Subramanian Raju, Wang Jianhong, Murray Bernard, Custodio Joseph, Hao Jia, Lazerwith Scott, MacLennan Staiger Kelly, Mwangi Judy, Sun Hailing, Tang Jennifer, Wang Kelly, Rhodes Gerry, Wijaya Samantha, Zhang Heather, Smith Bill J
Gilead Sciences, Inc, Foster City, CA, USA.
Xenobiotica. 2022 Dec;52(12):1020-1030. doi: 10.1080/00498254.2023.2169207. Epub 2023 Jan 26.
Bictegravir (BIC) is a potent small-molecule integrase strand-transfer inhibitor (INSTI) and a component of Biktarvy, a single-tablet combination regimen that is currently approved for the treatment of human immunodeficiency virus type 1 (HIV-1) infection. The properties, pharmacokinetics (PK), and drug-drug interaction (DDI) profile of BIC were characterised and .BIC is a weakly acidic, ionisable, lipophilic, highly plasma protein-bound BCS class 2 molecule, which makes it difficult to predict human PK using standard methods. Its systemic plasma clearance is low, and the volume of distribution is approximately the volume of extracellular water in nonclinical species. BIC metabolism is predominantly mediated by cytochrome P450 enzyme (CYP) 3A and UDP-glucuronosyltransferase 1A1. BIC shows a low potential to perpetrate clinically meaningful DDIs known drug metabolising enzymes or transporters.The human PK of BIC was predicted using a combination of bioavailability and volume of distribution scaled from nonclinical species and a modified - correlation (IVIVC) correction for clearance. Phase 1 studies in healthy subjects largely bore out the prediction and supported the methods used. The approach presented herein could be useful for other drug molecules where standard projections are not sufficiently accurate. .
比克替拉韦(BIC)是一种强效小分子整合酶链转移抑制剂(INSTI),也是必妥维的成分之一,必妥维是一种单片复方治疗方案,目前已被批准用于治疗1型人类免疫缺陷病毒(HIV-1)感染。对BIC的性质、药代动力学(PK)和药物-药物相互作用(DDI)特征进行了表征。BIC是一种弱酸性、可电离、亲脂性、血浆蛋白高度结合的BCS 2类分子,这使得使用标准方法预测人体PK变得困难。其全身血浆清除率较低,在非临床物种中的分布容积约为细胞外液体积。BIC的代谢主要由细胞色素P450酶(CYP)3A和尿苷二磷酸葡萄糖醛酸转移酶1A1介导。BIC对已知药物代谢酶或转运蛋白产生具有临床意义的DDIs的可能性较低。使用从非临床物种缩放的生物利用度和分布容积的组合以及清除率的修正体内-体外相关性(IVIVC)校正来预测BIC的人体PK。在健康受试者中进行的1期研究在很大程度上证实了该预测并支持所使用的方法。本文提出的方法可能对其他标准预测不够准确的药物分子有用。