San Francisco, California, United States
Gen AI molecular simulations that reproduce wetlab results
- Revenue
- $900K
- Year founded
- 2024
- Team size
- 6
As of November 2026, Latka tracks 5 drug discovery software companies under $1M in annual revenue. They have combined revenues of $2.5M and employ 23 people.
Every company below sells drug discovery software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
Drug Discovery Software encompasses a range of tools and applications that aid in the development of new pharmaceuticals. These solutions streamline the research process by enabling researchers to design, analyze, and optimize drug candidates more efficiently. Common use cases include target identification, lead optimization, and preclinical trials, wherein software facilitates simulations and predictions that guide decision-making during the drug discovery pipeline. Typically, drug discovery software features include molecular modeling, compound library management, virtual screening, and data analysis capabilities. Users of this software include pharmaceutical companies, biotech firms, and academic institutions focused on drug development. By automating complex processes, these tools help researchers reduce costs and timeframes associated with bringing new medicines to market.
Sorting: Highest -> Lowest
Showing 5 of 5 companies ranked by annual revenue.
San Francisco, California, United States
Gen AI molecular simulations that reproduce wetlab results
Copenhagen, Denmark
We hate overly complex software. So we built grit42 grit42 was created to serve drug discovery labs that don’t want to get lost in the corners of an enterprise data platform, but do want to find a better way to manage data and compounds than keeping track of endless versions of spreadsheets. Our scientific data management platform is free and open source, and we offer a range of point solutions for research labs built on top of that. The founding partners of grit42 have spent a combined 60+ years managing data, compounds, and test animals at large pharma companies. So we get where you’re coming from, and where you want to go. And with grit42, we want to help you get there faster and easier.
Glendale, California, United States
We are a research-driven startup building the next generation of AI4Science models that simulate molecular interactions at the quantum level to supercharge drug discovery. Our thesis is that the failure of existing molecular dynamics to accurately predict binding affinities to ligands is entirely driven by the failure to simulate quantum dynamics rather than the choice of AI architecture. We are building on top of our research & our models don't make mistakes. We are an early-stage & well-funded startup. Join the revolution in AI4Science!
Barcelona, Spain
Developer of software created for computational drug discovery. The company's software uses big data, artificial intelligence and machine lLearning technologies as well as offers a versatile set of programs and applications, enabling biotechnology, pharmaceutical companies and research centers to get access to scalable and affordable in silico drug discovery to accelerate the development of new drugs.
Latka tracks 5 drug discovery software companies under $1M in annual revenue. Together they generate $2.5M in annual revenue and employ 23 people.
Ångström AI is the largest, with $900K in annual revenue, founded in 2024.
The average drug discovery software company in this list makes $499.8K a year, across 5 companies with reported revenue.
Ranked by annual revenue, the leaders are Ångström AI, grit42, Tamarind Bio, Simulacra AI and Mind the Byte.
- Offers tools for molecular modeling and simulations - Supports data analysis related to drug interactions and efficacy - Aids in target identification and validation in the drug discovery process - Includes features for library management of drug compounds - Must facilitate preclinical trial planning and analysis - Not just general research software; must specifically cater to drug discovery workflows