Towards a comprehensivecomputational platform for nextgeneration drug development –A Russian‐German joint venture         ...
We aim to provide a comprehensive platform ofbioinformatics, systems biological and cheminformatics                      t...
Some facts about geneXplain:  Founded in April 2010, starting active business July 2010  International (German-Russian) ...
proteinscompounds               networks            genes
Some facts about geneXplain:  Founded in April 2010, starting active business July 2010  International (German-Russian) ...
The idea:  Providing a platform of methods for  Biomedical research  Focus: drug development  Complete pipeline from h...
GeneXplainTM Platform: A Workflow for Drug Discovery                                                  The geneXplain platf...
Proof of concept:                    Net2Drug consortium                                     EU FP6, Coordinator: A. Kel  ...
Proof of concept:                     Net2Drug consortium                                      EU FP6, Coordinator: A. Kel...
GeneXplainTM Platform: A Workflow for Drug Discovery                                                  The geneXplain platf...
The cheminformatics portfolio:  PASS   predicts biological activities of chemical compounds from their structural formula...
How to get there:                      GeneXplainTM Platform: A Workflow for Drug Discovery                               ...
The way:             The geneXplain platform  Integrated collection of bioinformatic and systems   biological program mod...
Upstream analysis of causes                              Key node
The way:              The geneXplain platform  Integrated collection of bioinformatic and systems biological   program mo...
The geneXplain platform
The geneXplain platform
The geneXplain platform
The geneXplain platform            Public Private Partnership Clash of cultures:      Cheminformatics: commercial approa...
The geneXplain platform            Public Private Partnership The disadvantages of the public domain are advantages of a ...
The geneXplain platform            Public Private Partnership Advantages for the user      Standardized interface      ...
www.genexplain.comContact:Edgar Wingender            edgar.wingender@genexplain.com
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German Russian Workshop 2011 - geneXplain

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Towards a comprehensive computational platform for next generation drug development – A Russian‐German joint venture

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German Russian Workshop 2011 - geneXplain

  1. 1. Towards a comprehensivecomputational platform for nextgeneration drug development –A Russian‐German joint venture Edgar Wingender CEO Wolfenbüttel, Am Exer 10b GmbH http://www.genexplain.com
  2. 2. We aim to provide a comprehensive platform ofbioinformatics, systems biological and cheminformatics tools for a personalized medicine and pharmacogenomics
  3. 3. Some facts about geneXplain:  Founded in April 2010, starting active business July 2010  International (German-Russian) shareholder structure  Managing directors: E. Wingender (CEO), A. Kel (CSO)  Product portfolio in bioinformatics, systems biology, cheminformatics  Development close to science and research  Participation in international and national research consortia - SYSCOL (EU FP7) - GERONTOSHIELDS (BMBF)
  4. 4. proteinscompounds networks genes
  5. 5. Some facts about geneXplain:  Founded in April 2010, starting active business July 2010  International (German-Russian) shareholder structure  Managing directors: E. Wingender (CEO), A. Kel (CSO)  Product portfolio in bioinformatics, systems biology, cheminformatics  Close to science and research  Participation in international and national research consortia - SYSCOL (EU FP7) - GERONTOSHIELDS (BMBF) - TEMPUS (EU)
  6. 6. The idea:  Providing a platform of methods for  Biomedical research  Focus: drug development  Complete pipeline from high-throughput data to a lead structure  High-throughput data:  Genomics  Transkriptomics  Proteomics  Public private partnership
  7. 7. GeneXplainTM Platform: A Workflow for Drug Discovery The geneXplain platformTM is a new product integrating bio- and cheminformatics tools for pharmacogenomics. It provides a drug discovery workflow that guides from the statistical analysis of biological high-throughput data to a panel of potential lead compounds for further validation. Statistics Input: High-throughput data from patients (genomics, Within the geneXplain platformTM, transcriptomics, ChIP-seq, identification of drug target protein proteomics, etc.) molecules by bioinformatics and Output: List of relevant genes or systems biology methods, is proteins complemented by prediction of Any pre-processed list of biological activities and adverse genes or proteins from Bioinformatics effects for chemical compounds, own experiments, from Search for regulatory modules in any literature or databases based on multilevel neighborhoods genomic regions of atoms (MNA) descriptors. Output: List of transcription factors potentially responsible for the observed (co-)regulation of genes Any list of transcription factors; any list of genes or proteins from own experiments, from literature Systems BiologyThe workflow or databases to be mapped on Topological analysis of the networks known pathwaysThe incorporated statistical upstream of transcription factors,analyses help to identify relevant simulation of the network behavior,genes or proteins in the raw patient stratificationdata, e.g. those that are Hypotheses about gene regulators Output: List of potential master regulatorsdifferentially expressed. essential for theThe Bioinformatics block allows studied processto reveal potential regulation ofgenes by transcription factors ormiRNAs.Systems biology approachesanalyze networks of molecular Cheminformaticsevents and suggest promising Prediction of biological activities of the Hypotheses compounds, selection of compounds withdrug target molecules and their about targetmechanisms of action. required effects and without adverse or molecules andThe integrated PASS tool enables their role in the toxic effects.to direct compound screening by studied process Output: List of potential lead structurespre-selection of chemicals with Hypotheses for for validationdesirable and without adverse or validations and clinicaltoxic effects. trials Systematic generation of statistically significant hypotheses
  8. 8. Proof of concept: Net2Drug consortium EU FP6, Coordinator: A. Kel Transcriptomics breast cancer cell line Statistical evaluation Integrated bioinformatic analysis (promoter & pathway analysis) Systems biological simulation Cheminformatic identification of candidate drugs
  9. 9. Proof of concept: Net2Drug consortium EU FP6, Coordinator: A. Kel Transcriptomics breast cancer cell line Results: Statistical evaluation Out of 24 million compounds, 16 substances turned out to be feasibleIntegrated bioinformatic analysis for experimental testing. (promoter & pathway analysis) For 2 compounds, highly specific activities were found. Systems biological simulation Cheminformatic identification of candidate drugs
  10. 10. GeneXplainTM Platform: A Workflow for Drug Discovery The geneXplain platformTM is a new product integrating bio- and cheminformatics tools for pharmacogenomics. It provides a drug discovery workflow that guides from the statistical analysis of biological high-throughput data to a panel of potential lead compounds for further validation. Statistics Input: High-throughput data from patients (genomics, Within the geneXplain platformTM, transcriptomics, ChIP-seq, identification of drug target protein proteomics, etc.) molecules by bioinformatics and Output: List of relevant genes or systems biology methods, is proteins complemented by prediction of Any pre-processed list of biological activities and adverse genes or proteins from Bioinformatics effects for chemical compounds, own experiments, from Search for regulatory modules in any literature or databases based on multilevel neighborhoods genomic regions of atoms (MNA) descriptors. Output: List of transcription factors potentially responsible for the observed (co-)regulation of genes Any list of transcription factors; any list of genes or proteins from own experiments, from literature Systems BiologyThe workflow or databases to be mapped on Topological analysis of the networks known pathwaysThe incorporated statistical upstream of transcription factors,analyses help to identify relevant simulation of the network behavior,genes or proteins in the raw patient stratificationdata, e.g. those that are Hypotheses about gene regulators Output: List of potential master regulatorsdifferentially expressed. essential for theThe Bioinformatics block allows studied processto reveal potential regulation ofgenes by transcription factors ormiRNAs.Systems biology approachesanalyze networks of molecular Cheminformaticsevents and suggest promising Prediction of biological activities of the Hypotheses compounds, selection of compounds withdrug target molecules and their about targetmechanisms of action. required effects and without adverse or molecules andThe integrated PASS tool enables their role in the toxic effects.to direct compound screening by studied process Output: List of potential lead structurespre-selection of chemicals with Hypotheses for for validationdesirable and without adverse or validations and clinicaltoxic effects. trials Systematic generation of statistically significant hypotheses
  11. 11. The cheminformatics portfolio:  PASS predicts biological activities of chemical compounds from their structural formulae; assigns probability values to each activity and identifies those parts of the molecule that are responsible for this activitiy  PharmaExpert mines large amounts of predictions generated by PASS to filter out those compounds that optimaly fit user-defined requirements  GUSAR generates quantitative structure-activity relationship (QSAR) models
  12. 12. How to get there: GeneXplainTM Platform: A Workflow for Drug Discovery The geneXplain platformTM is a new product integrating bio- and cheminformatics tools for pharmacogenomics. It provides a drug discovery workflow that guides from the statistical analysis of biological high-throughput data to a panel of potential lead compounds for further validation. Statistics Input: High-throughput data from patients (genomics, Within the geneXplain platformTM, transcriptomics, ChIP-seq, identification of drug target protein proteomics, etc.) molecules by bioinformatics and Output: List of relevant genes or systems biology methods, is proteins complemented by prediction of Any pre-processed list of biological activities and adverse genes or proteins from Bioinformatics effects for chemical compounds, own experiments, from Search for regulatory modules in any literature or databases based on multilevel neighborhoods genomic regions of atoms (MNA) descriptors. Output: List of transcription factors potentially responsible for the observed (co-)regulation of genes Any list of transcription factors; any list of genes or proteins from own experiments, from literature Systems BiologyThe workflow or databases to be mapped on Topological analysis of the networks known pathwaysThe incorporated statistical upstream of transcription factors,analyses help to identify relevant simulation of the network behavior,genes or proteins in the raw patient stratificationdata, e.g. those that are Hypotheses about gene regulators Output: List of potential master regulatorsdifferentially expressed. essential for theThe Bioinformatics block allows studied processto reveal potential regulation ofgenes by transcription factors ormiRNAs.Systems biology approachesanalyze networks of molecular Cheminformaticsevents and suggest promising Prediction of biological activities of the Hypotheses compounds, selection of compounds withdrug target molecules and their about targetmechanisms of action. required effects and without adverse or molecules andThe integrated PASS tool enables their role in the toxic effects.to direct compound screening by studied process Output: List of potential lead structurespre-selection of chemicals with Hypotheses for for validationdesirable and without adverse or validations and clinicaltoxic effects. trials Systematic generation of statistically significant hypotheses
  13. 13. The way: The geneXplain platform  Integrated collection of bioinformatic and systems biological program modules („Bricks“)  Based on proven BioUML technology  Statistical analysis of high-throughput data  Integrated bioinformatic promoter- and network analysis  Systems biological simulation  Unified look-and-feel  Workflow management system  Pre-defined standard workflows  Easy integration of own tools and scripts
  14. 14. Upstream analysis of causes Key node
  15. 15. The way: The geneXplain platform  Integrated collection of bioinformatic and systems biological program modules („Bricks“)  Based on proven BioUML technology  Statistical analysis of high-throughput data  Integrated bioinformatic promoter- and network analysis  Systems biological simulation  Unified look-and-feel  Workflow management system  Pre-defined standard workflows  Easy integration of own tools and scripts
  16. 16. The geneXplain platform
  17. 17. The geneXplain platform
  18. 18. The geneXplain platform
  19. 19. The geneXplain platform Public Private Partnership Clash of cultures:  Cheminformatics: commercial approaches accepted  Bioinformatics: public domain prevalent (Internet culture) Advantages of public-domain services:  Latest state of the art  Visibility („marketing“ through publications, conference talks, etc.)  High acceptance Disadvantages of public-domain services:  No unified look-and-feel  Low user-friendliness  Poor support  Uncertainty on side of users without expertise  Unsure long-term perspective
  20. 20. The geneXplain platform Public Private Partnership The disadvantages of the public domain are advantages of a commercial offer Optimal: combination of free and commercial tools Business model:  Platform with integrated free and proprietary offerings  Payable access  Payable support
  21. 21. The geneXplain platform Public Private Partnership Advantages for the user  Standardized interface  Integrated workflows  Default parametrizations byexperts  Selection of free modules by experts in the field  Selection of proprietary, uszually low-price modules by the user  Full cost-control by the user
  22. 22. www.genexplain.comContact:Edgar Wingender edgar.wingender@genexplain.com

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