BIIE 0246 synthesis Dose response analysis Fig can be perfor
Dose response analysis (Fig. 2) can be performed on BIIE 0246 synthesis in culture, in tissue, in animals or even in patients. Many different responses can be measured, including mRNA levels, reporter gene activity, gene product (e.g. enzyme) activity or even physiological functions such as inhibition of ovulation. As in the case of steroid ligand binding curves, dose response curves ex vivo generally follow a sigmoidal shape with a Hill slope value of 1 (Fig. 2). Dose response curves with the same Hill slope are considered to be parallel, while those that differ are non-parallel. In the absence of dose response analysis, relative responses obtained by single doses of progestogens will vary depending on which part of the dose response curve is represented for each progestogen. For example, if the dose for all progestogens is already at the maximal response, then the progestogens could be incorrectly reported to have the same ‘potency’. Furthermore, if the data from incomplete curves represents different parts of the curve, or off-target competing receptors are present, plots will be non-parallel. Taken together, this will result in misleading estimates of relative potency, efficacy and biocharacter. In clinical and animal studies, the term ‘potency’ has been widely used to describe many different progestogen actions, including RBAs, relative responses to fixed constant doses in animal or clinical assays, or a dose required to obtain a particular defined response, which may not be maximal , . Some studies have included dose response analysis , but often only three doses are arbitrarily chosen and full curves are not generated , . Most assays describing the ‘potency’ of progestogens are based on the progestational effects of these ligands on uterine glandular proliferation, pregnancy maintenance, glycogen deposition in endometrial glands, delay-of menses, or inhibition of ovulation ,  using animal models , ,  or healthy female volunteers , , . An early study involving administration of three different doses of progestogens to women reported that the ‘potency’ of norgestrel was lower in a glycogen deposition assay than in the delay of menses test . When assessing the significance of this result, it should be noted that the “potencies” determined were not obtained from full dose response curves and the plots were non-parallel. Another possible reason for differences in relative ‘potencies’ between different assays is the inclusion of estrogen together with the progestogen in some assays, such as in the delay of menses assay , but not others, since estrogen could affect the response by, for example, changing receptor levels. A rat study by Lundeen and co-workers showed that TMG was more ‘potent’ than MPA when assessing complement component C3 expression in epithelial cells of the uterus, less ‘potent’ than MPA in the proliferation of endometrial stromal cells, and ‘equipotent’ in inhibiting ovulation . In these assays, once again the plots generated did not reach a maximal level and were not parallel. Differences were also observed when comparing the ‘potencies’ of progestogens in a bioassay measuring endometrial transformation in rabbits (‘potency’ rank order MPA≥dydrogesterone>NET) to that of an ex vivo assay measuring their transactivation potential via the human PR (‘potency’ rank order MPA≥NET>dydrogesterone) . Although the bioassay dose response curves did not reach a maximal level, indicating that the ED50 values obtained by this assay may be inaccurate, the change in rank order may also be due to difference in metabolism between the animal study compared to the in vitro cell line study. Interestingly, the rank order for ‘potency’ of the same progestogens in a clinical assay measuring endometrial protection, by dose response analysis, indicated that NET>MPA>dydrogesterone , possibly reflecting species-specific intracellular responses. A comparison between the rank order for potencies of progestogens in the above bioassays with their RBAs for the PR (Table 1), illustrates that generally the two do not correlate. There could be many reasons for this, including differences in the levels of competing SRs in the different target tissues/cells.