Srinivas N R
Adjunct Professor, Dr Reddy's Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad, Telangana, India.
Drug Res (Stuttg). 2016 Feb;66(2):82-93. doi: 10.1055/s-0035-1549983. Epub 2015 May 26.
Statins are widely prescribed medicines and are also available in fixed dose combinations with other drugs to treat several chronic ailments. Given the safety issues associated with statins it may be important to assess feasibility of a single time concentration strategy for prediction of exposure (area under the curve; AUC). The peak concentration (Cmax) was used to establish relationship with AUC separately for pravastatin and simvastatin using published pharmacokinetic data. The regression equations generated for statins were used to predict the AUC values from various literature references. The fold difference of the observed divided by predicted values along with correlation coefficient (r) were used to judge the feasibility of the single time point approach. Both pravastatin and simvastatin showed excellent correlation of Cmax vs. AUC values with r value ≥ 0.9638 (p<0.001). The fold difference was within 0.5-fold to 2-fold for 220 out of 227 AUC predictions and >81% of the predicted values were in a narrower range of >0.75-fold but <1.5-fold difference. Predicted vs. observed AUC values showed excellent correlation for pravastatin (r=0.9708, n=115; p<0.001) and simvastatin (r=0.9810; n=117; p<0.001) suggesting the utility of Cmax for AUC predictions. On the basis of the present work, it is feasible to develop a single concentration time point strategy that coincides with Cmax occurrence for both pravastatin and simvastatin from a therapeutic drug monitoring perspective.
他汀类药物是广泛使用的处方药，也有与其他药物的固定剂量组合剂型，用于治疗多种慢性疾病。鉴于与他汀类药物相关的安全性问题，评估单次浓度策略预测暴露量（曲线下面积；AUC）的可行性可能很重要。利用已发表的药代动力学数据，分别针对普伐他汀和辛伐他汀，使用峰浓度（Cmax）来建立与AUC的关系。为他汀类药物生成的回归方程用于从各种文献参考中预测AUC值。观察值与预测值的倍数差异以及相关系数（r）用于判断单时间点方法的可行性。普伐他汀和辛伐他汀的Cmax与AUC值均显示出极好的相关性，r值≥0.9638（p<0.001）。在227次AUC预测中，有220次的倍数差异在0.5倍至2倍之间，超过81%的预测值在更窄的范围，即差异>0.75倍但<1.5倍。预测的与观察到的AUC值显示，普伐他汀（r=0.9708，n=115；p<0.001）和辛伐他汀（r=0.9810；n=117；p<0.001）具有极好的相关性，这表明Cmax可用于AUC预测。基于目前的工作，从治疗药物监测的角度来看，针对普伐他汀和辛伐他汀开发与Cmax出现时间一致的单浓度时间点策略是可行的。
