Literature DB >> 25525570

Prevalence estimates of substandard drugs in Mongolia using a random sample survey.

Daariimaa Khurelbat1, Gereltuya Dorj2, Enkhtuul Bayarsaikhan1, Munkhdelger Chimedsuren3, Tsetsegmaa Sanjjav4, Takeshi Morimoto5, Michael Morley6, Katharine Morley7.   

Abstract

To determine the prevalence of substandard drugs in urban (Ulaanbaatar) and rural (selected provinces) areas of Mongolia, samples of 9 common, therapeutically important drugs were collected from randomly selected drug outlets in Ulaanbaatar and 4 rural provinces by "mystery shoppers". Samples were analyzed by visual inspection, registration status, and biochemical analysis. Samples failing to meet all Pharmacopeia quality tests were considered substandard. In the rural provinces, 69 out of 388 samples were substandard, giving an estimated prevalence of substandard drugs of 17.8% (95% CI: 14.1-22.0). There were 85 unregistered samples, giving a prevalence estimate of unregistered drugs of 21.9%. (95% CI: 17.9-26.3). In the urban Ulaanbaatar districts, 112 out of 848 samples were substandard, giving an estimated prevalence of substandard drugs of 13.2% (95% CI: 11.0-15.7). There were 150 unregistered samples, giving a prevalence estimate of unregistered drugs of 17.7% (95% CI: 15.2-20.4). In the rural provinces, 35 out of 85 (41.2%) unregistered samples were substandard; whereas 34 out of 303 (11.2%) registered samples were substandard. (p < 0.0001) In the urban districts, 18 out of 150 (12.0%) unregistered samples were substandard, whereas 94 out of 698 registered were substandard. (13.5%) (p = 0.6). The prevalence of substandard and unregistered drugs is higher in rural provinces. There is a significant association between substandard and unregistered drugs in the provinces but not in the urban districts. The underlying causes for substandard drugs need to be further investigated in order to help formulate strategies to improve pharmacovigilance and the drug supply quality in Mongolia.

Entities:  

Keywords:  Asia; Developing countries; Falsified; Medication quality; Patient safety; Substandard

Year:  2014        PMID: 25525570      PMCID: PMC4265637          DOI: 10.1186/2193-1801-3-709

Source DB:  PubMed          Journal:  Springerplus        ISSN: 2193-1801


Background

Poor quality drugs have been increasingly recognized as a global public health threat because they have the potential to result in inadequate treatment, cause adverse effects from toxic ingredients, and promote drug resistance. The nomenclature of the categories of poor quality medications can be confusing. The World Health Organization recently chose to group all categories together as “SSFFC”: substandard, spurious, falsely-labeled, falsified, and counterfeit. Revision of these categories as: “substandard” - drugs that for unintentional reasons do not meet the legally required quality specifications of a country’s regulators, “unregistered” - drugs that do not have the legally required marketing authorization from the country’s regulators, and “falsified” - drugs that are unlawful, and violate the regulators quality specifications, with criminal intent was subsequently suggested (Attaran et al. 2012). Fernandez, et al. raise the issue that a genuine drug found to have an insufficient amount of an active ingredient could be substandard or degraded (Fernandez et al. 2011), indicating poor quality drugs can result from issues in production or external factors such as environmental conditions, impacting quality after distribution. The true extent of the problem is difficult to ascertain. Reasons for this include the difficulty and expense in performing a methodologically sound study, reluctance of governments to disclose information and the fact that many of the effects on patients are difficult to detect and hidden in other public health statistics (Cockburn et al. 2005). In his 2010 article, Newton states there is an urgent need for data of sufficient sample size, with random sampling design to reliably estimate the prevalence of poor quality medicines (Newton, et al. 2010) Literature reviews of prevalence studies on falsified/substandard drugs report that the percentage of substandard drugs in various Asian and African countries range from 8-46% (Caudron et al. 2008), and the median prevalence of substandard/falsified medicines was 28.5% (range 11–48%) (Almuzaini et al. 2013). The World Health Organization (WHO) conducted a survey on the quality of selected anti-malarial medication in 6 subSaharan African countries, which found that 28.5% of the samples failed to meet testing requirements, with 11.6% having extreme deviations, and therefore likely to have negative health implications (Sabartova et al. 2011a). Another WHO survey was conducted on the quality of anti-tuberculosis medications in Russia, and found 11.3% of the samples failed to meet study specifications, with 1.0% having extreme deviations (Sabartova et al. 2011b). In 1999, WHO conducted a survey of drug quality in Myanmar and Vietnam, and found that 16% of the samples did not meet all specifications of testing (Wondemagegnehu 1999). Between 2004–2006 the pharmaceutical procurement system in Mongolia underwent decentralization, and is now 100% privatized. In the current system, the Division of Pharmaceutical and Medical Devices, Mongolian Ministry of Health (MoH) is responsible for the policy, planning and regulatory affairs in providing pharmaceutical care in Mongolia. The special licenses for manufacturing, importing, purchasing pharmaceuticals and medical devices are granted by the Special Permission Committee of the MoH. Drugs are distributed through drug wholesalers and retail drug outlets (community pharmacies and revolving drug funds (RDF)). Wholesalers can import and procure drugs with an approval and special permission from the Mongolian Minister of Health. In 2011, there were 158 registered drug wholesaling companies and 42 local drug manufacturing companies, some of which act as both wholesalers and retailers. Approximately 85% of all drugs are imported from other countries, primarily Russia and India, followed by Germany, Slovenia and China. Poor quality drugs have been a concern in Mongolia, supported by the findings from a 2006 study on unregistered, falsified and substandard drugs (Mongolia Ministry of Health 2006). Using convenience sampling methods, 225 samples were collected from 40 drug outlets around the country, 55 of which were felt to be “suspicious” and were sent for further testing. Sixteen of these were felt to be “inconsistent” and 8 were possibly counterfeit. A 2008 study by Tsetsegmaa found that 11 of the 16 medications reported in the surveillance were substandard (Tsetsegmaa 2008). In a 2009 report, lack of knowledge about the effectiveness of drug quality monitoring in Mongolia was reported as a gap that should be a priority for further investigation (Abdelkrim 2009). This research study was undertaken to address these concerns, and provide data of good methodological quality to accurately determine the prevalence of substandard drugs in the rural and urban areas of Mongolia after the decentralization and privatization of the Mongolian pharmaceutical system. This information will be of value to Mongolian policy makers, public health officials and pharmaceutical practitioners to reliably determine the extent of the problem, and then can serve as a valid comparison for future studies to evaluate interventions to improve the drug supply quality. It will also help guide further research to better understand the health impact of poor quality medications in Mongolia.

Methods

Site selection

Mongolia is a landlocked country in north central Asia, with 21 rural provinces, plus 1 municipality, the capital city of Ulaanbaatar where over 60% of the population lives. Because the conditions in rural provinces vary greatly from the urban area of Ulaanbaatar, samples were collected, analyzed, and reported independently. Samples for this study were collected from 4 districts in Ulaanbaatar (Chingeltei, Khan-Uul, Bayanzurkh, and Songinokhair) and 4 rural provinces (Bayan-Uglii, Dornogobi, Selenge, and Umnugobi) representing the main geographic regions of the country. Samples were obtained from the different types of drug outlets in the provinces: Revolving Drug Fund (RDF- a government outlet), retail pharmacy outlets, and wholesalers. In Ulaanbaatar districts, samples were only obtained from retail pharmacy outlets and wholesalers, as RDF outlets are only present in the provinces. Samples from unofficial drug outlets and the informal market were not included in this study. Medications included in the study were selected based on high therapeutic importance and utilization based on discussions with local experts from Schools of Pharmacy, Public Health, and Mongolian National University of Medical Sciences. They are all on the Essential Drug List and available with or without a prescription. All samples were tablets or capsules and include antimicrobials (ampicillin, amoxicillin, co-trimoxazole, metronidazole, doxycycline, nystatin), analgesics (paracetamol and ibuprofen), and bromhexin, a commonly used medication for respiratory illness (Table  1).
Table 1

Drugs in study population

Name of drugDosage formPharmacopeia reference
Metronidazole250 mg/tabMongolian National Pharmacopeia 2011
Pharmacopeia of the People’s Republic of China 2005. Vol. II,
Nystatin500000 ID/tabBritish Pharmacopeia 2001. Vol.2
Ibuprofen400 mg/tabMongolian National Pharmacopeia 2011
Pharmacopeia of the People’s Republic of China 2005. Vol. II,
Co-trimoxazole480 mg/tabMongolian National Standard-MNS 6149-2010
Amoxicillin500 mg/capMongolian National Pharmacopeia 2011
Paracetamol500 mg/tabMongolian National Pharmacopeia 2011
Pharmacopeia of the People’s Republic of China 2005. Vol. II,
Ampicillin500 mg/capBritish Pharmacopeia 2001. Vol. 2
Mongolian National Pharmacopeia 2011
USP 23
Bromhexin8 mg/tabMongolian National Pharmacopeia 2011
Pharmacopeia of the People’s Republic of China 2005. Vol. II,
Doxycycline100 mg/capMongolian National Standard-MNS 5776–2007
Pharmacopeia of the People’s Republic of China 2005. Vol. II,
Drugs in study population

Sample size calculation

Prevalence studies from other countries indicate a wide range of substandard drugs, 8-46% (Caudron et al. 2008), and 11–48% (Almuzaini et al. 2013). Based on this information and the previous studies of falsified/substandard drugs in Mongolia, we targeted our sample size to detect at least a 5% prevalence (alpha of 0.05 and beta of 0.9). This calculation was 134 samples for each drug (1206 for all drug types combined) distributed among the provinces or districts. In order to detect a 10% prevalence, the sample size needed was 67 (603 combined) and 15% prevalence was 38 samples (342 combined).

Sampling techniques

The sampling strategy included weighting the sample size by population and the number of the types of drug outlets in the province or district. Drug outlets to be sampled were selected randomly. A sample was defined as 100 dosage units (tablet or capsule) of a given drug of the same lot number purchased in blister packs of 10 dosage units. Samples were collected from the 4 provinces between May 2012 and September 2012 and from the 4 Ulaanbaatar districts between July 2012 and March 2013 by “mystery shoppers”. These were trained field workers, who presented themselves as local customers, and followed the study protocol for obtaining drug samples based on recommended sampling techniques (Newton et al. 2009). If they were unable to purchase the necessary quantity for a complete sample from one batch or lot, this was noted and attempts were made to purchase it from another randomly selected outlet of the same type. Collected samples were placed in a box, then transported to and stored in lockers at the School of Pharmacy, Mongolian National University of Medical Sciences. The transport box and lockers met the temperature and humidity requires of the WHO Guidelines for the Sampling of Pharmaceutical Products, and were accessible only by the main study investigator.

Sample analysis

Sample analysis for each sample consisted of visual inspection of the packaging and labeling, and determination of registration status, expiration date, country of manufacture, biochemical analysis, and company of manufacture. An online database developed by the Ministry of Health in Mongolia (Licemed) and archive documents from the registration of drugs were used to complete the visual inspection. The database includes information such as size, color, labeling and numbers of the packages and labeling. In addition, the WHO guideline for the Development of Measures to Combat Counterfeit Drugs was used. (World Health Organization 1999) A sample was considered suspicious if the package and labeling was not consistent with registered information for that drug and manufacturer. Samples with suspicious packaging and labeling were sent to the manufacturers for confirmation. If the manufacturer confirmed that it was their product, the sample was considered acceptable. The registration status of all samples was determined by visual inspection of the packaging, and then confirmed using the drug registration archives at the Mongolian Ministry of Health. Registration was not considered a requirement for determining whether or not a sample was substandard. Drug samples underwent biochemical analysis by 1 of 3 laboratories in Mongolia: Drug and Bio-preparation Central Laboratory of Specialized Professional Inspection Agency (SPIA); Drug Control Laboratory, School of Pharmacy, Mongolian National University of Medical Sciences; and the Drug Testing Laboratory “Monos Group”. These laboratories are accredited by the Standardization and Technical Regulatory Office of the Centre for Standardization and Measurement in Mongolia, which is responsible for the technical standards in local production and quality control. The Pharmacopoeias were chosen according the country of origin of the sample or specification requirements of the manufacturer (Table  1). (British Pharmacopoeia 2001, Mongolian Pharmacopeia 2011, Pharmacopeia of the People’s Republic of China 2005). These requirements vary by drug, and include 8–11 of the following tests: appearance, assay, disintegration, dissolution, hardness, identification, irradiance absorption, water, friability, weight average and weight variation (Table  2). The qualitative analysis included: 1). visual inspection of package and labeling, 2). characteristics of the sample (appearance, odor, color dosage form), 3). uniformity of weight, disintegration, and dissolution, 4). identification of components by chemical reaction, and thin layer chromatography, spectrum analysis on UV spectrophotometer and IR spectrophotometer. Quantitative analysis included assay of active compounds by spectrophotometric, titrometric and chromatographic methods. A sample was considered to be substandard if it failed to pass all required tests for the drug required by the article requirements in the Pharmacopeia used, that is, if the sample failed one or more of the required tests it was considered substandard.
Table 2

Sample analysis definitions

TestDefinition
AppearanceClean, smooth surface and uniform color of tablet or capsule
Friction and substantialTablet crushing strength
Weight averageAverage weight of 20 tablets
Weight variationDifference between the weight of the content of each solid form and the average weight of solid forms
DisintegrationDisintegration or disbursement of solid preparations into fragments or particles in a liquid medium
DissolutionRate and degree of dissolution of active ingredients in liquid medium
Content uniformityContents of single ingredient solid preparations
Water (Loss on drying)Determine water loss on drying
IdentificationVerify identity by visual inspection
Irradiance absorptionAbsorbance in the ultraviolet region
AssayDetermine content of active ingredients
Sample analysis definitions

Ethics approval

Ethics approval was obtained from the World Health Organization Ethics Review Committee and the Medical Ethics Committee of the Ministry of Health, Mongolia.

Statistical analyses

Measurements were presented as numbers and percentages with 95% confidence intervals (CIs), and were compared with the chi-square test or Fisher’s exact test. P values <0.05 were regarded as statistically significant.

Results

Description of sample and analysis results

Sample description

The number of samples collected for this study was 388 from the rural provinces and 848 from the urban districts of Ulaanbaatar. The distribution of the samples based on location by drug outlet type is presented in Table  3, and location by drug in Table  4.
Table 3

Number of samples by location and drug outlet type

WholesaleRetailRDF*Total
N%N%N%N%
Rural provinces
Bayan-Ulgii153.97719.8348.812632.5
Dornogobi143.6307.7369.38020.6
Selenge123.15213.45814.912231.4
Umnugobi102.6277.0235.96015.5
All provinces 51 13.1 186 47.9 151 38.9 388 100
Urban districts
Bayanzurkh414.824829.2NANA28934.1
Chingeltei505.911113.1NANA16119.0
Khan-Uul323.89711.4NANA12915.2
Songinokhairkhan263.124328.7NANA26931.7
All districts 149 17.6 699 82.4 NA NA 848 100

*RDF: Revolving Drug Fund (government outlet).

Table 4

Number of samples by drug and location

AmoxicillinAmpicillinBromhexinCo-trimoxazoleDoxycyclineIbuprofenMetronidazoleNystatinParacetamolTotal
Rural province N % N % N % N % N % N % N % N % N % N %
Bayan-Ulgii174.4143.6133.4174.4102.6133.4143.6153.9133.412632.5
Dornogobi112.882.182.1102.6102.682.182.192.382.18020.6
Selenge123.1133.4143.6143.6143.6133.4133.4184.6112.812231.4
Umnugobi61.551.361.561.592.392.361.571.861.56015.5
All provinces 46 12 40 10 41 11 47 12 43 11 43 11 41 11 49 13 38 10 388 100
Urban district
Bayanzurkh333.9374.4414.8303.5273.2313.7374.4313.7222.628934.1
Chingeltei242.8151.8131.5182.1172.0202.4212.5192.2141.716119.0
Khan-Uul141.7151.8192.2141.7111.3121.4161.9161.9121.412915.2
Songinokhairkhan303.5273.2333.9333.9283.3323.8354.1344.017226931.7
All districts 101 11.9 94 11.1 106 12.5 95 11.2 83 9.8 95 11.2 109 12.9 100 11.8 65 7.7 848 100
Number of samples by location and drug outlet type *RDF: Revolving Drug Fund (government outlet). Number of samples by drug and location

Sample inspection

Out of 388 samples from the rural provinces, only 3 were found to be past expiration date. There were 4 others that expired within the data collection period of May to August 2012, so may have recently expired. Out of 848 samples from the Ulaanbaatar districts, none were found to be past expiration date. On initial inspection, 22 drug samples from the rural provinces and urban districts combined were found to have variation in the packaging and labeling of the drugs when compared with the products registered in Mongolia. Upon review by the manufacturer, all 22 were found to be acceptable or meeting standards due to packaging updates.

Biochemical sample analysis

Failure to pass the assay test (e.g. amount of required ingredients fell outside range of Pharmacopeia standards) was the most common reason that a sample was found to be substandard. Failure to pass this test indicates that the sample did not meet the threshold requirements regarding amount of drug present and does not give any information about the degree or direction of deviation from the required standard (Table  5). In the provincial group, 51 out of 388 (13.4%, 95% CI: 9.9-16.9) samples failed the assay test. The other common reasons were weight variation and weight average. There were a few samples failing tests for dissolution, disintegration and friction (Table  6). In the Ulaanbaatar district samples, 55 out of 848 (6.6%, 95% CI: 4.9- 8.4 failed the assay test (Table  5). The other common reasons were disintegration and dissolution. There were a few samples that failed the following tests weight variation, weight average, and friction (Table  7).
Table 5

Number of samples failing assay by location

RuralUrban
N%95% CI*N%95% CI*
Failed assay 5113.19.9, 16.9556.54.9, 8.4
Passed assay 33786.983.1, 90.179393.591.6, 95.1
Total 388 100 848 100

*CI: confidence interval

Table 6

Sample analysis for drugs by acceptability from rural provinces

AmoxicillinAmpicillinBromhexinCo-trimoxazoleDoxycyclineIbuprofenMetronidazoleNystatinParacetamolTotal
#%#%#%#%#%#%#%#%#%#%
Not acceptable
Assay21%00%00%62%41%114%176%73%42%512%
Disintegration00%00%00%10%00%52%10%00%00%70%
Dissolution10%00%00%00%00%52%21%00%31%110%
Friction00%00%00%51%00%00%00%00%00%50%
Wt average00%00%00%10%00%00%155%00%00%161%
Wt variation10%00%00%31%10%52%124%00%52%271%
Not acceptable total 4 1% 0 0% 0 0% 16 5% 5 2% 26 9% 47 16% 7 3% 12 5% 117 4%
Acceptable
Appearance4614%4014%4117%4714%4314%4314%4114%4917%3814%38815%
Assay4413%4014%4117%4112%3913%3211%248%4214%3413%33713%
Disintegration4614%4014%4117%4614%4314%3813%4014%4917%3814%38114%
Dissolution4514%4014%21%51%4314%3813%3914%00%3513%2479%
Friction00%00%00%4012%00%00%00%00%00%402%
Identification4614%4014%4117%4714%4314%4314%4114%4917%3814%38815%
Irradiance absorption00%00%00%00%52%00%00%00%00%50%
Substantial00%00%00%21%00%00%00%00%00%20%
Water41%00%00%00%00%00%00%00%00%40%
Wt average4614%4014%4117%4614%4314%4314%269%4917%3814%37214%
Wt variation4514%4014%4117%4413%4214%3813%2910%4917%3312%36114%
Acceptable total 322 99% 280 100% 248 100% 318 95% 301 98% 275 91% 240 84% 287 97% 254 95% 2525 96%
Grand total 326 100% 280 100% 248 100% 334 100% 306 100% 301 100% 287 100% 294 100% 266 100% 2642 100%
Table 7

Sample analysis for drugs by acceptability from urban districts

AmoxicillinAmpicillinBromhexinCo-trimoxazoleDoxycyclineIbuprofenMetronidazoleNystatinParacetamolTotal
#%#%#%#%#%#%#%#%#%# %
Not Acceptable
Assay91%00%00%00%81%81%61%234%10%551%
Disintegration00%00%00%20%00%365%00%00%61%441%
Dissolution00%00%00%10%10%81%51%00%51%200%
Friction00%00%00%00%00%10%00%00%00%10%
Wt Average00%00%00%00%00%00%30%00%00%30%
Wt Variation20%00%00%00%71%20%30%00%10%150%
Not Acceptable Total 112%00%00%30%163%558%172%234%133%1382%
Acceptable Appearance10114%9414%10614%9513%8314%9513%10914%10017%6514%84814%
Assay9213%9414%10614%9513%7513%8712%10313%7813%6414%79313%
Disintegration10114%9414%10614%9112%8314%598%10914%10017%5913%80213%
Dissolution10114%9414%20%9312%8214%8612%10113%20%5813%61910%
Friction10%00%10414%9412%10%629%30%10%00%2664%
Identification10114%9414%10614%9513%8314%9513%10914%10017%6514%84814%
Wt Average10114%9414%10614%9513%8314%9513%10614%10017%6514%84514%
Wt Variation9914%9414%10614%9513%7613%9313%10614%10017%6414%83314%
Total Acceptable 69798%658100%742100%753100%56697%67292%74698%58196%44097%585498%
Grand Total 708 100% 658 100% 742 100% 756 100% 582 100% 727 100% 763 100% 603 100% 453 100% 5992 100%
Number of samples failing assay by location *CI: confidence interval Sample analysis for drugs by acceptability from rural provinces Sample analysis for drugs by acceptability from urban districts

Prevalence of substandard drugs

Rural provinces

Out of 388 samples collected from all 4 rural provinces, 69 were classified as substandard. This gives a substandard drug prevalence rate of 17.8% (95% CI: 14.1-22.0) in the rural provinces (Table  8).
Table 8

Prevalence of substandard drug samples by location

RuralUrban
N%95% CI*N%95% CI*
Substandard 6917.814.1, 22.011213.211.0, 15.7
Acceptable 31982.278.0, 85.973686.884.3, 89.0
Total 388 100 848 100

*CI: confidence interval.

Prevalence of substandard drug samples by location *CI: confidence interval.

Urban districts

Out of 848 samples collected from all 4 urban districts of Ulaanbaatar, 112 were classified as substandard. This gives a prevalence rate of 13.2% (95% CI: 11.0-15.7) substandard drugs in the urban districts of Ulaanbaatar (Table  8).

Registration status

Out of 388 samples collected from the 4 provinces, 85 were unregistered. This gives a prevalence estimate of unregistered drugs in the provinces of 21.9%. (95% CI: 18.0-26.3) (Table  9). Out of the 85 unregistered samples, 35 were substandard (41.2%), compared with 34 substandard samples out of the 303 registered samples (11.2%). This is a statistically significant difference (p < 0.0001) (Table  10).
Table 9

Prevalence of unregistered drug samples by location

RuralUrban
N%95% CI*N%95% CI*
Unregistered 8521.918.0, 26.315017.715.2, 20.4
Registered 30378.173.6,82.169882.379.6, 84.8
Total 388 100 848 100

*CI: confidence interval.

Table 10

Substandard samples by location and registration status

SubstandardAcceptableTotal
Rural provincesN%N%N% Substandard
Unregistered359.05012.98541.2
Registered348.826969.330311.2
All provinces 69 17.8 319 82.2 388
Urban districts N % N % N % Substandard
Unregistered182.113215.615012.0
Registered9411.160471.269813.5
All districts 112 13.2 736 86.8 848
Prevalence of unregistered drug samples by location *CI: confidence interval. Substandard samples by location and registration status

Districts of Ulaanbaatar

Out of 848 samples, collected from the 4 districts of Ulaanbaatar, 150 were unregistered. This gives a prevalence estimate of unregistered drugs in the Ulaanbaatar districts of 17.7% (95% CI: 15.2-20.4) (Table  9). Out of 150 unregistered samples, 18 were substandard (12.0%), compared with 94 substandard samples out of the 698 registered samples (13.5%). This difference is not statistically significant (p = 0.6) (Table  10).

Discussion

Our results provide prevalence estimates for substandard drugs in Mongolia of 17.8% in the rural provinces and 13.2% in the urban districts of Ulaanbaatar, based on failure to meet the threshold quality standards established in the selected Pharmacopeia. While our study design does not allow us to directly compare these results from these 2 regions, it is interesting to note a modestly higher prevalence of substandard drugs in the rural sample. We also noted a significant association between substandard and unregistered drugs in the provinces, but not in the urban districts. Our prevalence estimates of substandard drugs of 17.8% and 13.2% in Mongolia are in alignment with the range of 11-14% reported by Almuzaini et al. in their recent review of substandard and falsified medications in low and middle income countries in Asia and Africa (Almuzaini et al. 2013). Our prevalence estimates are lower than the median percentage of 28% reported in this review, however, this comparison is limited by the differences in methodology, sample size, inclusion criteria and drugs selected between the various studies reported and ours. The most common reason for a sample to be substandard was failure to pass assay test, which is consistent with the findings of other studies (Almuzaini et al. 2013). Failure to pass the assay test, along with failure to pass the disintegration and dissolution tests, the other most common reasons in our study, indicates that the bioavailability of the active ingredients was compromised. This can lead to ineffective treatment, and in the case of antibiotics, promote drug resistance. Of note, almost none of the samples were found to be post-expiration date, suggesting other factors are contributing to the degradation in drug quality. Further investigation into drug transport and storage conditions may help better understand this, especially given the extreme weather conditions found in Mongolia. Another interesting finding of our study was the 21.9% prevalence of unregistered drugs in the provinces and 17.7% in the districts of Ulaanbaatar. This raises the importance of further investigation of the drug supply chain and evaluation of drug regulatory policies. Such initiatives could be undertaken at the national level and through collaborations with neighboring countries. We believe this may be an especially important step to improve the quality of the drug supply in the provinces where there was a statistically significant association between unregistered and substandard drug samples. An adequate sample size is essential to obtaining valid results. Our sample size calculations indicated that we would need 342 samples for each region to detect a 15% prevalence. We achieved this in both the rural provinces (N = 388, 17.8% prevalence) and the urban districts (N = 848, 13.2% prevalence). However, there are some weaknesses in our study that could underestimate our prevalence estimates. These include the potential for drug outlet personnel to selectively provide drugs if they were suspicious about the reason for the purchase, and excluding drug samples from the unlicensed market, where the prevalence of substandard drugs has found to be significantly higher (Almuzaini et al. 2013). Another potential issue is that the biochemical analysis was performed at 3 different drug testing laboratories in Mongolia. Although they all used the same Pharmacoepeia standards, the possibility of variability in testing between facilities exists. In order to confirm the accuracy of the results, we had planned to send 10% of the samples to an outside lab for verification. Because of budgetary constraints, only 4 substandard samples (2.2%) were actually sent for testing at an outside reference laboratory (National Institute of Drug Quality Control of Vietnam, Hanoi, Vietnam). These 4 samples were all verified as correctly classified, but it is not a large enough number and did not include any acceptable samples, therefore we cannot claim to validate our findings by outside reference laboratory testing. Another important limitation of our study is that it does not provide any details about the degree of variation from the threshold requirements of the Pharmacopeia quality standards. Our study also does not provide any information about the presence of harmful ingredients. Because of this, our ability to make any inferences about the potential clinical, safety, or economic impact of the substandard drugs in Mongolia is limited, but it does support the need for increased pharmacovigilance and review of drug regulatory policies. Further details of the biochemical analysis of the substandard samples, particularly the degree and direction of the deviation of the samples failing the assay, could provide additional valuable insight into the public health impact of poor drug quality.

Conclusions

Our findings indicate that the presence of substandard drugs raise a genuine concern in both urban and rural areas of Mongolia. In addition, we found that unregistered drugs are common in both areas, with a significant association between substandard and unregistered drugs in the rural provinces. This highlights an important opportunity to improve the quality of the drug supply in Mongolia by reviewing and enforcing drug registration and inspection polices. Improving drug storage conditions and importation monitoring at borders are other interventions that can potentially improve drug supply quality, especially in rural provinces. Other areas for further investigation to better understand the quality of the drug supply in Mongolia would be to determine the degree of variation in the assay results for substandard drug samples, sampling the unlicensed market, and investigating the drug supply chain, especially in the provinces. Another important area for further study of the public health impact of substandard drugs is evaluating the patterns of antibiotic resistance and health outcomes for people living in areas with a high prevalence of substandard drugs.
  7 in total

Review 1.  Substandard medicines in resource-poor settings: a problem that can no longer be ignored.

Authors:  J-M Caudron; N Ford; M Henkens; C Macé; R Kiddle-Monroe; J Pinel
Journal:  Trop Med Int Health       Date:  2008-07-08       Impact factor: 2.622

2.  How to achieve international action on falsified and substandard medicines.

Authors:  Amir Attaran; Donna Barry; Shamnad Basheer; Roger Bate; David Benton; James Chauvin; Laurie Garrett; Ilona Kickbusch; Jillian Clare Kohler; Kamal Midha; Paul N Newton; Sania Nishtar; Paul Orhii; Martin McKee
Journal:  BMJ       Date:  2012-11-13

3.  Poor quality drugs: grand challenges in high throughput detection, countrywide sampling, and forensics in developing countries.

Authors:  Facundo M Fernandez; Dana Hostetler; Kristen Powell; Harparkash Kaur; Michael D Green; Dallas C Mildenhall; Paul N Newton
Journal:  Analyst       Date:  2010-11-25       Impact factor: 4.616

4.  Impact of poor-quality medicines in the 'developing' world.

Authors:  Paul N Newton; Michael D Green; Facundo M Fernández
Journal:  Trends Pharmacol Sci       Date:  2010-02-01       Impact factor: 14.819

5.  Substandard and counterfeit medicines: a systematic review of the literature.

Authors:  Tariq Almuzaini; Imti Choonara; Helen Sammons
Journal:  BMJ Open       Date:  2013-08-17       Impact factor: 2.692

Review 6.  Guidelines for field surveys of the quality of medicines: a proposal.

Authors:  Paul N Newton; Sue J Lee; Catherine Goodman; Facundo M Fernández; Shunmay Yeung; Souly Phanouvong; Harparkash Kaur; Abdinasir A Amin; Christopher J M Whitty; Gilbert O Kokwaro; Niklas Lindegårdh; Patrick Lukulay; Lisa J White; Nicholas P J Day; Michael D Green; Nicholas J White
Journal:  PLoS Med       Date:  2009-03-24       Impact factor: 11.069

7.  The global threat of counterfeit drugs: why industry and governments must communicate the dangers.

Authors:  Robert Cockburn; Paul N Newton; E Kyeremateng Agyarko; Dora Akunyili; Nicholas J White
Journal:  PLoS Med       Date:  2005-03-14       Impact factor: 11.069

  7 in total
  8 in total

1.  Erroneous formulation of delayed-release omeprazole capsules: alert for importing countries.

Authors:  Mohammad Sofiqur Rahman; Naoko Yoshida; Hirohito Tsuboi; Tep Keila; Tey Sovannarith; Heng Bun Kiet; Eav Dararth; Theingi Zin; Tsuyoshi Tanimoto; Kazuko Kimura
Journal:  BMC Pharmacol Toxicol       Date:  2017-05-03       Impact factor: 2.483

2.  A cross-sectional analysis of falsified, counterfeit and substandard medicines in a low-middle income country.

Authors:  Daariimaa Khurelbat; Gereltuya Dorj; Bruce Sunderland; Tsetsegmaa Sanjjav; Enkhtuul Bayarsaikhan; Davaadagva Damdinjav; Gantuya Dorj; Altantuya Jigjidsuren; Oyun Lkhagvasuren; Baasandorj Erdenetsetseg
Journal:  BMC Public Health       Date:  2020-05-20       Impact factor: 3.295

3.  Initial experience with the novel p64MW HPC flow diverter from a cohort study in unruptured anterior circulation aneurysms under dual antiplatelet medication.

Authors:  Andrey Petrov; Ganbaatar Rentsenkhuu; Baatarjan Nota; Erdenebat Ganzorig; Boldbat Regzengombo; Sara Jagusch; Elina Henkes; Hans Henkes
Journal:  Interv Neuroradiol       Date:  2020-07-08       Impact factor: 1.610

4.  Patient safety and public health concerns: poor dissolution rate of pioglitazone tablets obtained from China, Myanmar and internet sites.

Authors:  Mohammad Sofiqur Rahman; Naoko Yoshida; Hirohito Tsuboi; Erina Maeda; Andrea Vanessa Velasco Ibarra; Theingi Zin; Yoshio Akimoto; Tsuyoshi Tanimoto; Kazuko Kimura
Journal:  BMC Pharmacol Toxicol       Date:  2021-03-02       Impact factor: 2.483

5.  Characterizing Medicine Quality by Active Pharmaceutical Ingredient Levels: A Systematic Review and Meta-Analysis across Low- and Middle-Income Countries.

Authors:  Sachiko Ozawa; Hui-Han Chen; Yi-Fang Ashley Lee; Colleen R Higgins; Tatenda T Yemeke
Journal:  Am J Trop Med Hyg       Date:  2022-06-15       Impact factor: 3.707

6.  Substandard and falsified antibiotics: neglected drivers of antimicrobial resistance?

Authors:  Guillermo A Zabala; Khonsavath Bellingham; Vayouly Vidhamaly; Phonepasith Boupha; Kem Boutsamay; Paul N Newton; Céline Caillet
Journal:  BMJ Glob Health       Date:  2022-08

7.  Prevalence and Estimated Economic Burden of Substandard and Falsified Medicines in Low- and Middle-Income Countries: A Systematic Review and Meta-analysis.

Authors:  Sachiko Ozawa; Daniel R Evans; Sophia Bessias; Deson G Haynie; Tatenda T Yemeke; Sarah K Laing; James E Herrington
Journal:  JAMA Netw Open       Date:  2018-08-03

8.  A systematic review of substandard, falsified, unlicensed and unregistered medicine sampling studies: a focus on context, prevalence, and quality.

Authors:  Dominic McManus; Bernard David Naughton
Journal:  BMJ Glob Health       Date:  2020-08
  8 in total

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