Technologies for Detecting Falsified and Substandard Drugs in Low and Middle-Income Countries

Falsified and substandard drugs are a global health problem, particularly in low- and middle-income countries (LMIC) that have weak pharmacovigilance and drug regulatory systems. Poor quality medicines have important health consequences, including the potential for treatment failure, development of antimicrobial resistance, and serious adverse drug reactions, increasing healthcare costs and undermining the public's confidence in healthcare systems. This article presents a review of the methods employed for the analysis of pharmaceutical formulations. Technologies for detecting substandard and falsified drugs were identified primarily through literature reviews. Key-informant interviews with experts augmented our methods when warranted. In order to aid comparisons, technologies were assigned a suitability score for use in LMIC ranging from 0–8. Scores measured the need for electricity, need for sample preparation, need for reagents, portability, level of training required, and speed of analysis. Technologies with higher scores were deemed the most feasible in LMICs. We categorized technologies that cost $10,000 USD or less as low cost, $10,000–100,000 USD as medium cost and those greater than $100,000 USD as high cost technologies (all prices are 2013 USD). This search strategy yielded information on 42 unique technologies. Five technologies were deemed both low cost and had feasibility scores between 6–8, and an additional four technologies had medium cost and high feasibility. Twelve technologies were deemed portable and therefore could be used in the field. Many technologies can aid in the detection of substandard and falsified drugs that vary from the simplest of checklists for packaging to the most complex mass spectrometry analyses. Although there is no single technology that can serve all the requirements of detecting falsified and substandard drugs, there is an opportunity to bifurcate the technologies into specific niches to address specific sections within the workflow process of detecting products.