Acellera

Acellera

Barcelona, Spain· Est.
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Private Company

Total funding raised: $29M

Overview

Acellera's mission is to transform drug discovery into a high-accuracy, computable task by developing algorithms that automate the process. Founded in 2016, the company has built a robust technology stack, including the QuantumBind® platform and open-source tools like ACEMD, OpenMM, and ACEGEN, backed by over 18 years of computational know-how and thousands of academic citations. While currently a private company with no external investment, Acellera is developing an internal pipeline of drug candidates and plans to raise funding in 2026 to scale its ambitious goals.

OncologyImmunologyInflammatory DiseasesInfectious DiseasesNeurology

Technology Platform

QuantumBind® is an integrated platform combining generative AI chemistry, neural network potentials trained on quantum mechanics data, and active learning to accelerate small-molecule discovery and potency optimization with quantum-level accuracy.

Funding History

5
Total raised:$29M
Series B$15M
Series A$8M
Series A$3M
Seed$2.5M

Opportunities

The primary growth opportunity lies in successfully commercializing the QuantumBind® platform through enterprise partnerships with pharmaceutical companies, leveraging its unique AI/quantum chemistry blend.
Additionally, advancing its internal pipeline of kinase inhibitors and other targets into later-stage development could create significant asset value for out-licensing or partnership deals, particularly in oncology and immunology.

Risk Factors

Key risks include reliance on a future funding round in 2026, the high technical and biological risk of translating its computational pipeline into successful clinical candidates, and intense competition in the AI drug discovery sector from larger, well-capitalized players.

Competitive Landscape

Acellera competes with AI-driven drug discovery companies like Exscientia, Recursion, and Schrödinger. Its differentiation stems from a strong foundation in physics-based simulation (ACEMD, OpenMM) and quantum chemistry, combined with AI, aiming for higher predictive accuracy. Its open-source contributions and dual platform/pipeline model also set it apart.