We extract drug monographs, interaction matrices, dosage guidelines, pill identifier metadata, and patient reviews from Drugs.com. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Drug Monographs objects from drugs.com. All fields typed and schema-versioned.
"drug_name": "Lipitor", "generic_name": "atorvastatin", "drug_class": "Statins", "csa_schedule": "Not a controlled drug", "pregnancy_category": "X", "indications": "['High Cholesterol', 'Prevention of Cardiovascular Disease']"
| # | drug_name | generic_name | brand_names | drug_class | csa_schedule | fda_approval_history |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Interaction Checker objects from drugs.com. All fields typed and schema-versioned.
"drug_a": "atorvastatin", "drug_b": "clarithromycin", "interaction_severity": "Major", "interaction_mechanism": "CYP3A4 inhibition", "clinical_management": "Avoid combination or limit atorvastatin dose to 20 mg/day.", "evidence_level": "High"
| # | drug_a | drug_b | interaction_severity | interaction_mechanism | clinical_management | patient_instructions |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Patient Reviews objects from drugs.com. All fields typed and schema-versioned.
"drug_name": "Lexapro", "condition": "Anxiety", "reviewer_rating": 8.5, "review_text": "Helped with panic attacks but caused mild nausea initially.", "time_on_medication": "1 to 6 months", "helpful_votes": 42
| # | drug_name | condition | reviewer_rating | review_text | time_on_medication | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pill Identifier objects from drugs.com. All fields typed and schema-versioned.
"imprint": "M 367", "colour": "White", "shape": "Capsule/Oblong", "drug_name": "Acetaminophen and Hydrocodone Bitartrate", "strength": "325 mg / 10 mg", "rx_otc": "Rx"
| # | imprint | colour | shape | drug_name | strength | manufacturer |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Side Effects objects from drugs.com. All fields typed and schema-versioned.
"drug_name": "Lisinopril", "system_organ_class": "Respiratory", "symptom": "Dry cough", "consumer_incidence_rate": "Very common", "severity": "Mild to Moderate", "requires_medical_attention": false
| # | drug_name | consumer_incidence_rate | professional_incidence_rate | system_organ_class | symptom | severity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Drugs.com scraper parses dense medical text, normalises complex interaction matrices, and captures pill imagery without truncating critical warnings or dosage guidelines.
Extract generic names, brand variants, drug classes, indications, and controlled substance schedules across the entire formulary.
Capture drug-drug, drug-food, and drug-disease interactions including severity levels and clinical management instructions.
Scrape imprints, shapes, colours, and high-resolution images mapped to specific NDCs and manufacturers.
Extract qualitative review text, numerical ratings, time on medication, and helpful votes paginated across all user submissions.
Parse consumer and professional side effect lists, categorised by system organ class and incidence rates.
Extract adult and paediatric dosage guidelines, renal dose adjustments, and administration protocols.
Capture FDA pregnancy categories and specific breastfeeding warnings for every compound.
Monitor and extract the latest FDA safety alerts, market withdrawals, and label changes.
Scrape price guide data, generic availability dates, and manufacturer coupon information.
Brief in. Clean data out.
Provide drug names, therapeutic classes, or specific data modules (e.g., just interactions). We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for drugs.com.
Schema validation, null-rate checks, and medical text truncation detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting medical data requires high fidelity. Here is how we ensure data integrity across millions of pharmaceutical records.
Drugs.com monographs contain deeply nested HTML lists, bolded warnings, and tabular dosage data. Standard text extraction strips this context. We use structural parsing to maintain the relationship between headers, paragraphs, and bullet points, ensuring clinical instructions remain coherent.
Checking interactions across thousands of drugs creates a massive combinatorial matrix. We optimise the interaction checker extraction by traversing the categorical interaction lists rather than brute-forcing pairwise queries, capturing the full severity matrix efficiently.
Popular drugs like Lexapro have thousands of paginated user reviews sorted by condition. Our crawlers iterate through every condition filter and pagination state, capturing the entire historical corpus of patient sentiment without timing out.
The Pill Identifier relies on high-quality imagery. We extract the source image URLs, download the assets directly to your S3 bucket, and map the object keys back to the structured metadata (imprint, colour, shape) in the JSON payload.
A missing contraindication due to a CSS selector change is unacceptable for healthcare data. We deploy strict schema validation on every run. If Drugs.com changes its DOM, the pipeline halts and alerts our engineers to update the selectors before pushing malformed data.
Health tech companies integrate interaction matrices and dosage guidelines into EHR systems and prescribing software.
Pharma companies monitor patient reviews and side effect reports to identify post-market adverse events and off-label usage.
Machine learning teams use structured monographs and symptom descriptions to train medical NLP classifiers and triage bots.
Virtual care platforms populate their internal drug databases with pricing, generic alternatives, and pregnancy warnings.
Life sciences firms track patient sentiment and reported efficacy across competing drug classes to inform R&D and marketing.
Digital pharmacies use the pill identifier database to verify inventory and provide visual aids for patient adherence apps.
"Drugs.com holds the most comprehensive, user-accessible pharmaceutical database on the web — but extracting structured interaction matrices requires a purpose-built pipeline."
Extracting medical data requires high-fidelity parsing. A missed contraindication or truncated dosage guideline renders the dataset useless. DataFlirt handles the complex DOM structures, nested interaction tables, and pagination logic so your clinical and data science teams receive clean, normalised records ready for analysis.
Everything supported by our drugs.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across IN/US/UK/DE regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About drugs.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Drugs.com is generally permissible under applicable law. DataFlirt targets only public, non-authenticated medical data, monographs, and reviews. We do not extract personal health information (PHI), circumvent authentication walls, or violate HIPAA/GDPR. Clients should review Drugs.com's ToS and consult legal counsel for specific use cases.
Instead of executing millions of pairwise queries in the interaction checker, we extract the pre-computed categorical interaction lists associated with each primary drug profile. This allows us to map the entire matrix efficiently and maintain high data freshness.
Yes. We extract the direct URLs to the highest resolution images available in the Pill Identifier database. We can either provide the URLs in the payload or download the assets directly to your designated S3 bucket.
Full formulary refreshes are typically scheduled weekly or monthly depending on client requirements. FDA alerts and new drug approval sections can be monitored on a daily or hourly cadence.
We handle full pagination. Our crawlers extract the entire historical corpus of reviews for a given drug, including condition filters, numerical ratings, and helpful vote counts.
Absolutely. We provide a sample run of up to 100 drug profiles or interaction matrices as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and medical text integrity before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of pill identifiers or a continuous feed of patient reviews and FDA alerts — we scope, build, and operate the pipeline. Tell us what you need.
