Implementation of field detection devices for antimalarial quality screening in Lao PDR-A cost-effectiveness analysis

Usefulness of medicine screening tools in the frame of pharmaceutical post-marketing surveillance

The negative consequences of Substandard and falsified (SF) medicines are widely documented nowadays and there is still an urgent need to find them in more efficient ways. Several screening tools have been developed for this purpose recently. In this study, three screening tools were used on 292 samples of ciprofloxacin and metronidazole collected in Cameroon. Each sample was then analyzed by HPLC and disintegration tests. Seven additional samples from the nitro-imidazole (secnidazole, ornidazole, tinidazole) and the fluoroquinolone (levofloxacin, ofloxacin, norfloxacin, moxifloxacin) families were analyzed to mimic falsified medicines. Placebo samples that contained only inert excipients were also tested to mimic falsified samples without active pharmaceutical ingredient (API). The three screening tools implemented were: a simplified visual inspection checklist, a low-cost handheld near infrared (NIR) spectrophotometer and paper analytical devices (PADs). Overall, 61.1% of the samples that failed disintegration and assay tests also failed the visual inspection checklist test. For the handheld NIR, one-class classifier models were built to detect the presence of ciprofloxacin and metronidazole, respectively. The APIs were correctly identified in all the samples with sensitivities and specificities of 100%. However, the importance of a representative and up-to-date spectral database was underlined by comparing models built with different calibration set spanning different variability spaces. The PADs were used only on ciprofloxacin samples and detected the API in all samples in which the presence of ciprofloxacin was confirmed by HPLC. However, these PADs were not specific to ciprofloxacin since they reacted like ciprofloxacin to other fluoroquinolone compounds. The advantages and drawbacks of each screening tool were highlighted. They are promising means in the frame of early detection of SF medicines and they can increase the speed of decision about SF medicines in the context of pharmaceutical post-marketing surveillance.

Comparing the return on investment of technologies to detect substandard and falsified amoxicillin: A Kenya case study

The prevalence of substandard and falsified medicines in low- and middle-income countries (LMICs) is a major global public health concern. Multiple screening technologies for post-market surveillance of medicine quality have been developed but there exists no clear guidance on which technology is optimal for LMICs. This study examined the return on investment (ROI) of implementing a select number of screening technologies for post-market surveillance of amoxicillin quality in a case study of Kenya. An agent-based model, Examining Screening Technologies using Economic Evaluations for Medicines (ESTEEM), was developed to estimate the costs, benefits, and ROI of implementing screening technologies for post-market surveillance of substandard and falsified amoxicillin for treatment of pediatric pneumonia in Kenya. The model simulated sampling, testing, and removal of substandard and falsified amoxicillin from the Kenyan market using five screening technologies: (1) Global Pharma Health Fund's GPHF-Minilab, (2) high-performance liquid chromatography (HPLC), (3) near-infrared spectroscopy (NIR), (4) paper analytical devices / antibiotic paper analytical devices (PADs/aPADs), and (5) Raman spectroscopy. The study team analyzed the population impact of utilizing amoxicillin for the treatment of pneumonia in children under age five in Kenya. We found that the GPHF-Minilab, NIR, and PADs/aPADs were similar in their abilities to rapidly screen for and remove substandard and falsified amoxicillin from the Kenyan market resulting in a higher ROI compared to HPLC. NIR and PADs/aPADs yielded the highest ROI at $21 (90% Uncertainty Range (UR) $5-$51) each, followed by GPHF-Minilab ($16, 90%UR $4 - $38), Raman ($9, 90%UR $2 - $21), and HPLC ($3, 90%UR $0 - $7). This study highlights screening technologies that can be used to reduce costs, speed up the removal of poor-quality medicines, and consequently improve health and economic outcomes in LMICs. National medicine regulatory authorities should adopt these fast, reliable, and low-cost screening technologies to better detect substandard and falsified medicines, reserving HPLC for confirmatory tests.

An open-source smartphone app for the quantitative evaluation of thin-layer chromatographic analyses in medicine quality screening

Substandard and falsified medicines present a serious threat to public health. Simple, low-cost screening tools are important in the identification of such products in low- and middle-income countries. In the present study, a smartphone-based imaging software was developed for the quantification of thin-layer chromatographic (TLC) analyses. A performance evaluation of this tool in the TLC analysis of 14 active pharmaceutical ingredients according to the procedures of the Global Pharma Health Fund (GPHF) Minilab was carried out, following international guidelines and assessing accuracy, repeatability, intermediate precision, specificity, linearity, range and robustness of the method. Relative standard deviations of 2.79% and 4.46% between individual measurements were observed in the assessments of repeatability and intermediate precision, respectively. Small deliberate variations of the conditions hardly affected the results. A locally producible wooden box was designed which ensures TLC photography under standardized conditions and shielding from ambient light. Photography and image analysis were carried out with a low-cost Android-based smartphone. The app allows to share TLC photos and quantification results using messaging apps, e-mail, cable or Bluetooth connections, or to upload them to a cloud. The app is available free of charge as General Public License (GPL) open-source software, and interested individuals or organizations are welcome to use and/or to further improve this software.

Surveillance for substandard and falsified medicines by local faith-based organizations in 13 low- and middle-income countries using the GPHF Minilab

This study evaluates the use of the Global Pharma Health Fund (GPHF) Minilab for medicine quality screening by 16 faith-based drug supply organizations located in 13 low- and middle-income countries. The study period included the year before the COVID-19 pandemic (2019) and the first year of the pandemic (2020). In total 1,919 medicine samples were screened using the GPHF Minilab, and samples showing serious quality deficiencies were subjected to compendial analysis in fully equipped laboratories. Thirty-four (1.8%) of the samples were found not to contain the declared active pharmaceutical ingredient (API), or less than 50% of the declared API, or undeclared APIs, and probably represented falsified products. Fifty-four (2.8%) of the samples were reported as substandard, although the true number of substandard medicines may have been higher due to the limited sensitivity of the GPHF Minilab. The number of probably falsified products increased during the COVID-19 pandemic, especially due to falsified preparations of chloroquine; chloroquine had been incorrectly advocated as treatment for COVID-19. The reports from this project resulted in four international WHO Medical Product Alerts and several national alerts. Within this project, the costs for GPHF Minilab analysis resulted as 25.85 € per sample. Medicine quality screening with the GPHF Minilab is a cost-effective way to contribute to the global surveillance for substandard and falsified medical products.

Modeling the Health and Economic Impact of Substandard and Falsified Medicines: A Review of Existing Models and Approaches

Substandard and falsified medicines are harmful to patients, causing prolonged illness, side effects, and preventable deaths. Moreover, they have an impact on the health system and society more broadly by leading to additional care, higher disease burden, productivity losses and loss of trust in health care. Models that estimate the health and economic impacts of substandard and falsified medicines can be useful for regulators to contextualize the problem and to make an economic case for solutions. Yet these models have not been systematically catalogued to date. We reviewed existing models that estimate the health and economic impact of substandard and falsified medicines to describe the varying modeling approaches and gaps in knowledge. We compared model characteristics, data sources, assumptions, and limitations. Seven models were identified. The models assessed the impact of antimalarial (n = 5) or antibiotic (n = 2) quality at a national (n = 4), regional (n = 2), or global (n = 1) level. Most models conducted uncertainty analysis and provided ranges around potential outcomes. We found that models are lacking for other medicines, few countries’ data have been analyzed, and capturing population heterogeneity remains a challenge. Providing the best estimates of the impact of substandard and falsified medicines on a level that is actionable for decision-makers is important. To enable this, research on the impact of substandard and falsified medicines should be expanded to more medicine types and classes and tailored to more countries that are affected, with greater specificity.