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AQEMIA Tech Stack

AI-driven drug discovery platform combining physics simulations with generative models

Biotechnology Research Paris, Île-de-France 51–200 employees Founded 2019 Privately Held

AQEMIA applies physics-based ML to drug discovery, moving beyond traditional screening and experimental dependency. The tech stack is lean but production-grade—Python, Kubernetes, ArgoCD, Terraform—reflecting a computational-first, DevOps-mature organization. Active pain points (scaling scientific teams, integrating physics simulations, accelerating discovery timelines) and a research-heavy hiring mix (5 research roles, 1 data, 2 engineers) signal a company pivoting from proof-of-concept toward operational scale: lead programs in in vivo optimization, a focus on program governance, and deliberate effort to double active programs and the program-management team.

Tech Stack 11 technologies

Core StackPython GitHub Actions ArgoCD Terraform Docker Kubernetes AWS GitHub Bash Terragrunt LinkedIn

What AQEMIA Is Building

◆Challenges

Scaling scientific teams
Accelerating drug discovery
Doubling number of programmes
Scaling program management team
Resource allocation challenges
Reducing time to discovery
Accelerating tool development
Integrating physics-based simulations
Doubling active programs
Reliability and availability

▲Active Projects

Lead optimization
Structure-based ai generative models
Physics-based calculations integration into generative ml workflow
Hit generation
Virtual screening and hit optimisation
Benefits administration
In vivo optimization program
Program governance methodology
Program assessment & governance
Translate computational chemistry research into real-world impact

Hiring Activity

Steady15 roles · 5 in 30d

Department

Research

5

Engineering

2

HR

2

Data

1

Finance

1

Ops

1

Seniority

Senior

4

Manager

3

Principal

3

Lead

1

VP

1

Notable leadership hires: Program Lead

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About AQEMIA

AQEMIA is a drug-discovery platform company founded in 2019, based in Paris with a London office, operating across France and the UK. The platform combines quantum-inspired physics calculations with generative AI to design novel drug candidates without reliance on large experimental datasets—a computational alternative to traditional high-throughput screening. The company operates its own proprietary programs (with lead candidates in in vivo optimization) and collaborates with pharmaceutical partners. The portfolio includes work on oncology and other major disease areas. The organization is 51–200 people, recently added to the French Tech 120 cohort and active in both the BioIndustry Association and Knowledge Quarter networks.

HeadquartersParis, Île-de-France

Company Size51–200 employees

Founded2019

Hiring MarketsFrance, United Kingdom

Frequently Asked Questions

What tech stack does AQEMIA use?

Python, Docker, Kubernetes, ArgoCD, AWS, Terraform, and GitHub Actions—core infrastructure for computational chemistry and ML model deployment.

What is AQEMIA working on?

Lead program optimization, structure-based generative AI models, physics-based simulation integration into ML workflows, virtual screening, hit generation, and in vivo optimization. Also scaling program governance and management infrastructure.