design point

IRI: https://spec.industrialontologies.org/ontology/construct/DesignPoint

Defined In: https://spec.industrialontologies.org/ontology/biopharma/DesignOfExperiments/

SubClass Of: information content entity

Class Hierarchy

owl:Thing › bfo:entity › bfo:continuant › bfo:generically dependent continuant › information content entity › design point

Direct subclasses:

• axial point
• center point
• control point
• corner point
• edge point

Definition

information content entity that is a combination of planned factor levels, with one factor level specified for each independent variable declared by a study design

Explanatory Notes

1) A design point specifies the planned factor levels for the independent variables that define one study condition. In some designs, independent variables may be assigned at different experimental-unit levels, such as whole-plot factors and subplot factors in a split-plot design. Depending on the study design, a design point may also include assignments for blocking variables or other nuisance variables when these are explicitly represented as part of the planned condition. 2) In DoE contexts, design points enable systematic study of main effects, interactions, and, where supported by the design type, curvature in the response surface. Depending on the design, design points may include corner points, center points, axial points, or other structured factor-level combinations. Replicate runs at a design point support estimation of variability and increase confidence in the observed response.

Examples

• In a two-factor factorial design, temperature is studied at 35 °C and 37 °C and pH at 6.8 and 7.2; the design point with coded levels Temperature = −1 and pH = +1 specifies the planned condition Temperature = 35 °C and pH = 7.2; separate study runs may concretize this same design point when the condition is replicated.

Counter-Examples

• Randomly adjusting pH between 6.5 and 7.5 without a predefined plan does not create design points, since the conditions are not predetermined by a structured experimental design.

Adapted From

• https://wolfson.huji.ac.il/purification/PDF/Others/GE_DOE_in_Protein_Production_and_Purification_Handbook.pdf and https://www.fda.gov/media/71535/download

Primitive Class

This class is declared primitive and it does not have necessary and sufficient condiftions defined.

Primitive Rationale

There are insufficient constructs to define a set of necessary and sufficient conditions.

Formal Axioms

First-Order Logic Axioms

DesignPoint(x) → InformationContentEntity(x) ∧ ∃s(StudyDesign(s) ∧ continuantPartOfAtAllTimes(x,s) ∧ ∀v((StudyDesignIndependentVariable(v) ∧ declares(s,v)) → ∃f(FactorLevel(f) ∧ hasContinuantPartAtAllTimes(x,f) ∧ isAbout(f,v) ∧ ∀g((FactorLevel(g) ∧ hasContinuantPartAtAllTimes(x,g) ∧ isAbout(g,v)) → g=f))) ∧ ∀f((FactorLevel(f) ∧ hasContinuantPartAtAllTimes(x,f)) → ∃v(StudyDesignIndependentVariable(v) ∧ declares(s,v) ∧ isAbout(f,v))))

Semi-Formal Natural Language Axioms

if x is a ‘design point’ then x is an ‘information content entity’ that is a ‘continuant part of at all times’ some ‘study design’, for every ‘study design independent variable’ declared by that study design x ‘has continuant part at all times’ exactly one ‘factor level’ that ‘is about’ that variable, and every ‘factor level’ that x ‘has continuant part at all times’ ‘is about’ a ‘study design independent variable’ declared by that same ‘study design’