{
  "version": 3,
  "created_at": "2026-07-10T19:05:21.996Z",
  "task_summary": "Reposition the EoE pMHC-II manuscript around personalization and reconcile it with the updated plans",
  "agents": [],
  "phases": [
    {
      "name": "Plan",
      "delegations": [
        {
          "steps": [
            {
              "title": "Build reconciliation table of discrepancies",
              "description": "Produce manuscript_reconciliation.csv listing every inconsistency between the manuscript, the two plans, and the underlying data files, with the resolved value and its source: (1) dairy antigen β-lactoglobulin→β-casein (FAQTQSLVY = P02666 aa67–75, sequence-verified; note bulk scan was on Bos d 5); (2) HLA allele DRB1*01:01 in data vs. DRB1*07:01 claimed; (3) NP surface coverage 5.97% vs 1.4%; (4) construct count 3+1 vs 9-panel; (5) budget $275–457k vs $8M Seed. This table is the authority for all downstream edits."
            },
            {
              "title": "Rebuild personalization-engine figure from real data",
              "description": "From pmhc_ii_candidates.csv (5 alleles × milk+egg, 303 strong binders/1800), render a publication-grade multi-panel figure (fig_personalization_engine.png, 300 dpi) showing the per-allele × per-antigen presentation hierarchy and the strong-binder funnel — the computational basis for HLA-driven, per-patient antigen selection. Load figure-style first and apply_figure_style(). Be explicit in the caption about what was scanned. This becomes the new Figure 1 anchoring the repositioned thesis."
            },
            {
              "title": "Rewrite Abstract and Introduction",
              "description": "Recast the Abstract and Introduction around the personalized/N-of-1 thesis: HLA-driven per-patient antigen selection as the central advance, the PACT™ shared-backbone/swappable-cassette manufacturing concept, and the biomarker-first discipline. Frame EoE's plural, patient-variable allergens (milk/wheat/egg/soy) as the hard problem the engine solves. Correct β-lactoglobulin→β-casein. Weave in the ASIT-landscape precedents (Nexvax2, Tzield/teplizumab, TAK-101/KAN-101) that the plans are built on."
            },
            {
              "title": "Restructure Results around the engine + validation cascade",
              "description": "Reorder Results so the personalization engine (multi-HLA epitope prediction) leads, followed by the specific validated constructs as worked examples/validation data. Fold the structural metrics (ipTM 0.87–0.90, 15/15 in-groove) and nanoparticle design in as supporting evidence for the tolerogenic-delivery choice. Reconcile all numbers to the reconciliation table (surface coverage, construct count, allele). Reuse existing figures 2 (structural) and 3 (nanoparticle) with corrected captions; add the new engine figure as Figure 1."
            },
            {
              "title": "Rewrite Discussion + reframe development roadmap",
              "description": "Rewrite Discussion around the biomarker-first spine (ipTM → K_D/T_m → tetramer → IL-10/Tr1 signature → in-vivo → human PD), the tolerogenic-context mandate (the Nexvax2 lesson against bare peptide), HLA/sensitization stratification, and early/pre-fibrostenotic target population. Replace the hackathon-scale $275–457k budget with the plan-consistent staged framing (or remove fundraising figures entirely, as is normal for a research manuscript) and point to the companion-diagnostic co-development. State limitations honestly: wheat/soy/egg epitopes as computational priors, β-casein attribution flagged for citation verification, single-allele data vs multi-HLA ambition."
            },
            {
              "title": "Assemble repositioned DOCX and change-log",
              "description": "Compile the revised text + figures into EoE_manuscript_personalized.docx (new version of the Final Main manuscript lineage where sensible, preserving figure embedding at 300 dpi). Write manuscript_changelog.md summarizing section-by-section what changed and why, cross-referencing the reconciliation table. Save all artifacts (DOCX, new figure PNG, reconciliation CSV, changelog MD) and embed the figure inline in the response."
            }
          ]
        }
      ],
      "id": "phase-0"
    }
  ],
  "desired_outputs": [
    "Repositioned manuscript DOCX aligned with the updated scientific and business plans",
    "New/updated figure showing multi-HLA personalized antigen-selection engine",
    "Reconciliation table documenting every factual fix (antigen identity, HLA allele, surface coverage, construct count, budget)",
    "Change-log memo summarizing what changed and why"
  ],
  "feasibility": {
    "rationale": "All three source documents and the underlying data (candidate CSVs, structural metrics, nanoparticle specs) are in the artifact store and have been read. The β-casein correction is sequence-verified. The main judgment call — how hard the computed data (β-lactoglobulin/egg bulk scan on 5 alleles vs. the β-casein lead epitope) supports the personalization narrative — is manageable by being explicit about provenance. Repositioning is a substantial but well-scoped rewrite.",
    "confidence": "high"
  }
}