Stage 01 / 07
Define.
A research target, chosen modality, constraints and objective priorities define the campaign.
Initializing
The flagship discovery workflow / Preview
Search the possibility space—not one molecule at a time.
Explore diverse therapeutic candidates across competing objectives. Make the trade-offs visible, challenge assumptions and advance a reviewable candidate set.
Drug design is not one optimization problem. It is many.
The v2 Drug Design Engine specifies batch-iterative generation and scoring across seven modalities and nine objectives. Pareto analysis preserves meaningful alternatives rather than hiding them behind a single score.
01
Define
02
Generate
03
Score
04
Optimize
05
Pareto Analysis
06
Agent Review
07
Advance
Explore the system
Drug Design Engine, made visible.
A hands-on preview of the workflow. All data, geometry and results below are illustrative—not experimental evidence.
DRUG DESIGN STUDIO / DEMO v2.0
Synthetic research previewSmall Molecule / illustrative geometryFX-04
Multi-objective profile
83.8
Weighted desirability
NondominatedRelative score out of 100. Not potency, safety or clinical efficacy.
Make trade-offs visible.
Candidate cloud
Nondominated status uses all nine objectives, not this two-dimensional projection.
Ranked by your priorities
Define
Specify a biological target, modality, modulation mode, selectivity, property priorities and search depth. Optional higher-fidelity scoring is deployment-dependent.
Configuration is illustrative and included in the export. It does not trigger scientific computation or change the fixed candidate data; no quantum hardware is connected.
Illustrative platform visualization — not experimental validation data. Synthetic demonstration; subject to expert review.
Illustrative platform visualization — not experimental validation data. In-silico candidates are hypotheses, not validated medicines. Qualified scientific review and experimental validation are required.
The autonomous drug campaign
From definition to the next decision.
Stage 02 / 07
Generate.
Explore candidate families across fictional search generations. No compounds are generated by this website.
Stage 03 / 07
Score.
Compare all nine objective profiles. Preserve limitations behind each estimate.
Stage 04 / 07
Optimize.
Reweight priorities and inspect alternatives. A high aggregate score does not remove individual weaknesses.
Stage 05 / 07
Pareto Analysis.
Retain nondominated alternatives rather than forcing every trade-off into a single winner.
Stage 06 / 07
Agent Review.
Specialist critics examine evidence, developability and prior-art context. Disagreement stays visible.
Stage 07 / 07
Advance.
A qualified reviewer chooses the next investigation. Computational candidates are not validated therapies.
Illustrative platform visualization — not experimental validation data. Synthetic demonstration; subject to expert review.
CAMPAIGN ANALYTICSSynthetic mathematical illustration
Optimization trajectory
Three fictional candidate families across illustrative search generations. These trends are authored examples, not measured optimization performance.
Illustrative platform visualization — not experimental validation data. Synthetic demonstration; subject to expert review.
Reviewable outputs
Carry the reasoning
with the result.
Nine-objective candidate profiles
Pareto frontier and chemical-space views
Optimization trajectories and response curves
Candidate rationale and review-ready dossiers
Conceptual media supplied by FantomX. Not a recording of a live scientific experiment.
FantomX.
From question to delivered science
Build the next scientific
workflow with FantomX.
From question to evidence. From evidence to candidate.
From candidate to delivered science.