An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings.

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

Patient Stratification for Antibiotic Prescriptions Based on the Bound-Free Phase Detection Immunoassay of C-Reactive Protein in Serum Samples.

C-reactive protein is a well-studied host response biomarker, whose diagnostic performance depends on its accurate classification into concentration zones defined by clinical scenario-specific cutoff values. We validated a newly developed, bead-based, bound-free phase detection immunoassay (BFPD-IA) versus a commercial CE-IVD enzyme-linked immunosorbent assay (ELISA) kit and a commercial CE-IVD immunoturbidimetric assay (ITA) kit. The latter was performed on a fully automated DPC Konelab 60i clinical analyzer used in routine diagnosis. We classified 53 samples into concentration zones derived from four different sets of cutoff values that are related to antibiotic prescription scenarios in the case of respiratory tract infections. The agreements between the methods were ELISA/ITA at 87.7%, ELISA/BFPD-IA at 87.3%, and ITA/-BFPD-IA at 93.9%, reaching 98-99% in all cases when considering the calculated relative combined uncertainty of the single measurement of each sample. In a subgroup of 37 samples, which were analyzed for absolute concentration quantification, the scatter plot slopes' correlations were as follows: ELISA/ITA 1.15, R2 = 0.97; BFPD-IA/ELISA 1.12, R2 = 0.95; BFPD-IA/ITA 0.95, R2 = 0.93. These very good performances and the agreement between BFPD-IA and ITA (routine diagnostic), combined with BFPD-IA's functional advantages over ITA (and ELISA)-such as quick time to result (~20 min), reduced consumed reagents (only one assay buffer and no washing), few and easy steps, and compatibility with nucleic-acid-amplification instruments-render it a potential approach for a reliable, cost-efficient, evidence-based point-of-care diagnostic test for guiding antibiotic prescriptions.

Expert guidance on target product profile development for AMR diagnostic tests.

Diagnostics are widely considered crucial in the fight against antimicrobial resistance (AMR), which is expected to kill 10 million people annually by 2030. Nevertheless, there remains a substantial gap between the need for AMR diagnostics versus their development and implementation. To help address this problem, target product profiles (TPP) have been developed to focus developers' attention on the key aspects of AMR diagnostic tests. However, during discussion between a multisectoral working group of 51 international experts from industry, academia and healthcare, it was noted that specific AMR-related TPPs could be extended by incorporating the interdependencies between the key characteristics associated with the development of such TPPs. Subsequently, the working group identified 46 characteristics associated with six main categories (ie, Intended Use, Diagnostic Question, Test Description, Assay Protocol, Performance and Commercial). The interdependencies of these characteristics were then identified and mapped against each other to generate new insights for use by stakeholders. Specifically, it may not be possible for diagnostics developers to achieve all of the recommendations in every category of a TPP and this publication indicates how prioritising specific TPP characteristics during diagnostics development may influence (or not) a range of other TPP characteristics associated with the diagnostic. The use of such guidance, in conjunction with specific TPPs, could lead to more efficient AMR diagnostics development.