PhAsIca Biosciences is building a physics-driven AI platform to make biomolecular condensates therapeutically tractable — opening access to cancer biology that conventional drug discovery struggles to reach.
Biomolecular condensates organise processes such as transcription, DNA repair, signalling and treatment resistance. Their dynamic, multicomponent nature makes them difficult to address with conventional approaches.
To identify, prioritise and modulate condensate-forming proteins and intrinsically disordered regions involved in tumour initiation, progression, immune escape and treatment resistance — enabling first-in-class therapies for cancers that remain beyond conventional drug discovery.
To turn biomolecular condensates from an “undruggable” layer of cancer biology into a predictable and actionable therapeutic frontier, using quantitative physics, artificial intelligence and experimental validation.
The platform models biomolecular condensates as integrated molecular systems rather than isolated proteins. It combines multiscale physics-based simulations, AI, bioinformatics and multi-omics to identify actionable interaction hotspots and rationally design therapeutic modulators.
Its proprietary layer integrates cancer-specific workflows, AI models trained on internal data, multi-omics prioritisation, modulator-design algorithms and an experimental validation cascade.
Multi-omics, AI and physics identify condensate-forming proteins driving cancer biology.
Multiscale simulations reveal the interaction network sustaining each condensate.
High-contact regions are computationally prioritised as therapeutic intervention points.
Physics- and AI-guided algorithms design peptides, small molecules and biologics.
Modulators disrupt or restructure pathogenic condensates, followed by experimental validation.
