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181 Startups in AI Drug Discovery

04.01.2021
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Özet

Artificial Intelligent and other complementary technologies are expected to make the discovery of new pharmaceuticals quicker, cheaper, and more effective.

We analyzed artificial intelligence startups impacting drug discovery

For this research, we identified 181 relevant solutions and analyze their patent and market activities.

Cytoreason and Pharnext are only the two of them.

Cytoreason , Israel

Israel-based startup CytoReason analyzes multi-omic, human clinical data to offer data-driven target discovery. The startup’s platform uses vast amounts of proprietary and public data to understand the complex systems of interactions inside cells. The solution uses machine learning algorithms and continual statistical learning to uncover disease-related cell/gene maps. The platform supports research and development (R&D) efforts across the drug development cycle.

Uses AI to: Organize and standardize immune-related gene, protein, cell, and microbiome data into a single, machine-readable, cell-level view of the immune-system.

Cytoreason allows researchers to gain novel insights related to mechanisms of disease, clinical markers, and drug discovery and validation.

Standigm 

South Korean startup Standigm offers novel drug design solutions. Standigm BEST explores an AI-generated latent chemical space to generate novel compounds with desired properties. Once the candidates have been identified, Standigm Insights provides biological interpretations to discover pathways and therapeutics patterns and prioritize potential targets. The startup’s solutions eliminate the uncertainty in the drug discovery process to save time and costs during development.

Uses AI to: Analyze biomedical data to predict how drug compounds would interact with people in the real world.

Standigm allows researchers to generate novel compounds satisfying desired properties and discover hidden indications and pathways

Get most from our interactive reports. Access and analyze up-to-date patent, startup, investment, and market data.

This figure shows the leading ten organizations in the subject technology field. Organization with the largest portfolio is on the top.
 

The Innovation Rate graph shows the annual patenting trend in the technology field.

This graph shows the origin of invested organizations.
 
 

This graph shows the number of investments in the last 10 years period.

The territory map shows the breakdown of patents across jurisdictions on the subject technology field. The territory map is useful visual tool that shows key markets where patent applicants on the subject technology field focus on.

The graph shows the technology areas by their IPC codes on the left X-axis. Y-axis corresponds to the period of search. This visualization shows the yearly patenting trends in the subject technology field by year. In an emerging technology area, the number of activity will grow over the years. Conversely, a declining technology area will show less patenting activity over the years.  

Analyze the technology focus of the selected organizations. Visual shows the presence of the organizations in different technology fields. It helps you to understand where organizations invest to build their portfolio.

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*Illustration by Michele Marconi