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Review

Monoclonal Antibodies Application in Lateral Flow Immunochromatographic Assays for Drugs of Abuse Detection

1
Medical Biotechnology Center, Moroccan Foundation for Advanced Science, Innovation & Research (MAScIR), Rabat 10100, Morocco
2
Laboratoire de Pharmacologie et Toxicologie, Faculté de Médecine et de Pharmacie, Université Mohammed V-Souissi, Rabat 10100, Morocco
*
Author to whom correspondence should be addressed.
Molecules 2021, 26(4), 1058; https://doi.org/10.3390/molecules26041058
Submission received: 20 January 2021 / Revised: 1 February 2021 / Accepted: 3 February 2021 / Published: 18 February 2021

Abstract

:
Lateral flow assays (lateral flow immunoassays and nucleic acid lateral flow assays) have experienced a great boom in a wide variety of early diagnostic and screening applications. As opposed to conventional examinations (High Performance Liquid Chromatography, Polymerase Chain Reaction, Gas chromatography-Mass Spectrometry, etc.), they obtain the results of a sample’s analysis within a short period. In resource-limited areas, these tests must be simple, reliable, and inexpensive. In this review, we outline the production process of antibodies against drugs of abuse (such as heroin, amphetamine, benzodiazepines, cannabis, etc.), used in lateral flow immunoassays as revelation or detection molecules, with a focus on the components, the principles, the formats, and the mechanisms of reaction of these assays. Further, we report the monoclonal antibody advantages over the polyclonal ones used against drugs of abuse. The perspective on aptamer use for lateral flow assay development was also discussed as a possible alternative to antibodies in view of improving the limit of detection, sensitivity, and specificity of lateral flow assays.

Graphical Abstract

1. Introduction

Monitoring the use of psychotropic drugs is a public health issue and is proving to be very useful in the workplace. This is because illicit drugs can affect the cognitive and motor functions [1,2,3,4,5,6,7,8,9]. In addition, many psychoactive drugs, especially benzodiazepines (BZDs), are strongly associated with illicit drug use [10].
The concentrations of psychotropic drugs in biological matrices (saliva, blood, urine, etc.) are low, which requires very sensitive, selective, and appropriate methods for their detection and quantification [11,12,13,14,15,16,17]. The most frequently used methods of drug detection today are based on procedures for separating compounds by chromatographic standard techniques (GC, HPLC, and LC). Their quantifications are then carried out using UV, electrochemical, or fluorescence detectors. The GC-MS or, even more, LC-MS, are the most efficient methods of analysis [11,16,18,19]. However, they are expensive and require trained and qualified clinicians to conduct the analyses. Every year—in order to simplify detection methods and reduce costs—new lateral flow immunoassay (LFIA) tests appear in all fields of medicine, including cancerology, toxicology, and infectology [17,18,19,20,21,22,23,24,25,26], to be used directly in places where patients are cared for, with no specialized laboratories. The goal is to have immediate results, so that certain diagnoses can be quickly included or excluded.
The LFIA tests have several advantages over conventional diagnostic tests. They provide immediate treatments in the events of potentially life-threatening diseases, specific treatments rather than presumptive treatments, and early measures to prevent transmission of the disease (i.e., in the hospital or the community). In addition, these tests avoid unnecessary treatments and further investigation through follow-up testing [27]. Despite these advantages, each LFIA has its own characteristics, which must be known by the practitioners if they want to use it correctly.
These assays are based on the antigen (Ag)-antibody biochemical interaction and their performances depend essentially on the characteristics of the antibodies (Abs), such as affinity, specificity, production process (i.e., monoclonal Ab or polyclonal Ab), and cross-reactivity [28]. Abs are the primary reagent used for LFIA for the detection of low concentrations of analytes (the drug consumed) in the sample. Their selection (Abs) is a critical step of LFIA development. For a competitive LFIA, which is most useful in the case of small molecules, such as drugs of abuse (DOA), we used only one antibody (Ab) that was sensitive and specific to the target molecule. In the case of a sandwich LFIA, we used two Abs that could bind to the analyte with high specificity and sensitivity, but before using them, we had to test the available pairs, to determine which pair met the requirements. In general the Abs most used by the majority of the authors are monoclonal antibodies (mAbs), in which is fixed a compound (gold nanoparticles, latex microbeads, etc.) that will allow the visualization of the Ag-Abs reaction [27]. Monoclonal Abs detect only one epitope, because they are produced from a family of genetically stable cells (cloned hybridoma); consequently, they have high specificity to the Ag than the polyclonal Abs that are less specific, because they are produced by different cell clones [28].
With these considerations, this review will provide information on the production and application of mAbs directed against DOA in rapid detection test (LFIA) development. LFIA principles and designs, as well as a summary about developed LFIA to detect DOA over the past ten years, will also be discussed.

2. Research Methodology and Study Selection

The electronic search strategy was conducted in Google Scholar, Web of Science, PubMed, PROQUEST (Dissertations and Thesis International Database), and Scopus, in accordance with Ömer Gülpınar and Adil Güçal Güçlü guidelines published in 2013 [29]. The survey was performed using several search terms—such as LFIA test, DOA, BZDs, heroin (HRN), cocaine (COC), amphetamine (AMP), methamphetamine (MET), cannabinoids (CNB) or Δ-9 tetrahydrocannabinol (THC), psychotropic molecules, opioid or synthetic opioid fentanyl (OPI), immunochromatographic tests, mAbs production, point of care testing (POCT), aptamers, DOA detection, and DOA analysis—to select eligible studies for inclusion in the present work. A total of 139 scientific articles were used to compose the present work. The characteristics used as criteria for eligibility were:
(1)
Original scientific publications from the year 2010 onwards.
(2)
Studies evaluating one or more LFIA test for their ability to detect the following DOA: OPI, BZDs; HRN, THC, MET, AMP, COC, etc.

3. Antibodies Production Processes: Focus on mAbs against Drugs of Abuse

The Abs are glycoproteins called immunoglobulins (Ig), secreted by B-lymphocytes, components of the adaptive immune system, in response to an immunogen. There are many different isotypes or classes (IgG, IgA, IgM, IgE, and IgD), but the IgG isotype is often the major component of commercially available Abs and constitutes the most fractions of blood proteins. IgG is further divided into four subclasses (IgG1, IgG2, IgG3, and IgG4), with the numbers corresponding to the decreasing order in which they are found in the blood [30].
Abs production is simple, but there are several factors that affect the probability of an animal to produce Abs against the injected Ag (immunogen). The factors influencing immunogenicity are [31]:
  • The molecular size of the injected Ags: the most active immunogens tend to have a high molecular mass (>14,000 Da). Indeed, small Ags (e.g., DOA) are known to be either non-antigenic or weakly antigenic.
  • The foreignness: an antigen must be a foreign substance to the animal (not self) to elicit an immune response.
  • The chemical complexity: the more complex the immunogen or substance is (chemically), the more immunogenic it will be. The DOA (BZD, heroin, amphetamine, morphine, etc.) are often of low molecular weight and, generally, for any very small Ag, the entire chemical structure is considered by the immune system as a single epitope to which an Ab binds.
Since they are unable to induce an immune response by themselves, they require a carrier molecule to act as a complete Ag. They are used as haptens or as a recognition site for the production of specific Abs by coupling them to a suitable carrier molecule (the immune response in the host animal can produce Abs against the entire immunogen and not just the drug molecule). Many proteins can be used as carriers, but the most commonly used ones are bovine serum albumin (BSA; 67 kDa) and keyhole limpet hemocyanin (KLH, 400 kDa), which are highly immunogenic because of their complexity (structure) and large sizes [32,33,34,35].
BSA is widely used as a blocking agent in development of immunoassays, such as ELISA and LFIA, because it is very accessible and available and has numerous useful groups to be linked to small molecules, including DOA, as a carrier molecule to induce the immune system. For this reason, it is recommended, for example, to use KLH as the carrier molecule (protein) to induce an immune response against the hapten and the BSA for Abs screening and purification, to assure the detection of the Ag (hapten) instead of the carrier Abs [32,33,35].
If morphine (MOP) is taken as a model for developing a DOA detection system based on LFIA, the carbon atoms in its positions 3, 6, 2, and group N, readily lend themselves to conjugation to the carrier protein (Figure 1).
The production of Abs directed against the MOP molecule using a carrier molecule in group N to produce a more specific assay for MOP detection is commonly used. This leaves positions 3 and 6 as antigenic determinants and, thus, allows the production of Abs more likely to be specific to MOP, without cross-reactivity to codeine (COD) or dihydrocodeine, for example. However, if the immunogen is produced via position 3, it is generally used to produce broad cross-reactive anti-opiate Abs (diacetylmorphine and MOP-3-glucuronide). Cross-reactivity to different opiates varies from one Ab to another. It is important that each Ab is fully characterized by the test developer. However, the production of MOP Abs in position 6 gives a better specificity to MOP relative to COD and MOP-3-glucuronide, and is expected to produce Abs with good cross-reactivity with 6-monoacetylmorphine and the active metabolite MOP-6-glucuronide [37].
When a mammal animal, such as a mouse, rabbit, sheep, goat, rat, or a horse (for large quantities of Ab) is immunized with an Ag immunogen, it will cause stimulation of all B-lymphocytes that produce Abs specific to that Ag. This stimulation will result in the clonal multiplication of these B-lymphocytes, which will turn into plasmacytes secreting the specific Ig. A clone produces the same Ig that has the same specificity for a given epitope. The Abs derived from a clone of plasmacytes are called monoclonal Abs (same Abs produced from a single clone).
The majority of the mAbs available in the market are IgG isotype because of their superior affinity and specificity compared to the other isotypes (IgM). However, in the natural situation, an Ag always produces a polyclonal serum [38]. Thus, the combination of Igs derived from different clones, but all recognizing different epitopes of the same Ag forms a polyclonal serum, called antiserum, specific for the given Ag.
The measure of binding strength between an Ag and an Ab is described by the affinity constant. This binding is non-covalent, reversible, and reaches equilibrium. In addition, high affinity Abs bind faster than low affinity ones and perform better in immunochemical methods [38].
In general, the commercial production of recombinant monoclonal antibodies (mAbs) follows principally similar workflow. The process begins with the generation of a mAb by immunizing an animal or by techniques using molecular biology methods involving the identification and optimization of the genetic coding sequence and the construction and identification of a stable high-producing clone.
Today, in the laboratory step, several techniques are well established and commonly used to obtain mAbs, namely: Epstein-Barr virus (EBV) lymphoblastoid transformation technique, hybridoma technique, and phage display technique (Scheme 1) [39].
Phage display technique is the most commonly applied technology to produce recombinant antibodies in the laboratory settings. This helps the isolation of proteins from diverse mutagenic libraries and investigates protein-protein, protein-peptide, and protein-DNA interactions, and consists, basically, in cloning Fab coding genes into bacteriophage plasmid vectors [39]. The advantages of this methodology are multiple: one library can generate a great number of new Abs, it is an in vitro process (so animal immunizations steps are not required), and, accordingly, even toxic antigens can be tested. Moreover, the Abs molecules can be rapidly obtained [39,40,41,42]. However, for LFIA development application, mAbs produced using this technique are still not widely used, and the mostly used ones are derived from mouse hybridoma (but exhibit a downside in human therapeutics).
In 1975, Georges Köhler and Cesar Milstein described the first technique developed for stable monoclonal antibody production. This technique consists of creating a hybridoma, a stable hybrid cell capable of producing a single type of antibody against a specific epitope present in an antigen (Scheme 2). It is also called the technique of hybridization cell and is a method for producing large numbers of mAbs. In LFIA development application (immunoassay diagnostic or screening tests in general), it is the mostly used technique to produce mAbs in all laboratories, but has a downside in human therapeutics. The hybridoma technique is currently performed following four main steps (Scheme 2):
  • Step 1: fusing the secretory lymphocyte of an Ab to the Ag used in the animal’s immunization with the myeloma using polyethylene glycol.
  • Step 2: identifying the Ab secretory hybridoma.
  • Step 3: isolating one cell and maintaining it in culture to obtain a single clone or family of cells, all of which are identical and secretive of the same mAb. It is limit-dilution cloning, and several successive clones are sometimes necessary to obtain a genetically stable clone.
  • Step 4: growing the cloned hybridoma in a bioreactor to obtain a mAb concentrate or in a roller system to obtain the less concentrated mAb as a culture supernatant. It can be injected into the abdomen of BALB/c mice (Bagg albino, laboratory-bred strain of the house mouse) to obtain ascites-concentrated mAb.
Overall, an immunization program usually involves injecting three to six animals with the same Ag. However, if appropriate Abs are not produced after multiple immunizations, it may be necessary to repeat the program with different animals and possibly a different immunogen [37].
This method was used by several authors for the development of mAbs against DOA. Indeed, Dehghannezhad et al. in 2012 [43] used it to produce a mAb and conjugated it to gold nanoparticles (GNPs) to develop a rapid competitive immunochromatographic strip test to detect MOP in urine samples. It was also used to develop Abs for the diagnosis and screening of different diseases and clinical cases, including arthritis, breast cancer, psoriasis, leukemia, transplant rejection, asthma, and toxicity [44,45,46,47,48,49,50,51,52].

4. Performances of an Antibody

After the Ab is produced, as described before, surface plasmon resonance (SPR), equilibrium dialysis, ELISA, or many other methods are widely used to indicate its affinity (termed as binding strength or binding constant) to the Ag, and demonstrate its characteristics and binding to the target drug in real-time, and in a label-free manner, using a refractive index change at a metal surface [53,54]. There is also the possibility of using ELISA to verify that the Ab meets the need with the target drug (i.e., sensitivity, specificity). In this way, the binding and displacement can be observed with each Ab. Careful titration of the Abs and labeled drug derivative may improve the assay characteristics, and then the assay may be further optimized by the addition of other proteins, surfactants, and stabilizers to the assay buffer.

Applications of mAbs and Their Comparison with Polycolonal Antibodies in the Development of LFIA

Specific mAbs provide accurate testing. They are used for the determination of ABO and rhesus blood groups, for HLA tissue grouping, for the immunolabeling of acute leukemia and for the development of immunological tests (enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay (LFIA), radioimmunoassay (RIA), etc.) [18,19,20,21,27,31,55,56,57,58,59,60]. Other Abs issued from animals conjugated to markers or enzymes are used for diagnostic kits manufacturing, immunocytochemical analysis, and research [18,19,20,21,27,31,55,56,57,58,60,61,62].
Their frequent usage in basic research has led to the study and the understanding of many biological processes. Moreover, a panel of mAbs is usually used to map and study the role of epitopes in certain cellular functions and mechanisms. They have also an important role in proteomics and mass biological screening tests [18,19,20,21,31,43,55,56,58,59]. In general, mAbs are used in diagnostic, agri-food, veterinary, microbiological, and toxicological tests [20,21,31,56,58,63]. However, mAbs generally have less affinity than pAbs, which may lead to less sensitive assays. It should be noted that in drug detection tests, an Ab may be too specific as it may be desirable to have broad cross-reactivity with a family of drugs (such as BZDs) or with a single drug and its metabolites (such as buprenorphine).
The mAbs offer the advantages of purity and homogeneity, which is useful in the circumstances where the Ab is labeled or conjugated within the framework of the LFIA’s development [61,64,65]. They all recognize specifically a single epitope and are homogeneous compared to pAbs, which allows the testing to be standardized. The monospecificity provided by mAbs, makes it possible to understand and evaluating changes in molecular conformation and structure, phosphorylation states, protein-protein interactions, and in identifying single members of protein families. However, the monospecificity of mAbs may also limit their advantages, because they should be generated to the Ag epitope to which it will bind (small change in the structure of an epitope can affect the function of a mAb) [38,66]. They can also identify an antigenic determinant in complex mixtures, such as biological fluids (blood, urine, milk, saliva, etc.).
Both polyclonal and monoclonal antibodies have their own advantages and disadvantages, which make them useful for different applications. The debate regarding whether mAbs are better than pAbs has been raging for years. Some researchers praise the batch-to-batch consistency and single-isotype nature of monoclonals, others swear by the ability of polyclonals to work in a wider range of applications, often enabling detection of the target antigen in both its native and denatured states.
The pAbs are heterogeneous and have a wide specificity than mAbs, because they are produced by a large number of B cell clones, each generating pAbs to a specific epitope. The pAbs’ production techniques are easy, fast, and low-cost compared to mAbs’ production techniques. However, their production costs depend on the quantities required and their use.
The best use of pAbs is to detect unknown antigens. pAbs are used as a secondary antibody (detectors) in immunoassays (e.g., ELISA, western blotting, microarray assays, immunohistochemistry, flow cytometry). Their role is to bind to different epitopes and amplify the signal, leading to better detection. When pAbs are used as detectors, more steps are needed, such as labeling and affinity purification, which may increases the costs. Moreover, a production of large quantities of PAbs requires a large number of animals, restrictive farming conditions, and expensive infrastructure.
In contrast, mAbs are often used as primary antibodies in immunoassays because of their ability to bind specifically to a single epitope of an Ag. They are easy to label and provide an unlimited source of antibody that is homogeneous and, once characterized, predictable in its behavior. Nowadays, mAbs specificity can be expanded by combining multiples mAbs that lead to the capture of multiple epitopes of an Ag.
Another advantage of mAbs is that, once their line is established, their supply is infinite, and the risk of isolating the desired cell line never has to occur again. In the opposite way, pAbs are prone to batch-to-batch variability and there is no guarantee that immunizing other animals will yield to a useable Ab.

5. Lateral Flow Immunoassays (LFIA)

5.1. Basic Components of a LFIA

The LFIA is a simple to use device used to confirm the presence or absence of a target analyte; also known as, quick test, lateral flow device, immunochromatographic assay, or as lateral flow assay (LFA) that is applicable to point-of-care testing (POCT). The principle of an LFA is based on the movement of a liquid sample though a strip with attached molecules that interact with the analyte, providing a signal that can be visually detected. Although the principle behind the LFA is simple, the device has a complex architecture, and many critical elements need to be considered during instrumental design.
Most of these listed tests are presented in the form of a plastic cassette or a card that contains nitrocellulose strips visible through the different windows or cells of the cassette [20,27,67,68,69,70,71]. In general, membrane-based tests consist of overlapping membranes or pads made of different materials that are mounted on a backing card, as described below (Figure 2).

5.1.1. Sample Pad

The sample pad is a membrane in which the sample is deposited, distributed, then directed to the conjugate pad (Figure 2). It is generally made of cellulose fiber with a good bed volume and low-analytes binding, to avoid their loss and ensure a good distribution of them. According to the sample biological matrices (saliva, water, blood, urine, serum, feces, milk, etc.), a sample pad pretreatment may be necessary before dispensing the sample. This pretreatment using some proteins, such as bovine serum albumin (BSA), buffer salts, or other liquids, is necessary to optimize the pH and the sample viscosity, to control the flow rate and also to avoid nonspecific binding [20,27,67,70,71,72]. Moreover, the sample pad is used as filter in order to remove redundant materials (e.g., red blood cells).

5.1.2. Conjugate Pad

This membrane is composed of cellulose filters or glass fibers. The main role of the conjugate pad is to hold the dried biorecognition elements (Abs, targets molecules or Ags) coupled to a particulate label (gold nanoparticles, colored latex, and carbon) and keep them functional and stable during the performance of the test (Figure 2). This is ensured by the conjugate buffer that contains carbohydrates (such as sucrose and borate), which serves also as a preservative and a re-solubilization agent. To select a conjugate pad, we should take into consideration the following points:
  • Low non-specific reaction of the sample or the antibody coupled to a nanoparticle (label) (Ab-NP).
  • Release of the Ab-NP or the sample should be quick and consistent between individual test strips.
  • Ab-NP must remain functional when dried on it.
After the selection of the appropriate conjugate pad, to achieve a high sensitivity of the LFIA we should pretreat it to minimize non-specific binding by blocking protein binding sites (using BSA solutions) and control the pH [20,27,67,70,71,72].

5.1.3. Test Pad, Reaction Membrane, or Nitrocellulose Membrane

The test membrane (Figure 2) is made of commonly materials such as nitrocellulose, polyvinylidene fluoride, cellulose acetate, or polyether sulfone. This membrane is considered as the most critical element in LFA strips that allows to read and to interpret the results. In order to select the appropriate test pad, it is important to consider the capillary flow time (FT) defined as the time a liquid (sample) needs to migrate along a membrane expressed in seconds/centimeters. This is the more accurate parameter, and it should be used when selecting the most effective strip material. Moreover, membrane pores size as well as the binding efficiency are a crucial criterion for test pad selection.
In general, the test membrane contains two lines named T for test and C for control (Figure 2). During the test performance, the liquid sample migrates and interacts with the analytes that are bound in the T and the C lines. The C line consists of testing the performance and control the reaction of the LFIA. The longer the membrane is, the more it allows a longer interaction between the Ab-NP and the analytes to be detected at the test line (T) [20,27,67,70,71,72].

5.1.4. Absorbent Pad or Wick Pad

The absorbent pad (AP) (Figure 2) is generally composed of a cellulose fiber that can decrease the FT by hindering the backflow [73,74,75], absorbing and increasing the volume of the sample through the entire assay (LFIA) and reserves waste. In addition, the right AP selection can increase the performances of the test and the criteria for selection are the same as that of the sample pad (material, thickness, etc.) [20,27,67,70].
There are many membranes available from multiple commercial sources, the selection of the appropriate one, as well as developing the right treatment plan, is essential for any LFIA.
Generally, the criteria for selecting a membrane for a LFIA to check are:
  • The analytes (drugs or proteins, etc.) size and the sample liquid viscosity.
  • The porosity and the pore size.
  • The thickness (µm) of each membrane.
  • The potential coating or treatment that the membrane surface needs.

5.2. Labels

Several molecules can be used for the revelation step namely: colloidal gold (GNPs); that is a colloidal suspension of nanoparticles of gold in water, liposomes, magnetic bead, silver nanoparticles, colored latex beads, quantum dots, organic fluorophores, magnetic nanoparticles (MNP), textile dyes, carbon nanoparticles, selenium nanoparticles, up converting phosphors, enzymes, and others [20,21,27,61,64,65,72,76,77]. These marked molecules must be able to retain their physicochemical properties after coupling to any Ab or nucleic acids and must also be detected in small quantities (ng) (concentrations in biological matrices) [57,61,78,79]. A reaction must also be revealed in the control window (C) (sandwich format) (Figure 2), regardless of the test window (T) result, to ensure that the procedure goes smoothly, and the test runs correctly.

5.3. Formats of LFIA

According to the element of revelation or detection, the LFAs are classified according to the following Scheme 3 [20,21]:
Nowadays, in the DOA field, there are a few commercialized kits based on the nucleic acid lateral flow assays (NALFA) or nucleic acid chromatographic tests. The most well-known and commercialized ones are the LFIA or immunochromatographic tests, where the revelation is often done by an Ab [20], based on Ab-Ag reaction [20,21,61,76,80].
Although, depending on the nature of the molecule sought, there are essentially two types of LFIA (Scheme 1): those based on Ag detection (e.g., BZDs, AMP, etc.) [57,61,80] and those based on Ab detection (e.g., HIV infection, Chagas disease or polyarthritis) [80,81,82]. Likewise, according to the size of the element detected (Ag or Ab), and the number of their detectors, there are tree common formats of the LFIA described below (Figure 3 and Figure 4).

5.3.1. Sandwich Format

The sandwich format is developed for the detection of large molecules, such as human serum albumin or Abs that have more than two epitopes or binding sites (HIV, arthritis, etc.) [80,81,83] (Figure 3).
Figure 3. Sandwich immunochromatographic test [84].
Figure 3. Sandwich immunochromatographic test [84].
Molecules 26 01058 g003
In a sandwich assay, the T and C lines contain both the target molecule Abs. Furthermore, another Ab against the same target molecule is conjugated to the nanoparticles (Ab-NP) to reveal the presence of the analyte. The results interpretation is simple. The signal is proportional to the concentration of analytes in the sample. If the target molecule is present in the sample, the Ab-NP will bind to it at the test line (T) and give a high signal intensity. In the opposite case, the Ab-NP will not bind to the Abs in the T line and no signal will be revealed (Figure 3).

5.3.2. Competitive (or Inhibition) Format

The competitive format is usually very useful for small molecules, such as psychotropic drugs (e.g., BZDs) [20,43,80] (Figure 4).
Figure 4. Competitive immunochromatographic test [84].
Figure 4. Competitive immunochromatographic test [84].
Molecules 26 01058 g004
The signal intensity is inversely proportional to the concentration of the target molecule present in the sample (Figure 4); it operates on the same principles as the competitive enzyme-linked immunosorbent assays (cELISA). The T line contains the target molecules (e.g., DOA) fixed. When the target molecule is absent in the sample, unbound Abs coupled to NP (Abs-NP) will bind to these target molecules (fixed on T line), which show a visual coloration. Conversely, when the target molecule is present in the sample, it binds to the Abs-NP and stops their binding to the target molecule (fixed) in the T line, so no visual coloration will appear in the T line, or it will show some colors, but the signal is lower if an analyte is present.

5.3.3. Complex Format or Multiplex Format

This test format can detect simultaneously more than one type of molecules [60,85,86]. The test contains a number of T lines equal to the number of target analytes to be detected. Recent works showed that, in many LFIA, combining several analytes into panels is critical for enhancing the diagnostic precision for a specific addiction or a disease, improving diagnostic efficiency and reducing cost [60]. Guteneva NV and al [61] developed a lateral-flow assay based on the quantification of MNP labels for multiplexed immunodetection of MOP, fentanyl, and MET in urine samples. The MNP used for LFIA in the literature vary in size (10–400 nm), they could be used for qualitative or quantitative measurements if they are coupled with an external reader, as well as enable immunomagnetic separation, which improves selectivity and sensitivity [87].

5.3.4. The Performance of a LFIA (Validity of the LFIA)

In general, a screening test is used to screen within a healthy target population those likely to have a disease from those healthy. This ability depends both on the test’s own performance and on the characteristics of the tested population. In general, a screening test should be inexpensive, simple to perform, valid, reliable, reproducible, and acceptable [17].
The specific performance of a screening test is its sensitivity and specificity [17,88]; they define the intrinsic validity of the test. They are defined and calculated under experimental conditions and are, therefore, independent of the type of person tested and the population studied.
In the DOA field, the characteristics of the population tested, in particular the prevalence of consumption of the target molecule (DOA), influence the extrinsic performance of the test. These extrinsic performances are the positive (PPV) and negative predictive values (NPV). They are relatives to the use of the test for a given population and differ according to the characteristics of the tested population. They are defined and calculated in the context of the screening situation and make it possible to assess the relevance of the use of the test in this specific population.

5.3.5. Intrinsic Performances: Sensitivity and Specificity

The sensitivity of a given test is the probability that this test will be positive if the person is consuming a DOA.
The specificity of a given test is the probability that the test will be negative if the tested person is not consuming a DOA.
The sensitivity of the test can therefore be calculated according to the following formula [88]:
Sensitivity = True positives (TP)/(TP + False negatives (FN)) × 100,
The specificity of the test can be calculated according to the following formula:
Specificity = True negatives (TN)/(TN + False positives (FP)) × 100,
The sensitivity and specificity of a test are interrelated. The increase in the sensitivity of a test is always at the expense of its specificity and vice versa.
The following Table 1 shows the likely results of LFIAs. The current conditions of the subjects (consumer or non-consumer) are presented in columns in terms of the test results in rows (positive or negative).
However, a test is accurate if the number of false positives (FP) and false negatives (FN) is the lowest possible.

5.3.6. Extrinsic Performance: Positive (PPV) and Negative Predictive Values (NPV)

The PPV and NPV are influenced by the prevalence of the consumption of a target molecule in the tested population. If the test is done in a population with a high prevalence, it is more likely that people whose test result is positive have the disease than if the test is done in a population with a low prevalence of the disease (which is usually the case in screening tests). These two values can be calculated according to the following formulas:
PPV = TP/(TP + FP) × 100,
NPV = TN/(TN + FN) × 100,
However, a screening test must offer a good compromise between high sensitivity (to screen the largest number of suspicious people) and high specificity (to avoid using the confirmatory test in healthy people).

5.4. Limitations and Opportunities in LFIA

The LFIA are easy to use, provide rapid and low-cost tests, samples do not need pretreatments before the analysis, and they have a long shelf life.
However, LFIA are considered as screening tests and they have some limitations: they cannot be used for quantification and, sometimes, their results need to be confirmed (especially when using samples with a high level of molecules that present some structural similarities to target analytes), further using standard and independent techniques, such as LC-MS-MS, GC-MS, HPLC, ELISA, RIA, PCR, etc. [11,17,89,90,91,92,93,94,95]. In routine, different compounds may present some structural similarities, which can generate false positive results due to Abs cross-reactions. For example, the same result is obtained when analyzing cannabis in a sample from a person taking drugs containing niflumic acid. All of the commercial tests available, whether salivary or urinary, present the same risk of errors. However, some are much more reliable than others, and that depends, as said above, on the characteristics of the Abs used as the detection molecule.
Various LFIA tests (competitive ones) have already been described for the specific or simultaneous detection of psychotropic molecules. In general, the tests with a specificity and sensitivity close to 100% are considered good tests. Their use is easy to implement in any analytical toxicology laboratory or in the workplace.
The results of our study selection research from 2010 to 2020 were reported in Table 2. In these reports, the test used is a competitive LFIA. The confirmatory methods, the used sample, the analytes, the labels and conjugates, and the limits of detection of the tests (LODs) are reported below (Table 2). In general, the analysis time is from 5 to 15 min.

6. Perspectives

In recent years, the concept of aptamers, artificial Abs, or “intelligent ligands” has been introduced. Aptamers are synthetic oligonucleotides (DNA or RNA), selected and characterized by systematic evolution of ligands by exponential enrichment (SELEX) [104,105,106,107], based on their high affinity and specificity to target Ags, such as peptides, drugs, proteins, small molecules cells, and tissues.
These molecules can be used as a possible alternative to mAbs in biomedical research, since they have affinities and specificities comparable to those of Abs for various molecules [105,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124].
Aptamers can also be used for targeted therapeutics or drug discovery [125,126,127,128,129,130,131,132,133,134,135,136], because they are non-immunogenic and can be easily stabilized by chemical modifications. As far as chemical and biological properties are concerned, their use against mAbs has several advantages. They are able to regenerate and to mark, stable to ambient temperature with a high reproducibility, and their structure can be modified. Moreover, their production costs can be reduced since they can be obtained by chemical synthesis, avoiding the use of animals or cells.
Nowadays, the aptamers are not widely used in LFAs. However, for the detection and recognition of psychotropic molecules, few aptamers were identified, more being devoted to COC, or its metabolite benzoylecgonine (BE), AMP, or MET (Table 3). Moreover, there are some aptamers for toxins detection, such as ochratoxin A (OTA) (Table 3). Since then, refined sequences have been identified and used to detect DOA (Table 3). These refined sequences are promising and require more studies to validate the use of aptamers for the detection of psychotropic drugs.

7. Conclusions

Monoclonal Abs have allowed the development of highly sophisticated assay methods that detect and quantify numerous markers and molecules in biological matrices, with a significantly improved specificity compared to polyclonal Abs. They are still widely used in some immunoassay tests, in particular because of their high sensitivity and specificity.
The contribution of Abs to human development holds great promise for the future. Their usefulness is already proven in the new technologies in genomics, proteomics, imaging, and nanobiotechnology. All LFIA tests require the use of Abs; it is this element of the system—and how it is produced—that is the key to the test’s performance (sensitivity and specificity).
The discovery of the aptamers opens up prospects with great socioeconomic impacts. It is clear that the acquisition of these technologies by laboratories is of particular importance for the future of the pharmaceutical industry. Indeed, investments must be made in this area.

Funding

This work was funded by the Moroccan ministry of transport, equipment, and logistics through the National Center for Scientific and Technical Research (CNRST), as part of the “Road safety scientific research support program” (Programme d’appui à la recherche scientifique en matière de sécurité routière) (contract no. 21/2017).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

In our work, we could not discuss all of the available scientific papers on LFA and their applications in the analysis of DOA. In this sense, we thank all of the authors of the papers we used, and we apologize to everyone who works in this field whose work we did not cite. The authors wish to thank, in particular, MAScIR Medical Biotechnology Center members for providing their support.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Baumeister, D.; Ciufolini, S.; Mondelli, V. Effects of psychotropic drugs on inflammation: Consequence or mediator of therapeutic effects in psychiatric treatment? Psychopharmacology 2016, 233, 1575–1589. [Google Scholar] [CrossRef] [PubMed]
  2. Scheifes, A.; Walraven, S.; Stolker, J.J.; Nijman, H.; Egberts, A.C.; Heerdink, E. Adverse events and the relation with quality of life in adults with intellectual disability and challenging behaviour using psychotropic drugs. Res. Dev. Disabil. 2016, 49, 13–21. [Google Scholar] [CrossRef]
  3. Correll, C.U.; Detraux, J.; De Lepeleire, J.; De Hert, M. Effects of antipsychotics, antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia, depression and bipolar disorder. World Psychiatry 2015, 14, 119–136. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Johnell, K.; Bergman, G.J.; Fastbom, J.; Danielsson, B.; Borg, N.; Salmi, P. Psychotropic drugs and the risk of fall injuries, hospitalisations and mortality among older adults. Int. J. Geriatr. Psychiatry 2016, 32, 414–420. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Shash, D.; Kurth, T.; Bertrand, M.; Dufouil, C.; Barberger-Gateau, P.; Berr, C.; Ritchie, K.; Dartigues, J.-F.; Bégaud, B.; Alpérovitch, A.; et al. Benzodiazepine, psychotropic medication, and dementia: A population-based cohort study. Alzheimer’s Dement. 2016, 12, 604–613. [Google Scholar] [CrossRef]
  6. Doghramji, K.; Jangro, W.C. Adverse effects of psychotropic medications on sleep. Psychiatr. Clin. N. Am. 2016, 39, 487–502. [Google Scholar] [CrossRef]
  7. Chang, K.J.; Son, S.J.; Kim, D.; Lee, K.S.; Roh, H.W.; Hong, C.H. P2-111: Effect of psychotropic drugs on development of diabetes mellitus in patients with Alzheimer’s disease. Alzheimer’s Dement. 2015, 11, P526. [Google Scholar] [CrossRef] [Green Version]
  8. Mawanda, F.; Ms, R.B.W.; Ms, K.M.; Ms, T.E.A. PTSD, Psychotropic medication use, and the risk of dementia among US veterans: A retrospective cohort study. J. Am. Geriatr. Soc. 2017, 65, 1043–1050. [Google Scholar] [CrossRef]
  9. Sikary, A.K.; Sasidharan, A.; Pillay, V.; Andrade, C. Prescription drug suicide in non-abusers: A 6-year forensic survey. Asian J. Psychiatry 2019, 44, 133–137. [Google Scholar] [CrossRef]
  10. Qriouet, Z.; Belaiche, A.; Qmichou, Z.; Cherrah, Y.; Sefrioui, H. Benzodiazepines use in Morocco: A nation wide consumption database study between 2004 and 2017. Asian J. Psychiatry 2020, 47, 101852. [Google Scholar] [CrossRef] [PubMed]
  11. Qriouet, Z.; Qmichou, Z.; Bouchoutrouch, N.; Mahi, H.; Cherrah, Y.; Sefrioui, H. Analytical methods used for the detection and quantification of benzodiazepines. J. Anal. Methods Chem. 2019, 2019, 2035492. [Google Scholar] [CrossRef] [Green Version]
  12. Woźniak, M.K.; Wiergowski, M.; Aszyk, J.; Kubica, P.; Namieśnik, J.; Biziuk, M. Application of gas chromatography-tandem mass spectrometry for the determination of amphetamine-type stimulants in blood and urine. J. Pharm. Biomed. Anal. 2018, 148, 58–64. [Google Scholar] [CrossRef]
  13. El-Beqqali, A.; Andersson, L.I.; Jeppsson, A.D.; Abdel-Rehim, M. Molecularly imprinted polymer-sol-gel tablet toward micro-solid phase extraction: II. Determination of amphetamine in human urine samples by liquid chromatography-tandem mass spectrometry. J. Chromatogr. B 2017, 1063, 130–135. [Google Scholar] [CrossRef]
  14. Eckart, K.; Röhrich, J.; Breitmeier, D.; Ferner, M.; Laufenberg-Feldmann, R.; Urban, R. Development of a new multi-analyte assay for the simultaneous detection of opioids in serum and other body fluids using liquid chromatography–tandem mass spectrometry. J. Chromatogr. B 2015, 1001, 1–8. [Google Scholar] [CrossRef]
  15. Boumba, V.A.; Rallis, G.; Petrikis, P.; Vougiouklakis, T.; Mavreas, V. Determination of clozapine, and five antidepressants in human plasma, serum and whole blood by gas chromatography–mass spectrometry: A simple tool for clinical and postmortem toxicological analysis. J. Chromatogr. B 2016, 1038, 43–48. [Google Scholar] [CrossRef]
  16. Pichini, S.; Cortes, L.; Marchei, E.; Solimini, R.; Pacifici, R.; Gómez-Roig, M.D.; García-Algar, O. Ultra-high-pressure liquid chromatography tandem mass spectrometry determination of antidepressant and anxiolytic drugs in neonatal meconium and maternal hair. J. Pharm. Biomed. Anal. 2016, 118, 9–16. [Google Scholar] [CrossRef]
  17. Gentili, S.; Solimini, R.; Tittarelli, R.; Mannocchi, G.; Busardò, F.P. A Study on the reliability of an on-site oral fluid drug test in a recreational context. J. Anal. Methods Chem. 2016, 2016, 1234581. [Google Scholar] [CrossRef] [PubMed]
  18. Wang, K.; Cui, D. The application of immunochromatographic analysis in early detection of gastric cancer. In Gastric Cancer Prewarning and Early Diagnosis System; Springer: Berlin/Heidelberg, Germany, 2017; pp. 129–156. [Google Scholar]
  19. Cao, F.; Xu, J.; Yan, S.; Yuan, X.; Yang, F.; Hou, L.; Zhao, L.; Zeng, L.; Liu, W.; Zhu, L.; et al. A surface plasmon resonance-based inhibition immunoassay for forensic determination of methamphetamine in human serum. Forensic Chem. 2018, 8, 21–27. [Google Scholar] [CrossRef]
  20. Bailes, J.; Mayoss, S.; Teale, P.; Soloviev, M. Gold nanoparticle antibody conjugates for use in competitive lateral flow assays. In Nanoparticles in Biology and Medicine; Springer: Berlin/Heidelberg, Germany, 2012; pp. 45–55. [Google Scholar]
  21. Urusov, A.; Petrakova, A.; Kuzmin, P.; Zherdev, A.; Sveshnikov, P.; Shafeev, G.; Dzantiev, B. Application of gold nanoparticles produced by laser ablation for immunochromatographic assay labeling. Anal. Biochem. 2015, 491, 65–71. [Google Scholar] [CrossRef] [PubMed]
  22. Ion, M.; Moldovan, C.; Dinulescu, S.; Muscalu, G.; Savin, M.; Mihailescu, C.-M.; Stan, D.; Matei, I. Fabrication of a new LFIA test for rapid quantitative detection of CK-MB, using inkjet-printing method. In Proceedings of the 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), Turin, Italy, 19–21 October 2017. [Google Scholar]
  23. Clarke, O.J.R.; Goodall, B.L.; Hui, H.P.; Vats, N.; Brosseau, C.L. Development of a SERS-based rapid vertical flow assay for point-of-care diagnostics. Anal. Chem. 2017, 89, 1405–1410. [Google Scholar] [CrossRef] [PubMed]
  24. Lai, J.J.; Stayton, P.S. Improving lateral-flow immunoassay (LFIA) diagnostics via biomarker enrichment for mHealth. In Mobile Health Technologies; Springer: Berlin/Heidelberg, Germany, 2015; pp. 71–84. [Google Scholar]
  25. Huang, D.; Ying, H.; Jiang, D.; Liu, F.; Tian, Y.; Du, C.; Zhang, L.; Pu, X. Rapid and sensitive detection of interleukin-6 in serum via time-resolved lateral flow immunoassay. Anal. Biochem. 2020, 588, 113468. [Google Scholar] [CrossRef]
  26. Cai, Y.; Kang, K.; Liu, Y.; Wang, Y.; He, X. Development of a lateral flow immunoassay of C-reactive protein detection based on red fluorescent nanoparticles. Anal. Biochem. 2018, 556, 129–135. [Google Scholar] [CrossRef]
  27. Tsai, T.-T.; Huang, T.-H.; Chen, C.-A.; Ho, N.Y.-J.; Chou, Y.-J.; Chen, C.-F. Development a stacking pad design for enhancing the sensitivity of lateral flow immunoassay. Sci. Rep. 2018, 8, 17319. [Google Scholar] [CrossRef] [Green Version]
  28. nanoComposix. Antibody Selection and Purification for Lateral Flow Rapid Tests. 2020. Available online: https://nanocomposix.com/pages/antibody-selection-and-purification-for-lateral-flow-rapid-tests#target (accessed on 2 October 2020).
  29. Gülpınar, Ö.; Güçlü, A.G. How to write a review article? Turk. J. Urol. 2013, 39 (Suppl. 1), 44. [Google Scholar]
  30. Vidarsson, G.; Dekkers, G.; Rispens, T. IgG Subclasses and Allotypes: From Structure to Effector Functions. Front. Immunol. 2014, 5, 520. [Google Scholar] [CrossRef] [Green Version]
  31. Guan, D.; Guo, L.; Liu, L.; Kong, N.; Kuang, H.; Xu, C. Development of an ELISA for nitrazepam based on a monoclonal antibody. Food Agric. Immunol. 2015, 26, 611–621. [Google Scholar] [CrossRef]
  32. Cuccuru, M.A.; Dessì, D.; Rappelli, P.; Fiori, P.L. A simple, rapid and inexpensive technique to bind small peptides to polystyrene surfaces for immunoenzymatic assays. J. Immunol. Methods 2012, 382, 216–219. [Google Scholar] [CrossRef] [PubMed]
  33. Zhao, R. Bovine serum albumin as an immunogenic carrier facilitating the development of hapten-specific monoclonal antibodies. bioRxiv 2020, 1–22. [Google Scholar] [CrossRef]
  34. Pravetoni, M.; Keyler, D.E.; Pidaparthi, R.; Carroll, F.; Runyon, S.P.; Murtaugh, M.P.; Earley, C.; Pentel, P.R. Structurally distinct nicotine immunogens elicit antibodies with non-overlapping specificities. Biochem. Pharmacol. 2012, 83, 543–550. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Guo, J.; Liu, L.; Xue, F.; Xing, C.; Song, S.; Kuang, H.; Xu, C. Development of a monoclonal antibody-based immunochromatographic strip for cephalexin. Food Agric. Immunol. 2014, 26, 282–292. [Google Scholar] [CrossRef]
  36. Cong, X.; Campomanes, P.; Kless, A.; Schapitz, I.; Wagener, M.; Koch, T.; Carloni, P. Structural determinants for the binding of morphinan agonists to the μ-opioid receptor. PLoS ONE 2015, 10, e0135998. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Kapp, R.W., Jr. Clarke’s Analysis of Drugs and Poisons; Moffat, A.C., Osselton, M.D., Widdop, B., Watts, J., Eds.; Pharmaceutical Press: London, UK, 2004; ISBN 0-853-69473-7. [Google Scholar]
  38. Zola, H. Monoclonal Antibodies: A Manual of Techniques; CRC Press: Boca Raton, FL, USA, 2013. [Google Scholar]
  39. Frei, J.; Lai, J.R. Protein and Antibody Engineering by Phage Display. In Methods in Enzymology; Elsevier: Amsterdam, The Netherlands, 2016; pp. 45–87. [Google Scholar]
  40. Teixeira, D.; Gonzalez-Pajuelo, M. Phage Display Technology for Selection of Antibody Fragments. In Biomedical Applications of Functionalized Nanomaterials; Elsevier: Amsterdam, The Netherlands, 2018; pp. 67–88. [Google Scholar]
  41. Chames, P.; Van Regenmortel, M.; Weiss, E.; Baty, D. Therapeutic antibodies: Successes, limitations and hopes for the future. Br. J. Pharmacol. 2009, 157, 220–233. [Google Scholar] [CrossRef]
  42. Koellhoffer, J.F.; Chen, G.; Sandesara, R.G.; Bale, S.; Saphire, E.O.; Chandran, K.; Sidhu, S.S.; Lai, J.R. Two synthetic antibodies that recognize and neutralize distinct proteolytic forms of the ebola virus envelope glycoprotein. ChemBioChem 2012, 13, 2549–2557. [Google Scholar] [CrossRef] [Green Version]
  43. Dehghannezhad, A.; Paknejad, M.; Rasaee, M.J.; Omidfar, K.; Ebrahimi, S.S.S.; Ghahremani, H. Development of a nanogold-based immunochromatographic assay for detection of morphine in urine using the Amor-HK16 monoclonal antibody. Hybridoma 2012, 31, 411–416. [Google Scholar] [CrossRef]
  44. Iqbal, M.N.; Ashraf, A.; Ling, S.; Wang, S. In vitro improved production of monoclonal antibody against zearalenone in supplemented cell culture media. PSM Biol. Res. 2018, 3, 106–110. [Google Scholar]
  45. Silva, B.G.; Tamashiro, W.M.D.S.C.; Ferreira, R.R.; Deffune, E.; Suazo, C.A.T. Assessment of kinetic and metabolic features of two hybridomas in suspension culture for production of two monoclonal antibodies for blood typing. Braz. J. Chem. Eng. 2018, 35, 497–508. [Google Scholar] [CrossRef] [Green Version]
  46. Rashidian, J.; Copaciu, R.; Su, Q.; Merritt, B.; Johnson, C.; Yahyabeik, A.; French, E.; Cummings, K. Generation and performance of R132H mutant IDH1 rabbit monoclonal antibody. Antibodies 2017, 6, 22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Sun, S.L.; Zhang, X.X.; Zhao, Q. Studies on rat-rat hybridoma technique and its application to obtain rat monoclonal antibodies anti-horseradish peroxidase. In Rat Hybridomas and Rat Monoclonal Antibodies (1990); CRC Press: Boca Raton, FL, USA, 2017; pp. 265–270. [Google Scholar]
  48. Lei, X.; Chen, J.; Yang, P.; Zhao, Y.; Wang, X.; Zhao, J.; Wang, C. The development of the hybridoma cell line secreting monoclonal antibody against S protein of a PEDV variant. Chin. J. Vet. Sci. 2016, 36, 206–215. [Google Scholar] [CrossRef] [PubMed]
  49. Lei, X.; Zhao, J.; Wang, X.; Zhao, Y.; Wang, C. Development of a hybridoma cell line secreting monoclonal antibody against s protein of a chinese variant of PEDV. Monoclon. Antibodies Immunodiagn. Immunother. 2015, 34, 12–16. [Google Scholar] [CrossRef]
  50. Alvarado, G.; Crowe, J.E. Development of human monoclonal antibodies against respiratory syncytial virus using a high efficiency human hybridoma technique. In Human Respiratory Syncytial Virus; Springer: Berlin/Heidelberg, Germany, 2016; pp. 63–76. [Google Scholar]
  51. Morita, I.; Oyama, H.; Yasuo, M.; Matsuda, K.; Katagi, K.; Ito, A.; Tatsuda, H.; Tanaka, H.; Morimoto, S.; Kobayashi, N. Antibody fragments for on-site testing of cannabinoids generated via in vitro affinity maturation. Biol. Pharm. Bull. 2017, 40, 174–181. [Google Scholar] [CrossRef] [Green Version]
  52. Owens, S.M.; Henry, R.; Brown, A. Anti-(+)—Methamphetamine Monoclonal Antibodies. Worldwide Patent Applications No. CA2901514A1, 14 August 2015. [Google Scholar]
  53. Ndao, D.; Hickman, D.; López-Deber, M.; Davranche, A.; Pfeifer, A.; Muhs, A. Binding affinity measurement of antibodies from crude hybridoma samples by SPR. BIO-Protocol 2014, 4, e1276. [Google Scholar] [CrossRef]
  54. Ross, G.M.S.; Bremer, M.G.E.G.; Wichers, J.H.; Van Amerongen, A.; Nielen, M.W.F. Rapid antibody selection using surface plasmon resonance for high-speed and sensitive hazelnut lateral flow prototypes. Biosensors 2018, 8, 130. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Bozokalfa, G.; Akbulut, H.; Demir, B.; Guler, E.; Gumus, Z.P.; Demirkol, D.O.; Aldemir, E.; Yamada, S.; Endo, T.; Coskunol, H.; et al. Polypeptide functional surface for the aptamer immobilization: Electrochemical cocaine biosensing. Anal. Chem. 2016, 88, 4161–4167. [Google Scholar] [CrossRef]
  56. Dinis-Oliveira, R.J. Heterogeneous and homogeneous immunoassays for drug analysis. Bioanalysis 2014, 6, 2877–2896. [Google Scholar] [CrossRef]
  57. Wille, S.M.; Di Fazio, V.; Toennes, S.W.; van Wel, J.H.; Ramaekers, J.G.; Samyn, N. Evaluation of Δ9-tetrahydrocannabinol detection using DrugWipe5S® screening and oral fluid quantification after Quantisal™ collection for roadside drug detection via a controlled study with chronic cannabis users. Drug Test. Anal. 2015, 7, 178–186. [Google Scholar] [CrossRef] [PubMed]
  58. Vidal, J.C.; Bertolín, J.R.; Bonel, L.; Asturias, L.; Arcos-Martínez, M.J.; Castillo, J.R. Rapid determination of recent cocaine use with magnetic particles-based enzyme immunoassays in serum, saliva, and urine fluids. J. Pharm. Biomed. Anal. 2016, 125, 54–61. [Google Scholar] [CrossRef] [PubMed]
  59. Cao, J.; Chen, X.Y.; Zhao, W.R. Determination of morphine in human urine by the novel competitive fluorescence immunoassay. J. Anal. Methods Chem. 2019, 2019, 7826090. [Google Scholar] [CrossRef] [PubMed]
  60. Tsai, T.-T.; Huang, T.-H.; Ho, N.Y.-J.; Chen, Y.-P.; Chen, C.-A.; Chen, C.-F. Development of a multiplex and sensitive lateral flow immunoassay for the diagnosis of periprosthetic joint infection. Sci. Rep. 2019, 9, 15679. [Google Scholar] [CrossRef]
  61. Guteneva, N.V.; Znoyko, S.L.; Orlov, A.V.; Nikitin, M.P.; Nikitin, P. Rapid lateral flow assays based on the quantification of magnetic nanoparticle labels for multiplexed immunodetection of small molecules: Application to the determination of drugs of abuse. Microchim. Acta 2019, 186, 621. [Google Scholar] [CrossRef] [PubMed]
  62. Feng, L.; Liu, Z.; Pan, Y.; Peng, D.; Wang, J.; Wang, Y.; Yuan, Z. Monoclonal Antibody used for Detecting Benzodiazepine Medicines and Enzyme-Linked Immunosorbent Assay Method and Kit. Patent No. CN104530240A, 22 April 2015. [Google Scholar]
  63. Hassanpour, S.; Hasanzadeh, M.; Saadati, A.; Shadjou, N.; Soleymani, J.; Jouyban, A. A novel paper based immunoassay of breast cancer specific carbohydrate (CA 15.3) using silver nanoparticles-reduced graphene oxide nano-ink technology: A new platform to construction of microfluidic paper-based analytical devices (μPADs) towards biomedical analysis. Microchem. J. 2019, 146, 345–358. [Google Scholar]
  64. Bahadır, E.B.; Sezgintürk, M.K. Lateral flow assays: Principles, designs and labels. TrAC Trends Anal. Chem. 2016, 82, 286–306. [Google Scholar] [CrossRef]
  65. Xie, Q.-Y.; Wu, Y.-H.; Xiong, Q.-R.; Xu, H.-Y.; Xiong, Y.-H.; Liu, K.; Jin, Y.; Lai, W.-H. Advantages of fluorescent microspheres compared with colloidal gold as a label in immunochromatographic lateral flow assays. Biosens. Bioelectron. 2014, 54, 262–265. [Google Scholar] [CrossRef] [PubMed]
  66. Lipman, N.S.; Jackson, L.R.; Trudel, L.J.; Weis-Garcia, F. Monoclonal versus polyclonal antibodies: Distinguishing characteristics, applications, and information resources. ILAR J. 2005, 46, 258–268. [Google Scholar] [CrossRef] [Green Version]
  67. Innova Biosciences. Guide to Lateral Flow Immunoassays; Innova Biosciences: Cambrige, UK, 2017; pp. 1–16. Available online: https://fnkprddata.blob.core.windows.net/domestic/download/pdf/IBS_A_guide_to_lateral_flow_immunoassays.pdf (accessed on 5 February 2021).
  68. Zhang, X.; Wu, C.; Wen, K.; Jiang, H.; Shena, J.; Zhang, S.; Wanga, Z. Comparison of fluorescent microspheres and colloidal gold as labels in lateral flow immunochromatographic assays for the detection of T-2 toxin. Molecules 2016, 21, 27. [Google Scholar] [CrossRef] [PubMed]
  69. Cai, Y.; Kang, K.; Li, Q.; Wang, Y.; He, X. Rapid and sensitive detection of cardiac troponin I for point-of-care tests based on red fluorescent microspheres. Molecules 2018, 23, 1102. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Zhou, G.; Mao, X.; Juncker, D. Immunochromatographic assay on thread. Anal. Chem. 2012, 84, 7736–7743. [Google Scholar] [CrossRef] [PubMed]
  71. Ching, K.H. Lateral flow immunoassay. In ELISA; Springer: Berlin/Heidelberg, Germany, 2015; pp. 127–137. [Google Scholar]
  72. Anfossi, L.; Giovannoli, C.; Giraudi, G.; Biagioli, F.; Passini, C.; Baggiani, C. A lateral flow immunoassay for the rapid detection of Ochratoxin a in wine and grape must. J. Agric. Food Chem. 2012, 60, 11491–11497. [Google Scholar] [CrossRef]
  73. Clayton, K.N. Comparing Anti-VEGF Antibodies and Aptamers on Paper Microfluidic-based Platforms. Master Thesis, California Polytechnic State University, San Luis Obispo, CA, USA, June 2012. [Google Scholar]
  74. Gupta, R.; Gupta, S. Lateral Flow Immunoassay for Detecting Vitamins. U.S. Patent Application NO. 14/007,006, 28 December 2014. [Google Scholar]
  75. Petruno, P.T.; Petrilla, J.F.; Brosnan, M.J.; Zhou, R.; Roitman, D.B. Lateral Flow Assay Systems and Methods. U.S. Patent 8,128,871, 6 March 2012. [Google Scholar]
  76. Hu, Q.; Wei, Q.; Zhang, P.; Li, S.; Xue, L.; Yang, R.-F.; Wang, C.; Zhou, L. An up-converting phosphor technology-based lateral flow assay for point-of-collection detection of morphine and methamphetamine in saliva. Analyst 2018, 143, 4646–4654. [Google Scholar] [CrossRef]
  77. Petrakova, A.V.; Urusov, A.E.; Zherdev, A.V.; Dzantiev, B.B. Gold nanoparticles of different shape for bicolor lateral flow test. Anal. Biochem. 2019, 568, 7–13. [Google Scholar] [CrossRef]
  78. Scherer, J.N.; Fiorentin, T.R.; Borille, B.T.; Pasa, G.; Sousa, T.R.V.; Von Diemen, L.; Limberger, R.P.; Pechansky, F. Reliability of point-of-collection testing devices for drugs of abuse in oral fluid: A systematic review and meta-analysis. J. Pharm. Biomed. Anal. 2017, 143, 77–85. [Google Scholar] [CrossRef]
  79. Plouffe, B.D.; Murthy, S.K. Fluorescence-based lateral flow assays for rapid oral fluid roadside detection of cannabis use. Electrophoresis 2017, 38, 501–506. [Google Scholar] [CrossRef]
  80. Market, F.C. Lateral flow immunoassay systems: Evolution from the current state of the art to the next generation of highly sensitive, quantitative rapid assays. Immunoass. Handb. 2013, 89, 89–107. [Google Scholar]
  81. Bristow, C.C.; Severe, L.; Pape, J.W.; Javanbakht, M.; Lee, S.-J.; Comulada, W.S.; Klausner, J.D. Dual rapid lateral flow immunoassay fingerstick wholeblood testing for syphilis and HIV infections is acceptable and accurate, Port-au-Prince, Haiti. BMC Infect. Dis. 2016, 16, 302. [Google Scholar] [CrossRef] [Green Version]
  82. Machiesky, L.; Côté, O.; Kirkegaard, L.H.; Mefferd, S.C.; Larkin, C. A rapid lateral flow immunoassay for identity testing of biotherapeutics. J. Immunol. Methods 2019, 474, 112666. [Google Scholar] [CrossRef]
  83. Zangheri, M.; Di Nardo, F.; Mirasoli, M.; Anfossi, L.; Nascetti, A.; Caputo, D.; De Cesare, G.; Guardigli, M.; Baggiani, C.; Roda, A. Chemiluminescence lateral flow immunoassay cartridge with integrated amorphous silicon photosensors array for human serum albumin detection in urine samples. Anal. Bioanal. Chem. 2016, 408, 8869–8879. [Google Scholar] [CrossRef] [Green Version]
  84. Creative Diagnostics. Common Formats of Lateral Flow Tests. 2020. Available online: https://www.cd-diatest.com/common-formats-of-lateral-flow-tests_d27 (accessed on 17 September 2020).
  85. Anfossi, L.; Di Nardo, F.; Cavalera, S.; Giovannoli, C.; Baggiani, C. Multiplex lateral flow immunoassay: An overview of strategies towards high-throughput point-of-need testing. Biosensors 2018, 9, 2. [Google Scholar] [CrossRef] [Green Version]
  86. Wu, Y.; Zhao, Y.; Leng, Y.; Lai, W.; Huang, X.; Xiong, Y. Emerging design strategies for constructing multiplex lateral flow test strip sensors. Biosens. Bioelectron. 2020, 157, 112168. [Google Scholar] [CrossRef] [PubMed]
  87. Poonlapdecha, W.; Seetang-Nun, Y.; Wonglumsom, W.; Tuitemwong, K.; Erickson, L.E.; Hansen, R.R.; Tuitemwong, P. Antibody-conjugated ferromagnetic nanoparticles with lateral flow test strip assay for rapid detection of Campylobacter jejuni in poultry samples. Int. J. Food Microbiol. 2018, 286, 6–14. [Google Scholar] [CrossRef] [PubMed]
  88. Blencowe, T.; Pehrsson, A.; Lillsunde, P.; Vimpari, K.; Houwing, S.; Smink, B.; Mathijssen, R.; Van Der Linden, T.; Legrand, S.-A.; Pil, K.; et al. An analytical evaluation of eight on-site oral fluid drug screening devices using laboratory confirmation results from oral fluid. Forensic Sci. Int. 2011, 208, 173–179. [Google Scholar] [CrossRef] [PubMed]
  89. Dahanayaka, N.J.; Warnasekara, J.; Rajapakse, R.M.S.R.; Ranathunga, S.Y.K.; Agampodi, S.B. Validity of lateral flow immunochromatographic-assays (LFIA) in diagnosis of leptospirosis. Ceylon Med. J. 2017, 62, 248–249. [Google Scholar] [CrossRef]
  90. Safavieh, M.; Ahmed, M.U.; Sokullu, E.; Ng, A.; Braescu, L.; Zourob, M. A simple cassette as point-of-care diagnostic device for naked-eye colorimetric bacteria detection. Analyst 2014, 139, 482–487. [Google Scholar] [CrossRef] [PubMed]
  91. Karakus, C.; Salih, B.A. Comparison of the lateral flow immunoassays (LFIA) for the diagnosis of Helicobacter pylori infection. J. Immunol. Methods 2013, 396, 8–14. [Google Scholar] [CrossRef]
  92. Lindsley, M.D.; Mekha, N.; Baggett, H.C.; Surinthong, Y.; Autthateinchai, R.; Sawatwong, P.; Harris, J.R.; Park, B.J.; Chiller, T.; Balajee, S.A.; et al. Evaluation of a newly developed lateral flow immunoassay for the diagnosis of cryptococcosis. Clin. Infect. Dis. 2011, 53, 321–325. [Google Scholar] [CrossRef] [Green Version]
  93. Shan, S.; Lai, W.; Xiong, Y.; Weihua, L.; Xu, H. Novel strategies to enhance lateral flow immunoassay sensitivity for detecting foodborne pathogens. J. Agric. Food Chem. 2015, 63, 745–753. [Google Scholar] [CrossRef] [PubMed]
  94. Kolosova, A.Y.; De Saeger, S.; Liberty, S.; Verheijen, R.; Van Peteghem, C. Development of a colloidal gold-based lateral-flow immunoassay for the rapid simultaneous detection of zearalenone and deoxynivalenol. Anal. Bioanal. Chem. 2007, 389, 2103–2107. [Google Scholar] [CrossRef]
  95. Nara, S.; Tripathi, V.; Singh, H.; Shrivastav, T.G. Colloidal gold probe based rapid immunochromatographic strip assay for cortisol. Anal. Chim. Acta 2010, 682, 66–71. [Google Scholar] [CrossRef]
  96. Wu, J.; Dong, M.; Zhang, C.; Wang, Y.; Xie, M.; Chen, Y. Magnetic lateral flow strip for the detection of cocaine in urine by naked eyes and smart phone camera. Sensors 2017, 17, 1286. [Google Scholar] [CrossRef] [Green Version]
  97. Teerinen, T.; Lappalainen, T.; Erho, T. A paper-based lateral flow assay for morphine. Anal. Bioanal. Chem. 2014, 406, 5955–5965. [Google Scholar] [CrossRef] [PubMed]
  98. Angelini, D.J.; Biggs, T.D.; Maughan, M.N.; Feasel, M.G.; Sisco, E.; Sekowski, J.W. Evaluation of a lateral flow immunoassay for the detection of the synthetic opioid fentanyl. Forensic Sci. Int. 2019, 300, 75–81. [Google Scholar] [CrossRef]
  99. Hudson, M.; Stuchinskaya, T.; Ramma, S.; Patel, J.; Sievers, C.; Goetz, S.; Hines, S.; Menzies, E.; Russell, D.A. Drug screening using the sweat of a fingerprint: Lateral flow detection of Δ9-tetrahydrocannabinol, cocaine, opiates and amphetamine. J. Anal. Toxicol. 2019, 43, 88–95. [Google Scholar] [CrossRef]
  100. Li, Z.; Chen, H.; Feng, S.; Liu, K.; Wang, P. Development and clinical validation of a sensitive lateral flow assay for rapid urine fentanyl screening in the emergency department. Clin. Chem. 2020, 66, 324–332. [Google Scholar] [CrossRef]
  101. Liu, J.; Hu, X.; Cao, F.; Zhang, Y.; Lu, J.; Zeng, L. A lateral flow strip based on gold nanoparticles to detect 6-monoacetylmorphine in oral fluid. R. Soc. Open Sci. 2018, 5, 180288. [Google Scholar] [CrossRef]
  102. Toubou, H.; Namera, A.; Arima, Y.; Uchida, Y.; Torikoshi, A.; Moriya, F.; Nagao, M. Detection of abused drugs in human blood by using the on-site drug-screening device Oratect® III. Leg. Med. 2014, 16, 308–313. [Google Scholar] [CrossRef]
  103. Chen, W.; Li, X.-N.; Wu, Q.; Yao, L.; Xu, J. Rapid and easy determination of morphine in chafing dish condiments with colloidal gold labeling based lateral flow strips. Food Sci. Hum. Wellness 2019, 8, 40–45. [Google Scholar] [CrossRef]
  104. Smith, J.E.; Chávez, J.L.; Hagen, J.A.; Kelley-Loughnane, N. Design and development of aptamer–gold nanoparticle based colorimetric assays for in-the-field applications. JoVE 2016, 112, e54063. [Google Scholar]
  105. Mousivand, M.; Anfossi, L.; Bagherzadeh, K.; Barbero, N.; Mirzadi-Gohari, A.; Javan-Nikkhah, M. In silico maturation of affinity and selectivity of DNA aptamers against aflatoxin B1 for biosensor development. Anal. Chim. Acta 2020, 1105, 178–186. [Google Scholar] [CrossRef]
  106. Eissa, S.; Zourob, M. In vitro selection of DNA aptamers targeting β-lactoglobulin and their integration in graphene-based biosensor for the detection of milk allergen. Biosens. Bioelectron. 2017, 91, 169–174. [Google Scholar] [CrossRef] [PubMed]
  107. Elshafey, R.; Siaj, M.; Zourob, M. DNA aptamers selection and characterization for development of label-free impedimetric aptasensor for neurotoxin anatoxin-a. Biosens. Bioelectron. 2015, 68, 295–302. [Google Scholar] [CrossRef] [PubMed]
  108. Mansouri, A.; Abnous, K.; Nabavinia, M.S.; Ramezani, M.; Taghdisi, S.M. In vitro selection of tacrolimus binding aptamer by systematic evolution of ligands by exponential enrichment method for the development of a fluorescent aptasensor for sensitive detection of tacrolimus. J. Pharm. Biomed. Anal. 2020, 177, 112853. [Google Scholar] [CrossRef] [PubMed]
  109. Zargar, T.; Khayamian, T.; Jafari, M.T. Immobilized aptamer paper spray ionization source for ion mobility spectrometry. J. Pharm. Biomed. Anal. 2017, 132, 232–237. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  110. Najafabadi, M.E.; Khayamian, T.; Hashemian, Z. Aptamer-conjugated magnetic nanoparticles for extraction of adenosine from urine followed by electrospray ion mobility spectrometry. J. Pharm. Biomed. Anal. 2015, 107, 244–250. [Google Scholar] [CrossRef]
  111. Kang, K.; Sachan, A.; Nilsen-Hamilton, M.; Shrotriya, P. Aptamer functionalized microcantilever sensors for cocaine detection. Langmuir 2011, 27, 14696–14702. [Google Scholar] [CrossRef] [Green Version]
  112. Guler, E.; Bozokalfa, G.; Demir, B.; Gumus, Z.P.; Guler, B.; Aldemir, E.; Timur, S.; Coskunol, H. An aptamer folding-based sensory platform decorated with nanoparticles for simple cocaine testing. Drug Test. Anal. 2016, 9, 578–587. [Google Scholar] [CrossRef] [PubMed]
  113. Shi, Q.; Shi, Y.; Pan, Y.; Yue, Z.; Zhang, H.; Yi, C. Colorimetric and bare eye determination of urinary methylamphetamine based on the use of aptamers and the salt-induced aggregation of unmodified gold nanoparticles. Microchim. Acta 2014, 182, 505–511. [Google Scholar] [CrossRef]
  114. Zhao, Q.; Wu, M.; Le, X.C.; Li, X.-F. Applications of aptamer affinity chromatography. TrAC Trends Anal. Chem. 2012, 41, 46–57. [Google Scholar] [CrossRef]
  115. Du, F.; Alam, N.; Pawliszyn, J. Aptamer-functionalized solid phase microextraction–liquid chromatography/tandem mass spectrometry for selective enrichment and determination of thrombin. Anal. Chim. Acta 2014, 845, 45–52. [Google Scholar] [CrossRef] [PubMed]
  116. Lin, S.; Gan, N.; Cao, Y.; Chen, Y.; Jiang, Q. Selective dispersive solid phase extraction-chromatography tandem mass spectrometry based on aptamer-functionalized UiO-66-NH2 for determination of polychlorinated biphenyls. J. Chromatogr. A 2016, 1446, 34–40. [Google Scholar] [CrossRef] [PubMed]
  117. Yuan, Q.; Lu, D.; Zhang, X.; Chen, Z.; Tan, W. Aptamer-conjugated optical nanomaterials for bioanalysis. TrAC Trends Anal. Chem. 2012, 39, 72–86. [Google Scholar] [CrossRef]
  118. Song, K.-M.; Cho, M.; Jo, H.; Min, K.; Jeon, S.H.; Kim, T.; Han, M.S.; Ku, J.K.; Ban, C. Gold nanoparticle-based colorimetric detection of kanamycin using a DNA aptamer. Anal. Biochem. 2011, 415, 175–181. [Google Scholar] [CrossRef]
  119. Shin, S.; Kim, I.-H.; Kang, W.; Yang, J.K.; Hah, S.S. An alternative to Western blot analysis using RNA aptamer-functionalized quantum dots. Bioorganic Med. Chem. Lett. 2010, 20, 3322–3325. [Google Scholar] [CrossRef]
  120. Vinkenborg, J.L.; Mayer, G.; Famulok, M. Aptamer-based affinity labeling of proteins. Angew. Chem. Int. Ed. 2012, 51, 9176–9180. [Google Scholar] [CrossRef]
  121. Cho, S.-J.; Woo, H.-M.; Kim, K.-S.; Oh, J.-W.; Jeong, Y.-J. Novel system for detecting SARS coronavirus nucleocapsid protein using an ssDNA aptamer. J. Biosci. Bioeng. 2011, 112, 535–540. [Google Scholar] [CrossRef] [PubMed]
  122. Yu, Q.; Zhao, Q.; Wang, S.; Zhao, S.; Zhang, S.; Yin, Y.; Dong, Y. Development of a lateral flow aptamer assay strip for facile identification of theranostic exosomes isolated from human lung carcinoma cells. Anal. Biochem. 2020, 594, 113591. [Google Scholar] [CrossRef]
  123. Dalirirad, S.; Steckl, A.J. Lateral flow assay using aptamer-based sensing for on-site detection of dopamine in urine. Anal. Biochem. 2020, 596, 113637. [Google Scholar] [CrossRef] [PubMed]
  124. Tripathi, P.; Kumar, A.; Sachan, M.; Gupta, S.; Nara, S. Aptamer-gold nanozyme based competitive lateral flow assay for rapid detection of CA125 in human serum. Biosens. Bioelectron. 2020, 165, 112368. [Google Scholar] [CrossRef]
  125. Neff, C.P.; Zhou, J.; Remling, L.; Kuruvilla, J.; Zhang, J.; Li, H.; Smith, D.D.; Swiderski, P.; Rossi, J.J.; Akkina, R. An aptamer-siRNA chimera suppresses HIV-1 viral loads and protects from helper CD4+ T cell decline in humanized mice. Sci. Transl. Med. 2011, 3, 66ra6. [Google Scholar] [CrossRef] [Green Version]
  126. Zhou, J.; Satheesan, S.; Li, H.; Weinberg, M.S.; Morris, K.V.; Burnett, J.C.; Rossi, J.J. Cell-specific RNA aptamer against human CCR5 specifically targets HIV-1 susceptible cells and inhibits HIV-1 infectivity. Chem. Biol. 2015, 22, 379–390. [Google Scholar] [CrossRef] [Green Version]
  127. Zhou, J.; Rossi, J.J. Therapeutic potential of aptamer-siRNA conjugates for treatment of HIV-1. BioDrugs 2012, 26, 393–400. [Google Scholar] [CrossRef] [PubMed]
  128. Wu, Y.; Sefah, K.; Liu, H.; Wang, R.; Tan, W. DNA aptamer-micelle as an efficient detection/delivery vehicle toward cancer cells. Proc. Natl. Acad. Sci. USA 2009, 107, 5–10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  129. Zhu, G.; Zheng, J.; Song, E.; Donovan, M.; Zhang, K.; Liu, C.; Tan, W. Self-assembled, aptamer-tethered DNA nanotrains for targeted transport of molecular drugs in cancer theranostics. Proc. Natl. Acad. Sci. USA 2013, 110, 7998–8003. [Google Scholar] [CrossRef] [Green Version]
  130. Xu, W.; Siddiqui, I.A.; Nihal, M.; Pilla, S.; Rosenthal, K.; Mukhtar, H.; Gong, S. Aptamer-conjugated and doxorubicin-loaded unimolecular micelles for targeted therapy of prostate cancer. Biomater. 2013, 34, 5244–5253. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  131. Mills, M.G.L.; Broomhall, L.S.; du Toit, J.T. Molecular aptamers for drug delivery. Trends Biotechnol. 2011, 29, 634–640. [Google Scholar]
  132. Zueva, E.; Rubio, L.I.; Ducongé, F.; Tavitian, B. Metastasis-focused cell-based SELEX generates aptamers inhibiting cell migration and invasion. Int. J. Cancer 2010, 128, 797–804. [Google Scholar] [CrossRef] [PubMed]
  133. Mercier, M.-C.; Dontenwill, M.; Choulier, L. Selection of nucleic acid aptamers targeting tumor cell-surface protein biomarkers. Cancers 2017, 9, 69. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  134. Scaggiante, B.; Dapas, B.; Farra, R.; Grassi, M.; Pozzato, G.; Giansante, C.; Fiotti, N.; Tamai, E.; Tonon, F.; Grassi, G. Aptamers as targeting delivery devices or anti-cancer drugs for fighting tumors. Curr. Drug Metab. 2013, 14, 565–582. [Google Scholar] [CrossRef] [PubMed]
  135. Wang, L.; Li, P.; Xiao, X.; Li, J.; Li, J.; Yang, H.; Tan, W. Generating lung-metastatic osteosarcoma targeting aptamers for in vivo and clinical tissue imaging. Talanta 2018, 188, 66–73. [Google Scholar] [CrossRef]
  136. Hu, X.; Tulsieram, K.L.; Zhou, Q.; Mu, L.; Wen, J. Polymeric nanoparticle–aptamer bioconjugates can diminish the toxicity of mercury in vivo. Toxicol. Lett. 2012, 208, 69–74. [Google Scholar] [CrossRef]
  137. Emrani, A.S.; Danesh, N.M.; Ramezani, M.; Taghdisi, S.M.; Abnous, K. A novel fluorescent aptasensor based on hairpin structure of complementary strand of aptamer and nanoparticles as a signal amplification approach for ultrasensitive detection of cocaine. Biosens. Bioelectron. 2016, 79, 288–293. [Google Scholar] [CrossRef]
  138. Shahdost-Fard, F.; Roushani, M. Conformation switching of an aptamer based on cocaine enhancement on a surface of modified GCE. Talanta 2016, 154, 7–14. [Google Scholar] [CrossRef]
  139. Wang, L.; Ma, W.; Chen, W.; Liu, L.; Ma, W.; Zhu, Y.; Xu, L.; Kuang, H.; Xu, C. An aptamer-based chromatographic strip assay for sensitive toxin semi-quantitative detection. Biosens. Bioelectron. 2011, 26, 3059–3062. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Molecular structure of morphine [36].
Figure 1. Molecular structure of morphine [36].
Molecules 26 01058 g001
Scheme 1. Schematic representation of phage display process. It consists of cycles, each including: incubation of the antibody (Ab) repertoire and the target, washing of nonspecific binders, elution, and amplification of specific binders for further cycle or for screening [40].
Scheme 1. Schematic representation of phage display process. It consists of cycles, each including: incubation of the antibody (Ab) repertoire and the target, washing of nonspecific binders, elution, and amplification of specific binders for further cycle or for screening [40].
Molecules 26 01058 sch001
Scheme 2. A schematic diagram showing the production of monoclonal antibodies (mAbs).
Scheme 2. A schematic diagram showing the production of monoclonal antibodies (mAbs).
Molecules 26 01058 sch002
Figure 2. Schematic representation of a typical lateral flow assay (LFA) that is composed of four types of membrane.
Figure 2. Schematic representation of a typical lateral flow assay (LFA) that is composed of four types of membrane.
Molecules 26 01058 g002
Scheme 3. Classification of LFA according to the element of revelation.
Scheme 3. Classification of LFA according to the element of revelation.
Molecules 26 01058 sch003
Table 1. Probable results for each test (lateral flow immunoassay, LFIA).
Table 1. Probable results for each test (lateral flow immunoassay, LFIA).
Test ResultsDOA ConsumptionTotal (n)
ConsumerNon-Consumer
Positive (P)TPFPTotal P tests
Negative (N)FNTNTotal N tests
Total of consumersTotal of non-consumerstotal numbers
True positives (TP) are the set of consumer subjects with a positive test result. True negatives (TN) are the set of non-consumer subjects with negative test result. False positives (FP) are those subjects who are not consumers, but their test result is positive. False negatives (FN) are subjects who are consumers, but their test result is negative.
Table 2. LFIA methods for the determination of drugs of abuse (DOA) in biological samples that have been reported in the literature (from 2010 to 2020).
Table 2. LFIA methods for the determination of drugs of abuse (DOA) in biological samples that have been reported in the literature (from 2010 to 2020).
ReferenceMolecules Detected (Analytes)LOD (ng/mL)Confirmatory MethodsUsed SampleMolecules of Revelation (Labels)
[43]MOP2000TLC *UrineGNPs
[96]COC5ELISA **MB
[61]MOP0.60Not givenMNP
MET3
[76]MOP20LC-MS ***SalivaUp-converting phosphor technology
MET25
[97]MOP1Not givenGNPs
[79]THC0.01Fluorescent and Gold Particle
[57]THC1–10UPLC-MS/MS ****Not given
1–5Serum
[98]OPI100Not givenSaliva
8Urine
[20]BZDs (Diazepam)Not givenPBSGNPs
[96]COC5ELISAUrineMagnetic bead
[99]THC0.19LC–MS-MSSweatNot given
BZD0.09
MOP0.068
AMP0.08
[100]Fentanyl (FTY)1LC-MS/MSUrineGNPs
[101]6-monoacetylmorphine4UPLCSalivaGNPs
[102]MET125LC-MSBloodGNPs
AMP125
MOP50
COD50
Dihydrocodeine50
Diazepam25
Alprazolam60
Estazolam15
Prazepam75
[103]MOP0.1Not givenChafing dish condimentsGNPs
LOD: Limit of detection. * TLC: Thin-layer chromatography. ** ELISA: enzyme-linked immunosorbent assay. *** LC-MS: Liquid chromatography tandem mass spectrometry. **** UPLC-MS/MS: Ultra performance liquid chromatography-tandem mass spectrometer.
Table 3. Some nucleic acids LFA methods for the determination of DOA in biological samples that have been reported in the literature.
Table 3. Some nucleic acids LFA methods for the determination of DOA in biological samples that have been reported in the literature.
ReferencesMolecules DetectedLODUsed SampleConfirmatory MethodsAptamer Used
[113]AMP or MET0.82 μMUrineNot given5′-ACG GTT GCA AGT GGG ACT CTG GTA GGC TGG GTT AAT TTG G-3′
[112]COC0.138 nMArtificial urineHPLC5′-C6-NH2-AGACAAGGAAAATCCTTCAATGAAGTGGGTCGSH2-C3-3′
BE1.66 μM
[55]725.27 ± 3.17 ng/mL5′-C6-NH2-AGACAAGGAAAATCCTTCAATGAAGTGGGTCG-SH2-3′
741 ± 1.28 ng/mLSynthetic Saliva
[111]COC5 ± 8.9 μM (1.5 ± 2.7 μg/mL)AcetonitrileNot given5′-GGGA GAC AAG GAA AAT CCT TCA ATG AAG TGG GTC GACA-3′
5′-GAC AAG GAA AAT CCT TCA ATG AAG TGG GTC-3′
[137]293 pMRat serumNot given5′-CCATAGGGAGACAAGGATAAATCCTTCAATGAAGTGGGTCTCCC-Thiol-3′
5′-FAM ATTGAAGGATTTATCCTT
GTCTCCCTATGCTTCAAT-Biotin-3′
[138]5.0 ± 0.1 pmol/LHuman blood serumNot given5′-C6-NH2-AGACAAGG AAAATCCTTCAATGAAGTGGGTCG-SH2-3′
[139]OTA1 ng/mLRed winesELISA5′-GAT CGG GTG TGG GTG GCG TAA AGG GAG CAT CGG ACA AAA AAA AAA AAA AAA AAA-SH-3′
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Qriouet, Z.; Cherrah, Y.; Sefrioui, H.; Qmichou, Z. Monoclonal Antibodies Application in Lateral Flow Immunochromatographic Assays for Drugs of Abuse Detection. Molecules 2021, 26, 1058. https://doi.org/10.3390/molecules26041058

AMA Style

Qriouet Z, Cherrah Y, Sefrioui H, Qmichou Z. Monoclonal Antibodies Application in Lateral Flow Immunochromatographic Assays for Drugs of Abuse Detection. Molecules. 2021; 26(4):1058. https://doi.org/10.3390/molecules26041058

Chicago/Turabian Style

Qriouet, Zidane, Yahia Cherrah, Hassan Sefrioui, and Zineb Qmichou. 2021. "Monoclonal Antibodies Application in Lateral Flow Immunochromatographic Assays for Drugs of Abuse Detection" Molecules 26, no. 4: 1058. https://doi.org/10.3390/molecules26041058

APA Style

Qriouet, Z., Cherrah, Y., Sefrioui, H., & Qmichou, Z. (2021). Monoclonal Antibodies Application in Lateral Flow Immunochromatographic Assays for Drugs of Abuse Detection. Molecules, 26(4), 1058. https://doi.org/10.3390/molecules26041058

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