About EVQLV

The startup develops antibody design platforms that utilize computational methods and large datasets to enhance the discovery and optimization of therapeutic antibodies. By enabling researchers and pharmaceutical companies to identify new candidates and refine existing ones, the platform accelerates the development of antibody-based treatments.

```xml <problem> Traditional antibody discovery and optimization methods are often slow, expensive, and failure-prone, requiring extensive iterative cycles of lab work and guesswork. Identifying antibodies against challenging therapeutic targets can be particularly difficult, consuming significant resources without guaranteeing success. </problem> <solution> EVQLV provides a computational antibody design platform that leverages machine learning, computational biology, and large datasets to accelerate and enhance the discovery and optimization of therapeutic antibodies. The platform uses in silico design and a Prescreened Human-Antibody Synthetic Intelligent Compendium (PHASIC) to generate diverse, fully-human antibodies without needing an antigen’s crystal structure. By calculating biophysical and machine-learned features, EVQLV creates digital signatures of antibodies, optimizing them for properties like affinity, immunogenicity, and stability. This approach reduces the need for extensive lab iterations, saving time and resources while increasing the likelihood of identifying viable therapeutic candidates. </solution> <features> - In silico antibody design and de novo antibody discovery - Prescreened Human-Antibody Synthetic Intelligent Compendium (PHASIC) for generating target-specific display antibodies - Antibody optimization for developability, including affinity, immunogenicity, and aggregation - Antibody structure prediction algorithm - Ability to work with any antibody format (e.g. scFv, nanobodies, bispecific antibodies, ADCs, AACs, AOCs, etc.) - Epitope prediction capabilities </features> <target_audience> The primary customers are researchers and pharmaceutical companies involved in antibody-based drug discovery and development, including those working on challenging therapeutic targets or seeking to optimize existing antibody candidates. </target_audience> ```

What does EVQLV do?

Where is EVQLV located?

EVQLV is based in Surfside, United States.

When was EVQLV founded?

EVQLV was founded in 2019.

How much funding has EVQLV raised?

EVQLV has raised 60000.

Location

Surfside, United States

Founded

2019

Funding

60000

Employees

8 employees

Major Investors

Techstars, Endeavor Miami, Space Florida, Bantam Group, Sidecar Angels

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EVQLV

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Executive Summary

evqlv.com 1K+

Crunchbase

Founded 2019 – Surfside, United States

Funding

Estimated Funding

Major Investors

Techstars, Endeavor Miami, Space Florida, Bantam Group, Sidecar Angels

Team (5+)

No team information available.

Company Description

Problem

Traditional antibody discovery and optimization methods are often slow, expensive, and failure-prone, requiring extensive iterative cycles of lab work and guesswork. Identifying antibodies against challenging therapeutic targets can be particularly difficult, consuming significant resources without guaranteeing success.

Solution

EVQLV provides a computational antibody design platform that leverages machine learning, computational biology, and large datasets to accelerate and enhance the discovery and optimization of therapeutic antibodies. The platform uses in silico design and a Prescreened Human-Antibody Synthetic Intelligent Compendium (PHASIC) to generate diverse, fully-human antibodies without needing an antigen’s crystal structure. By calculating biophysical and machine-learned features, EVQLV creates digital signatures of antibodies, optimizing them for properties like affinity, immunogenicity, and stability. This approach reduces the need for extensive lab iterations, saving time and resources while increasing the likelihood of identifying viable therapeutic candidates.

Features

In silico antibody design and de novo antibody discovery

Prescreened Human-Antibody Synthetic Intelligent Compendium (PHASIC) for generating target-specific display antibodies

Antibody optimization for developability, including affinity, immunogenicity, and aggregation

Antibody structure prediction algorithm

Ability to work with any antibody format (e.g. scFv, nanobodies, bispecific antibodies, ADCs, AACs, AOCs, etc.)

Epitope prediction capabilities

Target Audience

The primary customers are researchers and pharmaceutical companies involved in antibody-based drug discovery and development, including those working on challenging therapeutic targets or seeking to optimize existing antibody candidates.