Example 5: Model approach for pain killers

Problem:  to assess safety of pain killers.

Drug assessed:  aspirin, celecoxib, diclofenac, naproxen, indomethacin, ibuprofen, vioxx, etc.

Motivation:

  • NSAIDs – popular drugs for pain relief and antipyretic, more recently started to be used in cancer and even depression.
  • Main target – COX1,2.
  • Wide range of adverse effects.
  • Aspirin – risk of gastro-intestinal bleeding.
  • Selective COX-2 inhibitors (Coxibs) - efficient in pain relief but with unfavourable side effects (heart attacks).

Approach: to understand mechanisms of adverse effects of existing NSAIDs and to discover new NSAIDs we suggest to develop model of pain and inflammation. 

ex5_pain_1.jpg Results 1: Model of pain and inflammation have been developed and verified against data available internally and in public sources.

ex5_pain_2.jpg
Results 2: Using the model of pain and inflammation distribution of prostanoids (PGI2, TXA2,…) and pain mediators (PGE2,…) has been calculated for different NSAIDs and drug candidates.

Conclisions:

  • regulatory mechanisms underlying adverse effects of different anti-inflammatory drugs, pain killers and drug candidates have been reconstructed at the molecular, cellular, organ and organism levels;
  • potential organ specific protein targets for development of new pain killers and NSAIDs which are free from the adverse effects have been identified.

Advisory Software Packages:

On the basis of the models Advisory Software Packages (ASP) have been developed: COXulator, CLOTalyzer, CIRCulator.

These ASP are based on pre-developed and verified models which are (i) ready to use without going into model details/parameters, (ii) are tuned to specified procedure/experiment and (iii) can be easily exploited via user friendly interface. 

These models and ASP help people working on drug discovery/drug safety to integrate modelling approach into experimental research and, thereby, increase efficacy of their work.  The computer modelling of the pain involved pathways may predict:

  • new therapeutic targets for intervention;
  • compare the different targets and identify most efficient;
  • possible side effects for the drug treatment; compare the side effects of different drugs and identify the ways to minimize it.

Why all 3 ASP needed?

They are needed to:

  • facilitate and automatize the process of data management and interpretation;
  • improve and formalize the process of the decision making during drug development;
  • extend analysis of generated data at the expense of all available public literature data integrated in mathematical model.
ex5_pain_3_eng.jpg

How ASP could help in a decision making problem?

COXulator: Calculate true kinetic parameters (dissociation and rate constants) of drug precursor on the basis of measured dose dependence and type of essay. This allows to exclude from further development those compounds which do not satisfy “specificity” and “binding time” requirements.

CLOTalyser: On the basis of true kinetic parameters of the specified compound and essay type, one calculates response of platelets and/or EC suspention to drug precursor in terms of extracellular and intracellular concentrations of prostanoids and signaling intermediates. This allows to exclude from further development those compounds which do not satisfy “efficacy” requirements.

CIRCulator: On the basis of true kinetic parameters of the specified compound and anthropological/clinical data, one calculates response of platelets and/or EC to drug precursor in any part of blood circulation system in terms of extracellular and intracellular concentrations of prostanoids and signaling intermediates. This allows to:

  • exclude from further development those compounds which do not satisfy “safety” requirements;
  • explore individual specificity of various patients groups (gender, constitution, race,…) to the drug precursor;
  • chose optimal way of administration and dosage regime.


Pdf-description:

 

Download

Select language

RussianEnglish

Contacts

Institute for Systems Biology SPb

Moscow, Leninskie Gory, 1, build.75G, office. 613, Science park, 119992

+7(495)930-8407,   +7(495)930-8407, +7(495)783-8718

insysbio@insysbio.ru   insysbio@insysbio.ru

Search