Symbolia AI introduces BioForge for therapeutic discovery.Symbolia AI introduces BioForgefor therapeutic discovery.
BioForge integrates target biology, structural modeling, chemistry, biologics design, ADMET, docking, molecular dynamics, and active learning to accelerate drug discovery.
We are fusing natural-language scientific reasoning with computational workflows to turn therapeutic hypotheses into validation-ready programs.
AI scientist
platform for therapeutic discovery
Closed-loop
targets, molecules, models, and assays
BioForge
drug discovery operating system
Focus Areas
One discovery engine for therapeutic programs.
We are building BioForge as a closed-loop AI scientist platform: biomedical literature, knowledge graphs, multimodal data, generative design, docking, molecular dynamics, ADMET, active learning, and wet-lab validation feedback.
Protein Target Intelligence
AI scientist workflows for target identification, validation evidence, disease biology, pathway context, and tractability assessment.
Read applicationSmall Molecule Design
Generative design and evidence-weighted prioritization for small molecules, with docking, ADMET, novelty, and synthetic feasibility in the loop.
Read applicationPeptides, Binders, and Antibodies
Design support for peptide therapeutics, protein binders, antibody discovery, developability triage, and validation-ready binding hypotheses.
Read applicationDrug discovery needs closed-loop reasoning
BioForge applies Symbolia AI's AI scientist engine to therapeutic discovery, from protein targets and molecule design to wet-lab validation.
Scientific orchestration layer
LLM-based scientist workflows connect literature, domain knowledge, datasets, assumptions, and hypotheses in one traceable system.
Proprietary reasoning platform
BioForge fuses natural-language scientific reasoning with computational tools, structured evidence, and iterative validation workflows.
Multimodal evidence
Targets, structures, omics data, assays, chemistry, biologics sequences, ADMET signals, and partner datasets can be reasoned over together.
Better candidate prioritization
The platform ranks targets, molecules, peptides, binders, antibodies, assays, and validation paths with explicit scientific rationale.
Closed-loop learning
Bayesian optimization and active learning help decide what to design, simulate, synthesize, express, or test next as validation data arrives.
Partner-ready evidence
Outputs are designed for pharma R&D teams, biotech companies, translational labs, CRO partners, and platform discovery teams.
Questions before a partnership conversation.
BioForge is Symbolia AI's AI scientist platform for therapeutic discovery. It integrates target biology, chemistry, biologics design, ADMET, docking, molecular dynamics, and wet-lab validation feedback.
BioForge connects natural-language scientific reasoning with computational workflows, evidence graphs, and validation feedback so teams can move from broad therapeutic questions to ranked candidates and next experiments.
BioForge supports protein target intelligence, small molecule design, peptide and binder design, antibody discovery, ADMET and developability triage, docking, molecular dynamics, and wet-lab validation planning.
The platform is being designed for scientific literature, biomedical knowledge graphs, omics data, structures, compound libraries, sequences, assay results, ADMET signals, simulation outputs, and partner validation data.
Pharma teams, biotech companies, platform discovery groups, translational labs, CRO partners, and investors building therapeutic discovery programs are the best fit.
If you want to partner or collaborate with us, reach out!
We are building BioForge for protein targets, small molecules, peptides, binders, antibodies, ADMET, docking, molecular dynamics, and wet-lab validation, with pharma and biotech partners who want faster, sharper discovery loops.