Biopharma Manufacturing Process Lifecycle
type: Ontology
abstract: The Biopharma Manufacturing Process Lifecycle Ontology provides constructs for representing how biopharmaceutical manufacturing processes are designed, characterized, qualified, validated, and monitored over time. It supports the representation of lifecycle activities that connect product quality expectations, critical quality attributes, process understanding, risk assessment, control strategy development, facility and equipment qualification, process performance qualification, and continued process verification. The module is intended to provide a consistent way to describe how scientific and engineering knowledge about a biopharmaceutical process is generated, used to establish the commercial process, and maintained through ongoing manufacturing and lifecycle management.
license: http://opensource.org/licenses/MIT
imports: BiopharmaManufacturingExecution
imports: BiopharmaRiskManagement
imports: Certification
version IRI: BiopharmaManufacturingProcessLifecycle
copyright: Copyright (c) 2022, 2023, 2024, 2025, 2026 Open Applications Group
maturity: Provisional

continued process verification process
type: Class
subclass of: PlannedProcess
subclass of: Restriction
  on property: BFO_0000062
  some values from: manufacturing process qualification process
example: During commercial monoclonal-antibody production, data on pH, dissolved oxygen, viable-cell density, and metabolite concentrations are trended across batches. Statistical analysis confirms that the process remains within expected variation and that no drift occurs.
acronym: CPV
adapted from: https://www.biophorum.com/download/cvp-case-study-interactive-version/ and https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
counter example: Generating a one-time validation report at the end of process qualification without further data collection is not CPV, because it does not provide ongoing assurance of control.
explanatory note: Continued Process Verification is the third stage of process validation and extends beyond initial validation by embedding continuous monitoring and analysis into routine production. Manufacturers collect and evaluate data on critical process parameters, material attributes, quality attributes, and performance indicators to confirm that the process operates within established limits. This ongoing activity enables early detection of variability, supports statistical trend analysis, and provides the basis for corrective or preventive actions. Regulatory authorities, including the FDA and EMA, view CPV as a key element of lifecycle management ensuring consistent product quality throughout commercial manufacture.
first order logic axiom: ContinuedProcessVerificationProcess(x) → PlannedProcess(x) ∧ ∃p (precededBy(x, p) ∧ ManufacturingProcessQualificationProcess(p))
is primitive: true
natural language definition: planned process performed during routine commercial manufacturing to gain ongoing assurance, through periodic or continuous collection and analysis of product and process data, as to whether a manufacturing process remains in a state of control
primitive rationale: There are insufficient constructs to create a set of necessary and sufficient conditions.
semi formal natural language axiom: if x is a 'continued process verification process' then x is a 'planned process' and x is 'preceded by' some 'manufacturing process qualification process'

critical quality attribute identification process
type: Class
subclass of: PlannedProcess
equivalent class: Class
  intersection of: PlannedProcess
  intersection of: Restriction
    on property: BFO_0000062
    some values from: quality target product profile definition
  intersection of: Restriction
    on property: BFO_0000117
    some values from: RiskAssessmentProcess
  intersection of: Restriction
    on property: hasSpecifiedOutput
    some values from: CriticalQualityAttributeSpecification
example: critical quality attribute (CQA) identification process for a monoclonal antibody drug product in which potency, purity, aggregate level, charge variants, glycosylation, and visible particles are evaluated for potential impact on safety, efficacy, or quality; critical quality attribute (CQA) identification process for a sterile injectable biologic in which sterility, endotoxin, particulate matter, potency, purity, and stability-related attributes are evaluated; critical quality attribute (CQA) identification process in which prior knowledge and risk assessment are used to determine which drug product quality attributes require control in the control strategy; critical quality attribute (CQA) identification process for a lyophilized drug product in which reconstitution time, residual moisture, potency, purity, appearance, and stability are evaluated;
adapted from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4070262/ and https://database.ich.org/sites/default/files/Q8_R2_Guideline.pdf
explanatory note: 1) Criticality of an attribute is primarily based upon the severity of harm to the patient should the product fall outside the acceptable range for that attribute. 2) Risk assessment is used as part of this process, which may leverage prior knowledge and increasing product and process understanding, making it iterative. Targeted experimentation may also be performed iteratively in conjunction with risk assessment.
first order logic definition: CriticalQualityAttributeIdentificationProcess(x) ↔ PlannedProcess(x) ∧ ∃q (precededBy(x, q) ∧ QualityTargetProductProfileDefinition(q)) ∧ ∃r (hasOccurrentPart(x, r) ∧ RiskAssessmentProcess(r)) ∧ ∃c (hasSpecifiedOutput(x, c) ∧ CriticalQualityAttributeSpecification(c))
natural language definition: planned process that identifies critical quality attributes
semi formal natural language definition: every instance of 'critical quality attribute identification process' is defined as exactly an instance of 'planned process' that is 'preceded by' some 'quality target product profile definition', 'has occurrent part' some 'risk assessment process', and 'has specified output' some 'critical quality attribute specification'

design space
type: Class
subclass of: InformationContentEntity
subclass of: Restriction
  on property: describes
  some values from: ManufacturingProcess
subclass of: Restriction
  on property: isAbout
  some values from: Class
    union of: InputMaterialAttribute
    union of: ProcessParameter
example: During ultrafiltration, all studied combinations within a two-dimensional region defined by a transmembrane pressure of 1.5–2.5 bar and a crossflow rate of 20–30 L m⁻² h⁻¹ were demonstrated to maintain product clarity and yield
acronym: DSp
adapted from: https://wolfson.huji.ac.il/purification/PDF/Others/GE_DOE_in_Protein_Production_and_Purification_Handbook.pdf and https://www.biophorum.com/download/cvp-case-study-interactive-version/ and https://www.ema.europa.eu/en/documents/scientific-guideline/questions-and-answers-improving-understanding-normal-operating-range-nor-proven-acceptable-range-par-design-space-dsp-and-normal-variability-process-parameters_en.pdf
explanatory note: The design space represents the highest level of operational flexibility. Operation within the design space does not constitute a regulatory change, whereas movement outside the design space may require justification or regulatory variation. The design space is defined by process understanding and risk assessment, and may apply to a single unit operation or span multiple operations.
first order logic axiom: DesignSpace(x) → InformationContentEntity(x) ∧ ∃p (ManufacturingProcess(p) ∧ describes(x, p)) ∧ ∃v ((InputMaterialAttribute(v) ∨ ProcessParameter(v)) ∧ isAbout(x, v))
is primitive: true
natural language definition: information content entity that describes a manufacturing process through a multidimensional region of combinations of values of process parameters, input material attributes, or both, within which the process assures product quality
primitive rationale: There are insufficient constructs to create necessary and sufficient conditions.
semi formal natural language axiom: if x is a 'design space' then x is an 'information content entity' that 'describes' some 'manufacturing process' and 'is about' some 'input material attribute' or some 'process parameter'

drug product design process
type: Class
subclass of: PlannedProcess
subclass of: Restriction
  on property: BFO_0000062
  some values from: critical quality attribute identification process
example: Drug product design process for a monoclonal antibody formulation that evaluates buffer composition, stabilizers, surfactant level, and container closure system to support potency, purity, stability, and visible particle control over shelf life; Drug product design process for a lyophilized biologic that selects excipients and cycle-relevant formulation attributes to support cake appearance, reconstitution time, residual moisture, potency, and stability;
adapted from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4070262/
explanatory note: This process aims to ensure that the product meets patient needs and maintains performance through shelf life, supported by clinical and stability studies. Key elements commonly include: 1) Physical, chemical, and biological characterization of the drug substance 2) Identification and selection of excipient type and grade, including knowledge of intrinsic excipient variability 3) Characterization of drug–excipient interactions 4) Formulation optimization and identification of critical material attributes of both excipients and drug substance.
first order logic axiom: DrugProductDesignProcess(x) → PlannedProcess(x) ∧ ∃p (precededBy(x, p) ∧ CriticalQualityAttributeIdentificationProcess(p))
is primitive: true
natural language definition: planned process performed to develop a product that can deliver the desired quality target product profile over its entire shelf life
primitive rationale: There are insufficient constructs to create a set of necessary and sufficient conditions
semi formal natural language axiom: if x is a 'drug product design process' then x is a 'planned process' and x is 'preceded by' some 'critical quality attribute identification process'

edge of failure
type: Class
subclass of: InformationContentEntity
subclass of: Restriction
  on property: describes
  some values from: ManufacturingProcess
subclass of: Restriction
  on property: isAbout
  some values from: Class
    union of: InputMaterialAttribute
    union of: ProcessParameter
example: In a study varying pH and temperature, the combinations of pH and temperature at which the proportion of acidic charge variants reaches its maximum acceptable value define a two-dimensional edge of failure; in a single-parameter study, the pH value at which the proportion of acidic charge variants reaches its maximum acceptable value represents a one-dimensional edge of failure
adapted from: https://www.biopharminternational.com/view/evaluating-design-margin-edge-failure-and-process-capability and https://www.fda.gov/media/71535/download
explanatory note: 1) The edge of failure marks the limit of process robustness. 2) It may correspond to a single threshold value for a parameter or to a multidimensional surface in a parameter–attribute space. 3) Edge-of-failure analysis can be performed experimentally by extending process conditions until failure occurs or by simulation of extrapolated design-space models. 4) It is a scientific and developmental concept used to understand process risk and robustness and is not essential to establishing a design space.
first order logic axiom: EdgeOfFailure(x) → InformationContentEntity(x) ∧ ∃p (ManufacturingProcess(p) ∧ describes(x, p)) ∧ ∃v ((InputMaterialAttribute(v) ∨ ProcessParameter(v)) ∧ isAbout(x, v))
is primitive: true
natural language definition: information content entity that describes a manufacturing process through a boundary of values of process parameters, input material attributes, or both, beyond which that process can no longer assure product quality
primitive rationale: There are insufficient constructs to create necessary and sufficient conditions.
semi formal natural language axiom: if x is an 'edge of failure' then x is an 'information content entity' that 'describes' some 'manufacturing process' and 'is about' some 'input material attribute' or some 'process parameter'

manufacturing facility qualification process
type: Class
subclass of: PlannedProcess
subclass of: Restriction
  on property: BFO_0000117
  some values from: AttestingProcess
example: Manufacturing facility qualification process including commissioning and qualification of utilities before process performance qualification (PPQ); Facility qualification process verifying that cleanrooms, utilities, and production equipment are installed and operate according to design and process requirements; Qualification process for a biologics manufacturing suite demonstrating that HVAC, water systems, clean steam, and process equipment support anticipated commercial operation;
adapted from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
explanatory note: 1) This term is used for the FDA Process Validation Stage 2 activities that precede process performance qualification (PPQ). 2) These activities include those performed to assure proper facility design and commissioning, as well as activities demonstrating that utilities and equipment are built and installed in accordance with design specifications and operate in accordance with process requirements across anticipated operating ranges. 3) Qualification activities may include selection of appropriate construction materials, operating principles, and performance characteristics; verification of installation against design specifications; and verification of operation under anticipated routine production conditions, including interventions, stoppage, and start-up.
first order logic axiom: ManufacturingFacilityQualificationProcess(x) → PlannedProcess(x) ∧ ∃p (hasOccurrentPart(x, p) ∧ AttestingProcess(p))
is primitive: true
natural language definition: planned process performed to assure proper manufacturing facility design and commissioning and demonstrate that associated utilities and equipment perform properly under anticipated commercial operating conditions
primitive rationale: There are insufficient constructs to create a set of necessary and sufficient conditions.
semi formal natural language axiom: if x is a 'manufacturing facility qualification process' then x is a 'planned process' and x 'has occurrent part' some 'attesting process'

manufacturing process characterization process
type: Class
subclass of: PlannedProcess
example: cell culture process characterization to determine the effect of temperature and glucose feeding on product glycosylation
acronym: PC
adapted from: https://www.6sigma.us/process-improvement/process-characterization/ and https://www.biopharminternational.com/view/rational-step-wise-approach-process-characterization
counter example: unplanned troubleshooting of a failed batch
explanatory note: The process integrates analysis of historical data, designed experiments, and risk assessment to determine the criticality of parameters and material attributes, quantify their relationships with critical quality attributes (CQAs) and key performance indicators (KPIs), and establish scientifically justified parameter ranges that support control strategy, validation, and lifecycle management.
first order logic axiom: ManufacturingProcessCharacterizationProcess(x) → PlannedProcess(x)
is primitive: true
natural language definition: planned process that systematically develops and documents scientific understanding of how process parameters and material attributes influence quality and performance outcomes
primitive rationale: This class is expected to remain primitive.
semi formal natural language axiom: if x is a 'manufacturing process characterization process' then x is a 'planned process'

manufacturing process design process
type: Class
subclass of: PlannedProcess
equivalent class: Class
  intersection of: PlannedProcess
  intersection of: Restriction
    on property: BFO_0000117
    some values from: manufacturing process characterization process
  intersection of: Restriction
    on property: BFO_0000117
    some values from: process control strategy establishment
  intersection of: Restriction
    on property: BFO_0000117
    some values from: RiskAssessmentProcess
  intersection of: Restriction
    on property: hasSpecifiedOutput
    some values from: Class
      intersection of: PlanSpecification
      intersection of: Restriction
        on property: BFO_0000110
        some values from: ControlStrategy
      intersection of: Restriction
        on property: prescribes
        some values from: ManufacturingProcess
example: Manufacturing process design process for a monoclonal antibody drug substance process in which prior knowledge, risk assessment, process characterization, operating ranges, CPPs, and the control strategy are developed for the commercial process; Manufacturing process design process for a fed-batch cell culture process that defines input materials, process parameters, setpoints, normal operating ranges, proven acceptable ranges, monitoring points, and control elements;
adapted from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
explanatory note: 1) Process Design corresponds to Stage 1 of FDA’s Process Validation lifecycle. Its purpose is to establish the scientific and engineering understanding needed to design a robust commercial process. Activities include integration of prior knowledge, risk assessment, process characterization studies, model development, identification of critical process parameters (CPPs), classification of material attributes, establishment of operating ranges (e.g., setpoints, NORs, PARs), and definition of the control strategy. 2) In IOF Core, 'process design' is a synonym for 'plan specification'.
first order logic definition: ManufacturingProcessDesignProcess(x) ↔ PlannedProcess(x) ∧ ∃c∃s∃r∃o∃cs∃p(ManufacturingProcessCharacterizationProcess(c) ∧ ProcessControlStrategyEstablishment(s) ∧ RiskAssessmentProcess(r) ∧ PlanSpecification(o) ∧ ControlStrategy(cs) ∧ ManufacturingProcess(p) ∧ hasOccurrentPart(x,c) ∧ hasOccurrentPart(x,s) ∧ hasOccurrentPart(x,r) ∧ hasSpecifiedOutput(s,cs) ∧ hasSpecifiedOutput(x,o) ∧ hasContinuantPartAtAllTimes(o,cs) ∧ prescribes(o,p))
natural language definition: planned process that defines and develops the manufacturing steps, process parameters, materials, and control elements of a commercial manufacturing process in order to establish its process design
semi formal natural language definition: every instance of 'manufacturing process design process' is defined as exactly an instance of 'planned process' that 'has occurrent part' some 'manufacturing process characterization process', 'has occurrent part' some 'process control strategy establishment' that 'has specified output' some 'control strategy', 'has occurrent part' some 'risk assessment process', and 'has specified output' some 'plan specification' that 'has continuant part at all times' that same 'control strategy' and 'prescribes' some 'manufacturing process'

manufacturing process performance qualification process
type: Class
subclass of: PlannedProcess
equivalent class: Class
  intersection of: PlannedProcess
  intersection of: Restriction
    on property: BFO_0000062
    some values from: manufacturing facility qualification process
  intersection of: Restriction
    on property: BFO_0000117
    some values from: ManufacturingProcess
  intersection of: Restriction
    on property: hasInput
    some values from: Class
      intersection of: PlanSpecification
      intersection of: Restriction
        on property: BFO_0000110
        some values from: ControlStrategy
      intersection of: Restriction
        on property: prescribes
        some values from: ManufacturingProcess
  intersection of: Restriction
    on property: prescribedBy
    some values from: manufacturing process performance qualification specification
example: PPQ process for a commercial monoclonal antibody drug substance process executed at commercial scale using qualified bioreactors, utilities, and approved control procedures; PPQ process for a fed-batch cell culture process performed with heightened sampling and testing to confirm that the process design produces material meeting expected quality attributes;
acronym: PPQ
adapted from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
explanatory note: 1) In PPQ, trained personnel execute the commercial manufacturing process using previously qualified facility, utilities, and equipment, approved control procedures, and input materials in order to generate evidence that the process performs as expected at commercial scale. 2) PPQ is typically performed with heightened sampling, testing, and scrutiny relative to routine commercial production. 3) A successful PPQ confirms the process design and provides evidence that the commercial manufacturing process is capable of reproducible commercial manufacture.
first order logic definition: ManufacturingProcessPerformanceQualificationProcess(x) ↔ PlannedProcess(x) ∧ ∃q (ManufacturingFacilityQualificationProcess(q) ∧ precededBy(x, q)) ∧ ∃m (ManufacturingProcess(m) ∧ hasOccurrentPart(x, m)) ∧ ∃s (PlanSpecification(s) ∧ hasInput(x, s) ∧ ∃c (ControlStrategy(c) ∧ hasContinuantPartAtAllTimes(s, c)) ∧ ∃p (ManufacturingProcess(p) ∧ prescribes(s, p))) ∧ ∃r (ManufacturingProcessPerformanceQualificationSpecification(r) ∧ prescribedBy(x, r))
natural language definition: planned process in which a previously qualified facility, utilities, and equipment are used to confirm the process design in order to demonstrate that the commercial manufacturing process performs as expected
semi formal natural language definition: every instance of 'manufacturing process performance qualification process' is defined as exactly an instance of 'planned process' that is 'preceded by' some 'manufacturing facility qualification process', 'has occurrent part' some 'manufacturing process', 'has input' some 'plan specification' that 'has continuant part at all times' some 'control strategy' and 'prescribes' some 'manufacturing process', and is 'prescribed by' some 'manufacturing process performance qualification specification'

manufacturing process performance qualification specification
type: Class
subclass of: PlanSpecification
subclass of: Restriction
  on property: prescribes
  all values from: manufacturing process performance qualification process
example: process performance qualification (PPQ) protocol for a commercial monoclonal antibody drug substance process defining the process performance qualification (PPQ) batches, operating parameters, sampling plan, analytical testing, acceptance criteria, deviation handling, and statistical evaluation approach; process performance qualification (PPQ) specification for a biologics fill-finish process defining process conditions, in-process controls, container closure testing, sampling locations, and batch acceptance criteria;
abbreviation: PPQ protocol
abbreviation: PPQ specification
adapted from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
explanatory note: 1) It prescribes the manufacturing conditions, controls, testing, expected outcomes, and decision criteria for the manufacturing process performance qualification process. 2) It should specify operating parameters, processing limits, input materials, data collection and evaluation, testing and acceptance criteria, and the sampling plan. 3) It should also specify the statistical methods and provisions for handling deviations and nonconforming data that support a science- and risk-based decision about whether the process can consistently produce quality product. 4) If not previously accomplished, it should address facility design and qualification of utilities and equipment, personnel training and qualification, verification of material sources, and the validation status of analytical methods. 5) It should be reviewed and approved by the appropriate departments and the quality unit before execution of the prescribed process.
first order logic axiom: LA1: ManufacturingProcessPerformanceQualificationSpecification(x) → PlanSpecification(x) ∧ ∀y (prescribes(x, y) → ManufacturingProcessPerformanceQualificationProcess(y))
first order logic axiom: LA2: PlanSpecification(x) ∧ ∃y(ManufacturingProcessPerformanceQualificationProcess(y) ∧ prescribes(x,y)) → ManufacturingProcessPerformanceQualificationSpecification(x)
is primitive: true
natural language definition: plan specification that prescribes a manufacturing process performance qualification process
primitive rationale: See the general discussion under information content entity
semi formal natural language axiom: LA1: if x is a 'manufacturing process performance qualification specification' then x is a 'plan specification' and x 'prescribes' only 'manufacturing process performance qualification process'
semi formal natural language axiom: LA2: if x is a 'plan specification' that 'prescribes' some 'manufacturing process performance qualification process' then x is a 'manufacturing process performance qualification specification'

manufacturing process qualification process
type: Class
subclass of: PlannedProcess
subclass of: Restriction
  on property: BFO_0000062
  some values from: manufacturing process design process
subclass of: Restriction
  on property: BFO_0000117
  some values from: manufacturing facility qualification process
subclass of: Restriction
  on property: BFO_0000117
  some values from: manufacturing process performance qualification process
example: Process qualification for a commercial monoclonal antibody drug substance process, including facility and equipment qualification followed by process performance qualification (PPQ) batch execution; Process qualification for a fed-batch cell culture process where qualified bioreactors, utilities, and control procedures are used before process performance qualification (PPQ) runs demonstrate reproducible commercial performance; Process qualification for a downstream purification process including qualification of chromatography skids, filtration equipment, utilities, and process performance qualification (PPQ) execution at commercial scale;
adapted from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
explanatory note: 1) Process qualification corresponds to Stage 2 of FDA's process-validation lifecycle. It includes activities to assure proper facility design and commissioning and to qualify utilities and equipment, followed by process performance qualification. These two elements are sometimes referred to in industry as Stage 2A and Stage 2B. PPQ batch execution and associated analytical evaluation provide evidence used to determine whether the process is capable of reproducible commercial manufacture. Process qualification relies on knowledge generated during Stage 1 Process Design, including manufacturing process characterization, and precedes Stage 3 Continued Process Verification. 2) In IOF Core, 'process design' is a synonym for 'plan specification'.
first order logic axiom: ManufacturingProcessQualificationProcess(x) → PlannedProcess(x) ∧ ∃d (precededBy(x, d) ∧ ManufacturingProcessDesignProcess(d)) ∧ ∃f (hasOccurrentPart(x, f) ∧ ManufacturingFacilityQualificationProcess(f)) ∧ ∃p (hasOccurrentPart(x, p) ∧ ManufacturingProcessPerformanceQualificationProcess(p))
is primitive: true
natural language definition: planned process in which a manufacturing process design is evaluated, through facility design assurance, qualification of utilities and equipment, and process performance qualification, to determine whether it is capable of reproducible commercial manufacture
primitive rationale: There are insufficient constructs to create a set of necessary and sufficient conditions.
semi formal natural language axiom: if x is a 'manufacturing process qualification process' then x is a 'planned process', x is 'preceded by' some 'manufacturing process design process', x 'has occurrent part' some 'manufacturing facility qualification process', and x 'has occurrent part' some 'manufacturing process performance qualification process'

prior knowledge information content entity
type: Class
subclass of: InformationContentEntity
example: a prior knowledge summary stating that low-pH viral inactivation at a specified pH and hold time range has previously achieved acceptable viral clearance for a platform monoclonal antibody process; a prior knowledge report describing how Protein A resin binding capacity has varied across prior products, resin lots, and operating conditions; a Bayesian prior distribution for a glycosylation model parameter derived from historical fed-batch runs and used to support adaptive process control;
adapted from: https://database.ich.org/sites/default/files/Q11%20Guideline.pdf and https://database.ich.org/sites/default/files/Q10%20Guideline.pdf
explanatory note: 1) Prior knowledge can be derived from publicly available or internally documented sources. 2) A prior knowledge information content entity may represent only the portion relevant to a stated scope, such as a unit operation, parameter, quality attribute, scale range, or control decision. 3) Data derived from relevant prior knowledge, including platform manufacturing, can be leveraged. Accordingly, prior knowledge may be operationalized in data-derived forms such as statistical summaries and governed models, including Bayesian prior distributions, provided scope and provenance are specified.
first order logic axiom: PriorKnowledgeInformationContentEntity(x) → InformationContentEntity(x)
is primitive: true
natural language definition: information content entity that represents scientifically grounded understanding of a product, material, or process derived from prior experience, technical literature, historical data, and/or established scientific and engineering principles
primitive rationale: There are insufficient constructs to define necessary and sufficient conditions for this class. In particular, further work is needed to clarify how prior knowledge information content entities relate to evidence records, data summaries, models, reports, specifications, and other kinds of information content entities.
semi formal natural language axiom: if x is a 'prior knowledge information content entity' then x is an 'information content entity'

process control strategy establishment
type: Class
subclass of: PlannedProcess
equivalent class: Class
  intersection of: PlannedProcess
  intersection of: Restriction
    on property: BFO_0000062
    some values from: manufacturing process characterization process
  intersection of: Restriction
    on property: hasSpecifiedOutput
    some values from: ControlStrategy
example: Process control strategy establishment for a monoclonal antibody cell culture process using characterization data to define critical process parameters (CPP) controls, monitoring points, and response actions; Process control strategy establishment for a purification process using process characterization results to define chromatography operating ranges, impurity controls, and in-process testing; Process control strategy establishment using design of experiments (DoE) and risk assessment outputs to define setpoints, normal operating ranges, proven acceptable ranges, and material attribute controls;
adapted from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf
first order logic definition: ProcessControlStrategyEstablishment(x) ↔ PlannedProcess(x) ∧ ∃p (ManufacturingProcessCharacterizationProcess(p) ∧ precededBy(x, p)) ∧ ∃c (ControlStrategy(c) ∧ hasSpecifiedOutput(x, c))
natural language definition: planned process that uses scientific understanding of how process parameters and material attributes influence quality and performance outcomes to create a control strategy
semi formal natural language definition: every instance of 'process control strategy establishment' is defined as exactly an instance of 'planned process' that is 'preceded by' some 'manufacturing process characterization process' and 'has specified output' some 'control strategy'

process model development
type: Class
subclass of: PlannedProcess
example: During cell-culture process characterization, a mechanistic oxygen-transfer model and a data-driven regression model are developed to predict viable-cell density (performance indicator) and glycosylation profile (critical quality attribute) as functions of agitation rate, dissolved-oxygen setpoint, and glucose feed rate.
adapted from: https://www.biopharminternational.com/view/process-characterization-essentials-process-understanding-and-health-authorities-guidance and https://www.cytivalifesciences.com/en/us/insights/downstream-process-characterization
explanatory note: 1) This process uses experimental, historical, or platform data to generate and validate quantitative models that explain and predict the effects of process parameters and material attributes on critical quality attributes (CQAs) and key performance indicators (KPIs). 2) It supports the definition of design space, setpoints, control ranges, and parameter criticality during process characterization and provides a scientific basis for subsequent validation and lifecycle verification activities. 3) Process model development commonly occurs as part of manufacturing process characterization, but it can also occur during process control development, continued process verification, process improvement, or other lifecycle activities. 4) Detailed representation of a computation model is being developed within the IOF reference ontologies and will be incorporated in the future.
first order logic axiom: ProcessModelDevelopment(x) → PlannedProcess(x)
is primitive: true
natural language definition: planned process in which a mathematical or empirical model is developed to represent or predict a manufacturing process or relationships among its process parameters, material attributes, quality attributes, or performance indicators
primitive rationale: There are insufficient constructs present to represent necessary and sufficient conditions. In particular treatment of models is lacking.
semi formal natural language axiom: if x is a 'process model development' then x is a 'planned process'

process trending analysis
type: Class
subclass of: PlannedProcess
example: process trending analysis evaluates viable cell density, culture duration, product titer, aggregate level, and glycosylation results across consecutive commercial monoclonal antibody batches to identify gradual process drift and changes in inter-batch variability
adapted from: https://www.fda.gov/media/71021/download
explanatory note: Process trending analysis commonly occurs as part of continued process verification but may also support manufacturing process characterization, investigation, product quality review, comparability assessment, process improvement, and other lifecycle activities. It may evaluate process parameters, material attributes, quality attributes, performance indicators, deviations, yields, or other relevant process and product data using statistical or qualitative trending methods.
first order logic axiom: ProcessTrendingAnalysis(x) → PlannedProcess(x)
is primitive: true
natural language definition: planned process that systematically analyzes historical and/or current process and quality data to identify patterns, shifts, drifts, or abnormal variability in process parameters, material attributes, quality attributes, or performance indicators within and/or between batches
primitive rationale: There are insufficient constructs present to represent necessary and sufficient conditions.
semi formal natural language axiom: if x is a 'process trending analysis' then x is a 'planned process'

quality target product profile
type: Class
subclass of: RequirementSpecification
subclass of: Restriction
  on property: BFO_0000110
  some values from: QualityAttributeSpecification
example: quality target product profile (QTPP) for a sterile injectable monoclonal antibody drug product specifying the intended route of administration, dosage strength, sterility expectations, potency, purity, stability, and container-closure quality characteristics; quality target product profile (QTPP) for an oral solid dosage drug product specifying the intended dosage form, dosage strength, dissolution performance, impurity expectations, stability, and appearance; quality target product profile (QTPP) for an inhalation drug product specifying the intended delivery system, delivered dose, aerodynamic particle-size performance, purity, and stability
acronym: QTPP
adapted from: https://www.ema.europa.eu/en/documents/scientific-guideline/international-conference-harmonisation-technical-requirements-registration-pharmaceuticals-human-use-considerations-ich-guideline-q8-r2-phar…
explanatory note: The quality target product profile forms the basis of design for development of a drug product by providing a prospective summary of the drug product quality characteristics that should ideally be achieved to ensure the desired quality. Typical considerations include the intended clinical use, the route of administration, the dosage form and delivery system, the dosage strength or strengths, the container closure system, therapeutic moiety release or delivery characteristics, and attributes affecting pharmacokinetics such as dissolution performance or aerodynamic performance as appropriate to the dosage form. Considerations also include drug product quality criteria appropriate for the intended marketed product, such as sterility, purity, stability, and drug release.
first order logic axiom: QualityTargetProductProfile(x) → RequirementSpecification(x) ∧ ∃q (hasContinuantPartAtAllTimes(x, q) ∧ QualityAttributeSpecification(q))
is primitive: true
natural language definition: requirement specification that represents a prospective summary of the quality characteristics of a product that should ideally be achieved to ensure the desired quality, taking into account the safety and efficacy of that product
primitive rationale: This term is expected to remain primitive.
semi formal natural language axiom: if x is a 'quality target product profile' then x is a 'requirement specification', x 'has continuant part at all times' some 'quality attribute specification'

quality target product profile definition
type: Class
subclass of: PlannedProcess
equivalent class: Class
  intersection of: PlannedProcess
  intersection of: Restriction
    on property: hasSpecifiedOutput
    some values from: quality target product profile
example: quality target product profile (QTPP) definition process for a sterile injectable monoclonal antibody drug product; quality target product profile (QTPP) definition process establishing target product quality characteristics for a lyophilized biologic; quality target product profile (QTPP) definition process for an oral solid dosage product that establishes desired dosage form, strength, dissolution, stability, and quality targets;
adapted from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4070262/
first order logic definition: QualityTargetProductProfileDefinition(x) ↔ PlannedProcess(x) ∧ ∃q (hasSpecifiedOutput(x, q) ∧ QualityTargetProductProfile(q))
natural language definition: planned process in which a quality target product profile is established
semi formal natural language definition: every instance of 'quality target product profile definition' is defined as exactly an instance of 'planned process' that 'has specified output' some 'quality target product profile'