市场上开发的像治疗性单克隆抗体、生长因子等药物，占总开发数50%以上，在肿瘤治疗和其它相关疾病中有着广泛的应用。这些药物具有线性（如肾排泄）和非线性米氏方程排泄的混合排泄模式，其药物动力学的研究对合理设计给药方案，以便达到最佳治疗效果，起着至关重要的作用。本项目旨在加强与有关实际单位的合作，结合此类药物的实际动力学模型，利用数学方法来研究有关药物在病人体内的变化动态和关键的药动学参数，如半衰期、血药浓度曲线下的面积等；建立新的度量方法合理解释药物数据、数学模型和药物有效性三者之间的关系；设计可靠而稳健的算法来提高药物动力学模型参数和关键药动学参数的估计精度。该项目的实施，对于节约新药开发成本、缩短研发时间、提高新药开发成功率等有着积极的影响。

Some drugs such as therapeutic monoclonal antibodies (mAbs) and growth factors, at least 50 percent of drugs which are developed or under development, are widely used during chemotherapy or other disease. The clearance of these drugs is in particular of a mixed nature with a linear elimination (typical renal), and a nonlinear Michaelis-Menten process. Pharmacokinetics of these drugs, which concerns the movement of drugs in the body, plays an important role in the design of dosing regimens for the best benefit of therapeutic outcomes. In this project, we consider different accepted pharmacokinetic models with a particular emphasis on Michaelis-Menten elimination, and investigate their dynamical behaviors of the time course of drug concentration and widely used pharmacokinetic parameters, such as elimination half-time (t1/2) and the area under concentration curve (AUC) etc. Moreover, we will establish new metrics to link the relation among the pharmacokinetic data, pharmacokinetic models and their effectiveness of the drugs, and develop new strategies in order to improve the estimation of model parameters as well as pharmacokinetic parameters. The achievement of this project will have a positive impact on new drug development in reducing costs and time and decreasing failure rates during clinical trials。