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纯计算机模拟生物药剂学分类系统(BCS):面向全球药物的基于科学的质量标准。

Purely in silico BCS classification: science based quality standards for the world's drugs.

作者信息

Dahan Arik, Wolk Omri, Kim Young Hoon, Ramachandran Chandrasekharan, Crippen Gordon M, Takagi Toshihide, Bermejo Marival, Amidon Gordon L

机构信息

Department of Clinical Pharmacology, School of Pharmacy, Faculty of Health Sciences, Ben-Gurion University of the Negev , Beer-Sheva 84105, Israel.

出版信息

Mol Pharm. 2013 Nov 4;10(11):4378-90. doi: 10.1021/mp400485k. Epub 2013 Oct 23.

Abstract

BCS classification is a vital tool in the development of both generic and innovative drug products. The purpose of this work was to provisionally classify the world's top selling oral drugs according to the BCS, using in silico methods. Three different in silico methods were examined: the well-established group contribution (CLogP) and atom contribution (ALogP) methods, and a new method based solely on the molecular formula and element contribution (KLogP). Metoprolol was used as the benchmark for the low/high permeability class boundary. Solubility was estimated in silico using a thermodynamic equation that relies on the partition coefficient and melting point. The validity of each method was affirmed by comparison to reference data and literature. We then used each method to provisionally classify the orally administered, IR drug products found in the WHO Model list of Essential Medicines, and the top-selling oral drug products in the United States (US), Great Britain (GB), Spain (ES), Israel (IL), Japan (JP), and South Korea (KR). A combined list of 363 drugs was compiled from the various lists, and 257 drugs were classified using the different in silico permeability methods and literature solubility data, as well as BDDCS classification. Lastly, we calculated the solubility values for 185 drugs from the combined set using in silico approach. Permeability classification with the different in silico methods was correct for 69-72.4% of the 29 reference drugs with known human jejunal permeability, and for 84.6-92.9% of the 14 FDA reference drugs in the set. The correlations (r(2)) between experimental log P values of 154 drugs and their CLogP, ALogP and KLogP were 0.97, 0.82 and 0.71, respectively. The different in silico permeability methods produced comparable results: 30-34% of the US, GB, ES and IL top selling drugs were class 1, 27-36.4% were class 2, 22-25.5% were class 3, and 5.46-14% were class 4 drugs, while ∼8% could not be classified. The WHO list included significantly less class 1 and more class 3 drugs in comparison to the countries' lists, probably due to differences in commonly used drugs in developing vs industrial countries. BDDCS classified more drugs as class 1 compared to in silico BCS, likely due to the more lax benchmark for metabolism (70%), in comparison to the strict permeability benchmark (metoprolol). For 185 out of the 363 drugs, in silico solubility values were calculated, and successfully matched the literature solubility data. In conclusion, relatively simple in silico methods can be used to estimate both permeability and solubility. While CLogP produced the best correlation to experimental values, even KLogP, the most simplified in silico method that is based on molecular formula with no knowledge of molecular structure, produced comparable BCS classification to the sophisticated methods. This KLogP, when combined with a mean melting point and estimated dose, can be used to provisionally classify potential drugs from just molecular formula, even before synthesis. 49-59% of the world's top-selling drugs are highly soluble (class 1 and class 3), and are therefore candidates for waivers of in vivo bioequivalence studies. For these drugs, the replacement of expensive human studies with affordable in vitro dissolution tests would ensure their bioequivalence, and encourage the development and availability of generic drug products in both industrial and developing countries.

摘要

BCS分类是仿制药和创新药研发中的一项重要工具。本研究的目的是使用计算机模拟方法,根据BCS对全球畅销口服药物进行初步分类。研究考察了三种不同的计算机模拟方法:成熟的基团贡献法(CLogP)和原子贡献法(ALogP),以及一种仅基于分子式和元素贡献的新方法(KLogP)。美托洛尔用作低/高渗透性类别边界的基准。使用依赖于分配系数和熔点的热力学方程在计算机上估算溶解度。通过与参考数据和文献进行比较,确认了每种方法的有效性。然后,我们使用每种方法对世界卫生组织基本药物标准清单中的口服速释药物产品,以及美国、英国、西班牙、以色列、日本和韩国的畅销口服药物产品进行初步分类。从各个清单中编制了一份包含363种药物的综合清单,并使用不同的计算机模拟渗透性方法、文献溶解度数据以及BDDCS分类对257种药物进行了分类。最后,我们使用计算机模拟方法计算了综合集中185种药物的溶解度值。对于29种已知人体空肠渗透性的参考药物,不同计算机模拟方法的渗透性分类正确率为69 - 72.4%;对于数据集中14种FDA参考药物,正确率为84.6 - 92.9%。154种药物的实验log P值与它们的CLogP、ALogP和KLogP之间的相关性(r²)分别为0.97、0.82和0.71。不同的计算机模拟渗透性方法产生了可比的结果:美国、英国、西班牙和以色列畅销药物中,30 - 34%为1类,27 - 36.4%为2类,22 - 25.5%为3类,5.46 - 14%为4类药物,约8%无法分类。与各国清单相比,世界卫生组织清单中1类药物明显较少,3类药物较多,这可能是由于发展中国家与工业化国家常用药物存在差异。与计算机模拟BCS相比,BDDCS将更多药物分类为1类,这可能是因为其代谢基准(70%)比严格的渗透性基准(美托洛尔)更宽松。对于363种药物中的185种,计算了计算机模拟溶解度值,并成功与文献溶解度数据匹配。总之,相对简单的计算机模拟方法可用于估算渗透性和溶解度。虽然CLogP与实验值的相关性最佳,但即使是基于分子式且无需了解分子结构的最简化计算机模拟方法KLogP,也能产生与复杂方法相当的BCS分类。这种KLogP与平均熔点和估计剂量相结合,甚至在合成之前,仅根据分子式就可用于对潜在药物进行初步分类。全球畅销药物中有49 - 59%是高溶解性的(1类和3类),因此有资格豁免体内生物等效性研究。对于这些药物,用经济实惠且可在体外进行的溶出度试验替代昂贵的人体研究,将确保其生物等效性,并促进工业化国家和发展中国家仿制药的研发与供应。

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