Tools for Early Prediction of Drug Loading in Lipid-Based Formulations.
Tools for Early Prediction of Drug Loading in Lipid-Based Formulations.
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DOI：
10.1021/acs.molpharmaceut.5b00704
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发表时间：
2016-01-04
影响因子：
4.9
通讯作者：
Bergström CA
中科院分区：
文献类型：
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作者：
Alskär LC;Porter CJ;Bergström CA
目前，确定脂基制剂（LBFs）用于递送难水溶性药物的有效性主要是基于实验。在这项工作中，我们使用了不同的药物数据集和超过2000个溶解度测量来开发实验和计算工具来预测lbf的负载能力。开发了计算模型，以实现对LBFs中溶解度的计算机预测，从而预测药物负载能力。与混合单、二、甘油三酯（Maisine 35-1和Capmul MCM EP）的溶解度相关（R2 0.89），与Carbitol和其他乙氧基化辅料的溶解度相关（PEG400, R2 0.85；聚山梨酯80，R2 0.90; Cremophor EL, R2 0.93）。观察到熔点低于150°C会导致甘油的合理溶解度。根据单辅料的溶解度数据准确计算出LBFs的负载量（R2 0.91）。在不需要实验确定溶解度的情况下，计算机模型也能很好地预测这些复杂配方中的负载能力（R2 0.79）。这里建立的框架可以更好地理解药物在单一赋形剂中的溶解度和LBF负载能力。研究的大数据集表明，实验筛选工作可以通过关键赋形剂的溶解度测量或固体状态信息来合理化。这是第一次证明了复杂配方中的负载能力可以使用从计算的描述符和晶体药物的热性质中提取的分子信息来准确预测。
Identification of the usefulness of lipid-based formulations (LBFs) for delivery of poorly water-soluble drugs is at date mainly experimentally based. In this work we used a diverse drug data set, and more than 2,000 solubility measurements to develop experimental and computational tools to predict the loading capacity of LBFs. Computational models were developed to enable in silico prediction of solubility, and hence drug loading capacity, in the LBFs. Drug solubility in mixed mono-, di-, triglycerides (Maisine 35-1 and Capmul MCM EP) correlated (R2 0.89) as well as the drug solubility in Carbitol and other ethoxylated excipients (PEG400, R2 0.85; Polysorbate 80, R2 0.90; Cremophor EL, R2 0.93). A melting point below 150 °C was observed to result in a reasonable solubility in the glycerides. The loading capacity in LBFs was accurately calculated from solubility data in single excipients (R2 0.91). In silico models, without the demand of experimentally determined solubility, also gave good predictions of the loading capacity in these complex formulations (R2 0.79). The framework established here gives a better understanding of drug solubility in single excipients and of LBF loading capacity. The large data set studied revealed that experimental screening efforts can be rationalized by solubility measurements in key excipients or from solid state information. For the first time it was shown that loading capacity in complex formulations can be accurately predicted using molecular information extracted from calculated descriptors and thermal properties of the crystalline drug.