实施机械建模和全球灵敏度分析 (GSA) 来设计,优化和扩大滚筒压缩工艺的规模
Parind M Desai1, Chandan Bhugra1, Ananya Chowdhury2
1Drug Product Development, GSK R&D, Collegeville, PA, United States.
International journal of pharmaceutics
|May 5, 2024
概括
使用约翰逊模型的机械建模优化了高药载荷配方的滚筒紧缩. 这种方法成功地预测了固体分数,提高了过程稳定性和制药开发的扩展.
科学领域:
- 制药工程 制药工程
- 过程化学 过程化学
- 材料科学 材料科学 材料科学
背景情况:
- 制药行业越来越多地采用机械建模来提高过程稳定性,促进扩展,加快上市时间.
- 虽然已经建立了用于滚筒紧缩的建模方法,但它们对高药量配方的应用仍然有限.
研究的目的:
- 使用约翰逊机械模型,优化滚筒压缩加工,并指导使用高药载荷配方的扩展.
- 评估过程参数对固体分量 (SF) 的影响,并将模型预测与替代吞吐量方法进行比较.
主要方法:
- 约翰逊模型使用试点规模数据 (Minipactor) 进行校准,并在商业规模批量 (Macropactor) 上验证.
- 进行了全球灵敏度分析 (GSA),以评估滚动力,间隙和速度对固体分量的影响.
- 研究了吞吐量方法作为估计SF的替代方法.
主要成果:
- 约翰逊模型准确地预测了所有14个商业规模批次的固体分数值,在±0.04 SF以内.
- 吞吐量方法在11个批中的7个批中实现了±0.06 SF内的预测.
- 全球灵敏度分析确定滚动力是影响固体分量的最重要的参数.
结论:
- 机械建模,特别是约翰逊模型,为优化和扩大高药量产品的滚筒紧缩提供了强大的框架.
- 这项研究证明了机械建模的成功应用,以在制药过程中建立质量,扩大其在药物产品开发中的实用性.
- 约翰逊模型在预测固体分数方面提供了卓越的准确性,与高药载荷滚筒紧缩的吞吐量方法相比.
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