Skip to content

Atommap

3 viewers · 30d

Total raised

$31.1M

+$31.1M this year

1 filing since 2026 · latest Equity filed

Cumulative raised
LAST ROUND
Equity · $31.1M
ROUNDS
1
INVESTORS
29
FOUNDED
2023
HQ
New York, NY
SECTOR
Biotech
EMPLOYEES
N/A
30D VIEWERS
3

AI overview

Updated

Atommap Corp, which rebranded as Fathom Therapeutics in April 2026, is a New York-based drug design company using quantum chemistry and AI to model protein behavior at atomic resolution. Its Microcosmos engine simulates protein motion and protein-ligand interactions to generate the dynamic structural data needed to design small molecules against targets conventionally considered undruggable. The company runs internal discovery programs alongside partnered discovery collaborations, and maintains a second office in Boston. It was founded in 2023 by CEO Huafeng Xu with CTO Yujie Wu and Chief Computational Scientist Jesus Izaguirre.

What sets it apart

Proprietary simulation algorithms that accelerate atomic-resolution modeling of protein dynamics by roughly 10,000x without sacrificing accuracy, letting the team design molecules that modulate protein behavior rather than only bind static structures -- in one reported case producing potent degrader candidates against an undruggable target in six weeks.

Funding history

1 round
Equity+1Mar 6, 2026
Form D
+$31.1M$31.1M total

Latest SEC filings

via EDGAR · CIK 0002001012
Form D · Mar 6, 2026View on EDGAR

Products

1 tracked

Microcosmos

Computational drug design platform

A drug design engine that uses proprietary algorithms and quantum-chemistry-informed simulation, combined with AI, to model protein motion and protein-ligand interaction at atomic resolution. The dynamic behavior data it produces is used to design small molecules with differentiated therapeutic effects and reduced off-target risk.

  • Atomic-resolution simulation of protein motion and protein-ligand interactions
  • Roughly 10,000x acceleration of protein-dynamics modeling without loss of accuracy
  • Quantum chemistry combined with AI-based molecular design
  • Lab-in-the-loop experimental feedback into the design cycle