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Systems pharmacology

Computational systems pharmacology is a relatively new research area at the intersection of drug discovery/ development and mathematical modeling. Systems pharmacology integrates the methods of systems biology, PK/PD modeling, computational physiology, and development of these methods, focusing on the modeling of heterogeneous living systems of different levels of organization. In particular, it is of interest how metabolic or cellular level processes can influence physiological or clinically measured endpoints.

Such theoretical objects as model of disease, model of treatment, and tissue crosstalk models, allowing for the prediction of drug effects on the whole organism, are impossible without an understanding of top-down and bottom-up regulation. Another specific feature of the systems pharmacology approach is focusing on the mechanisms of processes, in contrast to the compartmental PK/PD approach.

All these advantages allow for researchers to solve actual problems arising during new drug development, thereby reducing both the cost of and time required for the study. Application of systems pharmacology has shown that drug development has become less random and therefore more effective.

Method application:

  • Prognosis of risks for the particular target choice at the initial stages of drug development;
  • Prediction of optimal pharmacokinetics and binding properties for a compound for maximal therapeutic effect;
  • Analysis of reasons to explain the failure of clinical trials in terms of mechanism of action and to search for possible modifications of treatment regimens, including use of combination therapy;
  • Reconstruction of mechanisms of action for drugs;
  • Search and analysis of adverse effects of a drug;
  • Taking into account individual genetic and physiological features for personalized doses and treatment regimens;
  • Predictions and explanations of long-term effects on the basis short-term measurements;
  • And so on…