The complex effect of granulocyte colony-stimulating factor on human granulopoiesis analyzed by a new physiologically-based mathematical model

Vainstein, Vladimir; Ginosar, Yuval; Shoham, M.; Ranmar, D.O.; Ianovski, Anton; Agur, Zvia

doi:10.1016/j.jtbi.2004.11.026

Cited by 50 publications

(66 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Elaborate mathematical models of the pathology and physiology at hand have been developed to enable precise quantitative predictions and, hence, to implement this approach in the clinic. A first step in this direction was carried out and the realism of these models has been verified in the pre-clinical setting (e.g., Arakelyan et al 2002Arakelyan et al , 2005Skomorovski et al 2003;Vainstein et al 2005). Subsequently, it is suggested that replacement of a conventional breast cancer treatment schedule, which involves 100 mg/m 2 of Taxotere applied every three weeks, by a weekly dosing of 30 mg/m 2 of Taxotere, can accelerate tumor shrinkage and significantly reduce its chemotherapy-induced neutropenia in specific patients (Arakelyan et al).…”

Section: Appendixmentioning

confidence: 99%

Optimizing Chemotherapy Scheduling Using Local Search Heuristics

Agur

Hassin

Levy

2006

Operations Research

View full text Add to dashboard Cite

We develop a method for computing efficient patient-specific drug protocols. Using this method, we identify two general categories of anticancer drug protocols, depending on the temporal cycle parameters of the host and cancer cells: a onetime intensive treatment, or a series of nonintensive treatments. Our method is based on a theoretical and experimental work showing that treatment efficacy can be improved by determining the dosing frequency on the drug-susceptible target and host cell-cycle parameters. Simulating the patient's pharmaco-dynamics in a simple model for cell population growth, we calculate the number of drug susceptible cells at every moment of therapy. Local search heuristics are then used to conduct a search for the desired solution, as defined by our criteria. These criteria include the patient's state at the end of a predetermined time period, the number of cancer and host cells at the end of treatment, and the time to the patient's cure. The process suggested here does not depend on the exact biological assumptions of the model, thus enabling its use in a more complex description of the system. We test three solution methods. Simulated annealing is compared to threshold acceptance and old bachelor acceptance, which are less known variants to this method. The conclusions concerning the three approximation methods are that good results can be achieved by choosing the proper parameters for each of the methods, but the computational effort required for achieving good results is much greater in simulated annealing than in the other methods. Also, a large number of iterations does not guarantee better solution quality, and resources would be better used in several short searches with different parameter values than in one long search.

show abstract

Section: Appendixmentioning

confidence: 99%

Optimizing Chemotherapy Scheduling Using Local Search Heuristics

Agur

Hassin

Levy

2006

Operations Research

View full text Add to dashboard Cite

show abstract

“…The repurposing of a compound instead involves a change either in the current application of an approved drug or in the intended/tested application of a drug under development. The disclosed techniques are based on more than two decades of biomathematical research in the area of disease control optimization and drug modeling: they are finalized to simulate the dynamics of key biological, pathological and pharmacological processes in a patient undergoing drug treatment [42][43][44][45][46][47][48][49][50][51]. The first stage of the mathematical-based approach consists of creating a model of drug pharmacokinetics (PK) and pharmacodynamics (PD).…”

Section: Mathematical-based Patentsmentioning

confidence: 99%

“…The cell-cycle structures incorporate experimental data on cell-cycle phase distribution in different BM compartments as well as results from radioactive labelling experiments. The granulopoiesis model parameters are instead estimated by a curve-fitting process based on a variety of in vivo experiments, as specified in [43]. The model prediction accuracy was originally tested by dividing a set of patients (mainly Caucasian females) into a "training set", whose clinical outcomes were used to adjust model parameters, and a "validation set", whose medical data were compared to the model-predicted neutrophil profiles upon simulation of docetaxel treatment [64].…”

Section: Mathematical-based Patentsmentioning

confidence: 99%

Computational Approaches for Translational Oncology: Concepts and Patents

Scianna¹,

Munaron

2016

PRA

View full text Add to dashboard Cite

Background: Cancer is a heterogeneous disease, which is based on an intricate network of processes at different spatiotemporal scales, from the genome to the tissue level. Hence the necessity for the biomedical and pharmaceutical research to work in a multiscale fashion. In this respect, a significant help derives from the collaboration with theoretical sciences. Indeed, mathematical models can provide insights into tumor-related processes and support clinical oncologists in the design of treatment regime, dosage, schedule and toxicity. Objective and Method: The main objective of this article is to review the recent computational-based patents which tackle some relevant aspects of tumor treatment. We first analyze a series of patents which concern the purposing or repurposing of anti-tumor compounds. These approaches rely on pharmacokinetics and pharmacodynamics modules, that incorporate data obtained in the different phases of clinical trials. Similar methods are also at the basis of other patents included in this paper, which deal with treatment optimization, in terms of maximizing therapy efficacy while minimizing side effects on the host. A group of patents predicting drug response and tumor evolution by the use of kinetics graphs are commented as well. We finally focus on patents that implement informatics tools to map and screen biological, medical, and pharmaceutical knowledge. Results and Conclusions: Despite promising aspects (and an increasing amount of the relative literature), we found few computational-based patents: there is still a significant effort to do for allowing modelling approaches to become an integral component of the pharmaceutical research.

show abstract

“…Due to the importance of G-CSF in treating bone marrow transplant and chemotherapy patients, there have been a variety of mathematical models of G-CSF kinetics [65] - [69]. In the hematological models described above, G-CSF is included implicitly using constant parameters such as neutrophil apoptosis and the maximal rate of differentiation into the neutrophil line [56,60].…”

Section: A More Sophisticated Modelmentioning

confidence: 99%