulphathiazole Muscle 1.17 3.55 101.01 106.27 84.41 4.38 3.85
Liver 1.20 3.65 107.84 109.60 81.49 1.58 4.55
Kidney 1.28 3.90 110.03 113.72 86.67 9.57 7.12
Fat and skin 1.06 3.20 100.28 102.82 64.76 4.36 5.47
Sulphamethazine Muscle 1.34 4.06 101.00 103.00 90.69 5.23 6.11
Liver 2.72 8.25 85.45 87.91 95.75 2.06 4.23
Kidney 1.47 4.47 87.53 89,17 90.13 2.61 3.88
Fat and skin 1.08 3.28 88.52 100.45 92.68 0.95 2.45
Sulphacetamide Muscle 1.54 4.67 65.23 68.11 48.02 4.05 4.41
Liver 0.98 2.98 54.89 55.31 45.48 4.18 4.12
Kidney 1.31 3.97 79.96 82.12 59.99 3.88 4.88
Fat and skin 2.89 8.76 50.87 52.22 44.96 1.49 3.33

Linear regression fit parameters of all observed concentrations per active substance and tissue

Tissue Y-Intercept (CI) Slope (CI) R2 RMSE W P-value Nt
Formulation A
M1 na na na na na na na
M2 na 5.461 (−4.075e+017– 4.075e+017) 0 114.6 0.79 0.0912 No
M3 534.4 (−268.5–1337) −41.42 (−114.1–31.26) 0.2695 74.7 0.897 0.3561 Yes
K1 396.7 (−105.7–899.2) −26.01 (−65.86–13.83) 0.6451 36.95 0.952 0.7292 Yes
K2 923.3 (511.3–1,335) −66.94 (−101.7–−32.18) 0.7001 73.13 0.964 0.8453 Yes
K3 2,195 (1,351–3,039) −150.9 (−218.2–−83.71) 0.6854 211.2 0.872 0.1067 Yes
L1 na na na na na na na
L2 409.1 (249.9–568.3) −25.05 (−37.25–−12.86) 0.646 50.07 0.891 0.1755 Yes
L3 394.1 (276.8–511.3) −23.76 (−32.51–−15.02) 0.708 40.02 0.965 0.854 Yes
F1 na na na na na na na
F2 659.5 (445.4–873.6) −43.75 (−60.80–−26.69) 0.7399 53.58 0.976 0.9425 Yes
F3 1,442 (987.5–1897) −97.05 (−133.3–−60.83) 0.7563 113.8 0.898 0.2076 Yes
I1 na na na na na na na
I2 138.6 (−572.5–849.6) −4.772 (−65.97–56.42) 0.02527 56.75 0.95 0.7127 Yes
I3 468.9 (−429.0–1,367) −27.92 (−105.2–49.35) 0.3576 71.67 0.95 0.7139 Yes
Formulation B
M1 1,320 (899.8–1,740) −92.89 (−127.5–−58.30) na na na na na
M2 417.8 (299.6–535.9) −26.03 (−35.45–−16.62) 0.8541 76.77 0.929 0.5405 Yes
M4 na na 0.2053 52.74 0.879 0.336 Yes
K1 1,676 (1,316–2,037) −109.8 (−137.7–−81.91) na na na na na
K2 421 (353.5–488.5) −31.26 (−37.48–−25.03) 0.8525 102.3 0.902 0.1961 Yes
K4 na na 0.7678 29.57 0.837 0.0411 No
L1 2,374 (1,718–3,031) −154.6 (−204.4–−104.8) na na na na na
L2 na 4.859 (−9.685e+016– 9.685e+016) 0.7603 202.8 0.937 0.4546 Yes
L4 na na 0.979 5.018 0.829 0.1371 Yes
F1 544.1 (220.6–867.6) −37.01 (−63.72–−10.30) na na na na na
F2 157 (−15.13–329.1) −7.13 (−22.11–7.852) 0.4961 64.61 0.967 0.8657 Yes
F4 na na na 27.25 0.999 0.9427 Yes
I1 1,037 (401.6–1673) −67.52 (−118.1–−16.89) na na na na na
I2 1,037 −67.52 0.4346 159.1 0.929 0.4364 Yes
I4 na na 0.9003 5.48 1 >0.9999 Yes
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Life Sciences, Molecular Biology, Microbiology and Virology, Life Sciences, other, Medicine, Veterinary Medicine
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