Protein-Design Model Validation Director

The mandate

The venture needs an independent answer to a bounded portfolio decision: whether its sequence-and-structure model produces enzymes more likely to survive expression, functional assay and fermentation conditions than established search methods.

The commissioned deliverable is a Protein Design Validation Dossier and Prospective Benchmark. It will include sequence and structural lineage, homology-safe partitions, frozen comparators, a blinded design queue, assay and fermentation acceptance ranges, calibrated uncertainty, failure accounting, reproducible model environments and an investment gate for advancing candidates into the next development portfolio.

Work begins 11 January 2027. Milestone one, the signed lineage audit and benchmark protocol, is due 29 January; milestone two, the leakage-controlled retrospective result and frozen prospective design set, is due 5 March; milestone three, the decoded synthesis, assay and fermentation evidence, is due 30 April; milestone four, the final validation opinion, model card and selection control, is due 11 June.

Acceptance requires Bioinformatics to recreate family partitions and scores from retained code, the wet-lab lead to confirm sample identities remained blinded until results locked, and Bioprocess Development to reproduce the agreed ranking of candidates under application-relevant conditions. The sponsors must sign every exclusion, failed synthesis and uncertainty boundary, and the benchmark must discriminate the design model from both similarity search and expert nomination under the pre-agreed measures.

The client will provide training snapshots, sequence sources, structural templates, embeddings, design histories, complete synthesis orders, laboratory notebooks, protocol versions, raw instrument files and fermentation results inside its research environment. Named protein scientists and data stewards will resolve provenance within two business days; patentability opinions, therapeutic claims, scale-plant capital design and selection of a long-term laboratory supplier remain outside scope.

Why this is external work

The scientists who built the model also chose most retrospective candidates and cannot independently establish that the apparent lift survives homology controls and complete failure accounting. Internal assay expertise is deep, but no team currently owns the evidence chain from training lineage through blinded nomination to fermentation relevance. An outside validation director gives the investment committee a result that can withstand both computational and experimental challenge.

What you will own

• Reconstruct sequence, structure, annotation and assay provenance across every benchmark candidate, marking contamination, near-homology and undocumented protocol change before scoring.
• Define family-aware and structure-aware partitions that prevent close biological relatives from turning memorisation or analogue retrieval into apparent generalisation.
• Freeze comparator methods, candidate budgets, success measures and exclusion rules before the prospective model and protein scientists submit their blinded nominations.
• Audit ranking, calibration and uncertainty measures against expression failure, inactive constructs and censored observations rather than analysing successful assays alone.
• Direct blinded synthesis and wet-lab execution across agreed functional and fermentation conditions, preserving sample identity, deviations and raw instrument evidence.
• Quantify where model advantage persists by protein family, novelty, assay regime and manufacturability constraint, including confidence intervals and adverse findings.
• Transfer the runnable benchmark, lineage graph, design-gate thresholds and unresolved model risks so future portfolio rounds can be challenged without external dependence.

Candidate qualifications

• Led independent validation of a protein, enzyme or molecular-design model whose predictions proceeded into blinded synthesis and application-relevant experimental testing.
• Detected sequence, structural or family leakage that materially changed a claimed generalisation result and can evidence the corrected partitioning approach.
• Designed prospective comparisons among machine-generated, similarity-based and expert-nominated candidates under a fixed experimental budget.
• Reconciled failed synthesis, assay censoring, protocol drift and batch effects without selectively excluding outcomes that weakened model performance.
• Connected computational ranking to expression, biochemical function and bioprocess behaviour while respecting the limits of small experimental samples.
• Delivered code, data lineage and wet-lab evidence that scientific leadership could reproduce and use as a continuing portfolio-selection control.