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Pharmaceutical Quality/Chemistry, Manufacturing & Controls (PQ/CMC)


As part of an effort intended to support future electronic acquisition and use of submitted information, FDA has undertaken a project to identify and prioritize pharmaceutical quality/chemistry, manufacturing and controls (PQ/CMC) information that would benefit from a structured submission approach. This structured and standardized information is intended to be submitted in the Module 3 of the Common Technical Document as defined by the International Council for Harmonisation’s (ICH) M4 Common Technical Document (CTD). The effort is scoped to some of what is currently submitted in Module 3 of the electronic Common Technical Document (eCTD) submission. It is not intended to be comprehensive in covering all eCTD product quality information, only those concepts that were considered amenable to structuring and would bring value to the quality review process.

The goal of this project is to establish electronic standards for submitting Pharmaceutical Quality (PQ) and Chemistry & Manufacturing Controls (CMC) data.

Specific objectives of the PQ/CMC Project are:

  1. Develop structured data standards for PQ/CMC
  2. Develop a data exchange standard for submitting the structured PQ/CMC data to the FDA

The submission of structured data in a standardized format should increase the efficiency of FDA’s review of PQ/CMC data contained in the Module 3 of eCTD submissions for a New Drug Application (NDA), an Investigational New Drug Application (IND), a Biologics License Application (BLA), an Abbreviated New Drug Application (ANDA), a New Animal Drug Application (NADA), an Abbreviated New Animal Drug Application (ANADA), an Investigational New Animal Drug (INAD), Generic Investigational New Animal Drugs (JINADs), and a Master File (MF).

For consistency of product quality data across FDA centers, the draft standardized data elements and terminologies were created by an Agency workgroup comprised of Subject Matter Experts (SMEs) from the Center for Drug Evaluation and Research (CDER), the Center for Veterinary Medicine (CVM), and the Center for Biologics Evaluation and Research (CBER).

1The Common Technical Document for the Registration of Pharmaceuticals for Human Use: Quality – M4Q(R1)

2Electronic Common Technical Document Specification V3.2.2

PQ-CMC CTD Triangle Figure 1: ICH CTD Modules

Figure 1: ICH CTD Modules

Data Standards Development Overall Scope

PQ/CMC structuring and standardization is intended to be accomplished in multiple phases. For the first phase, the Agency has focused on some of the sections of ICH eCTD that will provide the foundation for future phases.

  • Phase 1 covers the following topics: Drug Product, Drug Substance, Quality Specification, Batch Formula, Batch Analysis and Stability.
  • Phase 2 data standards are under development, and will cover the following topics: Drug Product Manufacturing, Drug Substance Manufacturing, etc.

The Phase 1 data elements are grouped logically into domains. The table below shows how the logical groups align with the ICH eCTD Module 3 sections.

# PQ/CMC Groups ICH eCTD Section Names ICH eCTD (v 3.2.2) Module Sections
1 Drug Substance Nomenclature and Structure 3.2.S.1.1; 3.2.S.1.2
Control of Materials 3.2.S.2.3; 3.2.S.2.4 (for intermediates ONLY)
Characterisation - Elucidation of Structure and other Characteristics 3.2.S.3.1
Characterisation - Impurities 3.2.S.3.2
2 Drug Product Description and Composition 3.2.P.1
Batch Formula 3.2.P.3.2
Control of Excipients - Specifications 3.2.P.4.1
Characterisation of Impurities 3.2.P.5.5
3 Quality Specification for Substance & Product Specification (includes Text and Acceptance Criteria) 3.2.S.4.1; 3.2.P.5.1
4 Batch Analysis for Substance & Product Batch Analysis and Batch information 3.2.S.4.4; 3.2.P.5.4
5 Stability for Substance & Product Stability Data 3.2.S.7.3; 3.2.P.8.3

Table 1: PQ/CMC Phase 1 Group alignment to ICH eCTD Module 3 Sections

Data Exchange Standards Development

The PQ/CMC Data exchange standard is intended to be developed as Health Level 7 (HL7) Fast Health Interoperable Resources (FHIR) representation. The project has been established with the HL7 Biomedical Research & Regulation (BR&R) work group and discussions regarding representing the PQ/CMC structured elements in FHIR occur during the work group meetings. These HL7 BR&R WG meetings are open to the public.

Related Federal Register Notice (FRN) and Public Meetings

2017 PQ/CMC FRN—In 2017, the FDA published a PQ/CMC Data Elements and Controlled Terminology document as part of FRN [https://www.federalregister.gov/a/2017-14456]. That document proposed structured data standards for a set of eCTD Module 3 content. There was a large volume of comments received from the industry in response to the FRN with overall support for structuring Module 3 content and detail comments on the data elements and controlled terminology. The comments and feedback were incorporated into the structured data elements and controlled terminology.

2018 PQ/CMC Public Meeting—The Agency then held a public meeting in 2018, in support of the 2017 FRN. The presentations and recordings from this public meeting can be accessed from the links below.

2022 PQ/CMC FRN—FDA released a Federal Register Notice in 2022 [https://www.regulations.gov/document/FDA-2022-N-0297-0001] that provides the updated PQ/CMC Phase 1 Data elements and controlled terminology as well as Draft mappings [Data Elements & Terminologies Document] to Health Level 7 (HL7) Fast Health Interoperable Resources (FHIR). The focus of this second FRN is to seek industry input on the FHIR mappings.

Conceptual Model

The Phase 1 data elements and controlled terminology have been published in the 2017 FRN. This is a high-level conceptual model covering the phase 1 groups/domains. The model is represented as a Unified Modeling Language (UML) Class diagram/data model. FDA is publishing this conceptual model to help provide context to the list of data elements and represent the relationships between the concepts. It is to only promote understanding of the domain. It is important to note that this is a high-level conceptual model; it is not a logical data model.

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