Orthogonal Measurements

Summary

Reliable measurements of quality attributes of medical products are required for quality control and verification of safety and efficacy. To reduce (i) the risk of measurement bias and (ii) the uncertainty in decision-making during product development, a combination of orthogonal and complementary analytical techniques are generally recommended. However, despite frequent reference to “orthogonal” and “complementary” measurements in guideances and the literature, neither term is clearly defined. How does one determine if two analytical methods are orthogonal or complementary to one another?  Definitions are needed to design a robust characterization strategy for a medical product.  Definitions for "orthogonal" and "complementary" are proposed that are compatible with existing metrological terminology and are applicable to complex measurement problems. Orthogonal methods target the quantitative evaluation of the true value of a product attribute to address unknown bias or interference. Complementary measurements include a broader scope of methods that reinforce each other to support a common decision.

Description

Definitions:

• Orthogonal measurements: Measurements that use different physical principles to measure the same property of the same sample with the goal of minimizing method-specific biases and interferences.
• Complementary measurements: Measurements that corroborate each other to support the same decision.
   

Flow chart for the determination of complementary and orthogonal measurements based on the determination of 1) the measurement purposes; 2) the samples to be measured; 3) the primary measurands; and 4) the main physical principles behind the measurement. The flow chart is a guide to help users determine whether two measurements are i) neither complementary nor orthogonal, ii) complementary but not orthogonal, or iii) both complementary and orthogonal.  Note that one condition must be met for two measurements to be complementary (same measurement purpose), while three additional conditions must be met for two measurements to be orthogonal (same samples, same primary measurands, and different measurement principles).

 

A) Measurand chart: An example of a measurand chart for the measurement of the particle size distribution of a virus like particle sample (VLP) comparing transmission electron microscopy (TEM), dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) measurements made on the same sample in the same conditions for the same measurement purpose. From left to right: the white boxes are the sample, the grey boxes are the measurements, the orange boxes describe the detection principle used to transform the physical phenomenon into a measurable signal, the violet boxes indicate the physical principle of the measurement, the blue boxes are the “intermediate” measurand, the green boxes are the primary measurand (particle size in this example) and the red boxes are the measurement purpose (decision to be made using the data collected). B) Notes are provided in the decision box to explain the logic on how the decisions regarding orthogonality and complementarity were determined. C) Confusion matrix for the determination of orthogonality and complementarity for all pairwise comparisons of the measurements. Note: The relationships in the chart are not absolute and are open to discussion.

Reference

Simon CG, Borgos SE, Calzolai L, Nelson BC, Parot J, Petersen EJ, Roesslein M, Xu X, Caputo F (2023) Orthogonal and complementary measurements of properties of drug products containing nanomaterials. Journal of Controlled Release 354, 120-127. https://doi.org/10.1016/j.jconrel.2022.12.049

Future Work

• Apply these concepts to biological measurements, such as cell viability
• Apply these concepts to quality assessment of complex drugs, such as mRNA therapeutics or lipid-based therapeutics
• Develop a terminology standard at ISO or ASTM