xpertsystems/hc-gen-007-sample

HC-GEN-007 — Gene Therapy Response Dataset: Multi-Modality Longitudinal Efficacy, Safety, Immunogenicity & Long-Term Follow-Up (Sample)

Synthetic patient-level dataset modeling longitudinal response to gene and cell therapy across 5 modalities (AAV, LNP-mRNA, CAR-T, CRISPR/Cas9, Lentiviral) and 12 indications, over a 24-month follow-up window with Year-15 long-term follow-up for integrating vectors (per FDA 2020 LTFU guidance).

This is a ~500-dosed-subject sample of the full HC-GEN-007 product (5,000 subjects). It is synthetic — generated by a benchmark-first simulation engine. It contains no real patient or product data. Product archetypes (e.g. AAV-FVIII, CART-CD19) are fictional.

Not for clinical use. This dataset is for ML development, benchmarking, schema prototyping, and education only. It must not be used to inform real patient care, trial design, or regulatory decisions.

Unit of observation

The unit is the dosed subject. The patient registry also retains AAV screen failures (nAb+) from the upstream eligibility gate, so the registry row count exceeds the dosed cohort. The five other tables key on subject_id for dosed subjects.

Calibration anchors

The engine is benchmark-first: each simulation parameter maps 1:1 to one validation metric, locked via exact index selection. Sample-level observed values (seed 42, ~500 dosed):

Metric	Observed	Target	Anchor
Modality coverage	1.00	=1.0	all 5 modalities present
Indication coverage	1.00	=1.0	all 12 indications present
Durable response rate	0.620	0.57–0.67	pooled pivotal response
Year-5 durability rate	0.710	0.65–0.77	LTFU durability
CRS rate (CAR-T, true)	0.780	0.72–0.84	Lee 2019 grading
ICANS rate (CAR-T)	0.323	0.26–0.38	ASTCT 2019 grading
SAE rate per patient-year	0.373	0.32–0.50	safety-model accounting
AAV nAb exclusion rate	0.300	0.27–0.33	pre-screen eligibility gate
CRISPR on-target edit separation	31 pp	≥15 (floor)	successful vs unsuccessful edit
Transfusion-independence separation	~0.88	≥0.40 (floor)	CRISPR hemoglobinopathy cohort
B-cell aplasia (CAR-T specificity)	high	≥0.30 (floor)	CD19-directed CAR-T
AAV nAb titer separation	large	≥3.0 (floor)	post-dose anti-capsid rise
CRS-label leak (non-CAR-T)	10	0–15 (disclosed bug)	see Limitations
Hepatotox outside high-dose AAV	0	=0 (floor)	referential integrity

Validation: Grade A+ (10.00/10) across all six canonical seeds (42, 7, 123, 2024, 99, 1), deterministic. The engine additionally passes its own internal 12/12 benchmark suite on every seed.

Tables

Six relational CSVs keyed on subject_id:

• hc_gen_007_patient_registry.csv — ~564 rows × 20 cols (dosed + nAb screen failures): indication (ICD-10), modality, product, demographics, baseline severity & scale, prior therapies, baseline nAb titer, HLA, conditioning, dose, infusion date, enrollment status.
• hc_gen_007_efficacy_outcomes.csv — ~6,000 longitudinal visits × 15 cols: VCN, transgene expression, primary-endpoint trajectory (scale-specific), response category, durability, motor-milestone / transfusion-independence / ABR-reduction flags, BCVA change, MRD, on-target edit %.
• hc_gen_007_adverse_events.csv — ~10,000 AEs × 18 cols: MedDRA PT/SOC, CTCAE grade, seriousness, relatedness, action, outcome, CRS (Lee grade), ICANS (ASTCT grade), hepatotoxicity, TMA, special-interest flags.
• hc_gen_007_immunogenicity_lab.csv — ~6,000 labs × 16 cols: anti-capsid & anti-transgene antibody titers, ALT/AST/bilirubin/LDH, ferritin, IL-6, troponin, CD3/CD19, B-cell aplasia, complement C3.
• hc_gen_007_long_term_followup.csv — ~3,700 annual records × 13 cols: durability, secondary malignancy, integration-site concern, VCN/transgene persistence, late AE, mortality, off-target events (to Year 15 for integrating vectors).
• hc_gen_007_trial_summary.csv — ~36 aggregate rows × 14 cols: per (indication, modality, cohort phase) response rate, AE/SAE rates per patient-year, CRS/ICANS/mortality/dropout rates.

Loading

import pandas as pd
registry = pd.read_csv("hc_gen_007_patient_registry.csv")
efficacy = pd.read_csv("hc_gen_007_efficacy_outcomes.csv")
aes      = pd.read_csv("hc_gen_007_adverse_events.csv")

# CRS rate among CAR-T (exclude the disclosed hepatotox mislabel)
cart = set(registry.loc[registry.modality=="CAR_T","subject_id"])
crs  = set(aes.loc[(aes.is_crs=="Y") & (aes.is_hepatotoxicity!="Y"),"subject_id"]) & cart
print(len(crs)/len(cart))

from datasets import load_dataset
registry = load_dataset("xpertsystems/hc-gen-007-sample", "patient_registry")

Use cases

• Multi-modality gene/cell-therapy response and durability modeling.
• CAR-T toxicity (CRS/ICANS) prediction and grading-aware safety models.
• AAV immunogenicity / nAb eligibility and hepatotoxicity-risk modeling.
• CRISPR on-target editing and transfusion-independence outcome modeling.
• Long-term-follow-up survival, integration-site, and durability analysis.
• Relational/longitudinal ML pipeline prototyping over a six-table star schema.

Limitations (honestly disclosed)

• Disclosed engine bug: hepatotoxicity events are mislabeled is_crs="Y". The high-dose-AAV hepatotoxicity special event is emitted with the CRS flag set true (the is_crs_flag tuple field is True for Hepatocellular injury rows; it should be False). This leaks ~10 non-CAR-T is_crs="Y" rows per 500 subjects. The engine's own Metric 4 hides this by intersecting with CAR-T IDs. To compute a correct CAR-T CRS rate, exclude rows where is_hepatotoxicity=="Y" (as in the loading example). The sample scorecard surfaces this as an explicit crs_label_leak_noncart metric rather than hiding it. Recommended full-product fix: set the CRS flag to False on the hepatotox tuple.
• Benchmark-first by construction. Headline rates (durable response, CRS, ICANS, nAb exclusion, Year-5 durability) are locked near-exactly to their BENCH targets via index selection, so cross-seed variance is minimal — realistic for a calibrated simulator but not a substitute for empirical trial heterogeneity.
• SAE rate runs slightly below its target. Observed ~0.37/PY vs BENCH 0.42; the special-event SAE accounting under-fills the quota. Within the engine's own ±0.08 tolerance.
• Synthetic, archetype-based. Modality/indication mappings and product archetypes are illustrative, not specific approved products.
• Marginal calibration, not full joint fidelity. Headline rates and the engineered structural separations (CRISPR edit gap, transfusion-independence concentration, CAR-T B-cell aplasia, AAV nAb rise) are anchored; higher-order correlations beyond those engineered are not independently validated.
• Small-sample note. At ~500 dosed subjects, cohort-specific rates (CRS/ICANS within CAR-T, hepatotox within high-dose AAV) are computed on modest subgroups; scorecard ranges accommodate this and structural floors are weighted to dominate.

Commercial / full version

	Sample (this)	Full (commercial)
Dosed subjects	~500	5,000 (configurable)
Tables	6 (full schema)	6 (full schema)
Formats	CSV	CSV / Parquet
Engine fixes	as-is, bug disclosed	is_crs hepatotox mislabel patched on request
Seeds / reproducibility	6 canonical	Unlimited
License	CC-BY-NC-4.0	Commercial
Support	—	SLA, custom modalities/indications, vertical extensions

Contact pradeep@xpertsystems.ai · https://xpertsystems.ai

Citation

@dataset{xpertsystems_hcgen007_2026,
  title  = {HC-GEN-007: Synthetic Gene Therapy Response Dataset --- Multi-Modality
            Longitudinal Efficacy, Safety, Immunogenicity & Long-Term Follow-Up (Sample)},
  author = {XpertSystems.ai},
  year   = {2026},
  publisher = {Hugging Face},
  note   = {Synthetic data. Not for clinical use. Fictional products. Calibration
            anchors: Lee et al. 2019 (CRS grading); ASTCT 2019 (ICANS grading);
            FDA 2020 Long-Term Follow-Up Guidance; AAV/CRISPR/CAR-T/lentiviral
            pivotal-trial response and durability benchmarks. Disclosed defect:
            hepatotoxicity special events mislabeled is_crs=Y.},
  url    = {https://huggingface.co/datasets/xpertsystems/hc-gen-007-sample}
}