— about drugly —

Founded by a pharmacist,
built for professionals

An AI-powered professional pharmaceutical reference platform designed for licensed healthcare professionals. Same category as DrugBank, Lexicomp, and UpToDate — faster, bilingual, and built for a new generation.

Professional-Use Platform

Drugly.ai is a professional reference platform for licensed healthcare professionals. It is not a medical device; it does not provide medical advice, diagnosis, or treatment. All content must be cross-checked against current SmPC / prescribing information / local protocols and combined with professional clinical judgment before any clinical decision.

— how it started —

The reference we wished we had

Drugly.ai began with something Enes, our founder, noticed as a working pharmacist: the professional drug references used every day were either prohibitively expensive, split across several subscriptions, or never designed for bilingual Turkish clinical workflows.

So we set out to build the reference we wanted to use ourselves: drug monographs, interaction checks, pharmacogenomics, clinical calculators and Turkish reimbursement rules in one place — in Turkish and English, and quick enough to check between patients.

Drugly is still built by a small, hands-on team, and every new feature starts from the same question: does this help a healthcare professional reach a trustworthy answer faster?

What we set out to fix

  • Expensive

    A Free plan to start — and Pro for just €2.99 a month.

  • Fragmented

    Drugs, interactions, PGx, calculators, cosmetics, herbal medicine and SUT — in one account.

  • English-only

    Bilingual from the start — Turkish and English — with SGK SUT checks and TİTCK product data built in.

— what drives us —

Mission & vision

Our Mission

Drugly.ai exists to give licensed healthcare professionals — pharmacists, physicians, nurses, researchers, and students in supervised programs — fast, structured, evidence-aligned professional reference information. By combining a comprehensive database, advanced AI features, and a bilingual (Turkish / English) workflow in a single platform, we are redefining the standard of professional reference tools.

Our Vision

We aim to define the next-generation standard for professional pharmaceutical reference tools — faster, more structured, bilingual, and built with an understanding of emerging-market workflows. In the category of DrugBank, Lexicomp, and UpToDate, but with a modern approach.

We envision a future where every professional clinical decision is supported by more comprehensive data, faster access, and better-structured references — never replacing professional clinical judgment, only strengthening it.

— the people behind it —

Meet the team

A pharmacist, a developer and a cosmetics expert — a small team that genuinely understands the daily work of healthcare professionals.

Enes

Founder & CEO · Licensed Pharmacist

Sets Drugly.ai's direction and leads product vision, platform architecture, clinical content review and data integration. Brings a working pharmacist's perspective to every feature, with domain expertise in pharmacogenomics, drug-interaction analysis and health-database design.

  • Product vision
  • Clinical content
  • Pharmacogenomics
  • Drug interactions

Sümeyye

Developer

Works alongside Enes on building Drugly.ai — from database architecture and API integrations to the interface healthcare professionals use every day. Focused on turning complex clinical data into fast, reliable, and intuitive tools.

  • Database architecture
  • API integrations
  • User interface

Nurcan

Cosmetic Expert & Marketing Specialist

Brings cosmetic expertise to Drugly.ai's cosmetic ingredient database, photo-safety checker and drug–cosmetic interaction tools, keeping cosmetic content accurate for professional users. As marketing specialist, shapes how Drugly.ai reaches pharmacists, clinicians and the wider skincare community.

  • Cosmetic ingredients
  • Skincare safety
  • Marketing
  • Community

Want to ask us something? Write to hello@drugly.ai — one of us will reply.

— how we work —

Principles we build by

A clinical reference tool has to be one you can trust. These four principles decide what we build and how.

Evidence first

Content is built on recognised primary sources — regulatory data, CPIC and PharmGKB guidance, WHO classifications and peer-reviewed literature.

Your judgment stays in charge

Drugly supports professional decisions; it never makes them. Everything is presented to be cross-checked against the current SmPC and local protocols.

AI with guardrails

The AI assistant helps you find and summarise drug information in Turkish or English. AI-generated content is identified as such — a starting point to verify, not an answer to act on.

Privacy by design

We never ask for patient data and we don't sell personal data. Payments run through Stripe, so we never see your card details.

Platform at a glance

10,000+ Drug Records
5,000+ Cosmetic Products
1,000+ Medicinal Plants
13,271 ICD-10 Codes
15 Clinical Calculators
5 Interaction Checkers

— what's inside —

Core features

Six connected modules in one account, plus a bilingual AI assistant.

Drug Reference

10,000+ drug records with indications, dosing, contraindications, side effects and pharmacokinetics.

  • Classification: ATC, ICD-10 and ICD-11
  • Special populations: pregnancy and lactation data
  • Safety alerts: FDA recalls and drug shortages

Interaction Checkers

Check drug–drug, drug–food, drug–disease and drug–lab interactions, with severity levels and clinical significance.

  • Cross-allergy: checks across related drug groups
  • Herb–drug: botanical interaction checks
  • Predicted severity: machine-learning estimates where no curated rating exists

Pharmacogenomics

Gene–drug relationships, clinical annotations and CPIC-based dosing guidance, powered by PharmGKB.

  • Variants: SNP and haplotype details
  • Phenotypes: impact on drug response
  • Clinical annotations: dosing recommendations with evidence levels

Clinical Tools & Labs

15 clinical calculators plus interactive labs for dosing, kinetics and receptor pharmacology.

  • Calculators: eGFR, CrCl, BSA, infusion and dosing
  • Labs: PK simulator, dose–response and receptor occupancy
  • Docking: with RDKit, Open Babel and AutoDock Vina

Cosmetics & Herbal

5,000+ cosmetic products with an INCI ingredient database, plus 1,000+ medicinal plants and their phytocompounds.

  • Photo-safety: flags photosensitising ingredients
  • Drug–cosmetic: interaction checks
  • Skincare: skin-type quiz and personalised picks

Built for Türkiye

SUT/SGK compliance tools and TİTCK licensed-product data, alongside DruglyLex — our English–Turkish pharmacology dictionary.

  • SUT check: prescriptions and reports against SUT and EK-4 rules
  • SGK lookup: reimbursement status from the EK-4/A list
  • DruglyLex: English–Turkish pharmacology terms

See every feature

— built on trusted sources —

Where the data comes from

Drugly.ai brings together and structures data from established scientific, clinical and regulatory sources, including:

  • PharmGKBgene–drug knowledge
  • CPICPGx dosing guidelines
  • openFDAlabels, recalls & shortages
  • LactMeddrugs & lactation
  • WHO ATCdrug classification
  • ICD-10 · ICD-11disease coding
  • TİTCKproducts licensed in Türkiye
  • SGK SUTreimbursement rules
  • ChEMBLbioactivity data
  • UniProtprotein targets
  • IUPHAR/BPS Guide to PHARMACOLOGYreceptor pharmacology · CC BY-SA 4.0
  • PubMedscientific literature

Source names are shown for attribution only; Drugly.ai is not affiliated with, or endorsed by, these organisations.

Data licences & citation

Drugly’s receptor affinity and interaction data (drug monograph, Receptor Binding & Occupancy Lab, Docking Lab, receptor–ligand dashboard, AI Assistant answers, API responses and exports) include data from the IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb), alongside entries curated by the Drugly team. GtoPdb data are licensed under CC BY-SA 4.0; the database itself is licensed under ODbL.

GtoPdb-derived data on Drugly, including adapted values (e.g. the midpoint of a value range, ΔG derived from pX), remain available under CC BY-SA 4.0: you may use, adapt and share them provided you give credit and share under the same licence. Drugly is not affiliated with, or endorsed by, IUPHAR, the BPS or GtoPdb.

Citation: Harding SD, Armstrong JF, Faccenda E, Southan C, Alexander SPH, Davenport AP, Spedding M, Davies JA. The IUPHAR/BPS Guide to PHARMACOLOGY in 2026. Nucleic Acids Res. 2026;54(D1):D1446–D1456. doi:10.1093/nar/gkaf1067

Ready to explore?

Join licensed healthcare professionals using Drugly.ai for faster, better-structured professional reference.

Create Professional Account

Questions first? Write to hello@drugly.ai.