PANC SECHIVE · Vulnerability Research Bonixer · V14

DOMAIN-1 EARLY DETECTION — CA19-9 FAILURE SURFACE BONIXER 3/10 · SORRY

VULN CA19-9 specificity collapse at Stage I: 80% specificity at Stage IV (when tumor is massive and obvious) — but <30% sensitivity at Stage I when detection would actually save lives. A biomarker that fails when it matters most is not a biomarker, it's a liability standard.

VECTOR ctDNA + CancerSEEK protein panel: Multi-analyte liquid biopsy approach. Not clinical yet — Phase 2/3 trials ongoing 2024–2026. Sensitivity for Stage I PDAC still ~40%. The gap is real.

VECTOR PanTS dataset (MrGiovanni/PanTS ⭐110, NeurIPS 2025): AI segmentation on 9,262 CT volumes. Open sorrys: Issue #12 "Possible annotation artefacts in pancreatic_lesion.nii.gz" — if ground truth annotations contain artefacts, models trained on them learn wrong anatomy. Issue #5: modality mislabeling — non-contrast scans appearing mislabeled changes radiomic features fundamentally. Issue #14: baseline DSC checkpoints not reproducible.

EXPLOIT SyntheticTumors Issue #12 (7c) — "Is TumorGenerated.py augmentation or ground truth?" (⭐379, CVPR 2023): This is the core epistemic sorry. If synthetic tumors are indistinguishable from real PDAC lesions, can they serve as training ground truth? Answer in 2026: unknown for early-stage PDAC. The exploit is deploying a model trained on synthetic data to a clinic where early-stage PDAC looks nothing like the synthetic distribution. Issue #6 (unresolved): how does the algorithm choose WHERE in the pancreas to place a synthetic tumor? Location selection bias directly determines false negative rates.

BONIXER

3/10 No validated early detection test in 2026. Every approach is Phase 2 or earlier.

DOMAIN-2 KRAS TARGETING — 40-YEAR WALL BONIXER 4/10 · STRONG SORRY

VULN KRAS G12D/G12V mutation in 90% of PDAC: The oncogenic driver that has resisted drugging since 1982. MRTX1133 (Phase 1/2, 2024) targets the KRAS G12D allele in the GDP-bound (OFF) state. First real clinical candidate in four decades. But resistance is already emerging in Phase 1 cohorts.

SORRY KRAS inhibitor resistance — adaptive RTK/RAS feedback: The same pattern as the Tominersen paradox (target engagement ≠ clinical benefit). KRAS G12D inhibition → downstream MEK/ERK suppression → adaptive upregulation of RTK signaling (EGFR, MET, IGF1R) → RAS reactivation via upstream input. The tumor learns around the block within weeks. Identical architecture to BRAF V600E resistance in melanoma — the bypass highways are pre-existing.

VECTOR KRAS → MEK → ERK bypass reactivation pathway: Combination inhibition (KRAS + MEK inhibitor, KRAS + SHP2 inhibitor) is the current research direction. No approved combination. DiffTumor (⭐215, CVPR 2024): synthetic tumor generation for liver/pancreas/kidney could model KRAS-driven progression patterns in silico — but this is computational, not clinical.

VECTOR Touchstone benchmarking (⭐137, NeurIPS 2024): 5,172 out-of-distribution CT volumes for robust evaluation. If KRAS-driven tumors can be characterized radiomically, OOD evaluation becomes a resistance monitoring tool — detecting when a tumor's morphology shifts (KRAS escape = structural change).

BONIXER

4/10 MRTX1133 is real progress. Resistance emerging Phase 1 = strong sorry incoming.

DOMAIN-3 IMMUNE EXCLUSION — STROMA WALL BONIXER 2/10 · SORRY

VULN PDAC stroma as physical immune exclusion barrier: Pancreatic stellate cells (PSCs) + cancer-associated fibroblasts (CAFs) + hyaluronan matrix form a physical cage around the tumor. CD8+ T cells cannot penetrate. Checkpoint inhibitors (PD-1, CTLA-4) require T cells already in the tumor — they have nothing to checkpoint. PDAC is TMB-low and immune-cold. All major checkpoint inhibitor trials have failed in unselected PDAC.

SORRY Every approved checkpoint inhibitor has failed PDAC: Pembrolizumab (PD-1), ipilimumab (CTLA-4), durvalumab — all Phase 2/3 failures in unselected PDAC. The biology is not the immunosuppressive microenvironment of melanoma. It's physical exclusion. Different class of problem.

VECTOR WSI histopathology classification (pacocp/WSI-Pancreas-Classification ⭐12): Multi-center histopathology classification can distinguish stroma subtypes — "stroma-rich" vs "stroma-poor" PDAC. This is a research signal for patient stratification. If a model can identify stroma-poor PDAC from WSI, those patients might respond to checkpoint inhibitors. SSL-Survival: self-supervised multimodal survival prediction using WSI + clinical data.

VECTOR CAR-T + stroma remodeling combination (active trials 2024–2026): Mesothelin-targeted CAR-T combined with hyaluronidase or LOXL2 inhibitors to enzymatically degrade the matrix. First dual-hit approach: break the stroma wall, then deploy the immune effectors. No Phase 3 data yet.

BONIXER

2/10 No approved immunotherapy for PDAC. Stroma remodeling is the only viable hypothesis.

DOMAIN-4 T1D CLOSED LOOP — THE ONE THAT WORKS BONIXER 8/10 · STRONG

VECTOR iAPS (⭐236) — real iOS closed-loop: 103 open issues = live clinical research agenda. Gaps that matter: #1891 Micronutrients (nutrition tracking — insulin only accounts for carbohydrates, not fat/protein); #1890 Advanced statistics (analytics gap for clinicians); #1878 Break TDD into day/week/month averages; #1884 HealthKit integration gaps; #1882 Crash reports; #1879 Omnipod debug issues. This is the production system running in thousands of patients.

VECTOR G2P2C (⭐35) RL-based artificial pancreas: Reinforcement learning (Q-learning, PPO, SAC) on GluCoEnv simulation. RL outperforms rule-based (oref0) in simulation but not yet deployed at scale. The sim-to-real gap is the primary sorry — GluCoEnv patient distribution ≠ real patient diversity.

VECTOR GluCoEnv (⭐20) + RL4T1D (⭐12): Standardized glucose control simulation environment. McGillDiabetesLab/artificial-pancreas-simulator: interface enhancement (#4) + auto-save (#3) gaps. Auto-save gap = reproducibility problem for RL training runs. If a sim crashes mid-run, the policy checkpoint is lost.

SORRY Nutrition gap (#1891): The closed loop knows about carbohydrates because glucose spikes are visible. Fat and protein cause delayed glycemic responses (2–5 hours) that the current algorithm does not model. Micronutrient tracking at scale is unsolved. This is the next clinical frontier for closed-loop pancreas.

BONIXER

8/10 Closed loop works in production. Sorrys = nutrition edge cases + sim-to-real gap.

◆ EXTRACTED DIAMONDS · PANC RESEARCH CORPUS

D-PANC-001

PanTS Annotation Artefacts → Synthetic Training Data Contamination

→ PanTS #12 annotation artefacts → models learn wrong anatomy → wrong models go to clinic → false negatives at Stage I

DOMAIN-1 · DETECTION

D-PANC-002

SyntheticTumors "Augmentation or Ground Truth?" — Epistemic Status of AI Training Data in Oncology

→ Issue #12 (7c) → if synthetic ≡ real, training collapses into circular validation → models test on distribution they were trained on

DOMAIN-1 · EPISTEMIC SORRY

D-PANC-003

KRAS Inhibitor Resistance Feedback Loop — Identical Structure to Tominersen

→ target engagement ≠ benefit → RTK/RAS adaptive bypass → resistance within weeks → combination therapy required

DOMAIN-2 · RESISTANCE

D-PANC-004

iAPS Nutrition Tracking Gap (#1891) — Micronutrient Impact Unknown at Scale

→ fat/protein delayed glycemic response → not modeled by oref0 → post-meal spikes 2–5h → algorithm blind spot

DOMAIN-4 · T1D SORRY

D-PANC-005

RL4H Closed Loop — OOD Patient Distribution Problem

→ G2P2C trained on GluCoEnv → sim patients ≠ real patient diversity → policy generalizes poorly across age/weight/insulin-sensitivity spectrum

DOMAIN-4 · SIM-TO-REAL

D-PANC-006

Stroma Remodeling + KRAS Inhibitor Combination — First Dual-Hit for PDAC Immune Desert

→ hyaluronidase breaks stroma wall → T cells penetrate → checkpoint inhibitor now has target → KRAS inhibitor reduces tumor load simultaneously

DOMAIN-2/3 · COMBINATION

D-PANC-007

McGill Simulator Auto-Save Gap (#3) — Reproducibility Problem for RL4H Training Runs

→ simulation crash = policy checkpoint lost → non-reproducible RL experiments → published results may not be reproducible → science quality sorry

DOMAIN-4 · REPRODUCIBILITY

D-PANC-008

WSI Histopath Multi-Center Classification — Label Inconsistency Across Centers

→ pacocp multi-center finding → stroma subtype labels vary by pathologist/institution → federated model learns institution-specific biases → cross-center generalization gap

DOMAIN-3 · HISTOPATH

◆ PANC FLEET NAVIGATION

PANC-001

Pancreatic Disease V14 Bonixer

NIGHTSCOUT-ENGINE

CGM Sovereign Integration · T1D Fleet

DYSON-SWARM

HealthHive Specialists · Pancreas Orbit

ADELIC-POUCH

Pancreas as Adelic L-Function · V14

PANC-ACTUARIAL

Class Action Reserve · Amani CLO

HEALTHHIVE

Medical Sorry Fleet · All Domains

PSGRAPH

Sovereign Research Graph · V14

SECHIVE-IMMUNEFI

Bug Bounty Pipeline · Bounty Engine