Pharmacodynamic model for chemotherapy-induced anemia in rats

Abstract

Anticancer agents often cause bone marrow toxicity resulting in progressive anemia which may influence the therapeutic effects of erythropoietic-stimulating agents. The objective of this study was to develop a pharmacodynamic (PD) model to describe chemotherapy-induced anemia in rats. Anemia was induced in male Wistar rats with a single intravenous (i.v.) injection of 60 mg/kg carboplatin. Hematological responses including reticulocytes, red blood cells (RBC), hemoglobin, and endogenous rat erythropoietin (EPO) were measured for up to 4 weeks. A catenary, lifespanbased, indirect response model served as a basic PD model to represent erythroid cellular populations in the bone marrow and blood involved in erythropoiesis. The model assumed that actively proliferating progenitor cells in the bone marrow are sensitive to anti-cancer agents and subject to an irreversible removal process. The removal rate of the target cells is proportional to drug activity concentrations and the cell numbers. An additional RBC loss from the circulation resulting from thrombocytopenia was described by a first-order process. The turnover process of rat EPO and EPOmediated feedback inhibition mechanism regulated by hemoglobin changes were incorporated. Reticulocyte counts decreased rapidly and reached a nadir by day 3 after administration of carboplatin and returned to the baseline by day 13. This was followed by a gradual increase and the rebound peak occurred at about day 15. The hemoglobin nadir was approximately 9 g/dl observed at about 11-13 days compared to its normal value of 13 g/dl and hemoglobin returned to the baseline by day 30. The increase in endogenous rat EPO mirrored inversely hemoglobin changes and the maximum increase was observed soon after the hemoglobin nadir. The carboplatin-treated rats exhibited progressive anemia. The proposed model adequately described the time course of hematological changes after carboplatin in rats and can be a useful tool to explore potential strategies for the management of anemia caused by chemotherapy.

Mechanism-based model characterizing bidirectional interaction between PEGylated liposomal CKD-602 (S-CKD602) and monocytes in cancer patients

“…[20][21][22][23][24] As monocytes are derived from the same granulocyte-macrophage progenitor cells as other leukocytes, PD models of leukocytopenia may be applicable to monocytopenia. A semiphysiological model proposed by Friberg et al 20,21 for chemotherapy-related myelosuppression was chosen as a standard model to describe monocytopenia after S-CKD602.…”

Semi-mechanistic population pharmacokinetic/pharmacodynamic model for neutropenia following therapy with the Plk-1 inhibitor BI 2536 and its application in clinical development

“…Efficacy data are often limited in these studies due to inclusion of different tumour types and the advanced disease state of the patients [6]. Over the last years, the time course of neutropenia or other drug related haematological toxicities have been modelled linking the pharmacokinetic (PK) model with a model that describes the haematological toxicity [7][8][9][10][11]. Among these approaches, the model developed by Friberg et al [9] has been applied repeatedly to describe the time course of myelosuppression after administration of several cytotoxic anticancer drugs [12][13][14][15][16][17][18][19].…”

Modeling Corticosteroid Effects in a Rat Model of Rheumatoid Arthritis I: Mechanistic Disease Progression Model for the Time Course of Collagen-Induced Arthritis in Lewis Rats

“…Other diseases have been described, including bacterial cell growth and irreversible loss after drug therapy, fasting plasma glucose in diabetes, and pain and bone mineral density progression in osteoarthritis (Jusko, 1971;Ravn et al, 1996;Meunier et al, 1999;Frey et al, 2003;Pillai et al, 2004;de Winter et al, 2006). Mechanism-based disease progression models are continually being derived because their insight into how various pathologies contribute to progression and how drugs exert their effects on specific processes is essential to optimizing therapy (Holford and Peace, 1992a,b;Nemeroff, 1994;Hoogendoorn et al, 2005;Holford et al, 2006;Meier et al, 2007;Woo et al, 2008). To date, there are limited mechanism-based models relevant to osteoarthritis and none specific to anti-inflammatory drug effects in rheumatoid arthritis (RA).…”