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Indirect relationship between lipophilicity and maximum residue limit of drugs determined for fatty tissue Cover

Indirect relationship between lipophilicity and maximum residue limit of drugs determined for fatty tissue

Open Access
|Sep 2015

References

  1. 1. Balaz S., Lukacova V.: Subcellular pharmacokinetics and its potential for library focusing. J Mol Graph Model 2002, 20, 479–490.10.1016/S1093-3263(01)00149-8
  2. 2. Blackwell T.: Veterinary Medical Ethics: Ethical question of the month - July 2002. Can Vet J 2002, 43, 749–750.
  3. 3. Bolton S., Bon C.: Pharmaceutical Statistics: Practical and Clinical Applications, Fourth Edition, Revised and Expanded, Informa Health Care, New York, 2003.
  4. 4. Bonora E., Willeit J., Kiechl, S., Oberhollenzer F., Egger G., Bonadonna R., Muggeo M.: Relationship between insulin and carotid atherosclerosis in the general population. The Bruneck Study. Stroke 1997, 6, 1147–1152.10.1161/01.STR.28.6.1147
  5. 5. EC, Commission Regulation (EU) No 37/2010 of 22 December 2009 on pharmacologically active substances and their classification regarding maximum residue limits in foodstuffs of animal origin. 2010R0037 - EN - 12.12.2010 - 002.001 - 1 Amended by Commission regulations in 2010 European Commission. 2010; pp. 1–76.
  6. 6. EC, Technical Guidance Document in Support of Commission Directive 93/67/EEC on Risk Assessment for New Notified Substances and Commission Regulation (EC) No 1488/94 On Risk Assessment for Existing Substances. Part II. European Commission, 1996.
  7. 7. EMEA, Committee for Medicinal Products for Human Use (CHMP), Guideline on the Environmental Risk Assessment of Medicinal Products for Human Use. 2006c.
  8. 8. FAO, Joint FAO/WHO Technical Workshop on Residues of Veterinary Drugs without ADI/MRL. 2004.
  9. 9. FDA, Environmental Impact Assessments (EIA’s) For Veterinary Medicinal Products (VMP’s) - Phase II VICH Gl38 Final Guidance. 2006b, pp. 1–37.
  10. 10. FDA, Guidance for Industry Environmental Assessment of Human Drug and Biologics Applications. 1998, pp. 1–41.
  11. 11. Grabowski T., Jaroszewski J.J., Piotrowski W.: Correlations between no observed effect level and selected parameters of the chemical structure for veterinary drugs. Toxicol In Vitro 2010, 24, 953–959.10.1016/j.tiv.2010.01.003
  12. 12. Grabowski T., Jaroszewski J.J., Piotrowski W., Feder M.: Qualitative structure residue relationship analysis in the determination of the maximum residue limit of veterinary drugs. Chemosphere 2012, 87, 312–318.10.1016/j.chemosphere.2011.12.003
  13. 13. HC, Policy on Extra-Label Drug Use (ELDU) in food producing animals. http://www.hc-sc.gc.ca/dhp–mps/vet/label–etiquet/pol_eldu–umdde–eng.php (Accessed April 7, 2008).
  14. 14. Kubinyi H.: QSAR: Hansch analysis and related approaches. In: Methods and principles, published by Wiley–VCH. Weinheim, 1993, Vol. 1, pp. 20–190.
  15. 15. Leardi R. Nature-inspired methods in chemometrics: genetic algorithms and artificial neural networks. 1st ed., Elsevier, Amsterdam, 2003.
  16. 16. Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J.: Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 2001, 46, 3–26.
  17. 17. Machatha S.G., Yalkowsky S.H.: Comparison of the octanol/water partition coefficients calculated by ClogP, ACDlogP and KowWin to experimentally determined values. Int J Pharm 2005, 294, 185–192.10.1016/j.ijpharm.2005.01.023
  18. 18. Martinez M.N., Amidon G.L.: A mechanistic approach to understanding the factors affecting drug absorption: a review of fundamentals. J Clin Pharmacol 2002, 42, 620–643.10.1177/00970002042006005
  19. 19. Mattisson I., Wirfält E., Andrén C., Gullberg B., Berglund G.:. Dietary fat intake-food sources and dietary correlates in the Malmö Diet and Cancer cohort. Public Health Nutr 2003, 6, 559–569.10.1079/PHN2003474
  20. 20. OECD, 117 OECD Guideline for Testing of Chemicals. 1989, pp. 1–11.
  21. 21. OECD, OECD Environment Health and Safety Publications Series on Testing and Assessment No. 58, Report on the Regulatory Uses and Applications in OECD Member Countries of (Quantitative) Structure-Activity Relationship ((Q)SAR) Models in the Assessment of New and Existing Chemicals. 2006, pp. 1–79.10.1787/oecd_papers-v6-art37-en
  22. 22. OECD, OECD Environment Health and Safety Publications Series on Testing and Assessment No. 69, Guidance Document on the Validation of (Quantitative) Structure-Activity Relationships ((Q)SAR) MODELS. 2007, pp. 1–154.
  23. 23. OECD, The report from the expert group on (Quantitative) Structure–Activity Relationships ((Q)SARs) on the principles for the validation of (Q)SARs. 2004, pp. 11–198.
  24. 24. Palm K., Luthman K., Artursson P.: An alternative explanation for the low membrane permeability of highly lipophilic drugs. Eur J Pharm Sci 1996, 4, 195–195.10.1016/S0928-0987(97)86597-9
  25. 25. Peng Y.; Taylor J. M., Yu B. A marginal regression model for multivariate failure time data with a surviving fraction. Lifetime Data Anal 2007, 13, 351–369.
  26. 26. Piatkowska M., Jedziniak P., Zmudzki J.: Review: Residues of veterinary medicinal products and coccidiostats in eggs – causes, control and results of surveillance program in Poland. Pol J Vet Sci 2012, 15, 803–812.10.2478/v10181-012-0123-223390776
  27. 27. Pratim R.P., Paul S., Mitra I., Roy K.: On two novel parameters for validation of predictive QSAR models. Molecules 2009, 14, 1660–1701.10.3390/molecules14051660625429619471190
  28. 28. Tetko I.V., Gasteiger J., Todeschini R., Mauri A., Livingstone D., Ertl P., Palyulin V.A., Radchenko E.V., Zefirov N.S., Makarenko A.S., Tanchuk V.Y., Prokopenko V.V.: Virtual computational chemistry laboratory - design and description. J Comput Aided Mol Des 2005, 19, 453–463.10.1007/s10822-005-8694-y16231203
  29. 29. Williams S.G., Taylor J.M., Liu N., Tra Y., Duchesne G.M., Kestin L.L., Martinez A., Pratt G.R., Sandler H.: Use of individual fraction size data from 3756 patients to directly determine the alpha/beta ratio of prostate cancer. Int J Radiat Oncol Biol Phys 2007, 68, 24–33.10.1016/j.ijrobp.2006.12.03617448868
  30. 30. Wils P., Warnery A., Phung-Ba V. Legrain S., Scherman D.: High lipophilicity decreases drug transport across intestinal epithelial cells. J Pharmacol Exp Ther 1994, 269, 654–658.
  31. 31. Yu B., Tiwari R.C., Cronin K.A., Feuer E.J.: Cure fraction estimation from the mixture cure models for grouped survival data. Stat Med 2004, 15, 1713–1747.10.1002/sim.177415160405
Language: English
Page range: 383 - 391
Submitted on: Feb 22, 2015
Accepted on: Sep 4, 2015
Published on: Sep 30, 2015
Published by: National Veterinary Research Institute in Pulawy
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Monika Marczak, Krystyna Marta Okoniewska, Jakub Okoniewski, Tomasz Grabowski, Jerzy Jan Jaroszewski, published by National Veterinary Research Institute in Pulawy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.