About Misogi Labs

Misogi Labs utilizes a physics-infused AI engine to predict ADME/PK properties of small molecules, enabling drug researchers to optimize molecular candidates efficiently. By minimizing experimental failures and reducing the need for animal testing, the platform accelerates the transition from molecule to high-quality clinical candidates.

```xml <problem> Drug discovery is often hampered by late-stage failures due to unfavorable Absorption, Distribution, Metabolism, and Excretion/Pharmacokinetic (ADME/PK) properties of small molecule candidates. Traditional methods for assessing these properties rely heavily on experimental testing, including animal studies, which are time-consuming, expensive, and may not accurately predict human responses. </problem> <solution> Misogi Labs offers an AI-driven platform that predicts ADME/PK properties of small molecules using a physics-infused AI engine. This platform enables researchers to virtually test and optimize molecular candidates early in the drug discovery process, reducing the reliance on experimental methods and animal testing. By integrating with physiological models, the AI-drug hunter predicts pharmacokinetic profiles in humans. The platform acts as a strategic coordinator, bringing together insights from medicinal chemists, pharmacologists, and computational scientists to guide multi-parameter optimization. </solution> <features> - Physics-infused AI engine for predicting ADME/PK properties. - Miso-5D: A large model pre-trained on multi-modal, physics-driven data, including 4D molecular conformations and quantum mechanical (QM) properties. - Generative AI to design new experiments and guide molecular optimization. - Seamless integration through an intuitive interface, providing access to real-time predictions and goal-directed molecular editing. - Integration with physiological models to predict pharmacokinetic profiles in humans. </features> <target_audience> The primary target audience includes pharmaceutical R&D teams, medicinal chemists, pharmacologists, and computational scientists involved in small molecule drug discovery and optimization. </target_audience> ```

What does Misogi Labs do?

Where is Misogi Labs located?

Misogi Labs is based in San Francisco, United States.

When was Misogi Labs founded?

Misogi Labs was founded in 2024.

Location

San Francisco, United States

Founded

2024

Employees

3 employees

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Misogi Labs

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Executive Summary

misogilabs.com 100+

Founded 2024 – San Francisco, United States

Funding

No funding information available.

Team (<5)

No team information available.

Company Description

Problem

Drug discovery is often hampered by late-stage failures due to unfavorable Absorption, Distribution, Metabolism, and Excretion/Pharmacokinetic (ADME/PK) properties of small molecule candidates. Traditional methods for assessing these properties rely heavily on experimental testing, including animal studies, which are time-consuming, expensive, and may not accurately predict human responses.

Solution

Misogi Labs offers an AI-driven platform that predicts ADME/PK properties of small molecules using a physics-infused AI engine. This platform enables researchers to virtually test and optimize molecular candidates early in the drug discovery process, reducing the reliance on experimental methods and animal testing. By integrating with physiological models, the AI-drug hunter predicts pharmacokinetic profiles in humans. The platform acts as a strategic coordinator, bringing together insights from medicinal chemists, pharmacologists, and computational scientists to guide multi-parameter optimization.

Features

Physics-infused AI engine for predicting ADME/PK properties.

Miso-5D: A large model pre-trained on multi-modal, physics-driven data, including 4D molecular conformations and quantum mechanical (QM) properties.

Generative AI to design new experiments and guide molecular optimization.

Seamless integration through an intuitive interface, providing access to real-time predictions and goal-directed molecular editing.

Integration with physiological models to predict pharmacokinetic profiles in humans.

Target Audience

The primary target audience includes pharmaceutical R&D teams, medicinal chemists, pharmacologists, and computational scientists involved in small molecule drug discovery and optimization.