Immunocure Discovery Solutions

About Immunocure Discovery Solutions

Immunocure utilizes its AxDrug platform, which combines generative AI with computational chemistry, to identify and optimize lead drug candidates from a database of 20 billion drug-like small molecules. This approach addresses the inefficiencies in traditional drug discovery processes by significantly reducing research and development costs and timelines for clients.

<problem> Traditional drug discovery methods are often inefficient, costly, and time-consuming, hindering the rapid development of effective therapeutics. Identifying promising drug candidates from vast chemical spaces and optimizing their properties for efficacy and safety presents a significant challenge. </problem> <solution> Immunocure addresses these challenges with AxDrug, an AI-powered drug discovery platform that integrates generative AI and computational chemistry to accelerate the identification and optimization of lead drug candidates. AxDrug leverages a database of 20 billion drug-like small molecules, combined with deep learning and machine learning models, to navigate the complexities of target validation, hit identification, hit-to-lead, and lead optimization. The platform's ChemBio-SAR module employs predictive models to identify druggable pockets, generate molecules, and validate drug-likeness and selectivity. AxDrug's DrugX tool integrates AI with physics-based methods for protein modeling, rapid screening, accurate docking, and molecular dynamic simulations, enabling the discovery of pioneering molecules, including those for challenging and intricate targets like intrinsically disordered proteins. </solution> <features> - Expansive Chemical Space (ECS) comprising 20 billion synthetically feasible, drug-like molecules, enhanced by generative chemistry algorithms - ChemBio-SAR module with deep learning and machine learning models for target validation, hit identification, and lead optimization - AI-enabled ADMET models for predicting absorption, distribution, metabolism, excretion, and toxicity properties - DrugX tool integrating AI with physics-based methods for protein modeling and druggability validation - Rapid virtual screening of the ECS, capable of screening 1 billion compounds per week - Molecular dynamic simulations (MDS) and free energy perturbations (FEP) for detailed insights into molecular complex dynamics and binding affinity - Knowledge hypergraphs linking chemotypes to targets, diseases, pathways, and toxicities - Capabilities for identifying druggable allosteric pockets and cryptic pockets within flexible proteins </features> <target_audience> Immunocure's primary customers are pharmaceutical and biotechnology companies, as well as research institutions, seeking to accelerate their drug discovery programs and reduce R&D costs. </target_audience>

What does Immunocure Discovery Solutions do?

Immunocure utilizes its AxDrug platform, which combines generative AI with computational chemistry, to identify and optimize lead drug candidates from a database of 20 billion drug-like small molecules. This approach addresses the inefficiencies in traditional drug discovery processes by significantly reducing research and development costs and timelines for clients.

Where is Immunocure Discovery Solutions located?

Immunocure Discovery Solutions is based in Brooklyn, United States.

When was Immunocure Discovery Solutions founded?

Immunocure Discovery Solutions was founded in 2019.

How much funding has Immunocure Discovery Solutions raised?

Immunocure Discovery Solutions has raised $3.0M.

Who founded Immunocure Discovery Solutions?

Immunocure Discovery Solutions was founded by Kranthi Raj K and Ravi Muttineni.

  • Kranthi Raj K - Co-Founder
  • Ravi Muttineni - Founder & CSO
Location
Brooklyn, United States
Founded
2019
Funding
$3.0M
Employees
28 employees
ID

Immunocure Discovery Solutions

Immunocure utilizes its AxDrug platform, which combines generative AI with computational chemistry, to identify and optimize lead drug candidates from a database of 20 billion drug-like small molecules. This approach addresses the inefficiencies in traditional drug discovery processes by significantly reducing research and development costs and timelines for clients.

Brooklyn, United StatesFounded 2019281K+ followers7/10 TractionRelative Traction Score based on online presence metrics compared to companies in the same age group.
Updated 3 months ago

Funding

$3.0M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Traditional drug discovery methods are often inefficient, costly, and time-consuming, hindering the rapid development of effective therapeutics. Identifying promising drug candidates from vast chemical spaces and optimizing their properties for efficacy and safety presents a significant challenge.

Solution

Immunocure addresses these challenges with AxDrug, an AI-powered drug discovery platform that integrates generative AI and computational chemistry to accelerate the identification and optimization of lead drug candidates. AxDrug leverages a database of 20 billion drug-like small molecules, combined with deep learning and machine learning models, to navigate the complexities of target validation, hit identification, hit-to-lead, and lead optimization. The platform's ChemBio-SAR module employs predictive models to identify druggable pockets, generate molecules, and validate drug-likeness and selectivity. AxDrug's DrugX tool integrates AI with physics-based methods for protein modeling, rapid screening, accurate docking, and molecular dynamic simulations, enabling the discovery of pioneering molecules, including those for challenging and intricate targets like intrinsically disordered proteins.

Target Audience

Immunocure's primary customers are pharmaceutical and biotechnology companies, as well as research institutions, seeking to accelerate their drug discovery programs and reduce R&D costs.

Features

  • Expansive Chemical Space (ECS) comprising 20 billion synthetically feasible, drug-like molecules, enhanced by generative chemistry algorithms
  • ChemBio-SAR module with deep learning and machine learning models for target validation, hit identification, and lead optimization
  • AI-enabled ADMET models for predicting absorption, distribution, metabolism, excretion, and toxicity properties
  • DrugX tool integrating AI with physics-based methods for protein modeling and druggability validation
  • Rapid virtual screening of the ECS, capable of screening 1 billion compounds per week
  • Molecular dynamic simulations (MDS) and free energy perturbations (FEP) for detailed insights into molecular complex dynamics and binding affinity
  • Knowledge hypergraphs linking chemotypes to targets, diseases, pathways, and toxicities
  • Capabilities for identifying druggable allosteric pockets and cryptic pockets within flexible proteins
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