AI Discovery
Generate and prioritize novel molecules across vast chemical spaces.
MEXIMIA combines artificial intelligence, computational chemistry and quantum technologies to discover novel therapeutics for psychiatric and neurological diseases.
Despite decades of research, developing new treatments for psychiatric and neurological diseases remains slow, expensive and highly uncertain.
Traditional drug discovery struggles to model the complex molecular interactions involved in CNS diseases. MEXIMIA is building a new computational approach.
An integrated framework designed to navigate chemical possibility, model molecular behavior, and prioritize the most promising paths forward.
Generate and prioritize novel molecules across vast chemical spaces.
Model how candidate compounds interact with biological targets.
Develop and scientifically benchmark hybrid quantum-classical methods to improve molecular simulations.
From biological target to optimized molecule, MEXIMIA integrates computational models to reduce the number of compounds that need to be experimentally tested.
MEXIMIA initially focuses on psychiatric and neurological disorders where better molecular understanding and new therapeutic approaches are urgently needed.
Psychiatry
Neurodegeneration
Neuroinflammation
Novel CNS targets
MEXIMIA is building a capital-efficient biotech platform combining collaborative discovery programs with proprietary therapeutic assets.
Explore a partnershipCollaborative drug-discovery programs using the MEXIMIA platform.
Internally generated molecules developed toward licensing and strategic partnerships.
PhD in Quantum Computing
Quantum technology and computational science
MD, PhD — Psychiatry
Clinical neuroscience and translational medicine
MD — Radiology
Healthcare entrepreneurship and business development
Our mission is to build the computational infrastructure that helps turn previously inaccessible biological questions into new medicines.
We are looking to collaborate with scientists, biotech companies, pharmaceutical partners and research institutions.