IMBM for Drug Development
IMBM develops sophisticated scientific methods for optimizing cancer clinical treatments. At present, we focus on optimization programs for various chemotherapeutic protocols with or without different combinations of hemopoietic growth factors. The methods are based on the analysis of mathematical models describing the complex cancer and hemopoietic dynamics, and on elaborate optimization algorithms. These developments enable a significant reduction of time and expenses in the drug-development process.
Analyzing Drug Efficacy
Analyzing drug efficacy is based on the mathematical models and technologies existing at IMBM. It contains detailed mathematical models for the dynamics of cancer growth and the hemopoietic process under drug administration. These single-purpose models are tightly based on an up-to-date biological, pharmaco-dynamic and pharmaco-kinetic information and adjusted according to the specifications of the drug developer. We use these models for constructing a single-purpose software tool to be used for evaluating specific administration protocols.
Thus, the user of this tool can set an initial state of the “virtual” patient and “start a treatment” with a specific drug protocol, to obtain:
Optimizing Treatment Protocols
IMBM implements its mathematical models in a further development for determining the optimal treatment protocol for a specific drug. Thus, sophisticated optimization algorithms are adapted to the specific characteristic of the drug to operate on the cancer models. Protocol’s “optimality” is determined by using pre-specified constraints on its applicability (e.g., the maximum tolerable toxicity), and a mathematical function of many different criteria is used for testing its efficacy.
Thus, the user can obtain:
The use of this tool will profoundly reduce time and
cost of drug development, and will minimize the risk of treating a
patient with ineffective protocols.
IMBM for Cancer Clinics
A long-term objective of IMBM is to develop sophisticated scientific methods for optimizing cancer treatments. Notably, we focus on the development of optimization programs for various chemotherapeutic protocols with or without different combinations of hemopoietic growth factors (some of these factors are still in clinical trials). The methods are based on the analysis of mathematical models describing the complex cancer and hemopoietic dynamics, and on elaborate optimization algorithms. These developments are expected to guarantee optimization of the treatment program for each individual patient, so as to ensure the best results according to physicians’ definitions.
Our scientific research provides tools for predicting: