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Using computational approach for optimizing thrombopoietin treatment effects Proof of concept in murine experiments


, : Using computational approach for optimizing thrombopoietin treatment effects Proof of concept in murine experiments. Blood 98(11 Part 2): 151b, November 16

Until recently, drug schedules have been selected mostly by a method of trial and error. Aiming to replace this method by a more formal approach, a mathematical model of murine thrombopoiesis was constructed, which was then implemented in computer simulations. This model succeeds in reproducing bone marrow dynamics and platelet count changes in the periphery. The effects of Thrombopoietin (TPO, the primary regulator of thrombopoiesis), administration were introduced into this model, which proved to be capable of retrieving published experimental results of TPO administration. With the aid of this biomathematical tool, TPO administration protocols have been identified, suggesting efficacious clinical results with a significant reduction in the total dose. The current work aims at prospectively validating the concept of using mathematical methodologies for selecting improved drug protocols and, in particular, those of haemopoietic growth factors such as TPO. In the present experiments, mice treated by a previously tested recombinant-mouse-TPO administration protocol, received a single dose of 17.5 mug/kg TPO, which is reported in literature to yield a significant rise in platelet counts. In the model recommended schedule, mice received 45% of the previous total dose, that is 2 mug/kg administered on 4 consecutive days - predicted by the model to have an equivalent response. The results, whose averages are displayed in the figure below, show that the two groups of mice achieved statistically similar platelet profiles, with essentially identical peaks. These results pinpoint the predictive power of formal and quantitative methods in protocol selection, thus saving time and money, and leading to improved, less expensive and more focused patient care.

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