Create README.md

README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - text-classification
+  - question-answering
+  - text-retrieval
+
+language:
+  - en
+
+tags:
+  - medical
+
+pretty_name: MedLens
+
+size_categories:
+  - 100K<n<1M
+---
+
+# Dataset Card for MedLens Drug-Drug Interaction (DDI) Evidence
+
+This dataset is a curated, multi-regional drug-drug interaction (DDI) and adverse drug event (ADE) signal database compiled from US, EU/EEA, and India regulatory and pharmacovigilance sources.
+
+It is structured as a SQLite database intended for deterministic offline medication-safety lookups.
+
+This also has a mobile version to put in mobile applications.
+
+---
+
+# Dataset Details
+
+## Dataset Description
+
+The MedLens DDI Evidence dataset aggregates prioritized DDI/ADE screening signals from five regional source files covering the US, EU/EEA, and India.
+
+Each record links a drug pair to one or more adverse effects, a severity level, interaction category, mechanism/rationale, evidence basis, source URLs, patient risk flags, and population relevance notes.
+
+The database contains:
+
+- **21,810** known interaction pairs
+- **105,460** pair-level adverse effect rows
+- **162,600** raw DDI signal rows (original source-level records, pre-deduplication)
+
+### Severity Breakdown Across Interaction Pairs
+
+| Severity | Pairs |
+|---|---:|
+| Major | 16,174 |
+| Moderate | 5,523 |
+| Minor | 113 |
+
+- **Curated by:** Ashutosh
+- **Language(s):** English (drug names are generic/INN)
+- **License:** CC BY 4.0
+
+---
+
+## Dataset Sources
+
+- **Repository:** [MedLens on GitHub](https://github.com/ashutosh-MedLens/MedLens) *(update with actual URL)*
+
+---
+
+# Uses
+
+## Direct Use
+
+- Offline/on-device medication safety screening
+- Drug-drug interaction lookup for clinical decision support prototypes
+- Pharmacovigilance research and signal analysis
+- Training or evaluation data for NLP models that classify or explain DDI severity
+- Regional comparison of interaction signals (US vs EU/EEA vs India)
+
+---
+
+## Out-of-Scope Use
+
+- **Not a substitute for clinical judgment or a licensed drug interaction database.**
+  Signals are screening-level, not patient-specific diagnoses or causality determinations.
+
+- Should not be used to generate or imply patient-specific medical advice.
+
+- Not suitable for production clinical systems without expert validation and regulatory clearance.
+
+- Does not cover all known drug interactions; coverage is limited to the source files below.
+
+---
+
+# Dataset Structure
+
+The SQLite database contains five tables.
+
+---
+
+## `known_interaction`
+
+Deduplicated drug-pair level interaction records.
+
+| Column | Type | Description |
+|---|---|---|
+| `drug_a`, `drug_b` | TEXT | Normalized generic drug names (alphabetical order) |
+| `severity` | TEXT | Consensus severity: `Major`, `Moderate`, or `Minor` |
+| `severity_rank` | INTEGER | Numeric rank (higher = more severe) |
+| `row_count` | INTEGER | Number of raw signals contributing to this pair |
+| `source_regions_json` | TEXT | JSON array of regions (e.g. `["us","eu/eea"]`) |
+| `evidence_bases_json` | TEXT | JSON array of evidence basis strings |
+| `source_bases_json` | TEXT | JSON array of source systems |
+| `source_urls_json` | TEXT | JSON array of reference URLs |
+| `mechanisms_json` | TEXT | JSON array of mechanism/rationale strings |
+| `risk_flags_json` | TEXT | JSON array of patient risk flag strings |
+| `dataset_types_json` | TEXT | JSON array of dataset type labels |
+| `use_case_notes_json` | TEXT | JSON array of use-case notes |
+
+---
+
+## `known_interaction_effect`
+
+One row per `(pair, adverse effect, severity)` combination.
+
+| Column | Type | Description |
+|---|---|---|
+| `known_interaction_id` | INTEGER | FK → `known_interaction.id` |
+| `adverse_effect` | TEXT | Adverse effect name (e.g. `qt prolongation`, `myelosuppression`) |
+| `severity` | TEXT | Effect-level severity |
+| `row_count` | INTEGER | Number of raw signals with this effect |
+| `source_regions_json` | TEXT | JSON array of regions |
+
+---
+
+## `ddi_raw_signal`
+
+Original source-level records before deduplication (**162,600 rows**).
+
+### Key Columns
+
+- `source_file`
+- `region`
+- `drug1_raw`
+- `drug2_raw`
+- `normalized_drug1`
+- `normalized_drug2`
+- `adverse_effect`
+- `severity`
+- `mechanism_or_rationale`
+- `interaction_category`
+- `interaction_direction`
+- `evidence_basis`
+- `source_basis`
+- `source_urls`
+- `population_relevance`
+- `patient_risk_flags`
+- `dataset_type`
+- `use_case_note`
+
+---
+
+## `evidence_import_file`
+
+Provenance table — one row per source CSV.
+
+| Source File | Region | Rows Seen | Rows Imported | Unique Pairs |
+|---|---|---:|---:|---:|
+| `usa_prioritized_ddi_ade_signals.csv` | us | 33,306 | 31,666 | 5,770 |
+| `eu_eea_prioritized_ddi_ade_signals.csv` | eu/eea | 58,567 | 50,911 | 8,724 |
+| `india_prioritized_ddi_ade_signals.csv` | india | 10,430 | 10,139 | 1,915 |
+| `india_expanded_prioritized_ddi_ade_signals.csv` | india_expanded | 55,297 | 49,188 | 14,565 |
+| `india_common_generic_ddi_5000.csv` | india_common_generic | 5,000 | 5,000 | 3,471 |
+
+---
+
+## `ddi_import_issue`
+
+Contains **15,696 rows** flagging drug name pairs that could not be resolved to canonical entries during import.
+
+This table is useful for improving normalization coverage.
+
+---
+
+# Dataset Creation
+
+## Curation Rationale
+
+Existing open DDI datasets tend to be US-centric or require a network connection.
+
+This dataset was assembled to enable fully offline, multi-regional medication safety checks — particularly for India, where brand-name and generic drug usage patterns differ significantly from the US/EU baseline.
+
+---
+
+# Source Data
+
+## Data Collection and Processing
+
+Raw DDI/ADE signals were compiled from the following public regulatory and pharmacovigilance sources.
+
+---
+
+### US Signals
+
+- [DailyMed](https://dailymed.nlm.nih.gov/dailymed/) — FDA-approved drug labeling
+- [TWOSIDES](https://tatonettilab.org/offsides/) — Post-market drug interaction database
+- [CMS Part D Drug Spending Dashboard](https://data.cms.gov/tools/medicare-part-d-drug-spending-dashboard)
+- ClinCalc Top-300 Drugs 2023
+
+---
+
+### EU/EEA Signals
+
+- EMA SmPC (Summary of Product Characteristics)
+- EMA DDI Guideline
+- [EudraVigilance](https://www.ema.europa.eu/en/human-regulatory-overview/research-and-development/pharmacovigilance-research-and-development/eudravigilance) — EU adverse reaction reports
+- EU ADR Reports / EU Union Register
+- WHO ATC/DDD Index
+
+---
+
+### India Signals
+
+- [PVPI](https://ipc.gov.in/PvPI/pv.html) — Pharmacovigilance Programme of India
+- NLEM 2022 (National List of Essential Medicines)
+- TWOSIDES
+
+Drug names were normalized to generic/INN form.
+
+Pairs were deduplicated by canonical `(drug_a, drug_b)` sorted order.
+
+Severity was aggregated by taking the highest severity signal per pair.
+
+---
+
+## Who Are the Source Data Producers?
+
+Data originates from:
+
+- US FDA (labeling, FAERS)
+- European Medicines Agency (EMA)
+- Indian Pharmacopoeia Commission / PVPI
+- Academic pharmacoepidemiology projects (TWOSIDES)
+- CMS (Medicare Part D utilization data)
+
+---
+
+# Personal and Sensitive Information
+
+This dataset contains no patient-level data.
+
+All records are drug-pair-level aggregate signals.
+
+No personally identifiable information (PII) is present.
+
+---
+
+# Bias, Risks, and Limitations
+
+- **Signal, not causality:**  
+  All records are screening-level DDI/ADE signals. They indicate a potential interaction of concern, not a confirmed causal relationship for any individual patient.
+
+- **Coverage gaps:**  
+  15,696 raw signals (≈9%) could not be resolved to canonical drug names and are excluded from the deduplicated interaction table.
+
+- **Severity aggregation:**  
+  Where multiple sources disagree on severity, the highest severity is taken. This may overstate risk for some pairs.
+
+- **Regional bias:**  
+  India coverage is strong for common generics but may underrepresent rare drugs. US coverage skews toward high-prescription-volume drugs (Top-300 proxy).
+
+- **Temporal limitations:**  
+  Signal databases are periodically updated; this snapshot reflects the state at import time.
+
+- **Not exhaustive:**  
+  Absence of a pair from this dataset does not mean the combination is safe.
+
+---
+
+# Recommendations
+
+- Always cross-reference with current product labeling and consult a qualified healthcare professional before making clinical decisions.
+
+- Use the `ddi_import_issue` table to identify drug names that failed normalization and expand coverage over time.
+
+- Treat `Major` severity pairs as requiring clinical review.
+
+- Treat `Minor` severity pairs as informational.
+
+---
+
+# Glossary
+
+| Term | Meaning |
+|---|---|
+| **DDI** | Drug-Drug Interaction |
+| **ADE** | Adverse Drug Event |
+| **FAERS** | FDA Adverse Event Reporting System |
+| **PVPI** | Pharmacovigilance Programme of India |
+| **NLEM** | National List of Essential Medicines (India) |
+| **INN** | International Nonproprietary Name (generic drug name) |
+| **TWOSIDES** | A database of drug pair adverse effects derived from post-market surveillance data |
+| **SmPC** | Summary of Product Characteristics (EU equivalent of US drug labeling) |
+
+---
+
+# Dataset Card Contact
+
+`prog.mishra@gmail.com`
+
+---
+
+# TODO Before Publishing
+
+- Update repository URL to the actual GitHub repository
+- Confirm final license choice:
+  - `CC BY 4.0`
+  - or `CC BY-NC 4.0` if non-commercial only
+- Add citation / BibTeX entry for versioned referencing