Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents

被引:385
作者
Simeoni, M
Magni, P
Cammia, C
De Nicolao, G
Croci, V
Pesenti, E
Germani, M
Poggesi, I
Rocchetti, M
机构
[1] Pharm Italia SpA, I-20014 Nerviano, MI, Italy
[2] Univ Pavia, Dipartimento Informat & Sistemist, Pavia, Italy
关键词
D O I
10.1158/0008-5472.CAN-03-2524
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The available mathematical models describing tumor growth and the effect of anticancer treatments on tumors in animals are of limited use within the drug industry. A simple and effective model would allow applying quantitative thinking to the preclinical development of oncology drugs. In this article, a minimal pharmacokinetic-pharmacodynamic model is presented, based on a system of ordinary differential equations that link the dosing regimen of a compound to the tumor growth in animal models. The growth of tumors in nontreated animals is described by an exponential growth followed by a linear growth. In treated animals, the tumor growth rate is decreased by a factor proportional to both drug concentration and number of proliferating tumor cells. A transit compartmental system is used to model the process of cell death, which occurs at later times. The parameters of the pharmacodynamic model are related to the growth characteristics of the tumor, to the drug potency, and to the kinetics of the tumor cell death. Therefore, such parameters can be used for ranking compounds based on their potency and for evaluating potential differences in the tumor cell death process. The model was extensively tested on discovery candidates and known anticancer drugs. It fitted well the experimental data, providing reliable parameter estimates. On the basis of the parameters estimated in a first experiment, the model successfully predicted the response of tumors exposed to drugs given at different dose levels and/or schedules. It is, thus, possible to use the model prospectively, optimizing the design of new experiments.
引用
收藏
页码:1094 / 1101
页数:8
相关论文
共 28 条
[1]   Conceptual frameworks for mathematical modeling of tumor growth dynamics [J].
Bajzer, Z ;
Marusic, M ;
VukPavlovic, S .
MATHEMATICAL AND COMPUTER MODELLING, 1996, 23 (06) :31-46
[2]   Modelling and mathematical problems related to tumor evolution and its interaction with the immune system [J].
Bellomo, N ;
Preziosi, L .
MATHEMATICAL AND COMPUTER MODELLING, 2000, 32 (3-4) :413-452
[3]   Experimental antitumor activity and pharmacokinetics of the camptothecin analog irinotecan (CPT-11) in mice [J].
Bissery, MC ;
Vrignaud, P ;
Lavelle, F ;
Chabot, GG .
ANTI-CANCER DRUGS, 1996, 7 (04) :437-460
[4]   Randomized trial of dose-dense versus conventionally scheduled and sequential versus concurrent combination chemotherapy as postoperative adjuvant treatment of node-positive primary breast cancer: First report of intergroup trial C9741/cancer and leukemia group B trial 9741 [J].
Citron, ML ;
Berry, DA ;
Cirrincione, C ;
Hudis, C ;
Winer, EP ;
Gradishar, WJ ;
Davidson, NE ;
Martino, S ;
Livingston, R ;
Ingle, JN ;
Perez, EA ;
Carpenter, J ;
Hurd, D ;
Holland, JF ;
Smith, BL ;
Sartor, CI ;
Leung, EH ;
Abrams, J ;
Schilsky, RL ;
Muss, HB ;
Norton, L .
JOURNAL OF CLINICAL ONCOLOGY, 2003, 21 (08) :1431-1439
[5]   MATHEMATICAL-MODELING OF GROWTH-KINETICS OF WALKER-256 CARCINOMA IN RATS [J].
DAGNINO, G ;
ROCCHETTI, M ;
URSO, R ;
GUAITANI, A ;
BARTOSEK, I .
ONCOLOGY, 1983, 40 (02) :143-147
[6]   Antitumor activity of combinations of anti-HER-2 antibody trastuzumab and oral fluoropyrimidines capecitabine/5′-dFUrd in human breast cancer models [J].
Fujimoto-Ouchi, K ;
Sekiguchi, F ;
Tanaka, Y .
CANCER CHEMOTHERAPY AND PHARMACOLOGY, 2002, 49 (03) :211-216
[7]   Pharmacometrics: modelling and simulation tools to improve decision making in clinical drug development [J].
Gieschke, R ;
Steimer, JL .
EUROPEAN JOURNAL OF DRUG METABOLISM AND PHARMACOKINETICS, 2000, 25 (01) :49-58
[8]   Enhanced antitumour activity of 6-hydroxymethylacylfulvene in combination with topotecan or paclitaxel in the MV522 lung carcinoma xenograft model [J].
Hammond, LA ;
Hilsenbeck, SG ;
Eckhardt, SG ;
Marty, J ;
Mangold, G ;
MacDonald, JR ;
Rowinsky, EK ;
Von Hoff, DD ;
Weitman, S .
EUROPEAN JOURNAL OF CANCER, 2000, 36 (18) :2430-2436
[9]   Sequential dose-dense doxorubicin, paclitaxel, and cyclophosphamide for resectable high-risk breast cancer: Feasibility and efficacy [J].
Hudis, C ;
Seidman, A ;
Baselga, J ;
Raptis, G ;
Lebwohl, D ;
Gilewski, T ;
Moynahan, M ;
Sklarin, N ;
Fennelly, D ;
Crown, JPA ;
Surbone, A ;
Uhlenhopp, M ;
Riedel, E ;
Yao, TJ ;
Norton, L .
JOURNAL OF CLINICAL ONCOLOGY, 1999, 17 (01) :93-100
[10]   Optimizing drug regimens in cancer chemotherapy by an efficacy-toxicity mathematical model [J].
Iliadis, A ;
Barbolosi, D .
COMPUTERS AND BIOMEDICAL RESEARCH, 2000, 33 (03) :211-226