Remesh Ambili
Associate Professor, Department of Pharmacology and Therapeutics, Dr SMCSI Medical College , Karakonam, India .
J Clin Diagn Res. 2013 Jul;7(7):1404-7. doi: 10.7860/JCDR/2013/6223.3144. Epub 2013 May 31.
There are various strategies for overcoming the major pitfalls of cancer chemotherapy, such as toxicity and drug resistance. The scientific computing of drug scheduling by optimisation before drug administration is one among them. In a majority of these strategies, the pharmacodynamic variations are given more importance than the pharmacokinetic variations. This study was meant to analyse the importance of the pharmacokinetic parameters (φ) of the individual patients in cancer chemotherapy scheduling, along with the pharmacodynamic factors.
A mathematical model is developed and it is implemented in the open source OCTAVE GNU LINUX. Optimisation is done by using an optimization tool in OCTAVE. The present study was aimed at evaluating the daily drug dosaging and cyclic chemotherapy which are commonly practised in the chemotherapy scheduling. Four cases were analyzed with and without considering the pharmacokinetic parameters. The optimal therapy was meant to reduce the number of cancer cells to a minimum at the end of the therapy and to minimise the emergence of resistant cancer cells. Since the dose was within tolerable limits, the toxic effects could also be minimised.
Even with the consideration of a 1 per cent effect (φ), the maximum possible dose and the performance index were increased in the daily scheduling. But in the cyclic therapy, even though the maximum tolerated dose or the performance index was not altered, the cumulative toxicity was greatly reduced.
Daily scheduling and cyclic chemotherapy can be applied alternatively more effectively, by considering the interindividual variations in the pharmacokinetic effect (φ).
克服癌症化疗的主要缺陷(如毒性和耐药性)有多种策略。给药前通过优化进行药物给药方案的科学计算就是其中之一。在大多数这些策略中,药效学变化比药代动力学变化更受重视。本研究旨在分析个体患者的药代动力学参数(φ)在癌症化疗方案制定中的重要性,以及药效学因素。
开发了一个数学模型,并在开源的OCTAVE GNU LINUX中实现。通过使用OCTAVE中的优化工具进行优化。本研究旨在评估化疗方案中常用的每日药物剂量和周期化疗。分析了4种情况,分别考虑和不考虑药代动力学参数。最佳治疗方案旨在在治疗结束时将癌细胞数量降至最低,并尽量减少耐药癌细胞的出现。由于剂量在可耐受范围内,毒性作用也可降至最低。
即使考虑1%的效应(φ),每日给药方案中的最大可能剂量和性能指标也会增加。但在周期化疗中,即使最大耐受剂量或性能指标没有改变,累积毒性也会大大降低。
通过考虑药代动力学效应(φ)中的个体差异,可以更有效地交替应用每日给药方案和周期化疗。