ISO/TS 21405

ISO/DTS TS:21405(E)
ISO/TC 215/WG 6
Secretariat: ANSI
Date: 2025-06-2011-14
Health informatics — Identification of medicinal products —
Methodology and framework for the development and
representation of IDMP ontology

DTS stage
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ISO #####-#:####(X)
Informatique de santé — Identification des médicaments — Méthodologie et cadre pour le développement et la
représentation de l’ontologie IDMP
2 © ISO #### – All rights reserved

ISO/DTS 21405:2025(E:(en)
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iii
ISO/DTS 21405:2025(E:(en)
Contents
Foreword . Error! Bookmark not defined.
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Benefits of an ontological approach for IDMP . 4
4.1 General . 4
4.2 Recommended methodology for collaborative IDMP ontology development – Ontology
governance in a collaborative ontology development framework . 6
4.3 Governance structures in ontology development and maintenance in alignment with the
ISO standards on IDMP . 7
5 Use cases for an IDMP ontology . 7
5.1 Practical applications of IDMP ontology in regulatory frameworks . 7
5.2 Identifying substances, pharmaceutical and medicinal products unambiguously . 8
5.3 Enabling interoperability between regulatory, manufacturing and healthcare domains . 19
5.4 Jurisdiction-agnostic medicinal products . 33
5.5 Ensuring interoperability between regulatory, clinical development and healthcare
domains . 35
5.6 Ensuring global interoperability for the detection of supply chain and drug shortages . 36
Annex A (informative) Examples of regional implementation . 37
Bibliography . 43

iv
ISO/DTS 21405:2025(E:(en)
Foreword
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ISO/IEC Directives, Part 2 (see www.iso.org/directives).
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However, implementers are cautioned that this may not represent the latest information, which may be
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This document was prepared by Technical Committee ISO/TC 215, Health informatics, in collaboration with
the European Committee for Standardization (CEN) Technical Committee CEN/TC 251, Health informatics, in
accordance with the Agreement on technical cooperation between ISO and CEN (Vienna Agreement).
Any feedback or questions on this document should be directed to the user’s national standards body. A
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v
ISO/DTS 21405:2025(E:(en)
Introduction
The set of five ISO 11615, ISO/TS 20443, ISO/TS 20451, ISO 11238, ISO/TS 19844, ISO 11239, ISO/TS 20440,
and ISO 11240 are the ISO Standards and four ISO Technical Specifications, which together provide the basis
for the unique Identification of Medicinal Products,identification of medicinal products (IDMP), comprise ISO
11615; ISO/TS 20443; ISO/TS 20451; ISO 11238; ISO/TS 19844; ISO 11239; ISO/TS 20440; and ISO 11240. ).
These sets of standards and technical specificationsdocuments present an opportunity to create global data
interoperability for the unambiguous identification of medicinal products. However, implementations of IDMP
by various IDMP stakeholders across jurisdictional domains are not fully standardized or harmonized and risk
inconsistency of interpretation. A uniform approach is needed so that the envisioned benefits from IDMP in
drug safety, innovation, regulatory, and other areas can be fully realized.
This document proposes an ontological framework for IDMP to provide the overarching structure and
principles for organizing knowledge within the domain of unambiguous identification of medicinal products.
Such a framework can provide the necessary foundation for global data interoperability through a set of
concepts, formal definitions and other metadata, their properties, the relations between them, and the logical
expressions that disambiguate them. This IDMP ontological framework complements the existing conceptual
models defined in the ISO documents on IDMP standards and technical specifications.
An IDMP ontology instantiates the principles represented in the IDMP ontological framework through a
particular representation of this domain knowledge. Furthermore, an IDMP ontology provides formal
semantic definitions for IDMP concepts that allow auto-classification and linkage of IDMP data and detection
of data issues and decrease the potential for misinterpretations and incorrect reporting.
The modelling of IDMP standards in the form of an open ontology requires the application of a set of rigorous
processes combined with various technology components, which together form a collaborative ontology
development structure. This framework includes feedback loops to IDMP stakeholders and interested parties,
including regulators and standards development organizations (SDOs), to ensure the relevant level of
governance for the accurate representation of IDMP standards representation.
Furthermore, considering the current global initiatives towards data interoperability, this ontological
framework aims to leverage and support those initiatives towards the common goal of cross-jurisdictional
unambiguous identification of medicinal products.
vi
ISO/DTS 21405:(en)
Health informatics — Identification of medicinal products —
Methodology and framework for the development and representation
of IDMP ontology
1 Scope
This document describes a standardized methodology and framework in support of anfor the development
and representation of an ontology that supports a global, open-source, global approach to adoption
ofimplementing the ISO standards on the identification of medicinal products (IDMP) (ISO 11615;,
ISO/TS 20443;, ISO/TS 20451;, ISO 11238; ISO/TS 19844;, ISO 11239;, ISO/TS 20440;, and ISO 11240) in the
form of an ).ontology. Realization of the full potential of IDMP requires fully self-describing data. For this
purpose, this document describes a methodology and framework that complements these sets of ISO IDMP
standardsthe existing conceptual and logical models in the ISO documents on IDMP with an IDMP ontology
that enables deep, semantic interoperability based on findable, accessible, interoperable and reusable (FAIR)
data principles. This methodology and framework enhance the usage of the IDMP data model as the foundation
of medicinal product identification and will ultimately enable collaboration towards drug safety and overall
operational efficiency.
This methodology and framework complement the existing conceptual and logical models in the ISO standards
on IDMP and corresponding technical specifications. This document also describes a methodology for the agile
adaptation of the ISO documents on IDMP standards in connection with cross-jurisdictional IDMP-related
legislation and initiatives. This document is intended to be complementary to and independent from formal
regulatory guidance. Thus, it enables cross-jurisdictional consistency and supports stakeholders in their
regional implementations of IDMP standards. This document does not mandate any specific ontology as an
implementation tool, nor is it an instructional guideline on how to build an ontologyontologies, which is out
of scope of this document.
This document includes key use cases described in the ISO standardsdocuments on IDMP ISO 11615,
ISO 11238 and ISO/TS 19844, as well as further use cases arising from the comprehensive deployment of the
ISO standardsdocuments on IDMP via an ontological framework. Thus, an ontology that represents the IDMP
standards aims to cover the complete collection of ISO standards on IDMP regarding key interoperability
issues that implementing stakeholders are facing.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp
— IEC Electropedia: available at https://www.electropedia.org/
3.1 3.1
axiom
statement that is taken to be true, to serve as a premise for further reasoning
ISO/DTS 21405:(en)
Note 1 to entry: Axioms may be formulated as natural language sentences or as formulae in a formal language. In the Web
Ontology Language (OWL) community, ‘Axiom’ is used to refer to statements that say what is true in the domain that are
‘basic’ in the sense that they are not inferred from other statements.
[SOURCE: ISO/IEC 21838-1:2021, 3.9]
3.2 3.2
chemical class
a grouping that relates chemicals by similar features.
Note 1 to entry: Chemicals can be classified by their structure (e.g. hydrocarbons), uses (e.g. pesticides), physical
properties ([e.g. volatile organic compounds [(VOCs]),)], radiological properties (e.g. radioactive materials), or other
factors.
Note 2 to entry: Adapted from Reference [18[SOURCE: Agency for Toxic Substancs and Disease Reigstry
(ATSDR)[1]
3.3
].
3.3
competency question
query that represents requirements in the form of questions
Note 1 to entry: An ontology (3.12) is required to answer competency questions.
Note 2 to entry: Adapted from Reference [19[2].].
3.33.4 3.4
concept
unit of knowledge created by a unique combination of characteristics
[SOURCE: ISO 1087:2019, 3.2.7, modified – — Notes to entry removed.]
3.43.5 3.5
conceptual model
description of common concepts (3.4) and their relationships, particularly in order to facilitate exchange of
information between parties within a specific domain of healthcare
[SOURCE: ISO/TS 18864:2017, 3.6]
3.53.6 3.6
functional group
in organic chemistry, any substituent or moiety in a molecule that causes the molecule’s characteristic
chemical reactions
Note 1 to entry: Adapted from Reference [20[SOURCE: Compendium of Chemical Terminology (IUPAC
“Gold Book”)][3]
3.7].
3.63.7
international nonproprietary name
INN
generic name
ISO/DTS 21405:(en)
globally recognised unique name of pharmaceutical substance and active pharmaceutical ingredient
Note 1 to entry: International Nonproprietary Namenonproprietary name (INN) facilitates the identification of
pharmaceutical substances or active pharmaceutical ingredients.
Note 2 to entry: In principle, INNINNs are selected only for the active moiety of the molecule, which is usually the base,
acid, or alcohol.
Note 3 to entry: Each INN is public property.
Note 4 to entry: Adapted from Reference [21[4]].
3.73.8 3.8
international nonproprietary name modified
INNM
extension of international nonproprietary name (INN) (3.7) including inactive moiety of the molecule
EXAMPLE : While oxacillin and ibufenac are INNs, oxacillin sodium and ibufenac sodium are INNMs designating
their salts in the name.
Note 1 to entry: Adapted from Reference [21[4].].
3.83.9
3.9
knowledge graph
graph representation of structured knowledge on concepts (3.4) and relationships between them
Note 1 to entry: A knowledge graph can comprise an ontology (3.12) and data related to the ontology.
Note 2 to entry: A knowledge graph can be represented as a collection of triples, with each triple (head, tail, relation)
denoting the fact that relation exists between head entity and tail entity.
[SOURCE: ISO/IEC 5392:2024, 3.14]
3.93.10 3.10
logical model
information model that specifies the structures and relationships between data elements but is independent
of any particular technology or implementation environment
[SOURCE: ISO 13972:2022, 3.1.8, modified — The preferred term “logical information model” was removed.]
3.103.11 3.11
metadata
record containing a description of a resource
[SOURCE: ISO 24622-1:2015, 2.10, modified — The preferred terms “metadata record” and “metadata
description” were removed.]
3.113.12 3.12
ontology
formal, explicit specification of a shared conceptualization
Note 1 to entry: An ontology typically includes definitions of concepts (3.4) and specified relationships between them, set
out in a formal way so that a machine can use them for reasoning.
Note 2 to entry: An ontology provides a comprehensive description of terminology, concepts, and nomenclature; outlines
the relationships among and between concepts and individuals; and includes statements that clarify concepts, refine
ISO/DTS 21405:(en)
definitions, and specify relationships (such as constraints, restrictions, and regular expressions) relevant to a particular
[ ]
domain or area of interest. 22. [5]
Note 3 to entry: Conceptualization is meant to denote the objects, concepts, and other entities that are presumed to exist
[ ]
in some area of interest and the relationships that hold them. 23. [6]
[SOURCE: ISO 25964-2:2013, 3.57 modified –— Note 1 to entry was changed, Notes 2 and 3 were added].]
3.123.13 3.13
provenance
information on the place and time of origin, derivation or generation of a dataset, proof of authenticity of the
dataset, or a record of past and present ownership of the dataset
[SOURCE: ISO/IEC 11179-33:2023, 3.11]
3.133.14 3.14
regression test
test type used following modifications to a test item or to its operational environment, to identify whether
regression failures occur
[SOURCE: ISO/IEC/IEEE 29119-1:2022, 3.64, modified — Changed term from "regression testing" to
"regression test"; changed "testing performed" to "test type used"; changed "failures in unmodified parts of
the test item" to " regression failures": removed notes to entry.]
3.15
Note 1 to entry: Adapted from ISO/IEC/IEEE 29119-1:2022, 3.64.
3.15
use case
description of behavioural requirements of a system and its interaction with a user
Note 1 to entry: A use case describes the users’ goal and the requirements including the sequence of interactions between
users and the system.
[SOURCE: ISO/IEC/IEEE 26515:2018, 3.15]
3.143.16 3.16
user story
simple narrative illustrating a user requirement from the perspective of a persona
[SOURCE: ISO/IEC/IEEE 26515:2018, 3.16]
3.153.17 3.17
vocabulary
terminological dictionary that contains designations and definitions from one or more domains or subjects
[SOURCE: ISO 1087:2019, 3.7.5], modified — Note 1 to entry was removed.]
4 Benefits of an ontological approach for IDMP
4.1 General
The provision of a shared vocabulary and a common understanding of concepts and relationships (conceptual
model) enables information to be shared and reused across different applications and domains. In a logical
model, relationships and data structures are further specified. Ontologies can facilitate interoperability even
further by providing a formal framework for querying, reasoning and inference, which enables automated
ISO/DTS 21405:(en)
processing of information based on logical rules and constraints. Figure 1Figure 1 shows the differences
between glossary, conceptual model, logical model and ontology, demonstrating an increased semantic
enrichment at each upper level.
2 3 4
Vocabulary
Conceptual Model Logical Model Ontology
common common approach to
common common data
terminology implementa�on
understanding structures
• concepts & • concepts & • concepts & • Concepts &
defini�ons defini�ons defini�ons defini�ons
• rela�onships • rela�onships • rela�onships
• constraints • constraints • constraints
• data structures • data structures
• axioms • axioms
• machine-readable
• interoperable
terminological descrip�on of common informa�on model that formal, explicit specifica�on
dic�onary that concepts and their specifies the structures of a shared conceptualiza�on
contains designa�ons rela�onships, par�cularly in and rela�onships between
An ontology typically includes
and defini�ons from order to facilitate exchange data elements but is
defini�ons of concepts and
one or more domains of informa�on between independent of any
specified rela�onships
or subjects par�es within a specific par�cular technology or
between them, set out in a
domain of healthcare implementa�on
formal way so that a machine
environment
can use them for reasoning
Key
1 ISO 1087:2019
2 ISO/TS 18864:2017
3 ISO 13972:2022
4 ISO 25964-2:2013
ISO/DTS 21405:(en)
Figure 1 — Differences in semantic richness between vocabulary, conceptual model, logical model,
and ontology
4.2 Recommended methodology for collaborative IDMP ontology development – Ontology
Governancegovernance in a collaborative ontology development framework
Governance in the context of ontology-related work provides a set of rules, policies, and procedures for
managing the ontology development process, and is thus critical to the success of collaborative ontology
development. It ensures that all involved stakeholders work effectively towards common goals, and that the
resulting ontology is consistent, accurate, and useful. The framework for overall development of an IDMP
ontology is the set of ISO IDMP standards on IDMP and related standards on their implementation guides.
Extensions to that framework supporting the development of the IDMP ontology described hereininclude:
herein include:
[ ]
— Developmentdevelopment guidelines and policies 24 [7] ;
[ ]
— Commoncommon, standardized modelling patterns 25 [8] ;
— Methodsmethods for mapping the ontology to reference as well as internal pharma company data to prove
[ ]
the efficacy and interoperability of the ontology 26 [9] ;
[ ]
— Samplesample data and queries for regression testing 27 [10] ;
— Aa continuous integration (CI) and continuous delivery (CI or CD) environment supporting global
[ ]
development collaboration 28 [11] .
The methodology supported herein adheres to the policies and guidelines, follows best practices in ontology
engineering, including development of key use cases and scoping competency questions as described in
Clause 5below,, and extends best practices using this framework for collaborative development, evolution,
and maintenance.
Important governance requirements in collaborative ontology development, which mightcan also be
beneficial in ensuring the wide adoption of ISO IDMP standards on IDMP, include the following.
ISO/DTS 21405:(en)
— - Standardization: Ontology governance ensures that all ontology developers follow the same standards,
naming conventions, and modelling methodologies, making it easier to integrate and share ontologies
across different systems and other ontologies.
— - Quality Assurance: Ontology governance provides guidelines for verifying the accuracy and
completeness of the ontology, ensuring that it meets the needs of its intended users, and that it is free of
errors and inconsistencies. It also provides a feedback mechanism that is required for continuous
improvement and for any incident requiring immediate attention.
— - Collaboration: Ontology governance encourages collaboration and communication among ontology
developers, helping them to identify and resolve issues, share knowledge, and ensure that the ontology is
aligned with the needs of its stakeholders and business area.
— - Management: Ontology governance provides a framework for managing the development and
maintenance of the ontology, including versioning, change management, and release management.
— - Sustainability: Ontology governance helps to ensure the sustainability of the ontology by providing
guidelines for ongoing maintenance and updates and ensuring that the ontology remains relevant and
useful over time.
4.3 Governance structures in ontology development and maintenance in alignment with
the ISO IDMP standards on IDMP
Decisions regarding ontology modelling and adaptations can be made by an executive board consisting of
standards development organizations, e.g.,. ISO, HL7 FHIR, regulatory agencies, pharma representatives and
further stakeholders, to ensure their alignment. These changes can be related to e.g. emerging requirements,
IDMP model clarification, controlled vocabularies, cardinalities and other constraints, and implementation
lessons learned, and include updates due to results of the systematic reviews of each of the ISO IDMP standards
on IDMP. These are implemented and documented in the IDMP ontology in an agile manner. In addition, end-
to-end testing for quality assurance and regression tests are performed throughout the ontology development
process, to identify any errors in syntax, logic, potential performance issues, missing content required by
development policies and guidelines, and other quality-related issues.
5 Use cases for an IDMP ontology
5.1 Practical applications of IDMP ontology in regulatory frameworks
The overarching goals of integrating and managing product data within an organizational framework
encompass a variety of critical business questions that need answers to ensure operational efficiency and
compliance. The unambiguous identification of medicinal products is vital for gaining and maintaining
oversight of the various identifiers involved in the manufacturing and regulatory processes. This clear
identification and linkage of product information entities to their medicinal products and manufactured items
are crucial for streamlining manufacturing operations, increasing quality and responsiveness, and ensuring a
smooth supply chain, and promoting patient safety at the end of the supply chain promoting patient safety.
Furthermore, establishing a robust association between the internal and external identifiers required for
product data submission is essential for regulatory compliance and efficiency. By simplifying product data
management processes, the goal is to increase overall performance and reduce the occurrence of errors, which
can have far-reaching implications for both safety and compliance. Improving data best practices is another
key objective, ensuring that the organization'sorganization’s data management strategies are aligned with
industry standards and across the industry domain. This includes enabling an automation strategy to reduce
manual interventions and increase reliability across all aspects of product data management.
An IDMP ontology also aims to unlock advanced analytics potential, particularly in the realm of
pharmacovigilance, where the ability to analyzeanalyse data effectively can lead to significant improvements
ISO/DTS 21405:(en)
in signal detection, and consequently patient safety and product quality. The use of an IDMP ontology as a data
fabric will enhance multi use case support, increasing the high precision required in the representation of
scientific knowledge. Using its natural property of modularity, this ontology will support different
pharmaceutical industry use cases and processes ensuing a constant alignment with IDMP specifications.
The use of an IDMP ontology should be thoroughly tested end-to-end with publicly available data as well as
internal pharma company data to prove its efficacy. The ISO standards on IDMP being revised on a regular
basis, there is a need to ensure a continuous testing with any further revisions for regular checks on backwards
compatibility.
With regards to some key quality assurance criteria, the creation of an IDMP ontology requires the
establishment of internal, organization-specific, set of testing to ensure each new version of the ISO standards
on IDMP results in a smooth integration and careful assessment of the potential impacts. This can be achieved
by setting-up a regression testing, a testing regarding syntactic pitfalls, to maintain backwards compatibility
by analysing the impact of the changes. The setting of acceptance criteria for assessing the quality and
completeness of the ontology, and ensuring it meets regulatory requirements and interoperability standards
will depend on the level of criticality of the IDMP ontology and the systems using it (e.g. GxP, non-GxP). This
way the quality of the ontology is ensured and sustainable for the organization, ensuring a continuous support
of the evolving use cases.
Exemplary use cases specific to the application of an IDMP ontology are described in 5.2, 5.3, 5.4, 5.5chapters
5.2; 5.3; 5.4; 5.5;, and 5.65.6.
5.2 IdentifyIdentifying substances, pharmaceutical and medicinal products unambiguously
5.2.1 Use case (UC) 1: Ensure (UC1): Ensuring unambiguous identification of substances
For the representation of the ISO IDMP standards on IDMP in an ontological format, an important use case to
consider is that of the unambiguous identification of substances. It emphasizes the importance of establishing
a robust, interoperable framework that enables the consistent and accurate classification of substances in
medicinal products. An IDMP ontology facilitates a unified structure for medicinal product information, thus
supporting regulatory compliance and enhancing the efficiency and reliability of data-sharing across borders
and contributing to improved patient safety.
5.2.2 Area of focus
The area of focus of UC1 for unambiguous substance identification is as follows:
— ISO 11238:2018
o Entities and relationships defined in the standard
— E, e.g.,. substance relationship (parent relation), active moiety, etc.
— Substance information:, e.g.,. INN/INNM.
— ISO 11615:2017
— Relations between Substance, Investigational and Authorized Medicinal Product (separate use cases)).
— A substance comprises an ingredient.
— An ingredient is used in a pharmaceutical product.
— A pharmaceutical product is a component of a medicinal product.
ISO/DTS 21405:(en)
— A substance comprises an ingredient.
— An ingredient is included in a manufactured item.
— A manufactured item is contained in a packaged item.
— A packaged item constitutes a packaged medicinal product.
— A packaged medicinal product is an instance of a medicinal product.
— Product cross-reference between Investigational and Authorized medicinal product.
— Predefined instance datasets including example substances, e.g. amlodipine.
5.2.3 UC1 description
The objective of this use case is to enable the maintenance of substance data and link it with both external and
internal standards. For instance, it is essential to distinguish between the active form and the salt or solvate
form of a substance or between the whole plant and its extract in a herbal. This will also enable the ability to
track changes across all relevant domains without manual intervention. The proper identification of the
substance and its related entities and identifiers allows a simple alignment between systems in multiple
departments, such as Clinical Trial Management Systems clinical trial management systems (CTMS),
Referencereference and Master Data Management systems ((master data management [(R)MDM), Enterprise
Resources Planning (] systems, enterprise resources planning [ERP (e.g.,. SAP),)], and Regulatory Information
Managementregulatory information management (RIM) systems, linking to the "“real substance"” concept,
and establishing a unique identifier (ID) for substance specifications.
Currently, the process is bogged down by manual efforts and extensive knowledge required to cross-reference
external databases with internal MDM and golden source systems. This results in repetitive, siloed, manual
data curation across various levels and systems, alongside manual report generation to bridge information
gaps, which is not only time-consuming but also prone to errors.
The envisioned gains and benefits of this use case within an IDMP ontology are multifaceted. Aligning data
[ ]
with a central knowledge graph (KG), e.g. the Global Substance Registration System (GSRS), 29)[12], ensures
data quality and eliminates the need for individual manual efforts by defining relationship types based on
trusted external standards. It facilitates the integration of substance data with other companies, such as during
mergers or when using comparator substances in clinical trials. An ontology also allows for the identification
and documentation of hierarchical relationships between substances based on global standards, identifies the
source/ or reference of a substance name to support data maintenance and quality assurance, and provides
trust and transparency in the data linkage by making the origin of data visible directly in the ontology
(metadata and provenance).
5.2.4 Stakeholders, actors, interfaces
In the complex landscape of pharmaceutical development and regulation, a diverse group of stakeholders are
pivotal in the unambiguous identification of substances. These include health authorities and data sources
across departments in pharma companies such as clinical; regulatory affairs; chemistry, manufacturing, and
controls (CMC); manufacturing; and pharmacovigilance. Key actors within these groups of stakeholders such
as master data managers and substance data stewards manage and oversee the integrity of substance data in
tandem with health authority reviewers to ensure compliance and safety across all stages of pharmaceutical
product development and management.
A network of systems and interfaces facilitates the management and exchange of substance data, including
global and regional substance registries such as the GSRS and the European Union Substance Registration
System (EU-SRS), alongside internal interfaces that bridge various departments like regulatory affairs (RA),
ISO/DTS 21405:(en)
clinical, CMC, product supply, and the CTMS with the MDM system. Additionally, the World Health
Organization'sOrganization’s International Nonproprietary Names (WHO INN) system, anatomical
therapeutic chemical (ATC) coding system, various pharmacopoeias, and the Extended EudraVigilance
Medicinal Product Dictionary (xEVMPD) for encoding medicinal products are integral parts of this system
landscape.
The data entities involved in this system landscape include active substances, excipients, adjuvants, and the
active moiety along with parent-child relations, which are critical for understanding the compositions of
pharmaceutical products and manufactured items. These entities also extend internally in pharma research
and development (R&D) to relations with projects, clinical studies, and other key components of the
pharmaceutical development process.
This domain-specific variability within the substance identification landscape poses challenges with data
accuracy for all involved stakeholders. To address these challenges, an IDMP ontology provides a structured
framework that supports harmonization of data definitions and relationships across relevant systems and
interfaces.
5.2.5 UC1 usage scenarios
5.2.5.1 Introduction to usage scenarios
Usage scenarios are specific, contextual examples that illustrate how the ontology will be utilized to represent
and organize knowledge within a given domain. They elaborate on the requirements outlined in the
description, including identification of requirements specific to an envisioned ontology or semantically driven
service or application. Scenarios are described as narrative, with supporting diagrams as appropriate. In an
agile process, every user story relevant to the use case should be included into one or more usage scenarios.
5.2.5.2 Usage scenario 1: alignalignin the ingredient with its relevant role
As a data producer, the goal is to verify and correct all ingredient roles, to improve knowledge of the
ingredients in a formula and enhance data flow from product lifecycle management (PLM) system to the
regulatory information management (RIM) system.
Previously, the role of the ingredient was only determined as active or excipient. The IDMP standard provides
4 roles – active, excipient, solvent/ or diluent, adjuvant. A verification of all the formulas by chemists is needed
to specify the role of each ingredient. A mass loading of data will need to be carried out.
5.2.5.3 Usage scenario 2: Identifyidentifying all clinical studies in which medicinal products
were administered in region
a) As a member of a regulatory agency validation group, the goal is to assess and characterize new
substances and identify substance relationships and ensure data quality on an ongoing basis, based on
globally standardized substance data.
b) A regulatory agent requests information of a Pharmapharma company on all clinical studies in which any
of the company’s authorized medicinal products were administered to patients.
c) The request is received by the CTMS data steward who queries registered products ([including medicinal
product identifiers (MPIDs)))] in a specific region.
d) The Master Data Managermaster data manager identifies all substances contained in the medicinal
products registered in the region. The substance data are aligned with external standards to avoid
misunderstandings and ensure patient safety.
e) The Master Data Manager/Substance Data StewardThe master data manager/substance data steward
queries substances (including internal and external IDs) contained in those clinical studies in the
ISO/DTS 21405:(en)
Substance Registrysubstance registry (based on, or sourced from GSRS, in a system to be defined, ideally
in a knowledge graph) where relevant internal and external data alignments are defined in the IDMP-
compatible way.
f) Based on this information, the Master Data Managermaster data manager collects relevant clinical studies
data from internal source systems and reports this information back to the Health Authorityhealth
authority.
Figure 2
Figure 2 represents the process flow addressed in use case 1: Ensure unambiguous identification of
substances.
UC1 Diagram
Ensure
Figure 2 — Use case 1: ensuring unambiguous identification of substances
5.2.5.4 UC1 competency questions (CQ)
5.2.5.4.1 Introduction to competency questions
Competency questions (CQ) are natural language questions outlining and constraining the scope of knowledge
[ ]
represented in an ontology. 30 [13]. They are questions that guide the selection of concepts, properties, and
relationships that the ontology needs to represent.
ISO/DTS 21405:(en)
5.2.5.4.2 CQ1: Which substances have the common active moiety ?
A medicinal product can contain a mixture of substances each of which can have different roles (active,
excipient, solvent ordiluentor diluent, adjuvant). It is the active ingredient in a medicinal product that is
responsible for the pharmacological activity of the medical product. In turn, the active moiety refers to the
part of the active ingredient which exerts the pharmacological action of the substance. This can consist of only
a part of or the entire molecule of the substance that is designated as the active ingredient. Since an active
moiety can exist in different forms in different substances, it is useful to be able to identify the possible
substances that have a certain common active moiety. This unambiguous identification of substances and
active moieties will enable a clear oversight of the involved substance identifiers.
EXAMPLE : Amlodipine
— Question: Give meWhat are all substances that have a common active moiety .>?
— Answer: Amlodipine besylate (+ internal substance ID)
— The dosage of the medicinal product is carried by the amount of alone, and not by the salt
.
— Answer: Amlodipine mesylate monohydrate (+ internal substance ID)
— In addition to the salt, the level of hydration is not to be considered for the same reason as above.
Figure 3Figure 3 demonstrates the query pattern for CQ1.

ISO/DTS 21405:(en)
Figure 3 — Query pattern diagram for CQ1 “Which substances have the common active moiety
?”
5.2.5.4.3 CQ2: What is the active moiety of ? Alternatively, what is the parent
substance of the substance ?
Whereas CQ1 starts with an active moiety and identifies all substances having that common active moiety,
CQ2 starts with a substance and identifies the active moiety for the substance. A substance is defined as a
matter of defined composition that has discrete existence, whose origin can be biological, mineral, or chemical.
A moiety is an entity within a substance that has a complete and continuous molecular structure. The strength
of a pharmaceutical product is often based on what is referred to as the active moiety of the molecule,
responsible for the physiological or pharmacological action of the drug substance. Linking a substance and its
active moiety not only gives clarity on how the substance potentially exerts its pharmacological activity, but
also, due to the way the ontology is modelled, gives an overview of how active moieties can be differently
defined under different contexts.
EXAMPLE Amlodipine
— Question: What is the parent substance of the substance Amlodipine Besylate (+ internal substance ID)?
— The display label of the input for the variable is made up of the preferred name (Amlodipine Besylate)
and internal substance ID (xyz) of the substance.
— Answer: Amlodipine (+ internal substance ID)
— The answer is made up of the preferred name (Amlodipine) and internal substance ID (mno) of the parent
substance queried.
Figure 4Figure 4 demonstrates the query pattern for CQ2.

ISO/DTS 21405:(en)
Figure 4 — Query pattern diagram for CQ2 “What is the parent substance of substance ?”
ISO/DTS 21405:(en)
5.2.5.4.4 CQ3: What are the products that contain substances with common active moiety
?
EXAMPLE : Amlodipine
— Question: What substances are related to the product family Amlodipine?
— Answer: Amlodipine, Amlodipine Besylate, Amlodipine Maleate, Amlodipine Mesylate, Amlodipine Benzoate,
Amlodipine Orotate, Amlodipine Hydrochloride, Amlodipine Camsylate, and Amlodipine Adipate.
— The answer is made up of the preferred names (Amlodipine Besylate, Amlodipine Maleate, …) and internal
substance IDs of the parent substance queried.
Figure 5Figure 5 demonstrates the query pattern for CQ3.

Figure 5 — Query pattern diagram for CQ3 “What are the products that contain substances with
common active moiety ?”
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