Industrial Trainee, Pfizer Global Research and Development, Sandwich, Kent, UK.
Eur J Pharm Sci. 2013 Jul 16;49(4):505-11. doi: 10.1016/j.ejps.2013.04.021. Epub 2013 Apr 29.
The low amounts of drug available in early discovery often results in limited information on the physico-chemical (solubility etc.) properties of a compound being obtained. As a result, predictive tools and miniaturised screens have been investigated to aid formulation development in early discovery. This study looks at the potential application of the quantum chemistry program, Conductor Screening Model for Real Solvents (COSMO-RS) to help with the selection of excipients for formulation development in early discovery. The excipient solubility predictions obtained from COSMO-RS were compared to experimentally obtained solubilities. The results showed that in general, COSMO-RS was able to help formulators with the selection of the most appropriate excipients to solubilise the model compound.
早期发现的药物含量低,通常会导致获得的化合物物理化学(溶解度等)性质的信息有限。因此,已经研究了预测工具和微型化屏幕,以帮助早期发现中的制剂开发。本研究着眼于量子化学程序Conductor Screening Model for Real Solvents (COSMO-RS)的潜在应用,以帮助选择用于早期发现制剂开发的赋形剂。从 COSMO-RS 获得的赋形剂溶解度预测值与实验获得的溶解度进行了比较。结果表明,一般来说,COSMO-RS 能够帮助制剂师选择最合适的赋形剂来溶解模型化合物。