LC-MS application for therapeutic drug monitoring in alternative matrices

Journal of Pharmaceutical and Biomedical Analysis 166 (2019) 40–51

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Journal of Pharmaceutical and Biomedical Analysis journal homepage: www.elsevier.com/locate/jpba

LC-MS application for therapeutic drug monitoring in alternative matrices Valeria Avataneo a,1 , Antonio D’Avolio a,∗,1 , Jessica Cusato a , Marco Cantù b , Amedeo De Nicolò a a b

Laboratory of Clinical Pharmacology and Pharmacogenetics, University of Turin, Department of Medical Sciences, Amedeo di Savoia Hospital, Turin, Italy2 Laboratory of Clinical Biochemistry and Pharmacology, Department of Laboratory Medicine EOLAB, Ente Ospedaliero Cantonale, Bellinzona, Switzerland

a r t i c l e

i n f o

Article history: Received 2 August 2018 Received in revised form 24 December 2018 Accepted 26 December 2018 Available online 29 December 2018 Keywords: Therapeutic drug monitoring Liquid chromatography Mass spectrometry LC-MS Alternative matrices Alternative sampling Dried blood spots Capillary microsampling Dried plasma spots Volumetric absorptive microsampling Urine Saliva Cerebro spinal fluid Hair Peripheral blood mononuclear cells Tissue biopsies Sweat Tears Breast milk Microdialysis

a b s t r a c t Nowadays the practice of therapeutic drug monitoring, consisting in the measurement of drugs concentrations in biological matrices in order to guide possible posological adjustments, is becoming more and more important for the management and optimization of several treatments, especially when drugs with narrow therapeutic indexes are administered. Although TDM on plasma samples is currently considered the gold standard, this practice shows some limitations: it requires venous blood sampling, centrifugation and, if necessary, shipment with refrigeration; moreover, drug concentrations in plasma or blood do not necessarily reflect the ones in the target tissues or cells. Therefore, in the recent years great attention has been given to alternative matrices for TDM purpose, in order to reduce invasiveness, costs or to obtain better information about drug concentrations at the active sites. This evolution is strongly sustained by the spreading use of liquid chromatography coupled with mass spectrometry (LC–MS) techniques for the analysis of small molecules, which is constantly increasing sensitivity and specificity of TDM assays. In this review, we present and summarize recently published LC–MS applications providing alternatives to plasma testing, in order to avoid blood withdrawal, plasma separation, refrigerated shipment or, if possible, to obtain better information about drug exposure in target cells. By analyzing the last 5 years of literature, reported in PubMed website, LC–MS/MS applications have been reported, with particular focus on the ones with higher probability to enter in the near future in clinical practice. Microsampling strategies and alternative biological matrices, from urine to tissue samples, have been included. © 2018 Elsevier B.V. All rights reserved.

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.1. Microsampling strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.1.1. Dried blood spots (DBS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.1.2. Capillary microsampling (CMS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

∗ Corresponding Author at: “Amedeo di Savoia” Hospital, C.so Svizzera 164, Torino 10149, Italy. E-mail address: [email protected] (A. D’Avolio). 1 Both authors equally contributed to this work. 2 PHASE I AIFA, UNI EN ISO 9001:2008 and 13485:2012 Certificate Laboratory; Certificate No. IT-64386 and DM/17/154/S; Certification for: “DESIGN, DEVELOPMENT AND APPLICATION OF DETERMINATION METHODS FOR ANTI-INFECTIVE DRUGS. PHARMACOGENETIC ANALYSES.” and “DESIGN AND PRODUCTION OF DIAGNOSTIC MEDICAL DEVICES IN VITRO” www.tdm-torino.org https://doi.org/10.1016/j.jpba.2018.12.040 0731-7085/© 2018 Elsevier B.V. All rights reserved.

V. Avataneo et al. / Journal of Pharmaceutical and Biomedical Analysis 166 (2019) 40–51

4.

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3.1.3. Dried plasma spots (DPS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.1.4. Volumetric absorptive microsampling (VAMS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.2. Alternative matrices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.2.1. Urine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.2.2. Saliva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.2.3. Cerebro spinal fluid (CSF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.2.4. Hair . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.2.5. Peripheral blood mononuclear cells (PBMC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.2.6. Tissue biopsies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.7. Sweat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.8. Tears . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.9. Breast milk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.10. Microdialysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Discussion and conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

1. Introduction In the recent years the interest in the concept of “personalized” or “precision” medicine has become more and more consistent in the scientific community, with a substantial increase in the number of pharmacogenetic and pharmacokinetic studies [1,2]. In this context, the practice of therapeutic drug monitoring (TDM) is gradually increasing over time and widening its application [2]. TDM consists in the quantification of drugs concentrations in biological matrices, in order to compare them with known therapeutic ranges, deriving from pharmacokinetic/pharmacodynamic studies: this allows to optimize the posology, avoiding concentration-dependent toxic effects and/or therapeutic failure due to underexposure to therapeutic drugs. TDM is routine practice for several therapies [3–9], such as immunosuppressive, antifungal, antibiotic, antiviral, anticonvulsants, antiarrhythmics and antipsychotic drugs. The current standard matrices for TDM are commonly liquid plasma or whole blood, and the vast majority of scientific studies prefers plasma as reference standard for the identification of therapeutic ranges because it is easier to deal with, if compared to whole blood; nevertheless also other matrices are now being considered because of a less invasive sampling, less expensive analysis or more reliable correlation with therapeutic effects. In fact, liquid plasma or blood samples are sometimes difficult to be obtained, such as in pediatrics or in critically ill patients; moreover the shipment costs are often too high to allow a widespread use of TDM. On the other hand, plasma or blood concentrations could sometimes not accurately mirror the drug concentrations at the active site (eg. pharmacological sanctuaries), thus creating a bias between analytical results and clinical outcome. Therefore, these two critical needs for less invasive and cheaper sampling and more reliable TDM results can be fulfilled with different approaches: in the first case, microsampling strategies or “simpler-to-achieve” matrices can be used, while more reliable results can be achieved through the choice of more specific biological matrices (nearer to the target site). Nevertheless, the adoption of microsampling, as well as the TDM in difficult to obtain matrices, is characterized by very low sample volumes or low expected concentrations, consequently these approaches require higher sensitivity than TDM in liquid plasma or whole blood. Considering this scenario, liquid chromatography coupled to mass spectrometry (LC–MS) has to be considered a gold standard for these kinds of applications, due to its high performance in terms of analytical sensitivity and specificity. For this reason, LC–MS is

now representing the leading force supporting a wider use of alternative matrices [10]. Therefore, the aim of this review is summarizing recent insights on LC–MS applications of TDM in alternative matrices, with particular focus on innovative applications which will most probably become routine in the near future and a critical view on current challenges and limitations related to their use. 2. Methods PubMed database has been checked with the following research entry: [LC–MS] AND [therapeutic drug monitoring] AND (([matrices] OR [CSF] OR [urine] OR [saliva] OR [tissue] OR [cell lysate] OR [PBMC] OR [dried blood spot] OR [dried plasma spot] OR [VAMS] OR [capillary microsampling] OR [sweat] OR [tears] OR [Breast Milk] OR [Microdialysis])). Articles were filtered for publication in the last five years, with particular priority for application on human patients in clinical contexts. 3. Results Several alternatives to TDM analysis on liquid plasma or blood will be described in this section. Generally, these different strategies are based on: a) devices able to collect low sample (primary plasma or blood) volumes; b) the use of alternative biological matrices (no plasma and no blood) either to facilitate the sampling or to obtain better information about drug concentrations at the target site. 3.1. Microsampling strategies These are techniques to avoid the invasive withdrawal and/or expensive shipment of liquid plasma or blood, minimizing the sample volume needed for the analysis [11]. There are several different approaches for microsampling, each one characterized by particular advantages and disadvantages (Table 1). 3.1.1. Dried blood spots (DBS) For blood collection purpose, a practical alternative to venous withdrawal is the Dried Blood Spots (DBS) technology. Briefly, in order to obtain DBS, the patient pricks his finger with a lancet and collects a drop of blood on a specific card. The disinfection before pricking and discarding the first drop are both described as important steps in order to limit contaminations (eg. by bacteria, disinfectant or interstitial fluid). Then, DBS have to be dried

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Table 1 Overview of the quali-quantitative performances of the different microsampling techniques, together with their actual (or potential) automation. Quantitative information is considered as accordance with plasma, absence of hematocrit effect and reproducibility of sampling volumes. Qualitative performance was intended as the combination of good qualitative sensitivity (low LOD) and high analytical specificity. DBS

DPS

VAMS

Capillary Microsampling

Quantitative Qualitative Automation Quantitative Qualitative Automation Quantitative Qualitative Automation Quantitative Qualitative Automation LC-MS LC-MS/MS Q-TOF Trap Shipment Storage and Management Safety Drug Stability Convenience

••• ••• • ••

••••• ••• •••••

••• •••• ••••• ••••

•••• •••• •••• ••••

••••• ••••• •• •••

••• •••• ••••• ••••

••••• ••••• ••••

•• •• •• ••

•••• •••• •• •••

•••• •••• •••••

••• •••• ••••• ••••

••• ••• ••• •••

••••• ••••• •• •••

••• •••• ••••• ••••

• • • •

•• •• ••

Footnote: •=very low; ••=low; •••=medium; ••••=high; •••••=very high.

at ambient temperature and shipped to the laboratory for the analysis [12–15]. In order to obtain a precise volume of blood, a common technique is based on the cut of one or more fixed diameter sub-punches from each spot and their immersion in solvents to extract the drugs of interest [15,16]. The main advantage of DBS is the minimal invasiveness and the capability to allow home-made sampling; nevertheless, DBS can also be useful for hospitalized patients, because most analytes show higher stability on these dried supports. Moreover, their shipment results considerably cheaper and their storage more convenient if compared to liquid samples, that must be handled as “hazardous” and cooled during the whole transport through the laboratory [17]. Considering this, DBS appear a really attractive option for particular circumstances, such as for pediatric patients [18,19] and in developing countries, where the collection of plasma is not always feasible [20,21]. DBS have been used for the TDM of immunosuppressants [22,23], and many different methods have been published on antidepressants [24–26], anticonvulsants [27,28], antifungals [29], antibiotics/antitubercolars [30,31], antivirals [32,33] and oncologic [34,35] drugs. Recently some groups proposed the application of DBS for the low-invasiveness testing of therapeutic compliance to antihypertensive therapy [36]. Nevertheless, as reported by Kloosterboer et al., DBS are not always suitable to replace plasma sampling in a routine setting: in that study a suboptimal improvement after hematocrit correction was shown for pipamperone, thus impeding a full clinical validation of the DBS method [37]. In fact, some drawbacks associated with the use of DBS have been reported in several works [15–17,38]: the small sample volume (<50 ␮L) requires very sensitive analytical techniques, often achievable only through LC–MS; then, in some cases, the patients may not be able to successfully fill the DBS card by themselves, thus impeding home-made sampling; finally, since for most drugs the current therapeutic ranges have been studied on plasma samples, the clinical validation must comprehend experiments focused on the blood-to-plasma concentration ratio. Other potential bias come from the fact that DBS are obtained from capillary, instead of venous, blood and without anticoagulants that, conversely, are normally present in the matrix used for the preparation of calibrators and quality controls. Anyway, the main concern about DBS regards the effect of interindividual variability of hematocrit: this has an important effect on blood spreading, spot size and thickness variability and, as a consequence, possible non-homogeneity in the sub-punched disks [12,13,39,40]. Moreover, possible bias is expected for drugs which show an extensive binding to plasma proteins and poor penetration in red blood cells: in these cases the quantification of drugs in blood will lead to an underestimation of drugs concentrations if compared to the ones in plasma.

On the other hand, theoretically the opposite issue can be valid for drugs which accumulate in red blood cells, which could be overestimated. Considering all these issues, an extensive validation before clinical application is mandatory. In this context, some groups proposed alternative solutions to overcome some of these challenges [41]: for example, Youhnovski et al. suggested the adoption of pre-cut dried blood spots (PCDBS) supported by a strip of double-sided adhesive tape that must be entirely used in the extraction process, thus eliminating the sub-punching step but requiring the use of a standard pipette to apply about 10 ␮L of blood [42], while Li et al. chose ® the adoption of devices like Microsafe and Drummond pipettes to spot a reproducible volume of sample [43]. Finally, several mathematical strategies have been developed for “hematocrit correction”, specific for different applications, in order to limit its effect and to allow a comparison of analytical results obtained from blood specimens with therapeutic ranges, which are normally referred to plasma concentrations [44–46].

3.1.2. Capillary microsampling (CMS) After the initial enthusiasm for DBS, the emerging need to face the hematocrit effect and to collect precise microvolumes of blood led to the development of devices based on the association of capillary microsampling (CMS) and DBS. For example, Leuthold et al. engineered a microfluidic-based sampling procedure able to collect exact volumes of blood directly on the surface of a standard DBS, thus limiting the hematocrit effect without complicating the sample collection [47]. Nevertheless, in some cases, blood could not be the most appropriate matrix for TDM, so some efforts were done in order to engineer capillaries with key features focused to facilitate plasma isolation [48]: for example, an optimization of the Aqua-CapTM sample collection tube (Drummond Scientific Co., Inc.; PA, USA) included the addition of a porous plug that, after contact with blood for 30 s, swells and seals the end of the tube, enabling it to hold the maximum blood volume and to undergo centrifugation; then, as additional strategies to optimize these devices, the interior part of the capillary has been spray-coated of EDTA to ensure adequate mixing with blood. Upon centrifugation, a thixotropic gel located in the middle of the tube migrates within the capillary according to density, to form a stable barrier between the erythrocytes and plasma. The isolated plasma can be dispensed using a specific device that must be inserted into the capillary tube and allowed to contact the plug: in this way, the latter is pushed (acting like a capillary pipette) to allow the extrusion of plasma [48]. Nevertheless, even if promising, CMS never entered in the clinical routine, being now restricted to use for pharmacokinetic studies on mice or rats, in order to follow the 3R rule (reduce, refine and

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replace) and to limit the number of animals used for research purposes [49,50]. 3.1.3. Dried plasma spots (DPS) Considering the failure of CMS to enter the clinical practice, Dried Plasma Spots (DPS) have been developed with the purpose to avoid the hematocrit and to take advantage of some DBS benefits, obtaining results which are comparable with the available therapeutic ranges. DPS can be obtained in two alternative manners: the first strategy requires the centrifugation of blood in order to obtain plasma, that is then spotted on the card with a pipette; for this purpose, a wide variety of supports can be used. For example, D’Avolio et al. used the Dried Sample Spots Device (DSSD, glass fiber filters) on which 100 ␮L of plasma were spotted with a pipette and then the whole support underwent the extraction process in order to quantify nine anti-HIV drugs: this protocol was successfully applied in a limited resources setting in Burundi on a population of 307 patients, among which 14 were children [51,52]. On the other hand, Protti et al. employed Whatman FTATM DMPK-B IND cards, on which a total of 10 ␮L of plasma were spotted and then the whole spots were completely punched out before the extraction of oxycodone and its major metabolites [53]. The second strategy to prepare DPS is based on the adoption of special membrane filters able to remove red blood cells from the blood spot, thus allowing the collection of a plasma spot [54,55]; unfortunately, even if promising, this idea has never been systematically applied to the clinical routine, probably due to its current high costs. 3.1.4. Volumetric absorptive microsampling (VAMS) A novel technique with the potential to replace DBS for what concerns the low invasiveness and the capability to perform homemade sampling is called Volumetric Absorptive Microsampling (VAMS) and consists in the absorption of a liquid sample onto an absorbent polymeric tip attached to a plastic sample handler [56,57]. The porous tips are designed to collect 10, 20 and, in the near future, 30 ␮L of wet matrix that can be either blood, plasma, serum, urine, tears, synovial fluid, cerebral spinal fluid or saliva [58]. After blood collection, VAMS must be left to dry for about two hours at room temperature in their clamshells and then stored or shipped in zip-closure plastic bags with desiccant; upon arrival to the laboratory, VAMS tips are removed from the handler and placed into extraction tubes for the extraction protocol with the most suitable solvents [57]. The analysis of the whole tip contributes to reduce issues of sample non-homogeneity, reported for DBS. Nevertheless, some negative effects of variability in hematocrit are still present [59]. In cases of automation the whole VAMS might be used [56]. The optimal extraction solvent is mainly dependent on the analytes of interest and can range from totally organic to partially aqueous: interestingly, about this, Ye and Gao demonstrated that a mixture of methanol:acetonitrile (1:1, v:v) is a good extraction solvent across a wide hematocrit range (20–70%) for both basic and acidic compounds, probably because this mixture benefits from the solvation ability of methanol and the elution strength of acetonitrile, resulting in more effective elution (desorption) of the compounds from the solid phase materials in dried blood analysis; in some cases the addition of 1% formic acid could further increase the recovery [60]. A problem in common with DBS concerns the addition of internal standard to the sample (at the earliest it can be added to the extraction solvent) and the absence of anticoagulant (which instead is present in standards and quality controls). A cross-laboratory experiment has been performed to investigate the hematocrit effect: it was shown that VAMS are able to collect precise blood volumes across a wide hematocrit range (20–65%) [61]. Anyway some molecules, such as fosfomycin, still present issues related to recovery [59] but it has been reported in literature that the inclusion of a sonication step in extraction

43

might improve recovery at high hematocrit values, in order to yield acceptable accuracy across a wide hematocrit range [57,62]. Nowadays VAMS are becoming largely valued for TDM purpose due to their easy-to-learn use, but care should be taken in order to avoid possible errors: the most common are the abuse of the tips during or after sampling, that might affect the amount of blood retained by the tip itself and the excessive immersion of the tip into blood, past the tip shoulder, that can result in trapping of excess blood on the plastic handler [57]. Since 2014 VAMS applications are reported in literature; for what concerns some attempts of TDM, they have been used for the quantification of antibiotics, especially in pediatric patients [63], anti-epileptics [64], immunosuppressants [65], anti-parasitic, especially in resource-poor areas [66], anti-anemics [67] and of hydroxychloroquine in rheumatoid arthritis pediatric patients [68]. 3.2. Alternative matrices Other than simplifying the blood sampling process through the adoption of devices, another possible option to obtain more reliable results or less invasive sampling could be the adoption of alternative biological matrices. In the following paragraphs a brief description of the most widely used alternative matrix is reported and some recent and innovative applications will be discussed. 3.2.1. Urine While analysis in human plasma and/or blood is considered a gold standard for quantitative TDM purpose, analysis in urine samples plays a similar role in the context of qualitative one. This depends on two main factors: the easy and really cheap availability of this kind of matrix and the accumulation of many target analytes (or their metabolites) in the urinary compartment. Therefore, a plethora of applications can be found in literature regarding drugs quantification in urine samples: even if a substantial part of them have a merely toxicological purpose [69–72], still urinary TDM has some applications in several particular contexts. Some interesting applications can be considered as intermediate between the two purposes. As an example, Petrides et al. [73] recently applied LC–MS for the TDM of opioids and benzodiazepines in urine and saliva samples in order to confirm treatment compliance and to identify cases of abuse. The comparison between the two matrixes, in this work, highlighted that the vast majority of drugs and metabolites (especially glucuronides) were more present in urine samples than in saliva, even if 6-acetylmorphine was more abundant in saliva samples. Other applications of LC–MS for TDM in urine samples comprehend the evaluation of therapeutic adherence in several context, such as for antihypertensive treatment. Our group [74] recently published a UHPLC-MS/MS method for the TDM of a wide panel of antihypertensive drugs in urine samples from patients with resistant hypertension, in order to identify possible cases of poor adherence. This paper demonstrated an high prevalence of partial and total non-adherence among the studied population. On the other hand, some major limitation were associated with the use of urine matrix. For example, photodegradation of light sensitive compounds can be much higher in urine samples than in whole blood, due to lower turbidity and possible longer exposure to daylight. Similarly, LC–MS has been applied to evaluate adherence in other clinical contexts, such as antireumatic/antiblastic treatments [75]. Another interesting LC–MS application for TDM in urine samples is the study of urinary disposition of drugs with renal toxicity: in these cases, the penetration of the drug could be a good predictor of renal damage. In a recent work from Simiele et al. [76], a HPLC-MS

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method was described for the quantification of tenofovir, a nucleotidic reverse transcriptase inhibitor with a consistent renal toxicity, in urine samples from patients with HIV. This method highlighted a very high disposition of this drug in urine, which was higher for patients with relevant renal toxicity (greater eGFR reduction). Anyway, the TDM in urine matrix results less relevant for quantitative purposes, since drugs kinetics in this compartment could be subjected to wider variations between and within patients, also depending on renal function, urinary pH or diuresis. Moreover, even if used for adherence testing, an important issue is the interpretation of data: in fact, some reports highlight that a reduction of current concentration cutoff values could increase significantly the proportion of patients considered as adherent [77]. This issue has to be deeply investigated through a regular revision of reference values in the adherent population. 3.2.2. Saliva While historically less used, due to various limitations, oral fluids are now deserving some investigation as potential candidate for TDM purpose. Major advantage of saliva as a matrix for TDM is the completely non-invasive sampling and the great amount of sample which can be recovered in almost any kind of patient. Saliva samples can be obtained by passive drool [78–80] or by use of cotton pads [81] ® or specific devices (eg. Salivette , Sarstedt), in order to make their sampling simpler and more reliable in terms of volume and saliva composition [82–85]. In some contexts saliva is proposed as alternative to urine samples for toxicology, due to less possibility of voluntary adulteration by the patient [73,86]. Nevertheless, some other applications are recently emerging, particularly considering the increasing use of mass spectrometry. In this scenario, particular interest is now emerging about TDM in saliva samples for the management of psychiatric treatments [26,81,84,87], due both to the very comfortable sampling, which limits the stress level for the patient, and to the capability to limit the phenomenon of “white-coat” adherence. Concerning this topic, a recent work from Preiskorn et al. [84] highlighted the good performance of a LC–MS/MS method for the quantification of methylphenidate and its active metabolite, ritalinic acid, in saliva for reducing stress levels (especially in children) associated to blood sampling in the context of therapeutic adherence monitoring. Moreover, a significant correlation was also observed between concentrations in plasma and saliva. Nevertheless, the inter-patient variability in the plasma/saliva concentration ratio resulted a considerable issue, which resulted strongly dependent on the salivary pH. In fact, weak bases, such as methylphenidate, can be protonated in the salivary compartment (typically acidic), thus preventing it to return in the plasmatic one: a similar, but opposite, phenomenon would explain the lower concentration of ritalinic acid in saliva than in plasma. Similar studies have been conducted for other psychotropic drugs [26,81,82,84,87,88], with similar results. Anyway, in some particular cases, such as for levetiracetam [87], salivary concentrations mimic in a reliable manner those in plasma, thus indicating saliva as a good surrogate matrix to be used for a fast and simple TDM. On the other hand, particularly due to intrapatient variability in the plasma/saliva ratio, the concentrations of methadone enantiomers [82,83,89] or fentanyl [82] in saliva did not result good markers of its effectiveness for pain management in oncology. Increasing attention is currently being given to TDM in saliva samples also in the antiretroviral therapy. Recently, a paper from Yamada et al. [90], evidenced as the concentrations of abacavir, tenofovir, darunavir, and raltegravir in saliva samples from HIV1 infected patients resulted significantly correlated with their

unbound concentration in plasma: nevertheless, although significant, this correlation remains too weak to allow a reliable TDM practice, while its usefulness remains good for critical patients, who cannot undergo blood sampling. Finally, studies have been conducted on saliva samples in order to evaluate their eligibility as alternative markers to whole blood for immunosuppressant drugs, such as tacrolimus [78–80]. Nevertheless, although tacrolimus concentrations in saliva resulted comparable with the expected free drug concentrations in plasma, their correlation with those in whole blood is still debated [78–80], particularly considering several factors affecting this correlation (rinsing before sampling, plasma proteins concentration, etc.), so the translation to the routine TDM practice in this field cannot be recommended, yet. Furthermore, the accuracy of the quantification of drugs in saliva samples can be affected by contamination of saliva, mainly by food/drink, so several approaches have been proposed to face this problem, such as the adoption of devices for the stimulation and collection of saliva [82–85,87,89]. 3.2.3. Cerebro spinal fluid (CSF) While in the latter cases the use of alternative matrices aims to reduce the pain, stress level and, in general, the invasiveness of sampling for TDM purpose, in some other cases highly invasive sampling can be useful for evaluating drug disposition in pharmacological “sanctuary” sites [91]. Among these sites, the CSF is one of the most important, since the extrusive effect of the blood-brain barrier (BBB) can create a wide variability in the CSF/plasma concentration ratios for many drugs, thus causing many patients to have ineffective drug concentration in CSF even though the concentrations in plasma are within the therapeutic ranges. Obviously, this issue is particularly important in the context of antimicrobial chemotherapy, where time windows of underexposure to antibiotic, antiviral or antifungal drugs can lead to the selection of resistant strains. According to this, several papers have recently been published regarding the application of LC–MS to the TDM of antimicrobial agents in CSF. Particularly, a paper by Qu et al. [92] recently described an interesting application of On-line Dual SPE-LC coupled with high resolution mass spectrometry (HMRS) to the TDM of amphotericin B, fluconazole and fluorocytosine in plasma and CSF. This kind of application, although technologically intensive, allowed a useful quantification of these antifungal drugs in CSF to identify cases of critical underexposure, especially in HIV positive patients affected by cryptococcal meningitis. Similarly, UHPLCMS/MS methods have also been applied to study vancomycin [93] and caspofungin [94] in CSF compartment, since the penetration of these drugs is pivotal for the treatment of cerebral bacterial and fungal infections, respectively. Another important field regarding the evaluation of drug penetration in CSF is the antiretroviral therapy, with several papers reporting LC–MS applications to quantify antiretroviral drugs in CSF [91]. In fact, while the current highly active antiretroviral therapy is capable of successfully suppress viral replication in the vast majority of the body compartments, many patients still show HIV-related neurocognitive impairment, most often due to a residual replication of HIV in the central nervous system: this phenomenon has been shown to be related to low penetration of some antiretroviral drugs in this compartment, so their measurement in the CSF could represent the best marker of exposure in this site [91,95]. Therefore, some works concerning the penetration of abacavir [96], efavirenz and its major metabolites [97] and other antiretroviral drugs [98] have recently been published, all based on UHPLC-MS/MS methods. This kind of studies allow the determination of an inhibitory quotient [98] in CSF, thus indicating the capability of each drug to inhibit HIV replica-

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tion in CNS: nevertheless, even though really promising, this kind of application is still limited to research and more studies are needed to translate it to the clinical routine. In turn, TDM in CSF matrix is also useful for the determination of the penetration of antitumor drugs. A recent paper [99] reported a UHPLC-MS/MS method for the quantification of avitinib, a tyrosinekinase inhibitor, and its metabolites in CSF: this application results very useful, since small-cell lung cancer is capable of developing brain metastasis, and the assessment of drug exposure in the brain could result in a decrease of cases of therapeutic failure and selection of resistant strains. Finally, LC–MS approaches can also be useful for the TDM of drugs for the treatment of neurological diseases. As an example, a recent paper by Tittarelli et al. [100] reported a UHPLC-MS/MS method for the evaluation of the concentrations of ␥-hydroxybutyric acid (GBH) and its glucoronide in the CSF of patients affected by narcolepsy and treated with sodium oxybate. This application resulted particularly useful, since the concentration of the active compound (GBH), increased disproportionally with the drug dose, enhancing the rationale for the TDM. 3.2.4. Hair The vast majority of biomatrices which can be used for TDM are capable to give useful information about the exposure, the distribution or either the elimination of drugs. Nevertheless, all these matrices are able to give a “snapshot” evaluation of the current state of the patient, therefore no information can be obtained about the history of exposure, unless constant monitoring is performed [101], or metabolites with a very long half-life are quantified. For a long-term evaluation patients exposure to xenobiotics, the evaluation of drug concentrations in hair has become a common practice, especially for toxicological purpose [87,102–106]. Briefly, since hair grow at a quite constant rate, each segment can be related to a time-period: therefore, the quantification of drugs in all hair segments can create a “history” of exposure, up to years, depending on the hair length and on the analytes stability. By a practical point of view, in order to have the best reliability for TDM, hair should be rinsed/decontaminated [103,106–109], divided into sections of known length and/or “pulverized” using a mill [103,108,110]. The best usefulness of drugs quantification in hair is for drugs which are accumulated in hair and result stable at room temperature for a long period, such as cannabinoids [102,104]. Nevertheless, the usefulness of TDM in hair is not limited to the anti-doping or legal medicine fields, but also to the quali-quantitative assessment of long-term adherence to chronic pharmacological treatments. In this field, some papers have recently been published regarding painkillers, such as tramadol and its metabolites [106], in order to distinguish cases of normal use from clear cases of abuse, but also antiretrovirals [108,109,111]. In fact, in the context of antiretroviral therapy, the problem of the long-term therapeutic adherence to the treatment is a key factor for the prevention of therapeutic failure and selection of resistant strains [112–114]. In this context, methods for adherence testing on hair have been reported for several widely used drugs, such as nevirapine, tenofovir, lamivudine, zidovudine, abacavir [108,109], atazanavir [111] and others. Nevertheless, several limitations and technical challenges are associated with the use of hair for TDM: the difficulty to identify the optimal extraction solvents, the time and type of rinse of hair before extraction, the stability of the analytes and the possible effect of natural pigmentation or hair dyes on analytes recovery or matrix effect [115]. Moreover, matched calibrators and quality controls are not currently available in hair matrix, further worsening the problem of matrix effect.

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For these reasons, a deep evaluation of all these issues should be performed during method development/validation, in order to obtain a reliable assay. Anyway, the quantitative information deriving from drug quantification in this matrix is relatively poor, so this kind of practice will probably remain limited to the evaluation of adherence.

3.2.5. Peripheral blood mononuclear cells (PBMC) In the recent years, while some simple qualitative applications (adherence testing or toxicological screening) are moving the attention to the use of highly available biological matrices, which require non-invasive sample withdrawal, the need of highly reliable information about drugs exposure at the active sites is increasing the interest in the intracellular TDM. The simplest-to-reach cells are obviously PBMCs, lymphocytes and monocytes from venous blood. These cells can be easily isolated from blood by density gradient separation (usually Ficoll), counted and then lysed, in order to extract intracellular content in the lysis medium [116–126]. This kind of practice keeps a really strong rationale for a plethora of widely used drugs, which directly act in lymphocytes and/or monocytes [117,118,120–126]. Among these, there is growing interest in the quantification of immunosuppressants in PBMC compartment, since these drugs are characterized by a narrow therapeutic range, but also by a really variable drug distribution in blood (protein binding, penetration in erythrocytes, etc.) which causes the TDM in whole blood samples to fail in indentifying, in some cases, under- or overexposure [78,125]. This often results in the recrudescence of symptoms of autoimmune diseases [120], either graft rejection [118,121,124–126] or excess of immunosuppression, causing the occurrence or reactivation of severe infections. In this context, some recent works reported LC–MS applications for the quantification of tacrolimus [118,121–123], everolimus [123], mycophenolic acid [124–127] and intracellular azathioprine metabolites [120] in the PBMC of treated patients. Some of these methods have been also actively tested on patients cohorts with promising results [118,121,124] Moreover, other than for immunosuppressants, PBMC represent the cellular target of other drug classes, such as antileukemic drugs [128] or antiretrovirals [129]: for this reason, the quantification of these drugs in PBMC is deserving increasing attention, with several publications reporting LC–MS methods for this purpose. As an interesting example, a recent work highlighted how only the concentration of the active metabolites of tenofovir alafenamide within PBMC can be considered as an eligible marker of therapeutic efficacy in patients treated with this prodrug, since the concentrations of the inactive compound (tenofovir) in plasma are not significantly correlated to the intracellular ones [130,131]. In the context of antitumor therapy, some recent papers recently applied LC–MS for assessing the penetration of tyrosine-kinase inhibitors dasatinib, imatinib, nilotinib within PBMC [132,133]. Similar works have been conducted on other antiblastic drugs, such as 5-fluorouracile [128]. Nevertheless, in the recent years, the use of drugs quantification in PBMC considerably widened, since they can represent a “surrogate” cellular matrix for studying drug penetration within the cells. In this context, several papers reported LC–MS methods to quantify drugs against hepatitis C (ribavirin, telaprevir, boceprevir) and B (entecavir) in PBMC [116,119,134]: in these cases, however, the rationale of the application of intra-PBMC concentrations of drug should be carefully evaluated, by comparing drug transporters expression in the different cell types (eg. PBMC vs hepatocytes) and by analyzing possible associations with clinical events (therapeutic failure or adverse events).

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Despite the increasing interest in drugs quantification within PBMCs, several technical challenges are still pending on the wide adoption of this practice to routine TDM [135]: the lack of optimized and standardized isolation and cell count procedures, which lead to difficult-to-interpret results (results in ng/sample, ng/million cells, ng/mL, etc.), but also problems in reducing/evaluating the impact of matrix effect (high cell concentration means high amount of phospholipids), still obtaining enough sensitivity. In a recent paper from our group, the influence of cell number on the amount of matrix effect for Tacrolimus and Everolimus quantification in PBMC by UHPLC-MS/MS was described, highlighting a strong and variable matrix effect when very high cell numbers were considered [123,136]. This kind of problem can be only faced by optimizing purification procedures, LC conditions, but also by choosing a correct internal standardization. In this case, a deep evaluation of the IS-normalized matrix effect, or matrix factor, could represent a really important step during the validation of this kind of test [136–138].

sweat samples has been largely based on immunoassays for mere screening of exposure, while LC–MS has been prevalently used for unbiased confirmation [144,143–147]; however, considering the evidence of a considerable amount of false positives and false negatives to immunotesting, many laboratories are trying to skip the adoption of immunoassays in favor of LC–MS techniques [142]. In detail, sweat sampling is commonly performed through the use of patches [142,143,145,147], in order to obtain disposition of target analytes for a longer period and to protect the sample from contamination from external environment: these then undergo analytes extraction though the addition and mixing with organic or aqueous solvents at a controlled pH. The resulting extracts can also be concentrated or further purified through SPE, in order to increase the sensitivity and/or the selectivity of the assay. This kind of approach can be found in several recent works aiming either at the evaluation of therapeutic adherence in pediatric [149] as well as non-pediatric patients, or also at the non-invasive screening of maternal drug abuse in newborns [143,150].

3.2.6. Tissue biopsies Going deeper to the site of action, in order to reach the best information from analytical results, the ideal matrix for TDM purpose would be the target tissue. Nevertheless, this is often difficult (or sometimes even impossible) to reach or the withdrawal would be too invasive to be conducted for a continuous monitoring. Anyway, although not for a “standard” TDM purpose, the quantification of some drugs in tissues has been conducted in several works in the recent years. One of the most investigated field is the antiretroviral therapy. Briefly, in the last years some works have been published investigating the penetration of antiretroviral drugs in lymphoid tissues [139,140]. These works opened important questions about the information taken from TDM on plasma samples and highlighted the importance of novel strategies to increase drug penetration in sanctuary sites, including the adoption of nanoformulations or the use of targeted prodrugs [91]. Similar works have been conducted for immunosuppressive treatments, such as for tacrolimus [141] in renal core biopsies, in order to better predict renal toxicity of this drug. The great technical challenges of these approaches, obviously, consist in the lack of standardization of data, the variability in cellularity of biopsies, blood contamination and, moreover, the impact of matrix effect. Nevertheless, despite the potential information deriving from TDM in tissues could be the most representative of drugs effectiveness/toxicity, we are currently very far from its adoption as a clinical routine practice.

3.2.8. Tears The adoption of tears as a matrix for TDM is favored by their ease of sampling and, moreover, compared either to sweat or oral fluids, tears are less prone to contamination by the environment (or food) and do not contain other lipid components of the skin (sebum) [151]. Moreover, tears are obviously the gold standard matrix for the measurement of ophthalmic drugs for topical use [152]. A disadvantage of the use of tears for TDM is obviously the difficulty of determining the volume of sample, as well as the absence of a standardized approach for their sampling. In fact, significant differences in chemical properties have been already described between stimulated and unstimulated tears [151,153,154]. In the context of therapeutic drug monitoring, the use of tears as possible alternative to plasma has been initially proposed for antiepileptic drugs [155–157]: several works were published in this field in the last decades, particularly concerning the capability of this matrix to provide a good correlation with the free fraction of the drug in plasma. Nevetheless, in the last five years less attention was posed on drugs quantification in tears, especially in human field, while the use of tears matrix is becoming progressively more important in the context of pharmacological studies on animals.

3.2.7. Sweat Other than the above listed matrices, some other have recently been explored for TDM purpose and are still deserving attention for some peculiar features. Among these, sweat is quite promising for the quali-quantitative measurement of the exposure to drugs of abuse or for controlling patients adherence to treatment [142,143]. The key advantages of sweat as a matrix for TDM are the great convenience in sampling and the capability to provide information about exposure to drugs in a reduced to intermediate time window, based on the type of device used for sampling (wipes vs patches, respectively) [142–147]. Nevertheless, some disadvantages are also present, such as the possible passive contamination from the environment and the difficulty to successfully determine the real amount of sample [142,143,148]. Concerning this issue, possible internal standardization of the sample volume has been proposed, using the amount of minerals contained in sweat as markers [148]. Testing on

3.2.9. Breast milk The evaluation of drugs penetration in breast milk can be pivotal for the correct management of pharmacological treatments during breastfeeding [158–167]. For this reason, several LC–MS methods have been developed in the recent years for TDM purposes in breast milk matrix [158–167]. The major application fields of TDM on breast milk matrix through LC–MS in the recent years included drugs of abuse and antidepressant [162], neuroleptics [164], antileukemic [158], antihypertensive [160,163] and anti-HIV therapies [161,165,166]. In particular, an interesting work from Muller et al. [162] investigated sertraline penetration in breast milk and in breasfeeding infants, reporting as the determination of these drugs through LC–MS in breas milk can be useful to limit their exposure in newborns. Similarly, O’Halloran et al. [164] reported a LC–MS/MS method for the quantification of amisulpride (a neuroleptic drug) in breast milk: this method demonstrated high drug concentrations in breast milk, resulting in therapeutic levels of this drug in the infant, with potential detrimental effects. Finally, great attention is posed in the recent years on drugs quantification in breast milk in the field of anti-HIV therapy and prophylaxis [161]: in fact, several interesting works reported methods using LC–MS for the quantification of nucleosides/nucleotide analogues (such as tenofovir and emtricitabine) [161,165,166]as

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well as non-nucleoside antiretroviral drugs [166], with particular usefulness in developing countries, where breastfeeding during antiretroviral treatment is not contraindicated for socioeconomical reasons. 3.2.10. Microdialysis Another technique which can provide a valid alternative to plasma sampling for TDM is the microdialysis. This technique is based on the use of catheters with semipermeable membranes capable to separate permeable components within the matrix, such as metabolites or, if present, drugs [168]. The great advantage of this technique is the unique capability to provide direct information about free drug concentrations in vivo in the interstitial fluid within the target tissue [168,169]. Moreover, by a merely practical point of view, microdialysates are free of plasma or interstitial proteins, making possible the direct analysis by LC–MS, typically after a dilution step [168,169]. Nevertheless, considering the application for TDM, in the recent years the use of microdialysis has been prevalently confined to research purposes, especially for use on animals during pharmacokinetic studies [169–173]. Among these applications, the ones concerning the penetration of antibiotics at the target site, such as in the work from Girondi et al. on clindamycin [169] or LarmenéBeld et al. [168], seem to have great potential to be translated to the clinical practice in the near future. 4. Discussion and conclusion The aim of TDM is to maximize the probability of a successful outcome and to minimize the probability of side effects. The use of TDM in clinical practice has gradually increased in the recent years, especially for antibiotic, immunosuppressant, anticancer, antiepilectic and antiretroviral drugs. Unfortunately, there are still several limitations to TDM and research PK data production, such as high costs related to sample withdrawal, preparation and analysis, but also to the shipment to the few certified TDM laboratories. To overcome these issues, research about simpler and cheaper ways to collect and ship samples is strongly increasing over time, and several applications have been developed on this basis. In this scenario, the use of alternative matrices for TDM (and particularly for PK studies) is of extreme interest. The ability to measure drug concentrations in non-invasive matrices such as saliva, urine and hair begins to find several applications, especially with regards to compliance. Nevertheless, to date, for routine TDM practice the reference matrices remain the blood (for immunosuppressant drugs, such as tacrolimus, sirolimus, etc.) and, above all, the plasma. This is due to the good knowledge of therapeutic ranges, which have been determined in these matrices, but also, in several cases, to the higher costs of more advanced techniques/devices. Many attractive methods and devices to collect samples for TDM and PK studies are now available: VAMS, capillaries, DBS and DPS sampling allow the collection of a small volume of blood or plasma on a sample support that can be shipped at room temperature – for thermostable drugs – via ordinary mail or couriered to a laboratory for analysis. These sampling devices have several advantages that make them useful for TDM in the clinical practice: sample low volumes; no need for sample storage at low temperatures (−20/−80 ◦ C or dry ice); safer collection of samples; and often cheaper and simpler way to send samples. Moreover, through the introduction of advanced analytical techniques and improved throughput, the field of use of these devices, based on mass spectrometric methods, has broadly expanded (Table 1). Clinicians and researchers well know the potential applications of microsampling based mass spectrometric applications. Analysts, on the other hand, face challenges of sensitivity,

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reproducibility and overall accuracy of these methods, other than correlation with reference matrices. In this review, we aimed to bring together these facets to discuss the advantages and current challenges of these devices, and their applications by mass spectrometry in clinical and research settings. Regardless of the sampling and shipment technology (and related specific bias related to it), the aspect referred to the method validation remains fundamental. This issue is particularly important if the methods are applied in clinical settings, and the technology used is mass spectrometry [136,137,174]. The use of mass spectrometry can enable to provide highly accurate analyses, however, the application of this technology is not necessarily translatable into accurate results. The pitfalls of LC–MS must be recognized, systematically addressed, and developed method must be fully validated. In particular, the differential impact of matrix effects (the most important issue in this field) on the analyte and the internal standard can lead to inaccurate results in mass spectrometry analyses. Then, the use of “stableisotope labeled” internal standards (SIL-IS) and the evaluation of IS-normalized matrix effect remain the best ways to ensure accurate results [136,137]. In conclusion, the use of alternative matrices is always a current and important topic, with an exciting potential of application compared to plasma and blood. Researchers and clinicians have still a lot of work to do; in fact, there are still many data that they will have to produce to validate these matrices in a routine clinical setting. At the same time, these alternative matrices will find more and more interest and applicability for pharmacokinetic studies, in particular when they are coupled to analytical techniques in mass spectrometry. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References [1] J. Cusato, S. Allegra, A. Nicolo, A. Calcagno, A. D’Avolio, Precision medicine for HIV: where are we? Pharmacogenomics 19 (2) (2017) 145–165. [2] E. Eliasson, J.D. Lindh, R.E. Malmstrom, O. Beck, M.L. Dahl, Therapeutic drug monitoring for tomorrow, Eur. J. Clin. Pharmacol. 69 (Suppl. 1) (2013) 25–32. [3] H.R. Ashbee, R.A. Barnes, E.M. Johnson, M.D. Richardson, R. Gorton, W.W. Hope, Therapeutic drug monitoring (TDM) of antifungal agents: guidelines from the British Society for Medical Mycology, J. Antimicrob. Chemother. 69 (5) (2014) 1162–1176. [4] C. Felice, M. Marzo, D. Pugliese, A. Papa, G.L. Rapaccini, L. Guidi, A. Armuzzi, Therapeutic drug monitoring of anti-TNF-alpha agents in inflammatory bowel diseases, Expert Opin. Biol. Ther. 15 (8) (2015) 1107–1117. [5] M.E. Joosse, J.N. Samsom, C.J. van der Woude, J.C. Escher, T. van Gelder, The role of therapeutic drug monitoring of anti-tumor necrosis factor alpha agents in children and adolescents with inflammatory bowel disease, Inflamm. Bowel Dis. 21 (9) (2015) 2214–2221. [6] N. Vande Casteele, B.G. Feagan, A. Gils, S. Vermeire, R. Khanna, W.J. Sandborn, B.G. Levesque, Therapeutic drug monitoring in inflammatory bowel disease: current state and future perspectives, Curr. Gastroenterol. Rep. 16 (4) (2014) 378. [7] L.T. Weber, Therapeutic drug monitoring in pediatric renal transplantation, Pediatr. Nephrol. 30 (2) (2014) 253–265. [8] N. Widmer, C. Bardin, E. Chatelut, A. Paci, J. Beijnen, D. Leveque, G. Veal, A. Astier, Review of therapeutic drug monitoring of anticancer drugs part two–targeted therapies, Eur. J. Cancer 50 (12) (2014) 2020–2036. [9] Z.K. Ye, C. Li, S.D. Zhai, Guidelines for therapeutic drug monitoring of vancomycin: a systematic review, PLoS One 9 (6) (2014), e99044. [10] J.E. Adaway, B.G. Keevil, Therapeutic drug monitoring and LC-MS/MS, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 883–884 (2011) 33–49. [11] G. Nys, M.G.M. Kok, A.-C. Servais, M. Fillet, Beyond dried blood spot: current microsampling techniques in the context of biomedical applications, Trac Trends Anal. Chem. 97 (2017) 326–332. [12] P. Timmerman, S. White, S. Globig, S. Ludtke, L. Brunet, J. Smeraglia, EBF recommendation on the validation of bioanalytical methods for dried blood spots, Bioanalysis 3 (14) (2011) 1567–1575. [13] P. Timmerman, S. White, Z. Cobb, R. de Vries, E. Thomas, B. van Baar, Update of the EBF recommendation for the use of DBS in regulated bioanalysis

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