Poirier Agnès, Cascais Anne-Christine, Bader Urs, Portmann Renée, Brun Marie-Elise, Walter Isabelle, Hillebrecht Alexander, Ullah Mohammed, Funk Christoph
Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland.
Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
Drug Metab Dispos. 2014 Sep;42(9):1411-22. doi: 10.1124/dmd.114.057943. Epub 2014 Jun 17.
The multidrug resistance protein 1 (MDR1) is known to limit brain penetration of drugs and play a key role in drug-drug interactions (DDIs). Theoretical cut-offs from regulatory guidelines are used to extrapolate MDR1 interactions from in vitro to in vivo. However, these cut-offs do not account for interlaboratory variability. Our aim was to calibrate our experimental system to allow better in vivo predictions. We selected 166 central nervous system (CNS) and non-CNS drugs to calibrate the MDR1 transport screening assay using Lewis lung cancer porcine kidney 1 epithelial cells overexpressing MDR1 (L-MDR1). A threshold efflux ratio (ER) of 2 was established as one parameter to assess brain penetration in lead optimization. The inhibitory potential of 57 molecules was evaluated using IC50 values based on the digoxin ER-IC50(ER)-or apparent permeability-IC50(Papp)-in L-MDR1 cells. Published clinical data for 68 DDIs involving digoxin as the victim drug were collected. DDI risk assessments were based on intestinal concentrations ([I2]) as well as unbound [I1u] and total plasma [I1T] concentrations. A receiver operating characteristic analysis identified an [I2]/IC50(ER) of 6.5 as the best predictor of a potential interaction with digoxin in patients. The model was further evaluated with a test set of 11 digoxin DDIs and 16 nondigoxin DDIs, resulting in only one false negative for each test set, no false positives among the digoxin DDIs, and two among the nondigoxin DDIs. Future refinements might include using cerebrospinal fluid to unbound plasma concentration ratios rather than therapeutic class, better estimation of [I2], and dynamic modeling of MDR1-mediated DDIs.
已知多药耐药蛋白1(MDR1)会限制药物进入大脑,并在药物相互作用(DDIs)中起关键作用。监管指南中的理论临界值用于从体外推断MDR1相互作用到体内情况。然而,这些临界值未考虑实验室间的变异性。我们的目标是校准我们的实验系统,以实现更好的体内预测。我们选择了166种中枢神经系统(CNS)和非CNS药物,使用过表达MDR1的Lewis肺癌猪肾1上皮细胞(L-MDR1)来校准MDR1转运筛选试验。确定流出比率(ER)阈值为2作为先导优化中评估脑渗透性的一个参数。基于地高辛ER-IC50(ER)或表观渗透率-IC50(Papp),在L-MDR1细胞中使用IC50值评估了57种分子的抑制潜力。收集了68例以地高辛为受影响药物的DDIs的已发表临床数据。DDI风险评估基于肠道浓度([I2])以及未结合的[I1u]和总血浆[I1T]浓度。受试者工作特征分析确定[I2]/IC50(ER)为6.5是患者与地高辛潜在相互作用的最佳预测指标。该模型用一组11例地高辛DDIs和16例非地高辛DDIs进行了进一步评估,每个测试组仅产生一个假阴性结果,地高辛DDIs中无假阳性结果,非地高辛DDIs中有两个假阳性结果。未来的改进可能包括使用脑脊液与未结合血浆浓度的比率而非治疗类别、更好地估计[I2]以及对MDR1介导的DDIs进行动态建模。