Model Approach for Clinical Trials

In the competitive pharmaceutical and biotech landscape, the market success of any new product depends on how well a company executes a clinical development program. Success depends on integrating scientific and clinical data to the development and commercialization of therapies.

Institute for Systems Biology SPb offers CRO and pharmaceutical companies services for analysis and processing data of preclinical and clinical trials (CT).

Our methods based on up-to-date model approach for analysis of CT data. Model approuch successfully used by many pharmaceutical companies for CT data analysis more then 30 years, that allows to save funds and time for carrying out of CTand minimize their costs.

Main advantages of model approach in comparison with standard methods are flexibility, scalability and more informativity of results and conclusions. Based on the same input data model approach allows to get more exact characteristics of studied effects. Moreover, model approach allows to find answers for great number of questions which are difficult to explain using standard methods. For example, using model approach it is posible to predict results of the one or another CT stages, analyze reasons of variability and etc.

At the present time it is possible to use model approach at the several ST stages.

We can define these activities into four basic types:

  1. Analysis of data obtained at the stage of preclinical trials: an increase of efficacy and decrease of the costs of CT.
  2. Analysis of data obtained at the different stages of clinical trials: detail analysis of CT results, population analysis.
  3. Prediction of results expected for the different CT stages: forecasting and development of the best CT design.
  4. Additional and related services.

Several examples of such studies you could find below:

1.1.  Estimation of single and multiple drug dose for the first stage of CT, estimation of optimal mode of drug introduction and dosing regimen.
ct_serv_1.1_eng.jpg

Advantages:

1.More accurate and safe dosage

2.Less number of trials

1.2. Estimation of single and multiple drug dose for the second stage of CT.
ct_serv_1.2_eng.jpg

Advantages:

1.More accurate and safe dosage

2.Less number of trials

2.1.  Analysis and processing of data obtained at the I – IV CT stages.
ct_serv_2.1_eng.jpg

Advantages:

1. Analysis of data with complex PK (Pharmacokinetics) and PD (Pharmacodynamics)

2. Analysis of poor data (one point at the patient)

3. Less number of CT data for receipt of adequate results

4. Inter- and intra- individual variability

2.2.  Analysis of variability reason and detection of correlations for more safe and effective way of drug development.
ct_serv_2.2_eng.jpg  

Advantages:

1.Information about dependence of different parameters, unavailable for other methods

2.3.  Analysis of subpopulations – gender, race, renal or hepatic failure etc.
ct_serv_2.3_eng.jpg

Advantages:

1. Application of automated search for finding of drug action differences in the various populations
3. Prediction of results expected for the different CT stages.
ct_serv_3_eng.jpg

Advantages:

There are possibilities to:

  • predict result of the CT stage before it gets start,
  • test and choose optimal design of CT, 
  • estimate adequacy of data sample.
4. Additional and related services.
  1. Prediction of results of testing on  drug bioequivalence. Estimation of sample size.

  2. Processing of results of testing on drug bioequivalence. More exact  and informative methods.

  3. Guidance for individual dosage based on CT results.

  4. Prediction of long time drug side effects based on molecular modeling.

  5. Prediction of drugs interactions (synergism of antagonism).

  6. Development of drug safety strategies.

 

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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

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