| 1. |
|
|
| 2. |
|
|
| 3. |
- Ekstrand, Carl, et al.
(författare)
-
A quantitative approach to analysing cortisol response in the horse
- 2016
-
Ingår i: Journal of Veterinary Pharmacology and Therapeutics. - : Wiley. - 0140-7783 .- 1365-2885. ; 39:3, s. 255-263
-
Tidskriftsartikel (refereegranskat)abstract
- The cortisol response to glucocorticoid intervention has, in spite of several studies in horses, not been fully characterized with regard to the determinants of onset, intensity and duration of response. Therefore, dexamethasone and cortisol response data were collected in a study applying a constant rate infusion regimen of dexamethasone (0.17, 1.7 and 17g/kg) to six Standardbreds. Plasma was analysed for dexamethasone and cortisol concentrations using UHPLC-MS/MS. Dexamethasone displayed linear kinetics within the concentration range studied. A turnover model of oscillatory behaviour accurately mimicked cortisol data. The mean baseline concentration range was 34-57g/L, the fractional turnover rate 0.47-1.5 1/h, the amplitude parameter 6.8-24g/L, the maximum inhibitory capacity 0.77-0.97, the drug potency 6-65ng/L and the sigmoidicity factor 0.7-30. This analysis provided a better understanding of the time course of the cortisol response in horses. This includes baseline variability within and between horses and determinants of the equilibrium concentration-response relationship. The analysis also challenged a protocol for a dexamethasone suppression test design and indicated future improvement to increase the predictability of the test.
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
- Ekstrand, Carl, et al.
(författare)
-
Plasma concentration-dependent suppression of endogenous hydrocortisone in the horse after intramuscular administration of dexamethasone-21-isonicotinate
- 2015
-
Ingår i: Journal of Veterinary Pharmacology and Therapeutics. - : Wiley. - 0140-7783 .- 1365-2885. ; 38:3, s. 235-242
-
Tidskriftsartikel (refereegranskat)abstract
- Detection times and screening limits (SL) are methods used to ensure that the performance of horses in equestrian sports is not altered by drugs. Drug concentration-response relationship and knowledge of concentration-time profiles in both plasma and urine are required. In this study, dexamethasone plasma and urine concentration-time profiles were investigated. Endogenous hydrocortisone plasma concentrations and their relationship to dexamethasone plasma concentrations were also explored. A single dose of dexamethasone-21-isonicotinate suspension (0.03mg/kg) was administered intramuscularly to six horses. Plasma was analysed for dexamethasone and hydrocortisone and urine for dexamethasone, using UPLC-MS/MS. Dexamethasone was quantifiable in plasma for 8.3 +/- 2.9days (LLOQ: 0.025g/L) and in urine for 9.8 +/- 3.1days (LLOQ: 0.15g/L). Maximum observed dexamethasone concentration in plasma was 0.61 +/- 0.12g/L and in urine 4.2 +/- 0.9g/L. Terminal plasma half-life was 38.7 +/- 19h. Hydrocortisone was significantly suppressed for 140h. The plasma half-life of hydrocortisone was 2.7 +/- 1.3h. Dexamethasone potency, efficacy and sigmoidicity factor for hydrocortisone suppression were 0.06 +/- 0.04g/L, 0.95 +/- 0.04 and 6.2 +/- 4.6, respectively. Hydrocortisone suppression relates to the plasma concentration of dexamethasone. Thus, determination of irrelevant plasma concentrations and SL is possible. Future research will determine whether hydrocortisone suppression can be used as a biomarker of the clinical effect of dexamethasone.
|
|
| 7. |
- Gabrielsson, Johan, et al.
(författare)
-
Animal Health Modeling & Simulation Society: a new society promoting model-based approaches in veterinary pharmacology
- 2013
-
Ingår i: Journal of Veterinary Pharmacology and Therapeutics. - : Wiley. - 0140-7783 .- 1365-2885. ; 36, s. 417-419
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The Animal Health Modeling & Simulation Society (AHM&S) is a newly founded association (2012) that aims to promote the development, application, and dissemination of modeling and simulation techniques in the field of Veterinary Pharmacology and Toxicology. The association is co-chaired by Pr. Johan Gabrielsson (Europe), Pr. Jim Riviere (USA), and secretary Dr. Jonathan Mochel (Switzerland). This short communication aims at presenting the membership, rationale and objectives of this group.
|
|
| 8. |
|
|
| 9. |
- Gabrielsson, Johan
(författare)
-
Mathematical modeling and simulation in animal Health. Part I: Moving beyond pharmacokinetics
- 2016
-
Ingår i: Journal of Veterinary Pharmacology and Therapeutics. - : Wiley. - 0140-7783 .- 1365-2885. ; 39, s. 213-223
-
Tidskriftsartikel (refereegranskat)abstract
- The application of mathematical modeling to problems in animal health has a rich history in the form of pharmacokinetic modeling applied to problems in veterinary medicine. Advances in modeling and simulation beyond pharmacokinetics have the potential to streamline and speed-up drug research and development programs. To foster these goals, a series of manuscripts will be published with the following goals: (i) expand the application of modeling and simulation to issues in veterinary pharmacology; (ii) bridge the gap between the level of modeling and simulation practiced in human and veterinary pharmacology; (iii) explore how modeling and simulation concepts can be used to improve our understanding of common issues not readily addressed in human pharmacology (e.g. breed differences, tissue residue depletion, vast weight ranges among adults within a single species, interspecies differences, small animal species research where data collection is limited to sparse sampling, availability of different sampling matrices); and (iv) describe how quantitative pharmacology approaches could help understanding key pharmacokinetic and pharmacodynamic characteristics of a drug candidate, with the goal of providing explicit, reproducible, and predictive evidence for optimizing drug development plans, enabling critical decision making, and eventually bringing safe and effective medicines to patients. This study introduces these concepts and introduces new approaches to modeling and simulation as well as clearly articulate basic assumptions and good practices. The driving force behind these activities is to create predictive models that are based on solid physiological and pharmacological principles as well as adhering to the limitations that are fundamental to applying mathematical and statistical models to biological systems.
|
|
| 10. |
|
|
