Antimalarial drug resistance is a major constraint for malaria control and elimination efforts. Artemisinin-based combination therapy is now the mainstay for malaria treatment. However, delayed parasite clearance following treatment with artemisinin derivatives has now spread in the Greater Mekong Sub region and may emerge or spread to other malaria endemic regions. This spread is of great concern for malaria control programmes, as no alternatives to artemisinin-based combination therapies are expected to be available in the near future. There is a need to strengthen surveillance systems for early detection and response to the antimalarial drug resistance threat. Current surveillance is mainly done through therapeutic efficacy studies; however these studies are complex and both time- and resource-intensive. For multiple common antimalarials, parasite drug resistance has been correlated with specific genetic mutations, and the molecular markers associated with antimalarial drug resistance offer a simple and powerful tool to monitor the emergence and spread of resistant parasites. Different techniques to analyse molecular markers associated with antimalarial drug resistance are available, each with advantages and disadvantages. However, procedures are not adequately harmonized to facilitate comparisons between sites. Here we describe the target product profiles for tests to analyse molecular markers associated with antimalarial drug resistance, discuss how use of current techniques can be standardised, and identify the requirements for an ideal product that would allow malaria endemic countries to provide useful spatial and temporal information on the spread of resistance.
Citation: Nsanzabana C, Ariey F, Beck H-P, Ding XC, Kamau E, Krishna S, et al. (2018) Molecular assays for antimalarial drug resistance surveillance: A target product profile. PLoS ONE 13(9): e0204347. https://doi.org/10.1371/journal.pone.0204347
Editor: Silvie Huijben, Arizona State University, UNITED STATES
Received: June 26, 2018; Accepted: September 5, 2018; Published: September 20, 2018
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: This is a meeting report, all the data are in the manuscript
Funding: This study was funded by the by the Department of Foreign Affairs and Trade of the Australian Government. The URL of the funder’s website is https://dfat.gov.au/. Grant number is AUSCORE-02, and the funding was received by the Foundation for Innovative New Diagnostics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: Sanjeev Krishna is a shareholder and Chairs the SAC for infectious diseases for QuantuMDx. This does not alter our adherence to PLOS ONE policies on sharing data and materials. Other authors have declared that no competing interests exist.
Antimalarial drug resistance is a major concern for malaria control and elimination programmes. Indeed, Plasmodium falciparum parasites have consistently developed resistance to the most widely used antimalarials, pushing national malaria control programmes to regular changes in antimalarial drug policy . Artemisinin-based combination therapy (ACT) is now the mainstay for malaria treatment in endemic regions, following recommendations from the World Health Organization (WHO) . However parasites with decreased susceptibility to artemisinin derivatives have emerged over the last ten years in different parts of the Greater Mekong Sub region (GMS) [3–7]. ACTs are failing due to both decreased susceptibility to artemisinin compounds and resistance to their partner drugs in Southeast Asia [8–14]. Strengthening of existing surveillance systems is needed to detect drug resistance in malaria endemic countries as it emerges or spreads to other regions. Antimalarial drug resistance surveillance is currently done through three different strategies: in vivo studies such as therapeutic efficacy studies (TESs), in vitro/ex vivo studies of cultured malaria parasites, and molecular studies assessing known markers of antimalarial drug resistance. These three techniques are complementary, but each has advantages and disadvantages . TES remains the gold standard for informing antimalarial drug policy change, as outcomes have direct clinical relevance , but these studies are challenging to conduct due to heavy financial and logistical constraints , and they cannot always confirm resistance, especially for combination therapies . Indeed, only monotherapy studies allow for the accurate differentiation of the drug component causing apparent ACT treatment failure . In vivo/ex vivo studies, such as measurement of IC50 (50% inhibitory concentration of a drug) or ring stage survival assays, can provide useful information about parasite susceptibility to antimalarial drugs, but require heavy infrastructure for parasite culture. Performance of these assays is generally restricted to well-equipped laboratories to validate new molecular markers of antimalarial drug resistance , or to link a resistance phenotype to a genotype . Molecular studies of antimalarial drug resistance markers provide information about the parasite genetics associated with resistance, i.e. single nucleotide polymorphisms (SNPs) or gene copy number variations (CNVs) that are associated with decreased susceptibility of parasites to antimalarial drugs. After markers of resistance have been identified by genotype-phenotype discovery studies, detection of these molecular markers provides a feasible means of tracking emergence and/or spread of antimalarial drug resistance, as easy-to-collect dried blood spot (DBS) samples can be used [22,23]. While numerous methodologies for blood spot collection, DNA extraction, PCR amplification, and analysis of molecular markers have been described, standardisation of these approaches is lacking . Given the potential role of molecular surveillance of drug resistance markers, a standardised approach is important to allow for comparability across the globe.
Here we describe the target product profile (TPP), with minimal and optimal characteristics, for techniques to analyse molecular markers associated with antimalarial drug resistance. This TPP was developed by a group of experts from academic institutions, public health institutions and industry at a meeting convened by the Foundation for Innovative New Diagnostics (FIND).
A draft TPP was developed based on a landscape analysis of antimalarial drug resistance surveillance methods performed by FIND . The listed properties were defined according to FIND’s standard procedures (https://www.finddx.org/target-product-profiles/), with characteristics described as either “minimal” or “optimal”. The experts were selected based on their experience and expertise in the field of molecular markers of antimalarial drug resistance. The participants selection was based on a review previously conducted by FIND on the methods used for surveillance of antimalarial drug resistance . Identified experts were contacted by email, invited to participate in the meeting and provided with a brief summary of the meeting’s objectives (S1 Table). Those who confirmed their attendance were provided with the draft TPP prior to the meeting including a questionnaire (S2 Table). The meeting was organised by FIND and held in Geneva on 21 and 22 September 2017 to reach consensus on the TPP. The experts were asked to present the different molecular techniques that are used in their laboratories and discussed their advantages and disadvantages (Table 1).
A session was organised to go through the draft TPP using the pre-established questionnaire as a guideline. Experts were asked to provide their opinion on the different assay characteristics, and discuss about them to reach a consensus. The discussion was moderated by one of interviewer from FIND. All the final decisions were made by consensus; none of the decisions were taken by voting. Comments and suggestions from the experts were collected and compiled in the meeting’s report. After the meeting, a revised draft TPP following suggestions from the experts’ meeting was sent to the meeting participants along with the meeting’s report. The experts were asked to review the revised draft and the meeting report, and confirm that both documents accurately reflected the discussions they had during the meeting. They were asked as well to provide additional suggestions on the revised TPP, and based on those comments, the TPP was finalised and sent to all participants for final review and approval. More details about the meeting can be found in S3 Table.
Twenty seven experts (including four observers) were invited to the meeting. Eighteen experts (including four observers) were able to attend the meeting, whereas nine experts were not available. All the experts are working in the field of antimalarial drug resistance. The majority of the participants (n = 13 [72.2%]) were research group leaders from academic institutions; other participants were coming from public health institutions such as WHO and the Centers for Disease Control and Prevention (CDC) or industry (Table 2). Most of the participants were coming from institutions based in the United States of America (USA), the United Kingdom (UK), Switzerland and France, while only 7 of them were female (Table 2).
The goal of a molecular assay is to detect genetic markers associated with antimalarial drug resistance in P. falciparum parasites using blood samples from infected individuals. Discussions were held to assess whether Plasmodium vivax should also be included in the TPP. The final consensus was that priority should be given to P. falciparum, as molecular markers are well characterised for decreased susceptibility to artemisinins and resistance to partner drugs for P. falciparum, but not for P. vivax. Rather, currently there is no clear evidence of P. vivax resistance to artemisinins, and for P. vivax resistance to chloroquine (CQ), amodiaquine (AQ) and sulfadoxine-pyrimethamine (SP), molecular markers have not been validated .
The target users are highly trained laboratory technicians. There was a consensus that surveillance of antimalarial drug resistance with current technologies would be best conducted by national or regional reference laboratories that receive samples from sentinel sites or other national sources.
The target implementation level is regional or national reference laboratories. Having reference laboratories performing all the analyses at a centralised facility will probably be most cost-effective and provide the most accurate results. In addition, constraining the implementation level to reference laboratories simplifies reporting, data monitoring, and procedure harmonization.
Technical and performance characteristics
The most important performance criteria were analytical sensitivity, analytical specificity, the specific molecular markers to be analysed, test sensitivity, and test specificity (Table 3). Because most samples will come from cross-sectional surveys, the minimum sensitivity for parasitaemia detection was set at the same level as that being used to characterise symptomatic infections. The optimal sensitivity was set to be equivalent to the most sensitive techniques currently used either for molecular diagnosis of malaria or detection of molecular markers associated with antimalarial drug resistance. The consensus about analytical specificity was that the method should be particular for P. falciparum. As above, it was agreed that molecular markers for P. vivax resistance are not yet adequately validated. A list of validated P. falciparum molecular markers was suggested (Table 3). The technique of choice should be able to analyse all relevant molecular markers associated with antimalarial drug resistance. The outcome of the test should be easy to read and interpret (mutant or wild type for SNPs or number of gene copies for CNVs). Optimally, it should be possible to quantify the percentage of each genotype in samples with multiple infections. The sensitivity and specificity of the testing was set to be at least 90% (ideally 95%) compared to Sanger sequencing. The repeatability and reproducibility of the technique were set at kappa >0.8 and >0.7, respectively, for minimal conditions, and >0.9 and >0.8, respectively, for optimal conditions.
Technical and operational characteristics
The operational characteristics of the molecular assay are summarized in Table 4. The discussions during the meeting were mainly on the assay format, assay throughput, and sample matrix. Concerning the assay format, there was consensus that a requirement for use of sophisticated laboratory equipment was appropriate because analyses should be conducted by national or regional reference laboratories. High throughput was preferred; however, it was agreed that the assay should be flexible enough to allow the laboratory to analyse small quantities of samples when appropriate (i.e. no restriction by batch size). DBS was the preferred format to collect samples. However, good quality filter paper should be used to ensure optimal yield and quality of DNA, especially after long term storage . Optimally, the assay should be able to use DNA extracted from a positive rapid diagnostic test (RDT), as RDTs are currently widely used in malaria endemic countries, especially in Africa, offering at times the best access to samples . Importantly, assays should routinely include negative and positive controls. It is of paramount importance that external controls are included for the assessment of the assay and calibration, and that a good quality control and quality assurance system is implemented to ensure good laboratory practice standardisation.
Assay cost characteristics
The cost of the assay should be low enough to be affordable in developing countries. The cost to analyse one sample for all mutations should ideally not be more than 10 USD, comparable to or cheaper than widely used PCR-RFLP assays .
Molecular markers of antimalarial drug resistance have proved to be useful for detection of early resistance emergence [5,7,60], spread of resistance , or absence of resistance , and are easy to interpret . Although TESs provide valuable resistance measurements that are easiest to directly translate to policy, they are confounded by many factors, including clinical immunity and varied pharmacokinetics, and they require extensive time for completion, so resistance may only be apparent once parasites resistant to both components of a drug combination have spread widely . Molecular techniques have the advantage of providing information in real time about the prevalence and ideally the frequency of resistant parasite strains circulating in the population using easily collected DBS or RDT samples [42,58,65], and this information is not typically confounded by clinical immunity. Even though, the presence of resistant parasites does not necessarily predict treatment failure , increasing prevalence of validated molecular markers of antimalarial drug resistance is associated with increasing treatment failure, and thus molecular markers offer a valuable early indicator of resistance emergence , and a practicable means of determining thresholds for policy makers. As an example, the WHO policy on Intermittent preventive treatment for infants (IPTi) with SP recommends ≤50% prevalence of Pfdhps 540 mutation as the threshold for implementation of SP-IPTi . A variety of different techniques to assess molecular markers associated with antimalarial drug resistance are already available (Table 1), however standardisation is needed to improve the quality of generated data .
New and improved technologies should focus on simple techniques that can be used by laboratories in malaria endemic countries. Techniques should be highly sensitive to detect minority strains, but also highly specific to yield accurate results. Indeed, according to the consensus obtained during the meeting of experts, priority should be given to specificity over sensitivity; it is better to miss strains at low level than to give inaccurate prevalence data. Increased multiplicity of infection in high transmission settings may compromise assessment of antimalarial drug resistance molecular markers . Indeed, genotyping of samples with multiple infections is challenging, as it is difficult to link different mutations to a specific strain, and therefore accurately assess haplotypes or frequencies of specific strains, in particular when considering CNV. New technologies under development, including amplicon sequencing, may allow assessment of drug resistance variants among polygenomic infections [70–74]. However, in the setting of high multiplicity of infection, prevalence data remains useful for surveillance purposes . Determination of CNV is a minimal requirement in this TPP, as resistance to some of the important artemisinin partner drugs such as mefloquine and piperaquine is associated with changes in gene copy numbers [76,77]. Currently, sequencing technologies and real-time PCR offer most of the desired characteristics described in the current TPPs, including the determination of CNVs (Table 1), and those technologies are becoming increasingly available and affordable in developing countries . Other new techniques are in development that could improve standardisation, with no DNA amplification [78,79] or DNA extraction step requirement [51,80]. However, these techniques are still at an early stage of development and are mainly under evaluation for diagnosis, and not surveillance.
Recent advances in sequencing technologies, such as next-generation sequencing (NGS) platforms that enable rapid whole genome sequencing (WGS), can provide in-depth information about molecular determinants of resistance, allowing detailed assessment of the spread of resistant strains [81–83]. They can provide as well information about new emerging mutations before they can be confirmed by phenotypic data from in vitro assessments and clinical data when available. The main objective of a molecular-based surveillance system should be the detection of resistance before it spreads. For artemisinin resistance, different foci have been discovered, and molecular determinants other than pfKelch13 may be involved [84,85], requiring a continuous search and validation for new molecular markers. The development of a surveillance system included in the local health system could be envisioned; samples would be collected at health posts, centres or hospitals and sent to reference laboratories for analysis and validation, while clinical data could be shared through electronic-based information system . Combined with local epidemiological data; drug usage and treatment efficacy data, WGS data could provide valuable information for modelling and predicting the spread of antimalarial drug resistance . The recent development of MinION nanopore portable sequencer and its application to molecular markers of resistance could facilitate as well sample analysis at point of care, while the data analysis could still be performed in the central reference laboratory [48,50]. NGS technologies also allow pooling of different samples by indexing them to reduce the analysis costs [41,42]. Even though the costs of all these NGS technologies have dramatically reduced in recent years and are affordable for developing countries, they still require high expertise in data analysis, and high computing power that are not always available in those countries. However, the establishment of centres of excellence or regional reference laboratories could overcome this issue.
To ensure the accuracy and the comparability of the results from different laboratories, a good external quality assurance (EQA) system should be implemented, providing validated and standardised external control material [88,89]. Indeed, different laboratories may use different protocols and standard operating procedures (SOPs) for the same methodology, and there is variability in operating procedures in different laboratories. An analogous EQA scheme for malaria nucleic acid amplification testing external quality assurance (NAAT EQA) has been developed by WHO and FIND , and could potentially be expanded to molecular markers of resistance.
In summary, techniques already exist with most of the required characteristics in this TPP for assays to analyse molecular markers associated with antimalarial drug resistance, and could be rapidly implemented in reference laboratories. Other techniques in development fulfil most of the criteria specified by the TPP and could potentially improve data analysis standardisation. However, the implementation of different techniques for routine surveillance of antimalarial drug resistance would need a consensus from policy makers to define implementation procedures, optimise their use, and implement good EQA practices. This TPP can also be used by assay manufacturers to guide development of new technologies to facilitate efficient surveillance of molecular markers associated with antimalarial drug resistance in endemic settings.
S2 Table. Draft target product profile and pre-meeting questionnaire.
Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the US Centers for Disease Control and Prevention, the U.S. Department of the Army, the U.S. Department of Defense or the U.S. Government.
We would like to thank the observers who attended the meeting of experts for their comments and suggestions.
- 1. Nsanzabana C, Djalle D, Guérin PJ, Ménard D, González IJ. Tools for surveillance of anti-malarial drug resistance: an assessment of the current landscape. Malar J. 2018;17: 75. pmid:29422048
- 2. WHO. Guidelines for the treatment of malaria [Internet]. Geneva; 2010 [cited 7 Apr 2017] p. 210. Available: http://apps.who.int/medicinedocs/documents/s19105en/s19105en.pdf
- 3. Noedl H, Se Y, Schaecher K, Smith BL, Socheat D, Fukuda MM, et al. Evidence of Artemisinin-Resistant Malaria in Western Cambodia. N Engl J Med. 2008;359: 2619–2620. pmid:19064625
- 4. Dondorp AM, Nosten F, Yi P, Das D, Phyo AP, Tarning J, et al. Artemisinin Resistance in Plasmodium falciparum Malaria. N Engl J Med. 2009;361: 455–467. pmid:19641202
- 5. Ashley EA, Dhorda M, Fairhurst RM, Amaratunga C, Lim P, Suon S, et al. Spread of Artemisinin Resistance in Plasmodium falciparum Malaria. N Engl J Med. 2014;371: 411–423. pmid:25075834
- 6. Ariey F, Witkowski B, Amaratunga C, Beghain J, Langlois A-C, Khim N, et al. A molecular marker of artemisinin-resistant Plasmodium falciparum malaria. Nature. 2014;505: 50–55. pmid:24352242
- 7. Takala-Harrison S, Jacob CG, Arze C, Cummings MP, Silva JC, Dondorp AM, et al. Independent Emergence of Artemisinin Resistance Mutations Among Plasmodium falciparum in Southeast Asia. J Infect Dis. 2015;211: 670–679. pmid:25180241
- 8. Leang R, Barrette A, Bouth DM, Menard D, Abdur R, Duong S, et al. Efficacy of Dihydroartemisinin-Piperaquine for Treatment of Uncomplicated Plasmodium falciparum and Plasmodium vivax in Cambodia, 2008 to 2010. Antimicrob Agents Chemother. 2013;57: 818–826. pmid:23208711
- 9. Lon C, Manning JE, Vanachayangkul P, So M, Sea D, Se Y, et al. Efficacy of Two versus Three-Day Regimens of Dihydroartemisinin-Piperaquine for Uncomplicated Malaria in Military Personnel in Northern Cambodia: An Open-Label Randomized Trial. von Seidlein L, editor. PLoS One. 2014;9: e93138. https://doi.org/10.1371/journal.pone.0093138 pmid:24667662
- 10. Saunders DL, Vanachayangkul P, Lon C, U.S. Army Military Malaria Research Program, National Center for Parasitology, Entomology, and Malaria Control (CNM), Royal Cambodian Armed Forces. Dihydroartemisinin–Piperaquine Failure in Cambodia. N Engl J Med. 2014;371: 484–485. pmid:25075853
- 11. Spring MD, Lin JT, Manning JE, Vanachayangkul P, Somethy S, Bun R, et al. Dihydroartemisinin-piperaquine failure associated with a triple mutant including kelch13 C580Y in Cambodia: an observational cohort study. Lancet Infect Dis. 2015;15: 683–691. pmid:25877962
- 12. Duru V, Khim N, Leang R, Kim S, Domergue A, Kloeung N, et al. Plasmodium falciparum dihydroartemisinin-piperaquine failures in Cambodia are associated with mutant K13 parasites presenting high survival rates in novel piperaquine in vitro assays: retrospective and prospective investigations. BMC Med. 2015;13: 305. pmid:26695060
- 13. Amaratunga C, Lim P, Suon S, Sreng S, Mao S, Sopha C, et al. Dihydroartemisinin–piperaquine resistance in Plasmodium falciparum malaria in Cambodia: a multisite prospective cohort study. Lancet Infect Dis. 2016;16: 357–365. pmid:26774243
- 14. WHO. Status report on artemisinin and ACT resistance (April 2017). In: World Health Organization [Internet]. Geneva: World Health Organization; 2017 [cited 5 Dec 2017] p. 11. Available: http://www.who.int/malaria/publications/atoz/artemisinin-resistance-april2017/en/
- 15. Vestergaard LS, Ringwald P. Responding to the challenge of antimalarial drug resistance by routine monitoring to update national malaria treatment policies. Am J Trop Med Hyg. 2007;77: 153–9. pmid:18165488
- 16. WHO. Methods for surveillance of antimalarial drug efficacy [Internet]. Geneva; 2009 [cited 29 Mar 2017] p. 85. Available: http://apps.who.int/iris/bitstream/10665/44048/1/9789241597531_eng.pdf
- 17. Price RN, Dorsey G, Ashley EA, Barnes KI, Baird JK, d’Alessandro U, et al. World Antimalarial Resistance Network I: Clinical efficacy of antimalarial drugs. Malar J. 2007;6: 119. pmid:17822532
- 18. Hedt BL, Laufer MK, Cohen T. Drug Resistance Surveillance in Resource-Poor Settings: Current Methods and Considerations for TB, HIV, and Malaria. Am J Trop Med Hyg. 2011;84: 192–199. pmid:21292884
- 19. Noedl H. Artemisinin resistance: how can we find it? Trends Parasitol. 2005;21: 404–5. pmid:16046187
- 20. Bacon DJ, Jambou R, Fandeur T, Le Bras J, Wongsrichanalai C, Fukuda MM, et al. World Antimalarial Resistance Network (WARN) II: In vitro antimalarial drug susceptibility. Malar J. 2007;6: 120. pmid:17822533
- 21. Witkowski B, Amaratunga C, Khim N, Sreng S, Chim P, Kim S, et al. Novel phenotypic assays for the detection of artemisinin-resistant Plasmodium falciparum malaria in Cambodia: in-vitro and ex-vivo drug-response studies. Lancet Infect Dis. 2013;13: 1043–1049. pmid:24035558
- 22. Plowe C V, Roper C, Barnwell JW, Happi CT, Joshi HH, Mbacham W, et al. World Antimalarial Resistance Network (WARN) III: Molecular markers for drug resistant malaria. Malar J. 2007;6: 121. pmid:17822535
- 23. Okell LC, Griffin JT, Roper C. Mapping sulphadoxine-pyrimethamine-resistant Plasmodium falciparum malaria in infected humans and in parasite populations in Africa. Sci Rep. 2017;7: 7389. pmid:28785011
- 24. Zolg JW, Chen GX, Plitt JR. Detection of pyrimethamine resistance in Plasmodium falciparum by mutation-specific polymerase chain reaction. Mol Biochem Parasitol. 1990;39: 257–65. pmid:2181308
- 25. Gyang FN, Peterson DS, Wellems TE. Plasmodium falciparum: rapid detection of dihydrofolate reductase mutations that confer resistance to cycloguanil and pyrimethamine. Exp Parasitol. 1992;74: 470–2. pmid:1592095
- 26. Gu WK, Weeden NF, Yu J, Wallace DH. Large-scale, cost-effective screening of PCR products in marker-assisted selection applications. Theor Appl Genet. 1995;91: 465–70. pmid:24169836
- 27. Wang P, Brooks DR, Sims PF, Hyde JE. A mutation-specific PCR system to detect sequence variation in the dihydropteroate synthetase gene of Plasmodium falciparum. Mol Biochem Parasitol. 1995;71: 115–25. pmid:7630375
- 28. Duraisingh MT, Curtis J, Warhurst DC. Plasmodium falciparum:Detection of Polymorphisms in theDihydrofolate ReductaseandDihydropteroate SynthetaseGenes by PCR and Restriction Digestion. Exp Parasitol. 1998;89: 1–8. pmid:9603482
- 29. LeClair NP, Conrad MD, Baliraine FN, Nsanzabana C, Nsobya SL, Rosenthal PJ. Optimization of a ligase detection reaction-fluorescent microsphere assay for characterization of resistance-mediating polymorphisms in African samples of Plasmodium falciparum. J Clin Microbiol. 2013;51: 2564–70. pmid:23720790
- 30. Durand R, Eslahpazire J, Jafari S, Delabre JF, Marmorat-Khuong A, di Piazza JP, et al. Use of molecular beacons to detect an antifolate resistance-associated mutation in Plasmodium falciparum. Antimicrob Agents Chemother. 2000;44: 3461–4. pmid:11083660
- 31. Abdel-Muhsin A-MA, Ranford-Cartwright LC, Medani A-R, Ahmed S, Suleiman S, Khan B, et al. Detection of mutations in the Plasmodium falciparum dihydrofolate reductase (dhfr) gene by dot-blot hybridization. Am J Trop Med Hyg. 2002;67: 24–7. pmid:12363059
- 32. Nair S, Brockman A, Paiphun L, Nosten F, Anderson TJC. Rapid genotyping of loci involved in antifolate drug resistance in Plasmodium falciparum by primer extension. Int J Parasitol. 2002;32: 852–8. pmid:12062556
- 33. Pickard AL, Wongsrichanalai C, Purfield A, Kamwendo D, Emery K, Zalewski C, et al. Resistance to antimalarials in Southeast Asia and genetic polymorphisms in pfmdr1. Antimicrob Agents Chemother. 2003;47: 2418–23. pmid:12878499
- 34. Purfield A, Nelson A, Laoboonchai A, Congpuong K, McDaniel P, Miller RS, et al. A new method for detection of pfmdr1 mutations in Plasmodium falciparum DNA using real-time PCR. Malar J. 2004;3: 9. pmid:15132750
- 35. Daniels R, Ndiaye D, Wall M, McKinney J, Séne PD, Sabeti PC, et al. Rapid, Field-Deployable Method for Genotyping and Discovery of Single-Nucleotide Polymorphisms Associated with Drug Resistance in Plasmodium falciparum. Antimicrob Agents Chemother. 2012;56: 2976–2986. pmid:22430961
- 36. Basco LK, Ringwald P. Molecular epidemiology of malaria in Cameroon. X. Evaluation of PFMDR1 mutations as genetic markers for resistance to amino alcohols and artemisinin derivatives. Am J Trop Med Hyg. 2002;66: 667–71. pmid:12224572
- 37. Schwöbel B, Alifrangis M, Salanti A, Jelinek T. Different mutation patterns of atovaquone resistance to Plasmodium falciparum in vitro and in vivo: rapid detection of codon 268 polymorphisms in the cytochrome b as potential in vivo resistance marker. Malar J. 2003;2: 5. pmid:12665429
- 38. Alifrangis M, Enosse S, Pearce R, Drakeley C, Roper C, Khalil IF, et al. A simple, high-throughput method to detect Plasmodium falciparum single nucleotide polymorphisms in the dihydrofolate reductase, dihydropteroate synthase, and P. falciparum chloroquine resistance transporter genes using polymerase chain reaction- and enzyme-linked immunosorbent assay-based technology. Am J Trop Med Hyg. 2005;72: 155–62. pmid:15741552
- 39. Crameri A, Marfurt J, Mugittu K, Maire N, Regos A, Coppee JY, et al. Rapid Microarray-Based Method for Monitoring of All Currently Known Single-Nucleotide Polymorphisms Associated with Parasite Resistance to Antimalaria Drugs. J Clin Microbiol. 2007;45: 3685–3691. pmid:17804664
- 40. Steenkeste N, Dillies M-A, Khim N, Sismeiro O, Chy S, Lim P, et al. FlexiChip package: an universal microarray with a dedicated analysis software for high-thoughput SNPs detection linked to anti-malarial drug resistance. Malar J. 2009;8: 229. pmid:19828052
- 41. Taylor SM, Parobek CM, Aragam N, Ngasala BE, Mårtensson A, Meshnick SR, et al. Pooled deep sequencing of Plasmodium falciparum isolates: an efficient and scalable tool to quantify prevailing malaria drug-resistance genotypes. J Infect Dis. 2013;208: 1998–2006. pmid:23908494
- 42. Nag S, Dalgaard MD, Kofoed P-E, Ursing J, Crespo M, Andersen LO, et al. High throughput resistance profiling of Plasmodium falciparum infections based on custom dual indexing and Illumina next generation sequencing-technology. Sci Rep. 2017;7: 2398. pmid:28546554
- 43. Carnevale EP, Kouri D, DaRe JT, McNamara DT, Mueller I, Zimmerman PA. A Multiplex Ligase Detection Reaction-Fluorescent Microsphere Assay for Simultaneous Detection of Single Nucleotide Polymorphisms Associated with Plasmodium falciparum Drug Resistance. J Clin Microbiol. 2007;45: 752–761. pmid:17121999
- 44. Moers APHA, Hallett RL, Burrow R, Schallig HDFH, Sutherland CJ, van Amerongen A. Detection of single-nucleotide polymorphisms in Plasmodium falciparum by PCR primer extension and lateral flow immunoassay. Antimicrob Agents Chemother. 2015;59: 365–71. pmid:25367901
- 45. Oriero EC, Jacobs J, Van Geertruyden J-P, Nwakanma D, D’Alessandro U. Molecular-based isothermal tests for field diagnosis of malaria and their potential contribution to malaria elimination. J Antimicrob Chemother. 2015;70: 2–13. pmid:25223973
- 46. Chahar M, Mishra N, Anvikar A, Dixit R, Valecha N. Establishment and application of a novel isothermal amplification assay for rapid detection of chloroquine resistance (K76T) in Plasmodium falciparum. Sci Rep. 2017;7: 41119. pmid:28134241
- 47. Yongkiettrakul S, Kampeera J, Chareanchim W, Rattanajak R, Pornthanakasem W, Kiatpathomchai W, et al. Simple detection of single nucleotide polymorphism in Plasmodium falciparum by SNP-LAMP assay combined with lateral flow dipstick. Parasitol Int. 2017;66: 964–971. pmid:27816495
- 48. Runtuwene LR, Tuda JSB, Mongan AE, Makalowski W, Frith MC, Imwong M, et al. Nanopore sequencing of drug-resistance-associated genes in malaria parasites, Plasmodium falciparum. Sci Rep. 2018;8: 8286. pmid:29844487
- 49. Nanoporetech. MinION products [Internet]. 2018 [cited 10 Aug 2018]. Available: https://nanoporetech.com/products/comparison
- 50. Imai K, Tarumoto N, Runtuwene LR, Sakai J, Hayashida K, Eshita Y, et al. An innovative diagnostic technology for the codon mutation C580Y in kelch13 of Plasmodium falciparum with MinION nanopore sequencer. Malar J. 2018;17: 217. pmid:29843734
- 51. Innovation4malaria. QPOC for malaria [Internet]. 2018 [cited 10 Aug 2018]. Available: htttp://www.innovation4malaria.org/quantumdx.html
- 52. Menard D, Dondorp A. Antimalarial Drug Resistance: A Threat to Malaria Elimination. Cold Spring Harb Perspect Med. 2017; a025619. pmid:28289248
- 53. Daniels R, Ndiaye D, Wall M, McKinney J, Séne PD, Sabeti PC, et al. Rapid, field-deployable method for genotyping and discovery of single-nucleotide polymorphisms associated with drug resistance in Plasmodium falciparum. Antimicrob Agents Chemother. 2012;56: 2976–86. pmid:22430961
- 54. Robin JD, Ludlow AT, LaRanger R, Wright WE, Shay JW. Comparison of DNA Quantification Methods for Next Generation Sequencing. Sci Rep. Nature Publishing Group; 2016;6: 24067. pmid:27048884
- 55. WHO. Global plan for artemisinin resistance containment (GPARC) [Internet]. Geneva; 2011 [cited 29 Mar 2017] p. 87. Available: http://apps.who.int/iris/bitstream/10665/44482/1/9789241500838_eng.pdf?ua=1
- 56. WHO. Minutes of the Evidence Review Group meeting on the emergence and spread of multidrug‐ resistant Plasmodium falciparum lineages in the Greater Mekong subregion [Internet]. Geneva; 2016 [cited 8 Aug 2017] p. 27. Available: http://www.who.int/malaria/mpac/mpac-mar2017-erg-multidrug-resistance-session6.pdf
- 57. Versteeg I, Mens PF. Development of a stable positive control to be used for quality assurance of rapid diagnostic tests for malaria. Diagn Microbiol Infect Dis. 2009;64: 256–60. pmid:19376669
- 58. Papa Mze N, Ndiaye YD, Diedhiou CK, Rahamatou S, Dieye B, Daniels RF, et al. RDTs as a source of DNA to study Plasmodium falciparum drug resistance in isolates from Senegal and the Comoros Islands. Malar J. 2015;14: 373. pmid:26415927
- 59. WHO/PQDx. A risk based approach for the assessment of In vitro diagnostics (IVDs) [Internet]. Geneva; 2014 [cited 5 Sep 2017] p. 17. Available: http://www.who.int/diagnostics_laboratory/evaluations/140513_risk_based_assessment_approach_buffet.pdf?ua=1
- 60. Chenet SM, Akinyi Okoth S, Huber CS, Chandrabose J, Lucchi NW, Talundzic E, et al. Independent Emergence of the Plasmodium falciparum Kelch Propeller Domain Mutant Allele C580Y in Guyana. J Infect Dis. 2016;213: 1472–1475. pmid:26690347
- 61. Abdul-Ghani R, Al-Maktari MT, Al-Shibani LA, Allam AF. A better resolution for integrating methods for monitoring Plasmodium falciparum resistance to antimalarial drugs. Acta Trop. 2014;137: 44–57. pmid:24801884
- 62. Taylor SM, Parobek CM, DeConti DK, Kayentao K, Coulibaly SO, Greenwood BM, et al. Absence of Putative Artemisinin Resistance Mutations Among Plasmodium falciparum in Sub-Saharan Africa: A Molecular Epidemiologic Study. J Infect Dis. 2015;211: 680–688. pmid:25180240
- 63. Wernsdorfer WH, Noedl H. Molecular markers for drug resistance in malaria: use in treatment, diagnosis and epidemiology. Curr Opin Infect Dis. 2003;16: 553–8. pmid:14624105
- 64. malERA Refresh Consultative Panel on Insecticide and Drug Resistance. malERA: An updated research agenda for insecticide and drug resistance in malaria elimination and eradication. PLOS Med. 2017;14: e1002450. pmid:29190671
- 65. Sow D, Nag S, Sylla K, Gaye O, Tine RC, Faye B, et al. Country-Wide Surveillance of Molecular Markers of Antimalarial Drug Resistance in Senegal by Use of Positive Malaria Rapid Diagnostic Tests. Am J Trop Med Hyg. 2017;97: 1593–1596. pmid:29140232
- 66. Picot S, Olliaro P, de Monbrison F, Bienvenu A-L, Price RN, Ringwald P. A systematic review and meta-analysis of evidence for correlation between molecular markers of parasite resistance and treatment outcome in falciparum malaria. Malar J. 2009;8: 89. pmid:19413906
- 67. Nsanzabana C, Hastings IM, Marfurt J, Müller I, Baea K, Rare L, et al. Quantifying the Evolution and Impact of Antimalarial Drug Resistance: Drug Use, Spread of Resistance, and Drug Failure over a 12‐Year Period in Papua New Guinea. J Infect Dis. 2010;201: 435–443. pmid:20047502
- 68. WHO/UNICEF. WHO | Intermittent preventive treatment for infants using sulfadoxine-pyrimethamine (IPTi-SP) for malaria control in Africa: implementation field guide. In: WHO [Internet]. World Health Organization; 2011 [cited 28 Aug 2018]. Available: http://www.who.int/malaria/publications/atoz/whoivb11_07/en/
- 69. Taylor AR, Flegg JA, Nsobya SL, Yeka A, Kamya MR, Rosenthal PJ, et al. Estimation of malaria haplotype and genotype frequencies: a statistical approach to overcome the challenge associated with multiclonal infections. Malar J. 2014;13: 102. pmid:24636676
- 70. Mideo N, Bailey JA, Hathaway NJ, Ngasala B, Saunders DL, Lon C, et al. A deep sequencing tool for partitioning clearance rates following antimalarial treatment in polyclonal infections. Evol Med public Heal. 2016;2016: 21–36. pmid:26817485
- 71. Rao PN, Uplekar S, Kayal S, Mallick PK, Bandyopadhyay N, Kale S, et al. A Method for Amplicon Deep Sequencing of Drug Resistance Genes in Plasmodium falciparum Clinical Isolates from India. Loeffelholz MJ, editor. J Clin Microbiol. 2016;54: 1500–11. pmid:27008882
- 72. Reteng P, Vrisca V, Sukarno I, Djarkoni IH, Kalangi JA, Jacobs GE, et al. Genetic polymorphisms in Plasmodium falciparum chloroquine resistance genes, pfcrt and pfmdr1, in North Sulawesi, Indonesia. BMC Res Notes. 2017;10: 147. pmid:28376874
- 73. Talundzic E, Ndiaye YD, Deme AB, Olsen C, Patel DS, Biliya S, et al. Molecular Epidemiology of Plasmodium falciparum kelch13 Mutations in Senegal Determined by Using Targeted Amplicon Deep Sequencing. Antimicrob Agents Chemother. 2017;61: e02116–16. pmid:28069653
- 74. Talundzic E, Ravishankar S, Kelley J, Patel D, Plucinski M, Schmedes S, et al. Next-Generation Sequencing and Bioinformatics Protocol for Malaria Drug Resistance Marker Surveillance. Antimicrob Agents Chemother. 2018;62: e02474–17. pmid:29439965
- 75. Hastings IM, Smith TA, Nsanzabana C. A Comparison of Methods to Detect and Quantify the Markers of Antimalarial Drug Resistance. Am J Trop Med Hyg. 2010;83: 489–495. pmid:20810808
- 76. Wilson CM, Volkman SK, Thaithong S, Martin RK, Kyle DE, Milhous WK, et al. Amplification of pfmdr 1 associated with mefloquine and halofantrine resistance in Plasmodium falciparum from Thailand. Mol Biochem Parasitol. 1993;57: 151–60. pmid:8426608
- 77. Witkowski B, Duru V, Khim N, Ross LS, Saintpierre B, Beghain J, et al. A surrogate marker of piperaquine-resistant Plasmodium falciparum malaria: a phenotype–genotype association study. Lancet Infect Dis. 2017;17: 174–183. pmid:27818097
- 78. Vembar SS, Seetin M, Lambert C, Nattestad M, Schatz MC, Baybayan P, et al. Complete telomere-to-telomere de novo assembly of the Plasmodium falciparum genome through long-read (>11 kb), single molecule, real-time sequencing. DNA Res. 2016;23: 339–351. pmid:27345719
- 79. Bryant JM, Baumgarten S, Lorthiois A, Scheidig-Benatar C, Claës A, Scherf A. De Novo Genome Assembly of a Plasmodium falciparum NF54 Clone Using Single-Molecule Real-Time Sequencing. Genome Announc. 2018;6. pmid:29437092
- 80. Roth JM, de Bes L, Sawa P, Omweri G, Osoti V, Oberheitmann B, et al. Plasmodium Detection and Differentiation by Direct-on-Blood PCR Nucleic Acid Lateral Flow Immunoassay: Development, Validation, and Evaluation. J Mol Diagn. 2018;20: 78–86. pmid:29056574
- 81. Miotto O, Amato R, Ashley EA, MacInnis B, Almagro-Garcia J, Amaratunga C, et al. Genetic architecture of artemisinin-resistant Plasmodium falciparum. Nat Genet. 2015;47: 226–234. pmid:25599401
- 82. MalariaGEN Plasmodium falciparum Community Project. Genomic epidemiology of artemisinin resistant malaria. Elife. 2016;5. pmid:26943619
- 83. Imwong M, Suwannasin K, Kunasol C, Sutawong K, Mayxay M, Rekol H, et al. The spread of artemisinin-resistant Plasmodium falciparum in the Greater Mekong subregion: a molecular epidemiology observational study. Lancet Infect Dis. 2017;17: 491–497. pmid:28161569
- 84. Sutherland CJ, Lansdell P, Sanders M, Muwanguzi J, van Schalkwyk DA, Kaur H, et al. pfk13 -Independent Treatment Failure in Four Imported Cases of Plasmodium falciparum Malaria Treated with Artemether-Lumefantrine in the United Kingdom. Antimicrob Agents Chemother. 2017;61. pmid:28137810
- 85. Ikeda M, Kaneko M, Tachibana S-I, Balikagala B, Sakurai-Yatsushiro M, Yatsushiro S, et al. Artemisinin—Resistant Plasmodium falciparum with High Survival Rates, Uganda, 2014–2016. Emerg Infect Dis. 2018;24: 718–726. pmid:29553316
- 86. Khamsiriwatchara A, Sudathip P, Sawang S, Vijakadge S, Potithavoranan T, Sangvichean A, et al. Artemisinin resistance containment project in Thailand. (I): Implementation of electronic-based malaria information system for early case detection and individual case management in provinces along the Thai-Cambodian border. Malar J. 2012;11: 247. pmid:22839508
- 87. Scott N, Ataide R, Wilson DP, Hellard M, Price RN, Simpson JA, et al. Implications of population-level immunity for the emergence of artemisinin-resistant malaria: a mathematical model. Malar J. 2018;17: 279. pmid:30071877
- 88. Taylor SM, Mayor A, Mombo-Ngoma G, Kenguele HM, Ouedraogo S, Ndam NT, et al. A Quality Control Program within a Clinical Trial Consortium for PCR Protocols To Detect Plasmodium Species. J Clin Microbiol. 2014;52: 2144–2149. pmid:24740073
- 89. Murphy SC, Hermsen CC, Douglas AD, Edwards NJ, Petersen I, Fahle GA, et al. External Quality Assurance of Malaria Nucleic Acid Testing for Clinical Trials and Eradication Surveillance. Kumar S, editor. PLoS One. 2014;9: e97398. pmid:24838112
- 90. WHO. WHO | WHO external quality assurance scheme for malaria nucleic acid amplification testing (NAAT EQA). In: WHO [Internet]. World Health Organization; 2018 [cited 6 Mar 2018]. Available: http://www.who.int/malaria/areas/diagnosis/faq-nucleic-acid-amplification-tests/en/