Bioinformatics: Proprietary Drug / Disease Targeting Tool
InMed's has developed a computer-based program to assist in the identification of novel cannabinoids using: (i) comprehensive algorithms to integrate data from numerous bioinformatics databases, (ii) a database on the structure of currently approved pharmaceutical products, and (iii) an extensive database on over 90 individual cannabinoid drugs found in cannabis.
- InMed's data included in its bioinformatics assessment tool are derived from both public and propriety based sources, and include information on:
- Protein-Protein interactions
- Gene Regulation
- Epigenetic modification
- Cell signal networks, and
- InMed uses processes called "random walk algorithms" and "guilt by association" to establish gene and protein-protein interaction networks to identify multi-target based approaches for therapy development for specific diseases.
- By using its comprehensive pharmaceutical and cannabinoid structures database, and by creating associations between approved pharmaceuticals (whose pharmacodynamics effects are well characterized) and cannabinoids with similar structures, InMed identifies active cannabinoids to act on above mentioned genes and proteins.
- Once a series of potentially active cannabinoids are identified for a specific disease target, InMed will test and confirm their activity in biological systems with in vitro and in vivo experimentation.
- This type of bioinformatics assessment, as a general approach, represents significant promise for future drug discovery, as it integrates many data sets and builds holistic models to approach a specific disease.
Bioinformatics / R&D
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