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

Overview of collected samples

As shown in Fig. 1, 2055 samples were tested and reported in the course of this study. Each of the eight samples sent to a second partner organization for re-testing (see “Methods”) was counted as a single sample. A total of 136 samples were excluded from the present data analysis, most frequently because they represented oral liquid dosage forms. With the exception of protocols for dry syrups containing artemether/lumefantrine, amoxicillin or amoxicillin/clavulanic acid, no Minilab protocols for oral liquid dosage forms exist, as the excipients present in syrups and suspension may interfere with the TLC analysis and may preclude the reliable interpretation of the result. As shown in Fig. 1, analytical results correctly based on GPHF Minilab protocols were reported for 1,919 samples, and these were included into the data analysis.

Figure 1
figure 1

Flow chart showing the evaluation of the reported medicine quality data.

Samples were collected and analyzed in 13 countries by 16 faith-based DSOs, as summarized in Table 1. Fifteen of these organizations are located in sub-Saharan Africa, one in India. Of the 1919 samples included in the data analysis, 1591 (82.9%) were collected from the own stock of these DSOs, or from private vendors. Private vendors are commercial sources from which these organizations purchase medicines for distribution to health facilities, therefore the two categories “own stock” and “private vendors” are combined in Table 1. A total of 205 samples (10.7%) were collected from health facilities. Only 10 samples (0.5%) were products donated to the DSOs. Further 111 samples (5.8%) were collected from informal vendors, with 106 of these collected in four of the five included countries of Central Africa.

Table 1 Overview of collected medicine samples, and results of analysis.

The different organizations involved in this study had different staffing capacities for their contribution to the Minilab surveillance project. The most active organization, located in Cameroon, contributed 512 samples. The partner organization in Rwanda joined the surveillance only in the second project year, and therefore contributed only nine samples.

The stated countries of origin of the included medicine samples are depicted in Fig. 2a. Half of the samples (966 samples; 50.3%) were stated to be produced in India, and 313 (16.3%) in China. Further 426 samples (22.2%) were stated to be produced in Africa, with Nigeria (159 samples; 8.3%), Kenya (98 samples; 5.1%) and Uganda (72 samples; 3.8%) as the most important African producer countries.

Figure 2
figure 2

Stated origin (a) and therapeutic categories (b) of the 1919 included samples.

As shown in Fig. 2b, 1252 samples (65.2%) were medicines for the treatment of infectious diseases, with antibacterials (808 samples; 42.1%) and antimalarials (339 samples; 17.7%) as most frequent categories. Among the medicines for non-communicable diseases, analgesics were included most frequently (225 samples; 11.7%). The most frequently tested dosage forms were tablets (1467 samples; 76.4%), followed by injections (250 samples; 13.0%), capsules (168 samples; 8.8%), and dry syrups (34 samples; 1.8%).

In total, 71 different APIs were tested according to the protocols of the GPHF Minilab manual. A detailed overview of the different APIs and dosage forms of the medicines included into the data analysis is given in Supplementary Table S1.

Results of sample analysis

A research pharmacist (G.G.) cross-checked the data reported by the partner organizations from Africa and Asia, and the categorization of the results as compliant or non-compliant by the partners. Corrections by the research pharmacist were required only in 15 cases (0.8%). Most frequently (six cases), a failure in disintegration testing had been incorrectly reported for modified release tablets; as stated in the GPHF Minilab manual23, these are in fact not expected to disintegrate under the test conditions specified in the Minilab protocol.

Samples which showed major quality deficiencies in the TLC analysis (absence of stated API, presence of undeclared substances, underdosage of declared API) and/or in the disintegration test (i.e., disintegration time > 2 h) were sent for compendial analysis to MEDS or Tübingen University. In eight ambiguous cases (0.4%) a re-test by a second Network member was sought. Three of these cases were found to be compliant in the Minilab re-test, in the other five cases further investigation was considered necessary. Subsequently conducted compendial analysis at the MEDS laboratory revealed that two suspected products were compliant with the specifications while three were not.

After these corrections, eventually 1831 samples (95.4%) were reported as compliant, while for 88 samples (4.6%) quality deficiencies were reported and these were considered as SF products (Fig. 1). Of the 88 samples reported to show deficiencies, 34 (1.8% of evaluated samples) were rated as probably falsified by the research pharmacist: for 16 of these 34 samples, TLC analysis showed that the stated API was absent. In another 9 samples the stated API was absent, but they contained a different, undeclared API. In the remaining 9 cases, visual analysis of the TLC results suggested that the API was present in a much smaller amount than stated on the label, and indeed compendial analysis confirmed for these samples that the API content was < 25% of the stated amount (see Table 2), and at the same time no decomposition products were detected. Examples of TLC results for different types of quality deficiencies are depicted in Fig. 3.

Table 2 Medicine samples identified in this study as probably falsified.
Figure 3
figure 3

Examples of TLC analysis of samples of the present study, showing (a) decomposition of the API; (b) absence of the declared APIs; (c) API content 12.2% of the stated amount; (d) absence of the declared API, and presence of a non-declared API (the non-declared API glibenclamide is not visible in the depicted TLC plate, but was discovered by the local partner in an additional, specific TLC analysis for glibenclamide, prompted by the observed hypoglycemic effect of the falsified medication36). (Photos: Gesa Gnegel, Lutz Heide and Difäm-EPN Minilab Network).

For 19 of the 34 samples rated as probably falsified, the quality deficiencies detected in the GPHF Minilab analysis were confirmed by compendial analysis in the WHO-prequalified laboratory of MEDS or in the laboratory of Tübingen University. For another four samples, compendial analysis was considered unnecessary since reports published by WHO or by a national medicines regulatory authority confirmed that these samples were falsified. For six samples, closely related products had previously been identified as falsified by compendial analysis or an (inter-)national alert. For the remaining five samples, the low number of tablets remaining after the Minilab testing did not allow a confirmation by compendial analysis, but the evidence from TLC analysis and packaging analysis was considered unequivocal.

In total 54 samples (2.8% of evaluated samples) were rated probably substandard (Fig. 2) because of one or several of the following reasons. The most common reason (20 samples) was deficient labelling, such as missing batch numbers or orthographic mistakes, however without conclusive evidence for falsification as described by Hauk et al.31. Fourteen samples showed visual deficiencies of the dosage forms, such as discolorations or cracks in case of tablets, or agglomeration of capsules. Sixteen samples showed non-compliance in disintegration testing. In two of these cases, the tablets had not disintegrated even after two days. The faith-based drug supply organization decided to contact the local manufacturer, presented the test result, and the manufacturer thereupon issued a product recall, as depicted in Supplementary Fig. S1.

In three out of the 54 samples rated as probably substandard, TLC analysis indicated an insufficient amount of the API, estimated to be in the range of 50–80% of the declared amount by visual inspection of the TLC plate. Unfortunately, in these three cases the sample size was insufficient to allow for compendial analysis. In five further samples, representing different batches of captopril tablets from two manufacturers, TLC analysis indicated decomposition of the API (Fig. 3a). Compendial analysis conducted for one sample from each manufacturer respectively proved API contents of only 66.1% and 50.7% of the declared amount, as well as elevated, non-compliant quantities of the decomposition product captopril disulfide.

The limited funds available for the present project did not permit to subject all samples rated as probably substandard to compendial analysis.

Samples identified as probably falsified in this study

Table 2 lists the 34 samples rated as probably falsified, with their declared APIs, their countries of discovery, their stated country of manufacture, and the result of their chemical analysis. Supplementary Table S2 provides further details on these samples, including the brand names of the products, batch numbers, expiry dates and names of the stated manufacturers.

Ten of these 34 samples were labeled to contain chloroquine as API, eight to contain quinine, and another eight to contain sulfamethoxazole/trimethoprim. Out of the 34 probably falsified medicines 32 were anti-infectives. Probably falsified samples were found only in five of the 13 countries where this study was conducted, i.e., in Cameroon, Chad, DRC, and CAR (Central Africa) and in Nigeria (West Africa). Out of the 111 medicines collected from informal vendors, 14 (12.6%) were rated as probably falsified, contrasting to 20 (i.e., only 1.1%) out of the 1,808 medicines from legal sources (p < 0.0001). Out of the 970 medicines collected from the own stock of the participating faith-based DSOs, only three (0.3%) were rated as probably falsified, indicating a largely successful product and supplier selection by the DSOs.

Fifteen of the 34 probably falsified samples were stated to be produced in Africa (13 of these in Nigeria), and the others in Europe (8), India (5), and China (5). For one sample no country of manufacture was indicated. However, the manufacturer and the country of origin stated on the label of a falsified medicine may obviously be incorrect. Some manufacturers named in Supplementary Table S2, such as Strides Arcolab, India, have an excellent international reputation which falsifiers may have criminally misused in the labelling of their falsified medicines. For the artemether/lumefantrine preparation listed in Supplementary Table S2, Strides Arcolab confirmed to the authors and to WHO that this product is a falsification. Some other manufacturers listed in Supplementary Table S2, such as “Enitop Pharmaceuticals Nig. Ltd” and “Pharmachim Bulgaria” are non-existing companies37.

Notably, out of the 34 probably falsified medicines, 22 samples (64.7%) were reported to show deficiencies already in visual inspection, such as missing data or mistakes in the labelling, or visible deficiencies of the dosage forms. In contrast, out of the 1885 medicines considered non-falsified, 34 (i.e., only 1.8%) were reported to show visual deficiencies. This difference is statistically significant (p < 0.0001) and emphasizes that careful visual inspection is an important and powerful tool in the screening for falsified medicines26,38,39.

Changes of the occurrence of substandard and falsified medicines in the course of the COVID-19 pandemic

Figure 4 compares the number of probably falsified and probably substandard samples reported in the two investigated years. In 2019 (before the pandemic), 11 samples (1.3%) out of 871 were probably falsified. In 2020 (during the pandemic) this increased to 23 (2.2%) out of 1048 samples. Though this difference does not reach statistical significance (p = 0.14), it indicates a trend towards an increase in the occurrence of falsified medicines, as has been predicted at the outset of the pandemic12. Notably, the observed increase was nearly entirely due to the occurrence of ten falsified chloroquine samples (nine samples in the first half of 2020, one in the second half).

Figure 4
figure 4

Changes of the occurrence of probably falsified and probably substandard medicines in the course of the COVID-19 pandemic.

Sharing data with stakeholders

All probably falsified samples listed in Table 2 and Supplementary Table 2, as well as four products rated as severely substandard (i.e. amount of the API estimated as 50–80% of the declared amount by visual inspection of the TLC plate; or TLC indicating major decomposition of the API, as shown in Fig. 3a) were reported to the WHO Global Surveillance and Monitoring System for SF Medical Products (Rapid Alert System). These reports were made by G.G., without mentioning the names of the partner organizations to protect their anonymity. WHO decided about further actions, such as contacting the stated manufacturers, informing responsible national regulatory authorities, and in very serious cases publishing international WHO Medical Product Alerts. The medicine quality analyses conducted within this study resulted in the release of four WHO Medical Product Alerts36,37,40,41, warning about the cases listed as No. 6, 7, 10–14, 16, 20, 21, 23 and 24 in Table 2/Supplementary Table S2. Several national drug regulatory authorities also published alerts about these cases, e.g. the National Authority for Food and Drug Administration of Nigeria (NAFDAC)42,43,44, the Ministère de la Santé et de la Population of CAR (Supplementary Fig. S2), the Laboratoire National de Contrôle de Qualité des Médicaments et d’Expertise (LANACOME) of Cameroun (Supplementary Fig. S3) and the Drug Regulatory Authority of Pakistan45. NAFDAC also published an alert about the case listed as No. 33 in Table 2/Supplementary Table S246.

Funding requirements for the surveillance for substandard and falsified medicines

As reported by Petersen et al.26, the initial provision of GPHF Minilabs for most partners of the Difäm-EPN Minilab Network in the years 2010–2015 had required approximately 5600 US$ per Minilab, and the initial training of the personnel required approximately 2300 US$ per partner organization. As summarized in Table 3, in the present reporting period (2019–2020) external funding was required for consumables, confirmatory compendial analyses, training, and for the research pharmacist (G.G.) at Difäm who also acted as network coordinator (total 0.2 full-time equivalents). All personnel costs required for the local GPHF Minilab analyses were borne by the faith-based DSOs in Africa and Asia themselves. Most of the tested medicine samples were obtained from the own stocks of the participating DSOs, or from the private vendors they used as source of their supplies (Table 1); no external funds were provided for the acquisition of these samples. A refund of the purchase costs for samples from external sources had been offered out of the project budget, but none of the DSOs claimed such refunds in the reporting period, probably due to the comparatively small sums involved. In the original project budget, one yearly network meeting had been foreseen and budgeted at 6,400 € each. Due to the outbreak of the COVID-19 pandemic, however, these meetings were held online, and this budget line remained untouched.

Table 3 Funding requirements for the surveillance for substandard and falsified medicines in the reporting period (Jan. 2019–Dec. 2020).

Based on the 1919 samples included into the data analysis (Fig. 1), the costs for consumables for GPHF Minilab analysis (Table 3) resulted as 7.45 € per sample on average. However, this varied between the partners: DSOs testing a small number of samples but including a high number of different APIs required higher costs per sample, e.g. since many reference standards needed to be replaced upon expiry.

Based on the total external funding of 49,600 € (Table 3), the total external costs amounted to 25.85 € per sample. Notably, a compendial analysis of all 1919 samples, even at the reduced rates offered by MEDS for this project (618 € per sample on average), would have costed approximately 1.2 million €, i.e., 23 times more than the actual external funding of the project.

Based on the 34 probably falsified medicines listed in Table 3, the external costs of the identification of one such product resulted as 1459 €.

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