药物发现
决策树
计算机科学
业务流程发现
生化工程
数据挖掘
工程类
运营管理
生物信息学
生物
在制品
业务流程
业务流程建模
作者
Yung-Chi Lee,Philip Zocharski,Brian Samas
标识
DOI:10.1016/s0378-5173(02)00704-4
摘要
Discovery and pre-clinical animal efficacy assessment formulation development efforts are challenged by limited compound availability and stringent timelines. The implementation and use of a systematic discovery formulation scheme can facilitate this important process. We observed that nearly 85% of Pfizer, Ann Arbor discovery compounds (n>300) submitted for discovery and pre-clinical injectable formulation development in the year 2000 could be formulated by pH adjustment, cosolvent addition, or a combination of the two approaches. Based on the vehicle data generated by this laboratory, a discovery formulation decision tree, that utilizes the solubilization approaches described above, is proposed. The proposed decision tree can be adapted and modified by pharmaceutical scientists to conform to best practices put forth by their institutions for discovery animal studies requiring injectable dosage forms.
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