Department of Biomedical Engineering, Oregon Health & Science University, 3303 SW Bond Avenue, Portland, OR 97239 USA ; In Silico Biosciences, Inc., 405 Waltham Street, Lexington, MA 02421 USA.
In Silico Biosciences, Inc., 405 Waltham Street, Lexington, MA 02421 USA.
Alzheimers Res Ther. 2012 Nov 26;4(6):50. doi: 10.1186/alzrt153. eCollection 2012.
A substantial number of therapeutic drugs for Alzheimer's disease (AD) have failed in late-stage trials, highlighting the translational disconnect with pathology-based animal models.
To bridge the gap between preclinical animal models and clinical outcomes, we implemented a conductance-based computational model of cortical circuitry to simulate working memory as a measure for cognitive function. The model was initially calibrated using preclinical data on receptor pharmacology of catecholamine and cholinergic neurotransmitters. The pathology of AD was subsequently implemented as synaptic and neuronal loss and a decrease in cholinergic tone. The model was further calibrated with clinical Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) results on acetylcholinesterase inhibitors and 5-HT6 antagonists to improve the model's prediction of clinical outcomes.
As an independent validation, we reproduced clinical data for apolipoprotein E (APOE) genotypes showing that the ApoE4 genotype reduces the network performance much more in mild cognitive impairment conditions than at later stages of AD pathology. We then demonstrated the differential effect of memantine, an N-Methyl-D-aspartic acid (NMDA) subunit selective weak inhibitor, in early and late AD pathology, and show that inhibition of the NMDA receptor NR2C/NR2D subunits located on inhibitory interneurons compensates for the greater excitatory decline observed with pathology.
This quantitative systems pharmacology approach is shown to be complementary to traditional animal models, with the potential to assess potential off-target effects, the consequences of pharmacologically active human metabolites, the effect of comedications, and the impact of a small number of well described genotypes.
大量治疗阿尔茨海默病（AD）的治疗药物在后期试验中失败，这突出了与基于病理学的动物模型之间的转化脱节。
为了弥合临床前动物模型和临床结果之间的差距，我们实施了皮质电路的基于电导率的计算模型，以模拟工作记忆作为认知功能的衡量标准。该模型最初使用儿茶酚胺和胆碱能神经递质的受体药理学的临床前数据进行校准。随后，AD 的病理学表现为突触和神经元丧失以及胆碱能张力下降。该模型进一步使用乙酰胆碱酯酶抑制剂和 5-HT6 拮抗剂的阿尔茨海默病临床评估量表认知子量表（ADAS-Cog）的临床结果进行校准，以提高模型对临床结果的预测能力。
作为独立验证，我们复制了载脂蛋白 E（APOE）基因型的临床数据，表明 ApoE4 基因型在轻度认知障碍情况下比在 AD 病理学的后期阶段更能降低网络性能。然后，我们展示了美金刚（一种 N-甲基-D-天冬氨酸（NMDA）亚单位选择性弱抑制剂）在早期和晚期 AD 病理学中的差异作用，并表明抑制位于抑制性中间神经元上的 NMDA 受体 NR2C/NR2D 亚基可补偿与病理学相关的更大的兴奋性下降。
这种定量系统药理学方法被证明是对传统动物模型的补充，具有评估潜在的脱靶效应、药理活性人代谢物的后果、共用药的影响以及少数描述良好的基因型的影响的潜力。
