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This data package contains information on The Anatomical Therapeutic Chemical (ATC) Classification System which is used for the classification of active ingredients of drugs according to the organ or system on which they act and their therapeutic, pharmacological and chemical properties. It is controlled by the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC), and was first published in 1976.
Overview
Overview
The ATC (Anatomical Therapeutic Chemical) classification system divides drugs into different groups according to the organ or system on which they act, their therapeutic intent or nature, and the drug's chemical characteristics. Different brands share the same code if they have the same active substance and indications. Each bottom-level ATC code stands for a pharmaceutically used substance, or a combination of substances, in a single indication (or use). This means that one drug can have more than one code, for example, acetylsalicylic acid (aspirin) has A01AD05 (WHO) as a drug for local oral treatment, B01AC06 (WHO) as a platelet inhibitor, and N02BA01 (WHO) as an analgesic and antipyretic); as well as one code can represent more than one active ingredient, for example, C09BB04 (WHO) is the combination of perindopril with amlodipine, two active ingredients that have their own codes (C09AA04 (WHO) and C08CA01 (WHO) respectively) when prescribed alone. The ATC classification system is a strict hierarchy, meaning that each code necessarily has one and only one parent code, except for the 14 codes at the topmost level which have no parents. The codes are semantic identifiers, meaning they depict in themselves the complete lineage of parenthood.
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Metadata
| Description | Value |
|---|---|
| Data Package Complexity | Simple |
| Available Enrichments | N/A |
| Keywords | Tuberculosis, Communicable Diseases, Infectious Disease, Sexually Transmitted Disease, HIV Diagnose, Viral Hepatitis |
| Other Titles | Hepatitis in the United States, Hepatitis National Statistics, HIV/AIDS National Statistics, Tuberculosis Geographic Distribution |
Included Datasets
- Anatomical Therapeutic Chemical Alterations 2005 to 2022
This dataset contains the ATC (Anatomical Therapeutic Chemical) Alterations from 2005 to 2022.
- Anatomical Therapeutic Chemical Codes 2018 to 2023
This dataset contains the Anatomical Therapeutic Chemical (ATC) classification system. In ATC the active substances are divided into different groups according to the organ or system on which they act and their therapeutic, pharmacological and chemical properties.
- Defined Daily Dose Alterations 2005 to 2021
This dataset contains the DDD (Defined Daily Dose) Alterations from 2005 to 2021.
- Defined Daily Dose Codes for 2018 to 2023
This dataset contains the Defined Daily Dose (DDD) 2018 to 2023. In order to measure drug use, it is important to have both a classification system and a unit of measurement. To deal with the objections against traditional units of measurement, a technical unit of measurement called the Defined Daily Dose (DDD) to be used in drug utilization studies was developed.
Data Engineering Overview
We deliver high-quality data
- Each dataset goes through 3 levels of quality review
- 2 Manual reviews are done by domain experts
- Then, an automated set of 60+ validations enforces every datum matches metadata & defined constraints
- Data is normalized into one unified type system
- All dates, unites, codes, currencies look the same
- All null values are normalized to the same value
- All dataset and field names are SQL and Hive compliant
- Data and Metadata
- Data is available in both CSV and Apache Parquet format, optimized for high read performance on distributed Hadoop, Spark & MPP clusters
- Metadata is provided in the open Frictionless Data standard, and its every field is normalized & validated
- Data Updates
- Data updates support replace-on-update: outdated foreign keys are deprecated, not deleted
Our data is curated and enriched by domain experts
Each dataset is manually curated by our team of doctors, pharmacists, public health & medical billing experts:
- Field names, descriptions, and normalized values are chosen by people who actually understand their meaning
- Healthcare & life science experts add categories, search keywords, descriptions and more to each dataset
- Both manual and automated data enrichment supported for clinical codes, providers, drugs, and geo-locations
- The data is always kept up to date – even when the source requires manual effort to get updates
- Support for data subscribers is provided directly by the domain experts who curated the data sets
- Every data source’s license is manually verified to allow for royalty-free commercial use and redistribution.
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About Us
John Snow Labs , an AI and NLP for healthcare company, provides state-of-the-art software, models, and data to help healthcare and life science organizations build, deploy, and operate AI projects.
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The Product Access unit grants subscribers use of the classification system. The license provides access to all features, with no limit on the number of users or the number of searches performed.
The Product Access dimension carries no charge on the Marketplace. Running the software on your own infrastructure through the cloud provider can generate underlying compute and hosting costs. An on-premise deployment requires a separate license key obtained directly from the vendor.
No. The software installs and runs entirely within your own infrastructure. Queries stay inside your secure network, with no persistent storage of patient identifiers or clinical notes. Only standard terminologies and user-defined mappings are stored, keeping data within your control.
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Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
Anatomical Therapeutic Chemical Alterations 2005 to 2022 | All historical revisions | All future revisions | Not included | |||
Anatomical Therapeutic Chemical Codes 2018 to 2023 | All historical revisions | All future revisions | Not included | |||
Defined Daily Dose Alterations 2005 to 2021 | All historical revisions | All future revisions | Not included | |||
Defined Daily Dose Codes for 2018 to 2023 | All historical revisions | All future revisions | Not included |
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UNIQUE BENEFITS FOR TRAINING
PARTICIPANTS:
Participants will engage with real-
-world attack techniques encounte-
red in actual cybercriminal activities.
They will also gain access to speciali-
zed cybersecurity systems, including
Endpoint Detection and Response
(EDR) with live forensics capabilities (also with protection of AWS resources to showcase cloud attack examples).
These tools will allow participants to
observe how effectively specific cybe-
rattack techniques can be detected
using advanced security tools. The
skills acquired during this training will
significantly enhance participants’
ability to detect and respond to real-
-world cyberattacks at an early stage.
UNIQUE BENEFITS FOR TRAINING
PARTICIPANTS:
Participants will engage with real-
-world attack techniques encounte-
red in actual cybercriminal activities.
They will also gain access to specia-
lized cybersecurity systems, inclu-
ding a Next-Generation Firewall with
comprehensive security features and
Endpoint Detection and Response
(EDR) with live forensics capabilities (also with protection of AWS resources to showcase cloud attack examples).
These tools will allow participants to
observe how effectively specific cybe-
rattack techniques can be detected
using advanced security tools. The
skills acquired during this training will
significantly enhance participants’
ability to detect and respond to real-
-world cyberattacks at an early stage.