Recent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines. Disbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire. Disbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data.

Background: Substandard and falsified medicines, mainly prevalent in low and middle-income countries (LMICs), cause avoidable morbidity and mortality, and put at stake the performance of health systems. They may be prevented by an adequate implementation of pharmaceutical Quality Assurance (QA) guidelines, but unfortunately, most guidelines address upstream stakeholders and specialized staff in the supply chain. A multi-layered approach is needed, in order to empower the health workers at the point-of-care to proactively contribute to the fight against poor-quality medicines. Visual inspection is a simple technique, suitable for field screening. The findings of a survey conducted in the Democratic Republic of the Congo (DRC) suggested that it might be a fairly good (yet partial) predictor of poor-quality, when compared to full laboratory tests. Methods and results: Starting from the 68-questions checklist originally used in the survey in the DRC, we developed a simplified checklist, specifically designed to guide health workers at the point of care to rapidly identify suspect poor-quality medicines. We selected those medicines’ attributes the assessment of which does not require technical expertise, or access to regulatory information. Attributes were categorized according to a 3-level risk scale, to guide decision-making on suspect poor-quality medicines, based on an informed risk assessment. The simplified checklist contains 26 binary questions (YES/NO), grouped into four themes: packaging, identification, traceability, and physical appearance. Each non-conformity corresponds to a level of risk for patients. The user is guided towards three possible actions: A) reasonably safe for dispensing; B) dispense with explanation; C) quarantine and make a risk-benefit evaluation before dispensing. Conclusion: The simplified checklist should now be implemented in real-life setting in LMICs. If proven useful in guiding health workers at the point-of-care to take rapid, transparent, patient-centred actions when facing a suspect poor-quality medicine, it could be further extended to address specific formulations. Digitalization for linkage with pharmacovigilance programs could also be considered.

Poor-quality medicines are a threat to public health in many low- and middle-income countries, and prospective surveys are needed to inform corrective actions. Therefore, we conducted a cross-sectional survey on a sample of products used for children and available in the private market in Kinshasa, Democratic Republic Congo: amoxicillin (AX) and artemether/lumefantrine (AL), powders for suspension, and paracetamol (PC) tablets 500 mg. Overall, 417 products were covertly purchased from 61 wholesalers. To obtain a representative sample, the products were weighted on their market shares and a subset of 239 samples was randomly extracted to undergo in-depth visual inspection locally, and they were chemically assessed at two accredited laboratories in Belgium. Samples were defined of “poor-quality” if they failed to comply with at least one specification of the International Pharmacopoeia (for AL) or United States Pharmacopoeia 37 (for AX and PC). Results are reported according to the Medicine Quality Assessment Reporting Guideline. The visual inspection detected nonconformities in the aspects of antimalarial powders for suspension, and poor-quality labels across all medicine types. According to chemical analysis, 27.2% samples were of poor quality and 59.5% of AL samples were underdosed in artemether. Poor quality was more frequent for locally manufactured antimalarials (83.3%, P = 0.021; 86.4%, P = 0.022) and PC (4.8%, P = 0.000). The poor quality of the surveyed products may decrease the treatment’s efficacy and favor the development of resistances to antimalarials. It is hoped that these findings may guide the corrective actions of the Democratic Republic of Congo Regulatory Authority, which was the main partner in the research.