Mechanism & Molecular Understanding
- Mechanism-of-action investigation
- Molecular interaction mapping
- Conformational and molecular dynamics
- Contact-network analysis
- Mechanistic hypothesis generation
- Computational–experimental validation strategies
PhAsIca Biosciences
Physics and AI for the next generation of molecular discovery
We combine predictive physics, artificial intelligence and multiscale molecular modelling to reveal how complex biological systems behave — and turn that understanding into better therapeutic and molecular design.
PhAsIca Biosciences is a computational biosciences company developing an advanced physics-based and AI-enabled discovery engine. Our technology connects molecular behaviour across scales — from individual molecular interactions to complex biological systems — helping us identify new targets, understand mechanisms and rationally design and optimise therapeutic candidates.
Predict.Design.Translate.
Our Technology
From molecular complexity to actionable predictions
Biological systems are dynamic, multicomponent and highly interconnected. Understanding them requires more than static structures or empirical screening.
PhAsIca combines advanced computational physics with artificial intelligence to model molecular behaviour across multiple spatial and temporal scales.
AI & Target Discovery
- AI-driven target identification and prioritisation
- Multi-omics and functional-data integration
- Target tractability assessment
- Virtual screening and candidate ranking
- Structure–activity relationship analysis
- Molecular optimisation
Advanced Molecular Modelling
- Atomistic molecular simulation
- Coarse-grained and multiscale molecular dynamics
- Molecular docking and binding analysis
- Free-energy calculations
- Protein and protein–nucleic-acid modelling
- Membrane and multicomponent system modelling
- Solubility, molecular compatibility and viscosity prediction
Biologics
- Antibody–target interaction modelling
- Antibody optimisation
- ADC optimisation
- Aggregation prediction
- Conjugation-site and linker analysis
- Molecular compatibility and developability assessment
Therapeutic Discovery
Applying computational intelligence to difficult cancer biology
PhAsIca is applying its technology to oncology programmes where conventional discovery approaches remain limited.
Our internal pipeline combines target discovery, mechanistic modelling and rational molecular design across multiple therapeutic modalities.
DNA Damage Response & Synthetic Lethality
We are developing a multimodal precision-oncology programme in DNA damage response and synthetic lethality, integrating complementary therapeutic mechanisms against the same disease biology.
Our approach combines molecular modelling, AI-guided design and experimental validation to explore strategies aimed at improving efficacy and increasing the barrier to therapeutic resistance.
New Oncology Targets
Our discovery engine has also identified previously unexplored therapeutic targets across major cancer indications.
These programmes originate computationally and progress through a staged validation process from molecular prediction to experimental testing.
Biologics
Phasica’s technology extends beyond small molecules and peptides to complex biologic therapeutics.
Our biologics work provides independent validation of the computational design capabilities underlying the platform, with one programme already progressing through in vivo evaluation and additional biologics undergoing cellular validation.
Together, these programmes demonstrate our ability to move from computational prediction to experimentally actionable therapeutic candidates.
Beyond Our Internal Pipeline
Computational innovation across the life sciences
The computational capabilities developed at PhAsIca can address molecular challenges far beyond our proprietary oncology programmes.
We work with selected industry and research partners on projects spanning molecular mechanism, target discovery, molecular optimisation, biologics, formulation and complex molecular systems.
Computational R&D projects
Focused engagements addressing defined molecular or mechanistic questions.
Collaborative discovery programmes
Joint programmes combining PhAsIca technology with partner biology, molecules or experimental capabilities.
Strategic R&D partnerships
Longer-term collaborations integrating advanced computational modelling into discovery and development programmes.
Our technology can support pharmaceutical and biotechnology companies, CROs, research organisations, consumer-health companies and other organisations working with complex molecular systems.
From understanding how molecules behave to deciding what to make next.
Science
Built on world-leading computational science
The scientific foundations of PhAsIca have been developed over more than a decade of research in computational biophysics, molecular simulation, artificial intelligence and cancer biology.
The company’s scientists have developed multiscale modelling technologies capable of connecting molecular interactions across scales that are inaccessible to conventional atomistic simulation alone.
These methods have been extensively benchmarked against experimental data and applied in research published in leading scientific journals including Science, Cell, Nature Communications, Nature Computational Science and ACS Central Science.
Selected publications
Mpipi
A physics-driven, residue-resolution framework predicting biomolecular sequence behaviour with near-quantitative accuracy — now a widely adopted reference model.
Nature Computational Science, 2021.
Mpipi-Recharged
Chemically informed coarse-graining of electrostatic forces for charge-rich protein and protein–nucleic-acid systems.
ACS Central Science, 2025.
Multiscale chromatin modelling
Near-atomistic modelling of chromatin architecture and material properties, integrated with cryo-electron tomography.
Science, 2025.
OpenCGChromatin
A high-performance multiscale framework for modelling chromatin and protein–DNA systems at near-atomistic resolution.
Nature Communications, 2026, in press.
Nucleosome plasticity & chromatin organisation
A multiscale framework resolving nucleosome dynamics and their role in chromatin structure and organisation.
Nature Communications, 2021.
PARP1 inhibitor selectivity
Molecular-interaction-network analysis explaining PARP1 inhibitor selectivity and binding affinity.
PLOS Computational Biology, 2026.
RNA2PS
A sequence-specific multiscale framework connecting RNA structure, thermodynamics and large-scale molecular behaviour.
bioRxiv, 2026; under peer review.
Liquid network connectivity in multicomponent condensates
A framework revealing how network connectivity regulates the stability and composition of biomolecular condensates with many components.
PNAS, 2020.
Minimal model for protein–RNA phase separation
Thermodynamics and kinetics of phase separation of protein–RNA mixtures captured by a minimal computational model.
Biophysical Journal, 2021.
Ageing into multiphase architectures
Simulations showing how single-component protein condensates can transform into multiphase architectures upon ageing.
PNAS, 2022.
RNA length and condensate stability
Multiscale simulations revealing the non-trivial effect of RNA length on the stability of condensates formed by RNA-binding proteins.
PLOS Computational Biology, 2022.
Droplet maturation and coalescence kinetics
A kinetic framework showing how the interplay between droplet maturation and coalescence modulates the shape of aged protein condensates.
Scientific Reports, 2022.
FUS mutations and condensate ageing
Charged mutations in the FUS low-complexity domain shown to modulate condensate ageing kinetics.
Cell Reports Physical Science, 2025.
Predicting saturation concentrations
A thermodynamic-integration approach for predicting saturation concentrations of phase-separating proteins.
bioRxiv, 2025.
Cross-β-sheet transitions at condensate interfaces
Local diffusion, concentration and inter-protein alignment shown to promote cross-β-sheet transitions at condensate interfaces.
2025.
Non-equilibrium regulation of condensates by RNA (REACT-RNA)
A framework showing how RNA synthesis and degradation regulate biomolecular condensates through non-equilibrium feedback.
bioRxiv, 2026.
Free-energy landscapes of chromatin polymorphism
A spectrum of free-energy landscape topologies shown to encode chromatin polymorphism and phase separation.
bioRxiv, 2026.
Phasica’s broader scientific foundations include modelling frameworks and collaborative studies published in:
Science · Cell · Nature Communications · Nature Computational Science · ACS Central Science · PNAS
Leadership
Building at the intersection of computation, biology and medicine
Phasica’s cofounders bring together expertise spanning computational biophysics, artificial intelligence, genomics, oncology, translational medicine and therapeutic development.
Rosana Collepardo-Guevara, PhD
Professor, University of Cambridge · Global leader in condensate biophysics · Pioneer in multiscale force-field development · Founder of international scientific consortia · 100+ publications
Jorge R. Espinosa, PhD
Professor, Universidad Complutense de Madrid · Elected Fellow of the Young Academy of Spain · Leading expert in drug discovery, AI and advanced computational methods · Director and founder of the UCM high-performance supercomputing centre · 100+ publications
Alberto Ocaña, MD, PhD
Director of Experimental Therapeutics, Hospital Clínico San Carlos · International leader in clinical oncology, translational therapeutics and precision oncology · 250+ publications
Balázs Győrffy, MD, PhD, DSc
Professor and Head of Bioinformatics at Semmelweis University and internationally recognised expert in cancer genomics, bioinformatics and translational data science. Member of the Hungarian Academy of Sciences.
Joaquín Martínez-López, MD, PhD
Professor of Medicine at the Complutense University of Madrid and Head of Haematology at Hospital Universitario 12 de Octubre. Medical oncologist with extensive expertise in haematological malignancies, precision medicine and therapeutic development.
Pedro Pérez Segura, MD, PhD
Professor of Medicine at the Complutense University of Madrid and Head of the Medical Oncology Division at the Hospital Clinic San Carlos. Medical oncologist and specialist in precision oncology, cancer genetics and translational cancer medicine.
Luis Martín Ezama, Global MBA
Biotech entrepreneur with 15+ years building companies across Europe, the USA and China · Fundraising, licensing, company building and strategic partnerships · Bridges AI, biotech and business
Our Ecosystem
Science without borders
PhAsIca brings together computational discovery, experimental biology and clinical translation through an international network across Europe.
Our scientific and translational ecosystem includes relationships with:
University of Cambridge, UK
Scientific innovation and computational biophysics.
Universidad Complutense de Madrid, Spain
Computational science, molecular modelling and experimental biophysics.
Semmelweis University, Hungary
Cancer genomics, bioinformatics and translational data science
Hospital Clínico San Carlos, Spain
Experimental therapeutics, translational oncology and clinical expertise.
Fundación CRIS Contra el Cáncer, Spain
Supporting innovative cancer research and translation.
News
International recognition for translational innovation
Award · 2026
Greatest Potential for Transfer of Technological Value
Macao International Innovation & Entrepreneurship Competition
The award recognised the translational and commercial potential of Phasica’s computational technology and marked an important step in the company’s engagement with the Asian innovation ecosystem.
Services
Complex molecular problem?
We combine physics, AI and advanced simulation to help uncover mechanisms, identify opportunities and guide molecular design.
We welcome conversations with biotechnology and pharmaceutical companies, CROs, research organisations and other life-science innovators interested in:
Computational discoveryMolecular modellingMechanistic investigationTherapeutic design and optimisationBiologics and ADC developmentComplex molecular systems
Contact PhAsIca Biosciences
Reveal more. Predict better. Design smarter.
PhAsIca Biosciences is building computational technology to make complex biology understandable — and actionable.