Related Experiment Video
Updated: Jun 26, 2026

Microbial Control and Monitoring Strategies for Cleanroom Environments and Cellular Therapies
Published on: March 17, 2023
Quality control of DL,CO instruments in global clinical trials
Abstract:
High inter- and intra-laboratory variability exists for the single-breath diffusing capacity of the lung for carbon monoxide (D(L,CO)) test. To detect small changes in diffusing capacity in multicentre clinical trials, accurate measurements are essential. The present study assessed whether regular D(L,CO) simulator testing maintained or improved instrument accuracy and reduced variability in multicentre trials. The 125 pulmonary function testing laboratories that participated in clinical trials for AIR(R) Inhaled Insulin validated and monitored the accuracy of their D(L,CO) measuring devices using a D(L,CO) simulator, which creates known target values for any device. Devices measuring a simulated D(L,CO) different from target by >3 mL.min-1.mmHg(-1) failed testing and were serviced. Device accuracy was assessed over time and with respect to differences in several variables. Initially, 31 (25%) laboratories had a D(L,CO) device that failed simulator testing. After fixing or replacing devices, 124 (99%) laboratories had passing devices. The percentage of failed tests significantly decreased over time. Differences in geographical region, device type, breath-hold time, temperature and pressure were not associated with meaningful differences in D(L,CO) device accuracy. Regular diffusing capacity of the lung for carbon monoxide simulator testing allows pulmonary function testing laboratories to maintain the accuracy of their diffusing capacity measurements, leading to reduced variability across laboratories in multicentre clinical trials.
Related Concept Videos
Clinically Relevant Drug Product Specifications: Methods of Establishment
Clinical Trials: Overview
Drug Product Performance: In Vitro–In Vivo Correlation
Clinical Trials
There are four phases in a clinical trial. A phase one...
Preclinical Development: Overview
Data Validation
Key parameters for method validation include:
