Decision-Grade Computational Evidence Before Wet-Lab Spend.
We help teams evaluate targets and candidate sets by producing structured, reproducible computational evidence packages for better experimental prioritization.
For Translational R&D & Discovery Teams
Designed for early-stage therapeutic teams that need to narrow the experimental search space with structured, multi-criteria candidate prioritization.
Best Suited For
- •Teams seeking to reduce avoidable compound attrition before synthesis or assay follow-up.
- •Programs that value transparent, reproducible structural scoring over opaque ranking outputs.
- •Translational groups that benefit from decision-grade evidence memos and structured metadata.
iBoundary Conditions & Assumptions
- •Requires a reasonably defined target context, decision question, and intended downstream use.
- •This engagement is designed for computational prioritization ahead of experimental follow-up.
✕Not Intended For
- •Not intended for programs seeking guaranteed biological outcomes from computational methods alone.
- •This engagement does not include direct wet-lab execution.
Typical Inputs
- Defined protein target structure (PDB) or sequence.
- Starting ligand library or functional context.
- Intended use case for the final candidate list.
Constraints & Assumptions
- Confidence is framed within the defined context of use and should not be generalized beyond it.
How This Engagement Works
Input Validation & Assumption Framing
Review of the biological target, literature context, and intended downstream use of the candidate shortlist.
Reproducible Triage Execution
Running a version-controlled, multi-step screening stack that can include docking, ranking, and supporting scoring logic.
Multi-Criteria Ranking
Filtering candidates against structural criteria, physicochemical limits, and contextual benchmarking where appropriate.
Structured Evidence Assembly
Compiling ranked outputs, uncertainty notes, reproducibility metadata, and a structured handoff package for experimental follow-up.
What You Receive
Structured deliverables designed for scientific review, internal decision-making, and clearer handoff into experimental follow-up.
Ranked Candidate Shortlist
CSV / SDF
A prioritized set of candidates that passed the defined selection and triage criteria.
Business Value:Supports internal review, synthesis planning, and targeted experimental follow-up.
Decision & Confidence Memo
PDF Memo
A structured summary of triage rationale, methodological limits, and uncertainty caveats.
Business Value:Helps internal stakeholders understand why specific candidates were prioritized over others.
Reproducibility Metadata
JSON
A complete record of runtime parameters, software versions, and execution context.
Business Value:Supports reruns, downstream review, and clearer internal traceability across screening rounds.
What the Confidence Pack Adds
The Confidence Pack is designed to move beyond raw ranking outputs by adding context, benchmarking, and explicit uncertainty framing where the target and dataset support it.
Consensus Scoring
Where appropriate, we use multiple scoring perspectives rather than a single ranking signal to reduce overreliance on one computational view of candidate quality.
Contextual Benchmarking
Where target data permits, we contextualize outputs with actives, decoys, or related ranking checks to better understand whether shortlisted candidates are meaningful enough for follow-up.
Explicit Caveats
We document assumptions, limitations, and context of use so downstream teams can interpret the output as a prioritization aid rather than as a stand-alone claim of biological success.
Structured Handoff
Deliverables are packaged for internal review and experimental follow-up, with enough methodological context to support reruns, discussion, and decision tracking.