Maeda Jin, Suzuki Tatsuya, Takayama Kozo
Formulation Technology Research Laboratories, Daiichi Sankyo Co., Ltd., 1-12-1 Shinomiya, Hiratsuka, Kanagawa 254-0014, Japan.
Chem Pharm Bull (Tokyo). 2012;60(9):1155-63. doi: 10.1248/cpb.c12-00340.
A reliable large-scale design space was constructed by integrating the reliability of a scale-up rule into the Bayesian estimation without enforcing a large-scale design of experiments (DoE). A small-scale DoE was conducted using various Froude numbers (X(1)) and blending times (X(2)) in the lubricant blending process for theophylline tablets. The response surfaces, design space, and their reliability of the compression rate of the powder mixture (Y(1)), tablet hardness (Y(2)), and dissolution rate (Y(3)) on a small scale were calculated using multivariate spline interpolation, a bootstrap resampling technique, and self-organizing map clustering. A constant Froude number was applied as a scale-up rule. Experiments were conducted at four different small scales with the same Froude number and blending time in order to determine the discrepancies in the response variables between the scales so as to indicate the reliability of the scale-up rule. Three experiments under an optimal condition and two experiments under other conditions were performed on a large scale. The response surfaces on the small scale were corrected to those on the large scale by Bayesian estimation using the large-scale results and the reliability of the scale-up rule. Large-scale experiments performed under three additional sets of conditions showed that the corrected design space was more reliable than the small-scale design space even when there was some discrepancy in the pharmaceutical quality between the manufacturing scales. This approach is useful for setting up a design space in pharmaceutical development when a DoE cannot be performed at a commercial large manufacturing scale.
通过将放大规则的可靠性整合到贝叶斯估计中，构建了一个可靠的大规模设计空间，而无需强制进行大规模实验设计（DoE）。在茶碱片润滑剂混合过程中，使用各种弗劳德数（X(1)）和混合时间（X(2)）进行了小规模的DoE。使用多元样条插值、自助重采样技术和自组织映射聚类计算了小规模下粉末混合物的压缩率（Y(1)）、片剂硬度（Y(2)）和溶出率（Y(3)）的响应面、设计空间及其可靠性。应用恒定的弗劳德数作为放大规则。为了确定不同规模之间响应变量的差异，从而表明放大规则的可靠性，在四个不同的小规模下进行了实验，弗劳德数和混合时间相同。在最优条件下进行了三次实验，在其他条件下进行了两次大规模实验。利用大规模结果和放大规则的可靠性，通过贝叶斯估计将小规模的响应面校正为大规模的响应面。在另外三组条件下进行的大规模实验表明，即使在生产规模之间的药品质量存在一些差异时，校正后的设计空间也比小规模设计空间更可靠。当无法在商业大规模生产规模下进行DoE时，这种方法对于在药物开发中建立设计空间很有用。
