deepMirror Ltd

deepMirror Ltd

AI-driven drug discovery platform enhancing R&D efficiency and security for biopharma teams.

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DateInvestorsAmountRound
-investor investor

€0.0

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N/A

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investor

€0.0

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$2.4m

Seed
Total Funding000k

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Revenues, earnings & profits over time
USD20222023
Revenues00000000
% growth-33 %
EBITDA00000000
Profit00000000
EV00000000
EV / revenue00.0x00.0x
EV / EBITDA00.0x00.0x
R&D budget00000000

Source: Dealroom estimates

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More about deepMirror Ltd
Made with AI
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DeepMirror.ai is a cutting-edge startup that operates in the pharmaceutical and biotech industry, leveraging artificial intelligence (AI) to accelerate the drug discovery process. The company offers a user-friendly app that employs generative and predictive AI to help clients design new molecules and predict their activity, DMPK (Drug Metabolism and Pharmacokinetics), and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties. This innovative approach allows clients to identify potential lead candidates up to 50% faster, potentially saving millions in research and development costs.

DeepMirror's primary clients are medicinal chemists and pharmaceutical companies. The platform's AI adapts to data from as few as 30 compounds, making it a versatile tool for drug discovery. It ranks synthesizable molecules based on predicted parameters, helping researchers find the most promising compounds more quickly and efficiently.

The company operates on a pay-to-use model. Clients pay to use the app, and in return, they retain full ownership of any data they upload or generate. All data is stored securely in a private cloud, encrypted, and only accessible by the client and their team, ensuring the highest level of data security and intellectual property protection.

In summary, DeepMirror.ai is a promising startup that uses AI to streamline the drug discovery process, serving medicinal chemists and pharmaceutical companies. Its business model is based on a pay-to-use app, with a strong emphasis on data security and client ownership of data.

Keywords: Artificial Intelligence, Drug Discovery, Medicinal Chemistry, DMPK, ADMET, Data Security, Intellectual Property, Pay-to-Use Model, Pharmaceutical Industry, Biotech Industry.

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