Drug development has always been an expensive and complicated. A number of therapies often discontinue from the clinical development at the later stages. It is not always possible to choose doses of medication or recruit a suitable patients group for trials. ISBM offers a new approach to solve these problems: quantitative systems pharmacology (QSP) modeling. Disease or organism system is described in the most precise mechanistic way, and the equations are based on literature data and basic knowledge. QSP models have the greatest planning horizon: built more on the early stages of the research, they predict what the developers can see on the second phase of clinical trials.
For the last decade the investigators from ISBM have developed many solutions for their partners- big pharmaceutical companies such as Pfizer, MedImmune, AstraZeneca and others. IRT aggregates years of modeling experience in the company and simplifies the development of QSP-models in the immuno-oncology field.
"It usually takes at least half of the year to build a QSP model describing the basics of immune response," said Oleg Demin Jr, a project leader. "IRT helps to shorten the time frame in incredible way: one can design a model template in few clicks. We described the processes in human body not only biologicaly, but also mathematically. For us cells, cytokines, proteins are all the variables, and the immunity is a complex system of equations. In fact, we have designed the human immune system on the computer and visualized it »
The software consists of two parts: IRT database and the special IRT navigator to access it. Current database version describes about 10 types of immune cells, 10 surface molecules, 20 cytokines and 300 processes associated with an immune response in human blood, lymph nodes and inflamed tissue. There are annotations of each process, cell and cytokine with cross references and links to the external databases in every interactive scheme (passport of immune cell and cytokine source profile). Platform user can see valuation parameters fitted with help of specific "in vitro" models against in vitro data or calculated using in vivo data measured for healthy humans, and extended annotation of rate equations and parameters.
Modeler needs to choose the objects of interest, and IRT navigator automatically generates and saves a model template with selected players, processes and corresponding parameters. Variation of these parameters enables to obtain a virtual patient population which can be used for in silico trials. This approach strongly improves all the drug development process, especially in immune oncology field. Pharmacologists will be able to give right medication doses supported by mathematical models to patients group that is most suitable to examine drug efficiency.
The project is believed to have a great future. Some big pharmaceutical companies have already adopted the platform. Oleg Demin Jr also explained that the Immune Response Template is a big step on the way of representation the entire human body as a computer program.
To get more information and try the IRT Demo please visit irt.insysbio.ru
About Institute for Systems Biology Moscow (ISBM):
Institute for Systems Biology Moscow, Ltd. is a leading R&D company providing services for mathematical modeling in drug research and development. ISBM is one of the pioneers in quantitative system pharmacology (QSP) modeling and simulation services and has been working on the market for more than 10 years. The company's aim is to assist right decisions on the critical stages of drug research and development. ISBM team continuously improves methods and tools for biological modeling. Moreover, company works with students and postgraduates forming professional community of QSP-modelers. Company has published a lot of scientific studies, and has presented at major international conferences of the field. The ISBM innovative approach has become an integral part of the drug development process implemented by our strategic partners: nowadays there are more than 100 completed projects in collaboration with leaders of pharma industry.
Story Source: Materials provided by Scienmag