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基于多孔载体的新型钙敏感受体盐酸西那卡塞口服自乳化给药系统的设计、开发与质量评价:体外与体内特征研究。

Quality by Design Enabled Development of Oral Self-Nanoemulsifying Drug Delivery System of a Novel Calcimimetic Cinacalcet HCl Using a Porous Carrier: In Vitro and In Vivo Characterisation.

机构信息

Roland Institute of Pharmaceutical Sciences (Affiliated to Biju Patnaik University of Technology), Berhampur, Odisha, India.

出版信息

AAPS PharmSciTech. 2019 Jun 6;20(5):216. doi: 10.1208/s12249-019-1411-2.

Abstract

In this present research, work quality by design-enabled development of cinacalcet HCl (CH)-loaded solid self-nanoemulsifying drug delivery system (S-SNEDDS) was conducted using a porous carrier in order to achieve immediate drug release and better oral bioavailability. Capmul MCM (CAP), Tween 20 (TW 20) and Transcutol P (TRP) were selected as excipients. Cumulative % drug release at 30 min (Q30), emulsification times (ET), mean globule size (GS) and polydispersity index (PDI) were identified as critical quality attributes (CQAs). Factor mode effect analysis (FMEA) and Taguchi screening design were applied for screening of factors. The optimised single dose of S-SNEDDS obtained using Box-Behnken design (BBD) consisted of 30 mg of CH, 50 mg of CAP, 149.75 mg of TW 20, 55 mg of TRP and 260.75 mg of Neusilin US2. It showed an average Q30 of 97.6%, ET of 23.3 min, GS of 89.5 nm and PDI of 0.211. DSC, XRD and SEM predict the amorphous form of S-SNEDDS. In vivo pharmacokinetic study revealed better pharmacokinetic parameters of S-SNEDDS. The above study concluded that the optimised S-SNEDDS is effective to achieve the desired objective. Graphical Abstract.

摘要

在本研究中,通过设计使盐酸西那卡塞(CH)负载的固体自乳化药物传递系统(S-SNEDDS)具有更好的工作质量,使用多孔载体来实现药物的快速释放和更好的口服生物利用度。Capmul MCM(CAP)、吐温 20(TW 20)和 Transcutol P(TRP)被选为辅料。累积 30 分钟时的药物释放百分比(Q30)、乳化时间(ET)、平均粒径(GS)和多分散指数(PDI)被确定为关键质量属性(CQAs)。因子模式效应分析(FMEA)和 Taguchi 筛选设计用于筛选因素。使用 Box-Behnken 设计(BBD)获得的优化单剂量 S-SNEDDS 由 30mg CH、50mg CAP、149.75mg TW 20、55mg TRP 和 260.75mg Neusilin US2 组成。它显示出平均 Q30 为 97.6%、ET 为 23.3 分钟、GS 为 89.5nm 和 PDI 为 0.211。DSC、XRD 和 SEM 预测 S-SNEDDS 的无定形形式。体内药代动力学研究表明 S-SNEDDS 的药代动力学参数更好。上述研究表明,优化的 S-SNEDDS 能够有效地达到预期目标。

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