Mandema Jaap W, Hermann David, Wang Wenping, Sheiner Tim, Milad Mark, Bakker-Arkema Rebecca, Hartman Daniel
Pharsight Corporation, Mountain View, CA 94040, USA.
AAPS J. 2005 Oct 7;7(3):E513-22. doi: 10.1208/aapsj070352.
The purpose of this study was to evaluate the value of model-based, quantitative decision making during the development of gemcabene, a novel lipid-altering agent. The decisions were driven by a model of the likely clinical profile of gemcabene in comparison with its competitors, such as 3-hydroxymethylglutaryl coenzyme A reductase inhibitors (statins), the cholesterol absorption inhibitor ezetimibe, and their combination. Dose-response models were developed for the lipid effects (low-density lipoprotein cholesterol [LDL-C] and high-density lipoprotein cholesterol); adverse effects, such as persistent alanine aminotransferase elevation and myalgia; tolerability issues, such as headache; and risk reduction for coronary artery disease-related events for 5 statins, ezetimibe, gemcabene, and their combinations. The integrated model was based on the joint analysis of publicly available summary-level data and proprietary patient-level data and included information from almost 10,000 patients. The model was made available and accessible to the development team by using the Pharsight Drug Model Explorer model visualization technology. The modeling greatly enhanced the understanding of the clinical profile of gemcabene when given alone or in combination with a statin. The interaction between statins and gemcabene for the LDL-C lowering effect was found to be significantly different from the interaction between statins and ezetimibe. Ezetimibe was found to have a pharmacological-independent interaction resulting in additional LDL-C lowering over the entire statin dose range. The gemcabene interaction was found to be less than independent, resulting in almost no additional LDL-C lowering at high-statin doses, although the drug has a significant LDL-C effect when administered alone or in combination with a low dose of a statin. The quick availability of the model after completion of the first phase II trial in the target patient population and the ability of the team to explore the potential clinical efficacy and safety of gemcabene in comparison with alternative treatment options facilitated a quick decision to stop development.
本研究的目的是评估在新型降脂药物吉卡宾(gemcabene)研发过程中基于模型的定量决策的价值。这些决策是由一个模型驱动的,该模型比较了吉卡宾与其竞争对手(如3-羟基-3-甲基戊二酰辅酶A还原酶抑制剂(他汀类药物)、胆固醇吸收抑制剂依泽替米贝及其组合)可能的临床特征。针对脂质效应(低密度脂蛋白胆固醇[LDL-C]和高密度脂蛋白胆固醇)、不良反应(如持续性丙氨酸氨基转移酶升高和肌痛)、耐受性问题(如头痛)以及5种他汀类药物、依泽替米贝、吉卡宾及其组合降低冠状动脉疾病相关事件风险等情况建立了剂量反应模型。该综合模型基于对公开可用的汇总水平数据和专有患者水平数据的联合分析,纳入了近10000名患者的信息。通过使用Pharsight Drug Model Explorer模型可视化技术,该模型可供研发团队使用和访问。该建模极大地增强了对单独使用或与他汀类药物联合使用时吉卡宾临床特征的理解。发现他汀类药物与吉卡宾在降低LDL-C效应方面的相互作用与他汀类药物与依泽替米贝之间的相互作用显著不同。发现依泽替米贝具有药理学上的非依赖性相互作用,在整个他汀类药物剂量范围内可额外降低LDL-C。发现吉卡宾的相互作用小于非依赖性,在高剂量他汀类药物时几乎不会额外降低LDL-C,尽管该药物单独使用或与低剂量他汀类药物联合使用时对LDL-C有显著作用。在目标患者群体中完成首次II期试验后,该模型很快可用,并且团队能够探索吉卡宾与其他治疗选择相比的潜在临床疗效和安全性,这有助于迅速做出停止研发的决定。