RECEPTOR.AI

The AI engine Fit Assessment

Beta

Receptor.AI leverages machine learning and AI technologies to discover new drug candidates and expand therapeutics, optimizing the drug discovery process.

Blurb

RECEPTOR.AI - AI-accelerated drug discovery

HQ Location

London (United Kingdom)

Founded

2021

Employees

11 - 50

Total funding raised

$11.79M

Last Funding Event

Undisclosed, $11.29M, November 13, 2024

Smart insights

  • Catherine Msc (Chief People Officer) worked at Lilium as Head of People Business Partnering for 1.5 years (2021 - 2022)
  • Val Miftakhov (Founder & CEO) worked at Google in various roles, including Head of R&D, Google for Work Incubation, for a total of 4 years (2012 - 2016)
  • 6m headcount growth: 25%
  • 1Y headcount growth: 94%
  • Headcount-to-last-round ratio: 5.3 employees/$M
Subspaces
  • Drug Discovery Optimization

Receptor.AI is a TechBio company developing generative AI techniques to design first-in-class therapeutics. Its multi-platform ecosystem is built to address challenging protein targets using a multimodal approach, allowing for the design of oral compounds with optimal biological activity and bioavailability. Peptides Platform: AI-guided de novo design and optimization of linear and cyclic peptides against challenging targets, including “undruggable” protein-protein interactions. Small molecule Platform: De novo AI-driven design of small molecules by leveraging key interactions related to biological activity with multiparametric optimization of over 80 drug properties. Induced Proximity Platform Engineering ternary complexes to transform structurally unresolved native and induced PPIs into druggable targets. Multilevel AI-driven Drug Discovery Infrastructure: Our drug discovery infrastructure consists of four hierarchical levels that facilitate seamless AI-driven preclinical drug discovery pipeline. Advanced data acquisition, generation and augmentation backs up state-of-the-art predictive and generative AI models for all major drug discovery tasks. These models empower dedicated workflows for different drug modalities and target classes. The whole discovery process is supervised and orchestrated by LLM agents that blend together human expertise and artificial intelligence.