# Rapid and precise determination of elemental impurities in pharmaceutical products by ICP-MS using combined standard addition and isotope dilution methods

Ines Korbi, Mathieu Menta, Justine Verdeil, Véronique Vacchina, Pablo Rodríguez-González, Olivier F X Donard, Houyem Abderrazak, Fabienne Séby

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Ines Korbi, Mathieu Menta, Justine Verdeil, Véronique Vacchina, Pablo Rodríguez-González, et al. Rapid and precise determination of elemental impurities in pharmaceutical products by ICP-MS using combined standard addition and isotope dilution methods. Microchemical Journal, 2025, 217, pp.114785. 10.1016/j.microc.2025.114785. hal-05371436

HAL Id: hal-05371436

https://hal.science/hal-05371436v1

Submitted on 18 Nov 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Rapid and precise determination of elemental impurities in pharmaceutical products by ICP-MS using combined standard addition and isotope dilution methods

Ines Korbi<sup>a,b,c</sup>, Mathieu Menta<sup>d</sup>, Justine Verdeil<sup>d</sup>, Véronique Vacchina<sup>d</sup>, Pablo Rodríguez-González<sup>e</sup>, Olivier F.X. Donard<sup>a</sup>, Houyem Abderrazak<sup>b</sup>, Fabienne Séby<sup>d,*</sup>

## ARTICLE INFO

### Keywords:

Elemental impurities

ICH Q3D

ICP-MS

Isotopic dilution

Pharmaceuticals

Sample preparation

## ABSTRACT

The determination of elemental impurities in pharmaceutical products has received increased attention due to recent regulatory requirements involving the use of advanced atomic spectrometry techniques. The carbon-rich matrices of drugs and the presence of excipients make sample preparation difficult and give rise to matrix effects that considerably affect ICP-MS measurements. In this study, the sample preparation step was optimized by experimental design using two heating devices (heating blocks and microwave-assisted digestion) in presence of HNO₃, HCl and HF. A digestion temperature of approximately 100 °C was found to achieve recoveries within the USP criteria (70–150 %) for 24 elements, with no significant difference in recoveries between the two devices. Isotope dilution (ID) was then applied for the first time to quantify 15 elemental impurities in the drug matrices. The procedure involving the addition of isotopic tracers prior to mineralization made it possible to overcome matrix effects and provided a unique sample preparation procedure regardless of the drug. The use of ID also improved measurement precision (mean RSD of 1.5 %) compared with external calibration (mean RSD of 2.3 %) or standard additions (mean RSD of 3.1 %). Recoveries ranged from 89 to 106 % for elements quantified by ID and from 80 to 110 % for those determined by standard additions. After successful validation according to USP requirements, the method was applied to different drugs. Concentrations found were below USP-authorized limits for all elements, with the exception of lead, which was present at concentrations of 0.2 µg g⁻¹ in a hypertensive and 0.7 µg g⁻¹ in a laxative (USP limit = 0.15 µg g⁻¹).

## 1. Introduction

Elemental impurities in pharmaceuticals result from the occurrence of catalytic residues, the incorporation of contaminated active pharmaceutical ingredients (APIs), or excipients during the synthesis [1,2]. Contamination could also originate from manufacturing equipment, production processes, or packaging [1,2]. The presence of even trace amounts of these elements is a cause for concern, and their concentrations must be kept within acceptable limits to ensure product quality and patient safety [3–9].

To control the concentration levels of elemental impurities in drugs,

the United States Pharmacopeia (USP) has recently introduced chapters (232) and (233) [9,10]. Chapter 232 defines the Permitted Daily Exposures (PDE) for 24 elemental impurities based on their toxicological properties through different administration routes [9]. Chapter (233) provides a comprehensive guidance on analytical procedures and validation requirements. It also highlights the use of Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) as analytical techniques [10]. Due to its greater sensitivity, ICP-MS is generally selected for analyzing elemental impurities in pharmaceutical products [5–7,11].

Drug samples generally consist of mixtures containing APIs along

<footnote><sup>a</sup> Institute of Analytical Sciences and Physical Chemistry for the Environment and Materials, University of Pau and Pays de l'Adour, Centre National de la Recherche Scientifique (CNRS), UMR 5254, 2 Av. du Président Pierre Angot, 64000 Pau, France</footnote>

<footnote><sup>b</sup> Useful Materials Laboratory (LMU), National Institute for Physical Chemical Analysis, Biotechpole Sidi Thabet, 2020 Ariana, Tunisia</footnote>

<footnote><sup>c</sup> National Institute of Applied Sciences and Technology (INSAT), 676 centre urbain nord BP, 1080 Tunis, Tunisia</footnote>

<footnote><sup>d</sup> Ultra Traces Analyses Aquitaine (UT2A), 2 Av. du Président Pierre Angot, 64000 Pau, France</footnote>

<footnote><sup>e</sup> University of Oviedo, C. San Francisco, 3, 33003 Oviedo, Asturias, Spain</footnote>

<footnote>* Corresponding author.
E-mail address: fabienne.seby@univ-pau.fr (F. Séby).</footnote>
with various organic and/or inorganic excipients [4,6,12]. Additionally, some of them include capsule shells or tablet coatings [12]. Due to the complexity of the matrix, the sample preparation step is often the most critical and complex part of the analytical process. In this context, sample preparation procedures are generally based on wet digestion [4], most often using microwaves. This allows to reach temperatures ranging from 160 °C to 220 °C [1,2,14,15,17,18]. However, under these conditions, some APIs, excipients, or sophisticated drugs cannot be completely digested. This generates interferences related to high residual carbon contents (RCC) when using ICP-MS analysis [1,15,18–21]. To increase the digestion efficiency, other microwave-based systems, such as microwave-induced combustion (MIC) and the single reaction chamber (SRC) system, have been used [1,20,22–25]. The latter system can achieve temperature and pressure up to 300 °C and 199 bar, respectively [1,22]. For propranolol hydrochloride, Muller et al. [1] observed a substantial RCC reduction in solutions obtained after mineralization with SRC compared with microwave-assisted digestion (MAD) [1]. They also showed that this system allowed levels of RCC and residual acidity that did not interfere later during ICP-MS analysis [1]. Despite of the fact that SRC offered many advantages, it has been shown that satisfactory and comparable spike recoveries have been obtained for certain drugs submitted to direct solubilization using an acidic solution [20]. Nevertheless, certain analytical strategies must be applied, such as the use of a collision-reaction cell and quantification using internal standardization or standard additions [15,18–20].

When examining the varieties of acids or acidic mixtures used to digest pharmaceutical products, nitric acid [1,14,16,20,23,26], aqua regia [1,15–17,27], or inverse aqua regia [1,2,15,18,20] were the most commonly mentioned. Nevertheless, it has been demonstrated that the platinum group elements (PGEs), including Pt, Pd, Os, Ir, Ru, and Rh, were not completely dissolved using only $HNO_3$ [4,15,17,18]. The addition of HCl was then also required to improve PGEs solubilization through the formation of soluble chlorocomplexes. Inverse aqua regia was found to be a good compromise to overcome spectral interferences caused by chlorine on the determination of some elements by ICP-MS [1,15,20]. In some studies dealing with drug samples containing excipients such as talc, silica, and/or titanium dioxide, hydrofluoric acid was also added [18,27]. However, the addition of HF did not significantly improve spike recoveries [27]. Furthermore, insoluble fluorides could also be formed after mineralization [18].

Other than the direct spectral interferences, the presence of residual carbon in final digests can suppress or enhance the ICP-MS signal intensity compared to standard solutions not containing carbon [11,22,28]. Quantification methods involving external calibration with addition of an internal standard [14–18,20,21,26] and the standard addition method [15,29] were then used. Although effective, these methods are time-consuming for routine analysis [29]. An interesting alternative is the use of isotope dilution (ID) calibration, the principle of which is based on the addition of known quantities of an isotope-enriched substance to the sample being analyzed [13,14,17,20]. After complete mixing, the isotope ratio obtained reflects the analyte concentration in the sample [30]. Whereas standard additions require several calibration points, ID is a one-point calibration strategy, making it interesting for routine analysis. The cost of isotope tracers is higher than conventional standards, but it can be offset by less human intervention. Furthermore, the loss of the analyte during sample preparation did not affect the analytical result after the isotope dilution step has occurred [31]. Isotopic dilution was also recognized for providing the most precise results [30,31]. To our knowledge, despite its advantages, the ID method has never been applied to the determination of elemental impurities in pharmaceuticals.

The aim of the study was therefore to develop an analytical method using ICP-MS for the accurate routine determination of 24 elemental impurities in pharmaceuticals. In this study, the potential of open systems such as heating blocks was compared to MAD, recognized as the reference method for mineralizing drugs. Heating blocks, never

employed in this context, are interesting because they are easier to use for routine analyses. This work then focused on optimizing and comparing closed and open systems for sample digestion using the Design Of Experiments technique (DOE). Secondly, the potential of ID for quantifying elemental impurities in pharmaceuticals was evaluated while adhering to the International Council for Harmonization (ICH) Q3D guideline.

## 2. Material and methods

### 2.1. Reagents, solutions and samples

Standards, samples, and solutions were prepared with ultrapure water (18.2 MΩ cm) provided by a Milli-Q system (Merck Millipore, Bedford, MA, USA). Sample digestion was performed with $HNO_3$ 69–70 % (w/w), HCl 37 % (w/w) (both from Instra-Analyzed Plus, J.T. Baker, Phillipsburg, NJ, USA), and HF 47–51 % (w/w) (Trace metal grade, Fisher Scientific, Hampton, NH, USA).

An yttrium stock standard solution (1000 mg $L^{-1}$, CPA Chem Ltd., Bogomilovo, Bulgaria) was used as an internal standard for ICP-MS analysis. Mono-elemental certified stock solutions containing 1000 mg $L^{-1}$ of Ag, As, Au, Ba, Cd, Co, Cr, Cu, Hg, Ir, Li, Mo, Ni, Os, Pb, Pd, Pt, Rh, Ru, Sb, Se, Sn, Tl or V (CPAchem Ltd., Bogomilovo, Bulgaria) were used to prepare solution S1. This solution was employed for element recovery determination and for quantification by external calibration and standard additions.

For isotope dilution quantification, two custom-made tracer solutions were used: the S2 tracer solution containing enriched isotopes of Ba, Cd, Cr, Cu, Hg, Li, Mo, Ni, Pb, Pt, Sb, Se, Sn and Tl, and the S3 tracer solution containing only silver. S2 and S3 tracer solutions were purchased from ISC-Science (Gijón, Spain). The isotope abundances and the element concentrations in these two solutions are presented in Table S1 (supplementary data).

The drug sample used for method optimization was purchased from a local pharmacy in Pau, France. This medication (drug A) is used to reduce cholesterol and is administered orally in tablet form with a Maximum Daily Dose (MDD) of 0.28 g per day (i.e. 2 tablets). Apart from the active ingredient, this drug also contains excipients, including lactose, silica, microcrystalline cellulose, talc, starch, titanium dioxide (E171), sodium stearyl fumarate, mannitol (E421), macrogol and red iron oxide (E172). Two additional drugs (B and C), administered orally, were also analyzed after method optimization. Drug B is used as an antihypertensive (tablet form with a MDD of 0.6 g per day (i.e. 2 tablets)) and was purchased from a pharmacy in Tunis (Tunisia). Excipients include cellulose, lactose, silica, magnesium stearate, titanium dioxide (E171), macrogol, and iron oxide. Drug C, obtained from a pharmacy in Pau, France, is a ballast laxative with a natural active substance. This drug is formulated as granules for oral suspension with a MDD of 7 g per day. Added excipients are citric acid anhydrous, sodium bicarbonate, sodium saccharin, mandarin dry flavoring, orange yellow S (E110) and sucrose.

### 2.2. Sample preparation procedures

The set of optimized strategies for sample preparation and quantification of elemental impurities in drug samples is shown in Fig. 1.

#### 2.2.1. Sample spiking procedure

According to USP chapter <233>, analytical procedures must demonstrate recoveries between 70 and 150 % of the added amount for samples spiked at concentrations of 50 %, 100 %, and 150 % of the J value for each target element [10]. The J values were calculated according to Eq. 1.
<figure><img src="image_4.png" /><figcaption>Fig. 1. Sample preparation and quantification strategies used for the determination of elemental impurities in drug samples (selected conditions for sample preparation and element quantification are presented with dotted blue lines). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

$$J = \frac{30 \% \times \text{PDE} (\mu\text{g day}^{-1})}{\text{MDD} (\text{g day}^{-1})} \quad (1)$$

The J values correspond to 30 % of the Permitted Daily Exposure (PDE) specific for each element, divided by the Maximum Daily Dose (MDD) of 10 g day⁻¹ (option 1) [32]. Considering an oral route administration, the calculated J values are reported in Table S2 (supplementary data) for each element.

Before spiking, the drug sample was manually ground and homogenized using a pestle and mortar. Masses of approximately 250 mg were accurately weighed and spiking was carried out by adding 100, 200, and 300 µL of solution S1 to reach concentration levels corresponding to 0.5, 1, and 1.5 J. The concentrations of each element in solution S1 are given in Table S3 (supplementary data).

### 2.2.2. Optimization of the sample digestion procedure by the Design of Experiments technique (DOE)

Three acid mixtures were first tested for drug mineralization: 6 mL of HNO₃; aqua regia (6 mL HCl and 2 mL HNO₃) and 3 mL HNO₃, 3 mL HCl, and 1 mL HF. In each case, heating was performed using a heating block digestion system (SCP Sciences, Courtaboeuf, France) with a temperature program of 30 min ramp to 90 °C and a hold at 90 °C for 180 min. Then, digests were diluted to 50 mL with ultrapure water and were 10-fold diluted before ICP-MS analysis. This procedure was applied in triplicate to both non-spiked and spiked samples.

After selection of the suitable acid mixture, the sample digestion procedure was optimized using experimental designs. In addition to heating blocks, microwave-assisted digestion (CEM Corporation, Matthews, NC, USA) was studied. Three factors were retained for both heating devices: temperature applied during digestion, mineralization time, and the solid/liquid ratio (S/L). A full factorial DOE based on a
second-order interaction with 7 coefficients as shown in Eq. (2) was then used.

$$Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \beta_3 X_3 + \beta_{12} X_1 X_2 + \beta_{13} X_1 X_3 + \beta_{23} X_2 X_3 \quad (2)$$

Y is the predicted response, $X_1$, $X_2$ and $X_3$ are the independent variables, and $\beta_0$, $\beta_1$, $\beta_2$, $\beta_3$, $\beta_{12}$, $\beta_{13}$ and $\beta_{23}$ are the coefficients obtained from the regression analysis.

The DOE consisted of 14 experiments including 11 runs using the two-level factorial designs presented in Tables S4 and S5 (supplementary data) for heating blocks and MAD, respectively, and 3 replicates for one center point to determine the curvature.

The multiple response criteria using the desirability function were employed to simultaneously optimize the recoveries of the 24 elements with the aim of achieving a response of 100 % recovery, with the lower limit set at 70 % and the upper limit at 150 % (USP acceptance range). All analytes were given the same importance. This global function ranges from 0 (total undesirability) to 1 (all responses are simultaneously within a desirable range), as defined by eq. (3):

$$D = (d_1^{r_1} \times d_2^{r_2} \times \dots \times d_n^{r_n})^{1/\sum r_j} = \left( \prod_{j=1}^{n} d_j^{r_j} \right)^{1/\sum r_j} \quad (3)$$

where $d_1, \dots, d_n$ correspond to the individual desirability functions for each response being optimized, n is the total number of responses, and r corresponds to the relative importance of each response in comparison to others. All data processing was carried out using Statgraphics 19 (FRANCESTAT, Neuilly sur Seine, France).

After optimization, the procedures applied for sample mineralization were as follows. For MAD, the acid mixture was 4.2 mL HNO₃, 4.2 mL HCl, and 1.6 mL HF and the temperature program was 30 min ramp to 115 °C and a hold at 115 °C for 15 min. By using the heating blocks, the acid mixture was 3.5 mL HNO₃, 3.5 mL HCl, and 1.3 mL HF and the temperature program applied was 30 min ramp to 92 °C and a hold at 92 °C for 150 min. In each case, digests were completed to 50 mL with ultrapure water and then 10-fold diluted before ICP-MS analysis. For each sample analysis, this procedure was applied in triplicate to both non-spiked and spiked samples.

## 2.3. ICP-MS analytical procedure

ICP-MS analysis was performed with an Agilent 7900 equipped with the ORS4 single reaction cell (Agilent Technologies, Santa Clara, CA, USA) using operating parameters listed in Table S6 (supplementary data). To minimize spectral interferences, the kinetic energy discrimination (KED) mode was used with helium (3.8 mL min⁻¹) for vanadium and arsenic, and with hydrogen (3.5 mL min⁻¹) for chromium and selenium.

The measurement conditions were optimized daily to give the highest intensity using a standard built-in software procedure. As illustrated in Fig. 1, different quantification methods were studied for the determination of elemental impurities in drug samples, external calibration with an internal standard, standard additions, and isotopic dilution.

### 2.3.1. External calibration quantification procedure

An external calibration was applied when selecting the acid mixture for sample digestion. In this case, yttrium was used as an internal standard and was added to sample solutions, standard solutions, and blanks to achieve a concentration of 1 µg L⁻¹. A series of six standard solutions (0 J - 0.5 J - 0.75 J - 1 J - 1.5 J - 2 J) were prepared by diluting the solution S1 in a matrix-matching solution containing HNO₃ 6 % (v/v) and HCl 6 % (v/v). Samples were 10-fold diluted in this acidic solution before analysis.

### 2.3.2. Standard addition quantification procedure

The standard addition quantification procedure was used during the

optimization of sample digestion. This procedure was also retained to determine As, Au, Co, Ir, Os, Pd, Rh, Ru, and V in drug samples. Calibration by standard additions was performed by adding the solution S1 in the test sample solution to obtain final concentrations of 0 J - 0.5 J - 0.75 J - 1 J - 1.5 J and 2 J.

### 2.3.3. Isotopic dilution quantification procedure

Isotopic dilution mass spectrometry (IDMS) was applied to the quantification of Ag, Ba, Cd, Cr, Cu, Hg, Li, Mo, Ni, Pb, Pt, Sb, Se, Sn and Tl in drug samples.

Two spiking procedures were compared in this study. The first procedure (ID1) involved adding the tracers S2 and S3 directly to the solid sample before digestion, while the second (ID2) involved adding the tracers S2 and S3 to the sample after the digestion procedure (Fig. 1).

For both procedures, 200 µL of S2 and S3 were accurately weighed and added to spiked and non-spiked samples to obtain concentration values corresponding to 1 J.

The analyte concentrations were calculated according to Eq. (4) obtained from [33]:

$$C = C_t \times \left(\frac{m_t}{m_s}\right) \times \left(\frac{M}{M_t}\right) \times \left(\frac{R_m \times A_{bt} - A_{at}}{A_a - R_m \times A_b}\right) \quad (4)$$

where C is the concentration of the analyte in the sample, $C_t$ the concentration of the analyte in the tracer, $m_t$ the mass of the tracer added to the sample, $m_s$ the mass of the sample uptake, M the natural atomic weight of the analyte, $M_t$ the atomic weight of the analyte in the tracer, $R_m$ the isotope ratio measured in the isotope-diluted sample, $A_{bt}$ the abundance of the isotope a in the tracer, $A_{at}$ the abundance of the isotope b in the tracer, $A_a$ the natural abundance of the isotope a, and $A_b$ the natural abundance of the isotope b (with a being the most abundant isotope in the tracer and b the most abundant natural isotope of the analyte). The level of the spike of the tracer was considered valid if $R_m$ was comprised between square root of $(A_{at}/A_{bt})$ and square root of $(A_a/A_b)$. Indeed, if $R_m$ is outside this range, erroneous concentration values could be obtained. In order to correct the mass bias effect, the isotope-diluted samples were bracketed by a sample of known isotopic composition.

### 2.3.4. Quality control and data processing

All analyses were performed in a quality environment that complies with good manufacturing practices (GMP). This involves installation qualification and annual operational qualification of instruments used for analysis and sample preparation. A daily performance check of the ICP-MS is also made routinely. In addition, the balances and micropipettes are regularly checked. The standards used are all certified and traceable to the international system.

All measurements were performed in triplicate, and the reported concentrations correspond to the mean value obtained from the three replicates. The associated measurement uncertainty, including those used for method validation, was calculated from the three values, considering a confidence interval of 68 %.

## 3. Results and discussion

### 3.1. Selection of the acid mixture for drug sample digestion

The acid mixture used for sample digestion was first studied between HNO₃, aqua regia, and the mixture of HNO₃, HCl, and HF (3:3:1 (v/v/v)). In each case, the drug sample was first spiked to a concentration of 0.5 J and then mineralized with the heating block system. Spike recoveries were then calculated after ICP-MS analysis considering element quantification by external calibration with an internal standard. Although solid residues were present, the use of nitric acid alone was interesting because this acid causes little interference in ICP-MS. Recoveries obtained in these conditions were within the acceptance limits (70–150 %) for all elements except palladium and osmium (Fig. S1,
supplementary data). However, recoveries close to the 70 % lower limit were achieved for many elements such as Ba, Cd, Cr, Cu, Hg, Mo, Ru, Tl, and V. For most of them, this could be attributed to poor sample solubilization in nitric acid, or to matrix effects during ICP-MS analysis. In case of mercury, as already observed, its volatilization during the open-system mineralization could also have occurred [7,27,28]. A number of studies have also highlighted the need to use HCl to stabilize mercury in digests by complexation [2,7,27,28]. Palladium presented an average recovery of (30 ± 5)% showing its low solubility in nitric acid during heating block digestion. The poor recoveries also obtained for osmium (24 ± 7)% were likely due to the formation of volatile oxidized species, such as OsO₄, as already observed when only nitric acid was used [1,14,15,20,26,27]. These Os volatile forms resulted in uncontrolled losses during sample preparation and in the ICP-MS sample introduction system [2,14,18,26,27]. Typically, aqua regia was generally employed for determining PGEs including Pd and Os [15,34]. Therefore, the addition of hydrochloric acid during digestion was expected to enhance recoveries for these elements. In these conditions, a significant improvement in osmium recoveries was observed ((114 ± 1)%) which can be attributed to the formation of the soluble hexachloro anionic complex [OsCl₆]²⁻ in HCl media, thus minimizing Os losses [16]. Palladium recoveries were also improved in aqua regia with a mean value within the acceptance criteria ((76 ± 1)%). Interestingly, except for Li, Ni, and Sn, the use of aqua regia had no negative impact on the recoveries of the other elements. Nevertheless, recoveries for Ba, Cd, Cr, Cu, Hg, Mo, Ru, Tl, and V remained close to the acceptable lower limit (70 %). Due to these observations, the addition of hydrofluoric acid in addition to HNO₃ and HCl was studied. Indeed, since the test drug sample contains excipients such as silica, titanium dioxide, and talc, its complete dissolution may require the use of HF to fully degrade the matrix and release the elements of interest into the solution [27,35]. To avoid damaging the ICP-MS sample introduction system and the torch by residual HF, the final digests were diluted ten times before analysis. Under these conditions, the recoveries demonstrated a real improvement in mineralization efficiency. Compared to nitric acid or aqua regia, the recoveries of many elements (As, Ba, Cd, Cr, Cu, Hg, Li, Mo, Ni, Pb, Pd, Ru, Sn, Tl and V) were closer to the target value of 100 %. The use of HF therefore seems to improve solubilization of excipients that could not be fully dissolved by either HNO₃ or aqua regia. However, some elements such as Ag, Au, Co, Ir, Rh, and Sb showed recoveries well over 100 % in this acid mixture. It is possible that the complete dissolution of excipients led to the simultaneous release of major elements such as Mg and Ti, resulting in significant matrix effects. Despite this problem, the mixture of acids containing HNO₃, HCl and HF was retained for the optimization of the sample preparation step, as it enabled higher recoveries for most elemental impurities.

## 3.2. Optimization of the sample preparation procedure using experimental designs

The sample preparation step was optimized by using and comparing two heating systems, microwave-assisted digestion (MAD) and heating blocks. MAD is often considered the most suitable for drug mineralization as it allows high temperatures and pressures to be applied in a closed environment, which promotes sample decomposition and minimizes analyte loss. On the other hand, heating blocks operate at atmospheric pressure and therefore at lower temperatures, which limits sample solubility and may increase the risk of volatile element loss. Despite these limitations, they offer advantages for routine use due to their simplicity of implementation, low cost and ability to process several samples simultaneously.

The Design Of Experiments (DOE) technique has been retained to optimize sample preparation, based on statistical Response Surface Methodology (RSM). The DOE has often been preferred to the One-Factor-At-a-Time (OFAT) approach, in which only one factor varies at a time while the others are fixed [36–38]. It is then possible to reduce the

number of experiments, estimate and unravel more precisely the effects of each factor and their interactions. Moreover, the use of a desirability function further enhanced the optimization process by enabling the simultaneous consideration of all elemental recoveries, rather than addressing each analyte individually [39]. In this study, the absence of significant curvature observed in the response surfaces confirmed that the quadratic model used in previous studies [40,41] was not necessary.

### 3.2.1. Selected factors and their associated levels

The factors studied were temperature, digestion time, and the solid/liquid (S/L) ratio. Temperature is a critical factor in the mineralization process because it influences the reaction kinetics and improves the degradation of the solid matrix by acids [42]. As mentioned in the ICH Q3D guideline [32], the duration of mineralization is also a key factor in ensuring complete digestion of the matrix. Insufficient time does not allow for complete dissolution, while excessive time promotes the loss of analytes. An optimal solid/liquid ratio ensures that there is sufficient acid to completely solubilize the sample through the interaction between the acid mixture and the sample components. These factors being closely related to the heating device used, two different DOE were carried out. For the case of heating blocks, the temperatures studied were 90 °C, 100 °C and 110 °C to assess the effect of moderate to slightly high temperatures, within the practical limits of this system. For MAD, the low level was set at 90 °C to allow direct comparison with heating blocks, while the intermediate and high levels were set at 145 °C and 200 °C, respectively, to explore the potential benefits of the higher temperatures that MAD can achieve. In terms of mineralization time, levels applied for heating blocks were 120, 150 and 180 min. MAD generally requires less time than heating blocks due to the higher temperatures applied and the more efficient energy transfer. Therefore, levels were set at 10, 20 and 30 min. Finally, for the S/L ratio, in order to avoid any problems due to sample heterogeneity, the sample mass was kept at 250 mg, and only the volume of the acid mixture was modified, while maintaining the proportions of each acid. For each heating device, the tested S/L ratios were 25, 30.35 and 35.7 to enable direct comparison. The full factorial experiment plans (Tables S3 and S4, supplementary data) were then applied, and the results obtained were the recoveries of the 24 elements.

### 3.2.2. Results obtained after optimization using DOE

The optimum levels of each factor and the interactions between factors were determined using a graphical representation of overall desirability obtained via three-dimensional (3D) response surface plots and two-dimensional (2D) contour plots, which are projections of the 3D surface plots (Figs. S2 and S3 (supplementary data), for heating blocks and MAD, respectively). For heating blocks, a maximum desirability of 0.85 was achieved for a temperature of 92 °C, a solid/liquid ratio of 30 and a mineralization time of 130 min. The desirability then gradually decreased, falling significantly at around 102 °C. Of the three factors studied, the solid-liquid ratio was clearly the most critical, with desirability falling significantly outside the 28–32 range. Since this heating method relies on thermal conduction, the energy transfer process is slow. As a result, the efficiency of mineralization was affected by the contact surface between the acids and the solid sample. The two other factors studied (temperature and digestion time) appeared to be less critical. With regard to temperature, desirability remained high (≥ 0.8) between 90 °C and 98 °C, gradually decreasing above 100 °C. For a S/L ratio of 30, the optimal mineralization time was 130 min, but it varied slightly between 130 and 180 min.

For the use of MAD, the maximum desirability was lower (0.69) than observed for heating blocks (0.85). The optimal conditions obtained were a temperature of 115 °C, a S/L ratio of 25 and a mineralization time of 15 min, excluding ramping up and cooling down times. In this case, the most critical factor was the mineralization time, which was optimal between 10 and 20 min but decreased significantly beyond that. It is possible that excessive mineralization time may have led to the release
of significant amounts of major elements from the excipients. Elements such as magnesium, silicon or titanium could then be released from talc, silicates, or titanium dioxide contained in the drug, respectively. These elements could then precipitate and/or co-precipitate with the elements being analyzed, resulting in lower recoveries. For MAD, the S/L ratio had little influence on desirability, with a wide range of optimal values between 25 and 30. As expected, the higher energy transfer of micro-waves promoted interaction between the acids and the solid sample. With regard to temperature, desirability decreased slightly between 115 °C and 150 °C, reaching zero at around 160 °C. Based on these results, the optimal efficiency was achieved at a temperature close to 100 °C for both heating devices. Under optimal conditions, the solutions digested using MAD were clear, while solid residues were present with heating blocks. Therefore, the MAD approach enabled complete mineralization of the sample. However, its over-efficiency most likely caused solubility problems for the elements studied due to their interactions with the major elements present in the excipients. This study confirms the findings of Pineiro et al. [20], who demonstrated that mineralization procedures were applicable to drugs even if residual solids were present in solution.

### 3.2.3. Comparison of heating devices

The optimized conditions were then applied to the test drug sample and the resulting recoveries are presented in Fig. 2. To avoid matrix effects, quantification was performed using standard additions. Under these conditions, similar results were obtained for heating blocks (Fig. 2a) and MAD (Fig. 2b). In both methods, the recoveries obtained were within the acceptance criteria (70–150 %) for the 24 elements. The statistical model was then validated by plotting the experimental responses against the predicted responses (Fig. 3). For both heating devices, the predicted and experimental responses aligned closely with the diagonal, indicating that the two responses were very similar. The dispersion of the experimental responses with respect to the diagonal was slightly greater with MAD (Fig. 3b) than for heating blocks (Fig. 3a), suggesting that the model seemed a little better suited when using the heating blocks. The goodness of fit between the model and experimental data was also estimated by calculating the coefficients of determination (R²). For heating blocks and MAD, the R² values were 0.954 and 0.945, respectively, indicating a satisfactory statistical model.

To select the most appropriate heating system for drug digestion, an ANOVA test was performed, comparing experimental element recoveries obtained from the two heating devices (Table S7, supplementary data). The high p-value obtained (0.53) showed no significant statistical difference in element recoveries between the heating blocks and the MAD methods. Under optimized conditions, both heating systems can therefore be used for drug mineralization. Since desirability data were more favorable for heating blocks, this system, easier to manage for routine analyses, was selected in the study.

## 3.3. Isotopic dilution for element determination in drug samples by ICP-MS

Regarding the determination of elemental impurities by ICP-MS, while spectral interference can be effectively eliminated using the collision/reaction device, controlling matrix effects remained a challenge. This was previously solved using standard addition, but its application is difficult to implement routinely. The use of isotopic dilution may therefore be a promising alternative, while improving measurement precision. Its application requires that the elements have at least two non-interfering isotopes. Consequently, monoisotopic elements such as As, Au, Co and Rh cannot be quantified by IDMS. Additionally, tracer standards for Pd, Ru, Os, and Ir were not available from the supplier due to the low solubility of their metallic forms. Finally, vanadium has two natural isotopes (⁵⁰V and ⁵¹V), but the abundance of the ⁵⁰V isotope (0.25 %) is too low to be detected by ICP-MS. For these reasons, isotopic dilution was only applied to Ag, Ba, Cd, Cr, Cu, Hg, Li, Mo, Ni, Pb, Pt, Sb, Se, Sn and Tl.

### 3.3.1. Optimization of the isotopic dilution procedure

As described in Fig. 1, two different approaches were compared for element quantification by isotopic dilution. The first approach (procedure ID1) involved adding the S2 and S3 tracer solutions to the sample before the digestion step. The second procedure (ID2) involved adding the tracers after the digestion step. For both procedures, element recoveries were assessed by considering the addition of tracers at a concentration corresponding to 1 J. The main advantage of ID1 is to avoid issues associated with losses during sample digestion; however, mineralization must be as optimal as possible. The ID2 procedure can be considered comparable to quantification by standard addition, with better measurement precision.

Recovery values achieved from the ID1 procedure were all within the USP acceptance criteria and ranged from 89 % for silver and antimony to 106 % for copper with a mean recovery of 96 % for the 15 elements (Table S8, supplementary data). Regarding ID2, element recoveries also complied with USP criteria (from 80 % for Cd and Pb to 110 % for Hg), except for silver which was only 68 % recovered (Table S8, supplementary data). Without considering this element, a mean recovery value of 92 % was obtained. The improvement in silver recovery (89 %) with procedure ID1 showed a solubilization deficiency for this element during sample preparation that could not be corrected by procedure ID2. Based on these results, isotopic dilution applied prior to digestion (ID1) has proven effective in accurately quantifying elemental impurities. However, for successful application of IDMS, it was essential to first achieve full isotopic equilibrium or complete mixing between the isotopically enriched tracers added and the endogenous element in the sample. The positive results obtained by ID1 showed that the mineralization step was under control following its optimization.

<figure><img src="image_5.png" /><figcaption>Fig. 2. Spike recoveries (n = 3) obtained in the optimized sample digestion conditions using (a) heating blocks and (b) MAD.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Experimental responses (black dots) versus predicted responses (red line) for (a) heating blocks ($R^2$ = 0.954, mean of experimental response = 93.4 % (blue dashed line)) and (b) microwave-assisted digestion ($R^2$ = 0.945, mean of response = 92.2 % (blue dashed line)). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

### 3.3.2. Comparison of ID with classical quantification methods

The recoveries obtained by the ID1 procedure and those achieved by external calibration with an internal standard, and standard additions were compared for three drug products having different matrices (Fig. S4, supplementary data). For drug A used to optimize the method, the recoveries obtained by the three quantification methods were within acceptance limits (70–150 %). However, for most elements, the values were significantly closer to 100 % with isotopic dilution than with the two other methods. To check the robustness of the method, two other drugs were analyzed. Independently from the quantification method used, recoveries were close to 100 % for most elements in these two samples. However, lithium and chromium in drug B, and lead in drug C showed different recoveries depending on the quantification mode. Indeed, isotope dilution significantly improved the accuracy of measurements for Li and Cr in drug B. Using ID, recoveries were (103 ± 1)% and (89 ± 1)% for Li and Cr, respectively, whereas they were only 80 % and 48 % by external calibration and standard additions. For chromium, only isotope dilution provided recoveries within acceptance limits. The same applied to Pb in drug C, which showed very low recoveries from external calibration (34 %) and standard additions (40 %), combined with a high level of uncertainty (close to ±25 %). The use of isotopic dilution enabled Pb recoveries to be achieved within the acceptance limits ((96 ± 2)%). These results showed that isotope dilution was the most suitable method for quantifying elemental impurities in drugs with different matrices. Unlike standard additions or external calibration, isotopic dilution allowed a single sample preparation method to be used without affecting elemental recoveries.

### 3.3.3. Optimization of measurement precision

Another advantage of ID was the increased precision of measurements [29–31]. The RSD (%) calculated from element recoveries obtained by ID1 have therefore been compared to those achieved by external calibration and standard additions. RSD values are presented in Table 1 for drug A. With the exception of Ba, Cu, Sb and Se, standard additions did not really improve measurement precision compared to external calibration. As expected, isotope dilution was the most precise method, with the lowest RSD values (below 2 % for all elements). The gain in precision was particularly significant for selenium which is generally difficult to measure due to significant matrix effects from residual carbon in the digest solution. In this case, isotope dilution resolved the problem while achieving excellent measurement precision. Therefore, this study comparing different quantification methods clearly showed that isotopic dilution has many advantages over external calibration and standard additions. Indeed, this method could resolve and integrate effectively matrix effects and mineralization partial deficiencies while achieving excellent measurement precision.

<caption>**Table 1**</caption>

Relative standard deviations (%RSD, n = 3) calculated from element recoveries obtained by external calibration, standard addition and isotopic dilution in drug A.

<table><thead><tr><th rowspan="2">Element</th><th colspan="3">RSD (%)</th></tr><tr><th>External calibration</th><th>Standard addition</th><th>Isotopic dilution (ID1)</th></tr></thead><tbody><tr><td>Li</td><td>2.1</td><td>4.2</td><td>1.6</td></tr><tr><td>Cr</td><td>1.8</td><td>4.0</td><td>1.0</td></tr><tr><td>Ni</td><td>0.9</td><td>5.1</td><td>1.0</td></tr><tr><td>Cu</td><td>2.3</td><td>1.9</td><td>1.8</td></tr><tr><td>Se</td><td>8.9</td><td>6.9</td><td>1.2</td></tr><tr><td>Mo</td><td>1.2</td><td>3.2</td><td>1.0</td></tr><tr><td>Ag</td><td>0.9</td><td>1.2</td><td>1.3</td></tr><tr><td>Cd</td><td>2.8</td><td>3.8</td><td>2.0</td></tr><tr><td>Sn</td><td>2.2</td><td>2.3</td><td>1.9</td></tr><tr><td>Sb</td><td>1.2</td><td>1.4</td><td>1.1</td></tr><tr><td>Ba</td><td>1.2</td><td>1.0</td><td>1.0</td></tr><tr><td>Pt</td><td>1.8</td><td>1.2</td><td>1.0</td></tr><tr><td>Hg</td><td>2.3</td><td>2.3</td><td>2.1</td></tr><tr><td>Tl</td><td>2.4</td><td>2.5</td><td>2.1</td></tr><tr><td>Pb</td><td>2.6</td><td>5.8</td><td>2.0</td></tr></tbody></table>

### 3.4. Method validation according to USP requirements

The analytical method optimized was then validated in compliance with USP requirements mentioned in chapter <233> [10]. Validation parameters studied were first those related to limits of the method such as detectability, precision of the instrumental method, and specificity. Then, the method quantitative parameters including accuracy, precision (repeatability and intermediate precision), and sensitivity (detection and quantification limits) were determined. Finally, the stability of target elements in the sample digests was evaluated. The analytical method applied was sample digestion using heating blocks in the optimized conditions. Analysis was then carried out by ICP-MS, 15 elements (Ag, Ba, Cd, Cr, Cu, Hg, Li, Mo, Ni, Pb, Pt, Sb, Se, Sn, and Tl) were quantified using isotopic dilution (ID1 procedure) and the other elements (As, Au, Co, Ir, Os, Pd, Rh, Ru and V) were quantified by standard additions.

#### 3.4.1. Method performance and limits

The detectability approach investigates the ability of the method to detect elemental impurities by analyzing a standard solution with a 1 J concentration, an unspiked sample, and spiked samples at concentration levels of 1 J and 0.8 J. Signal intensities of the spiked samples were then compared to signal intensities obtained from the standard solution. According to chapter <233>, the average value of the three replicate measurements of the spiked sample 1 (1 J) should be within ±15 % of the average value obtained for the replicate measurements of the
standard solution. In addition, the average value of the replicate measurements of spiked sample 2 (0.8 J) must provide a signal intensity less than that of the standard solution. These criteria were evaluated for the 24 elements and signal intensities in spiked sample 1 were within a range of variation between 1 % (Ag) and 10 % (Cu) considering all elements. On average, the spiked sample 2 showed 80 % intensities compared to that of the standard solution for all the elements. The method developed was therefore capable of detecting all elements appropriately.

The precision for the instrumental method (repeatability) was assessed through the analysis of six independent samples of drug A, individually spiked at the 1 J concentration level and then digested using heating blocks. This parameter is considered compliant if the % RSD calculated from the six signal intensity values is less than 20 %, which was the case with RSD values ranging from 3 % (Ag) to 13 % (Cr).

As recommended by USP chapter <233>, the specificity of the method was evaluated by comparing signal intensities measured in a blank, the 1 J standard solution, and the spiked test sample at 1 J. The specificity was demonstrated to be highly efficient since the background intensity from the blank was lower than signal intensities measured for both the 1 J standard solution and the 1 J spiked sample for each target element.

### 3.4.2. Method quantitative parameters

The method accuracy was evaluated by spike experiments at levels equivalent to 0.5 J, 1 J, and 1.5 J for each target element. The mean spike recovery values obtained were all within the USP acceptance range (70 % - 150 %) for the three spike levels (Table S9, supplementary data).

Method precision was evaluated in terms of repeatability (n = 6) and intermediate precision (n = 12, on two different days of analysis) using spiked samples at the 1 J concentration level. The relative standard deviation values (Table S9, supplementary data) were always below 15 % for all analytes, meeting the defined acceptance criteria (RSD < 20 % for repeatability and < 25 % for intermediate precision).

With regards to sensitivity, the limit of detection (LoD) was calculated as three times the standard deviation of the measured concentration for ten different blank samples and the limit of quantification (LoQ) was evaluated as ten times the standard deviation. The results are given in Table 2 for the 24 elements. Considering an oral administration, the resulting LoQs for all elements were lower than 30 % PDE (J values)

<table><caption>**Table 2**

LoD and LoQ values obtained by ICP-MS.</caption><thead><tr><th>Element</th><th>LoD (µg g<sup>-1</sup>)</th><th>LoQ (µg g<sup>-1</sup>)</th><th>ICH Q3D limit (µg g<sup>-1</sup>)<sup>a</sup></th></tr></thead><tbody><tr><td>Cd</td><td>0.0005</td><td>0.001</td><td>0.15</td></tr><tr><td>Pb</td><td>0.003</td><td>0.01</td><td>0.15</td></tr><tr><td>As</td><td>0.03</td><td>0.09</td><td>0.45</td></tr><tr><td>Hg</td><td>0.005</td><td>0.02</td><td>0.90</td></tr><tr><td>Co</td><td>0.05</td><td>0.2</td><td>1.5</td></tr><tr><td>V</td><td>0.03</td><td>0.09</td><td>3.0</td></tr><tr><td>Ni</td><td>0.06</td><td>0.2</td><td>6.0</td></tr><tr><td>Tl</td><td>0.0003</td><td>0.001</td><td>0.24</td></tr><tr><td>Au</td><td>0.0006</td><td>0.002</td><td>3.0</td></tr><tr><td>Os</td><td>0.001</td><td>0.005</td><td>3.0</td></tr><tr><td>Ir</td><td>0.001</td><td>0.004</td><td>3.0</td></tr><tr><td>Pd</td><td>0.007</td><td>0.02</td><td>3.0</td></tr><tr><td>Pt</td><td>0.001</td><td>0.004</td><td>3.0</td></tr><tr><td>Rh</td><td>0.0005</td><td>0.002</td><td>3.0</td></tr><tr><td>Ru</td><td>0.0009</td><td>0.003</td><td>3.0</td></tr><tr><td>Ag</td><td>0.001</td><td>0.005</td><td>4.5</td></tr><tr><td>Se</td><td>0.04</td><td>0.1</td><td>4.5</td></tr><tr><td>Li</td><td>0.04</td><td>0.1</td><td>16.5</td></tr><tr><td>Sb</td><td>0.005</td><td>0.02</td><td>36</td></tr><tr><td>Ba</td><td>0.015</td><td>0.05</td><td>42</td></tr><tr><td>Cu</td><td>0.05</td><td>0.2</td><td>90</td></tr><tr><td>Mo</td><td>0.01</td><td>0.02</td><td>90</td></tr><tr><td>Sn</td><td>0.01</td><td>0.03</td><td>180</td></tr><tr><td>Cr</td><td>0.2</td><td>0.8</td><td>330</td></tr></tbody></table>

indicating an overall good sensitivity performance of the method.

### 3.4.3. Element stability in digests over time

The stability of digested samples was evaluated by analyzing the 1 J spiked samples on the day of preparation (day 0). These solutions were stored at room temperature for two weeks and analyzed on days 7 and 15. Concentration differences between day 0 and subsequent days were ≤ ±5 % for all elements. Since this variation was of the same order of magnitude as the RSDs obtained during the method precision study, the digested solutions can be stored for two weeks before analysis.

### 3.5. Elemental impurity concentrations in different drug samples

After full validation, concentrations of elemental impurities were determined in three different drug samples using the optimized method. These drugs are administered orally to treat cholesterol (drug A), hypertension (drug B) and constipation (drug C). For drugs A and B, the active ingredient is a synthetic organic molecule, whereas in drug C, the active substance is of natural origin (psyllium seed). The results obtained are presented in Table 3. In drug A, all the elements analyzed had concentrations well below ICH Q3D-authorized limits listed in Table 2. Despite of the fact that these drugs are administered daily to lower cholesterol levels, this drug does not present a health risk in terms of elemental impurities. In drugs B and C, lead levels exceeded the limit set at 0.15 µg g<sup>-1</sup> (Table 2). This was particularly true for drug C, whose Pb concentration was around five times higher than the limit. In this case, the contamination is likely to have come from the active ingredient, which was derived from a plant. This plant is most likely capable of accumulating lead from the soil and the atmosphere and then finds its way into the seed. The high levels of copper and barium found in drug C probably have the same origin. In drug B, the high lead content was probably due to the manufacturing process or the addition of excipients that may contain this element.

In drugs A and B, while many elements had concentrations below the limits of detection or quantification, the high sensitivity and precision of the method developed enabled traces of elemental impurities to be

<table><caption>**Table 3**

Concentration values of elemental impurities in the studied drug samples.</caption><thead><tr><th rowspan="2">Elements</th><th colspan="3">Concentration values (c) (n = 3, µg g<sup>-1</sup>)</th></tr><tr><th>Drug A</th><th>Drug B</th><th>Drug C</th></tr></thead><tbody><tr><td colspan="4" style="text-align:center; font-weight:bold;">Isotopic dilution (ID1)</td></tr><tr><td>Li</td><td>LoD &lt; c &lt; LoQ</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Cr</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Ni</td><td>0.40 ± 0.01</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Cu</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td><td>1.92 ± 0.03</td></tr><tr><td>Se</td><td>&lt; LoD</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Mo</td><td>0.050 ± 0.003</td><td>0.152 ± 0.008</td><td>0.070 ± 0.002</td></tr><tr><td>Ag</td><td>&lt; LoD</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Cd</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Sn</td><td>0.060 ± 0.003</td><td>&lt; LoD</td><td>&lt; LoD</td></tr><tr><td>Sb</td><td>LoD &lt; c &lt; LoQ</td><td>0.23 ± 0.01</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Ba</td><td>0.200 ± 0.007</td><td>0.1881 ± 0.0004</td><td>6.60 ± 0.06</td></tr><tr><td>Pt</td><td>0.010 ± 0.002</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Hg</td><td>LoD &lt; c &lt; LoQ</td><td>&lt; LoD</td><td>&lt; LoD</td></tr><tr><td>Tl</td><td>LoD &lt; c &lt; LoQ</td><td>0.0027 ± 0.0003</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Pb</td><td>0.040 ± 0.002</td><td>0.2081 ± 0.0004</td><td>0.716 ± 0.003</td></tr><tr><td colspan="4" style="text-align:center; font-weight:bold;">Standard addition</td></tr><tr><td>As</td><td>&lt; LoD</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Au</td><td>0.12 ± 0.06</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Co</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td><td>&lt; LoD</td></tr><tr><td>Os</td><td>LoD &lt; c &lt; LoQ</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Pd</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td><td>&lt; LoD</td></tr><tr><td>Rh</td><td>0.006 ± 0.003</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>V</td><td>&lt; LoD</td><td>LoD &lt; c &lt; LoQ</td><td>&lt; LoD</td></tr><tr><td>Ir</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td><td>LoD &lt; c &lt; LoQ</td></tr><tr><td>Ru</td><td>&lt; LoD</td><td>&lt; LoD</td><td>&lt; LoD</td></tr></tbody></table>

<footnote><sup>a</sup> 30% PDE for an oral administration route (J values).</footnote>
quantified. In fact, elements such as Au, Ba, Mo, Ni, Pb, Pt, Rh and Sn were quantified in drug A. In drug B, the elements Ba, Mo, Pb, Sb and Tl were found. While the presence of Mo and Ni was characteristic of stainless steel and likely originated from the manufacturing process, the other elements may come from catalysts (Au, Pt and Rh) or added excipients, especially talc in drug A and magnesium stearate in drug B. This study demonstrated that applying a mineralization protocol with hydrofluoric acid was beneficial for solubilizing excipients such as talc, magnesium stearate, silica, or titanium dioxide, as they represented potential drug contaminants.

## 4. Conclusion

This study developed an analytical method for the determination of elemental impurities in drug products using experimental designs for the optimization of the sample preparation step. One of the most innovative aspects of this work was the application of isotopic dilution for the quantification of elemental impurities by ICP-MS. The presence of high levels of carbon in pharmaceutical samples and the occurrence of excipients generated significant matrix effects that were challenging for classical quantification methods. For elements stable in solution and having two non-interfering isotopes, the application of isotopic dilution allows to overcome these difficulties. This method has also proven to be able to correct solubilization defects when tracers were added before digestion. After a successful validation of the method according to USP requirements, the method was applied to different drug products. It was shown that isotopic dilution provided a unique sample preparation procedure regardless of the drug. It would be beneficial to apply this method to a wider range of drugs in order to assess its robustness and assist health authorities in enhancing the quality control of pharmaceuticals.

### CRediT authorship contribution statement

**Ines Korbi:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. **Mathieu Menta:** Writing – review & editing, Supervision, Investigation, Formal analysis. **Justine Verdeil:** Validation, Methodology, Formal analysis. **Véronique Vacchina:** Writing – review & editing, Supervision, Methodology. **Pablo Rodríguez-González:** Writing – review & editing, Methodology, Conceptualization. **Olivier F.X. Donard:** Writing – review & editing, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization. **Houyem Abderrazak:** Writing – review & editing, Supervision, Resources, Project administration. **Fabienne Séby:** Writing – review & editing, Writing – original draft, Supervision, Software, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.

### Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Ines Korbi reports financial support was provided by European Commission. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgments

The authors are grateful to the TUNTWIN project - the Horizon 2020 Framework Program of the European Union under the grant N° 952306 for supporting this study and to the High Ministry of Education and Research in Tunisia for doctoral grant.

## Appendix A. Supplementary data

Please find supplementary material provided with this file. Supplementary data to this article can be found online at [https://doi.org/10.1016/j.microc.2025.114785].

### Data availability

Data will be made available on request.

### References

[1] A.L. Muller, J.S. Oliveira, P.A. Mello, E.I. Muller, E.M. Flores, Study and determination of elemental impurities by ICP-MS in active pharmaceutical ingredients using single reaction chamber digestion in compliance with USP requirements, Talanta 136 (2015) 161–169, https://doi.org/10.1016/j.talanta.2014.12.023.

[2] C. Stoving, H. Jensen, B. Gammelgaard, S. Stürup, Development and validation of an ICP-OES method for quantitation of elemental impurities in tablets according to coming US pharmacopeia chapters, J. Pharm. Biomed. Anal. 84 (2013) 209–214, https://doi.org/10.1016/j.jpba.2013.06.007.

[3] A.C.M. Aleluia, M. de Souza Nascimento, A.M. Pinto dos Santos, W.N. Lopes dos Santos, A. de Freitas Santos Júnior, S.L. Costa Ferreira, Analytical approach of elemental impurities in pharmaceutical products: a worldwide review, Spectrochim. Acta B 205 (2023) 106689, https://doi.org/10.1016/j.sab.2023.106689.

[4] F.C. Pinheiro, J.A. Nóbrega, An overview of sample preparation procedures for determination of elemental impurities in medicines, Microchem. J. 175 (2022) 107189, https://doi.org/10.1016/j.microc.2022.107189.

[5] N. Lewen, The use of atomic spectroscopy in the pharmaceutical industry for the determination of trace elements in pharmaceuticals, J. Pharm. Biomed. Anal. 55 (2011) 653–661, https://doi.org/10.1016/j.jpba.2010.11.030.

[6] V. Balaram, Recent advances in the determination of elemental impurities in pharmaceuticals –status, challenges and moving frontiers, TrAC-trends Anal. Chem. 80 (2016) 83–95, https://doi.org/10.1016/j.trac.2016.02.001.

[7] P. Pohl, A. Bielawska-Pohl, A. Dzimitrowicz, P. Jamroz, M. Welna, Impact and practicability of recently introduced requirements on elemental impurities, TrAC-trends Anal. Chem. 101 (2018) 43–55, https://doi.org/10.1016/j.trac.2017.09.011.

[8] The United States Pharmacopeia convention. The United States Pharmacopeia, chapter 231: heavy metals, in: Revision Bulletin, Official January 1, 2018.

[9] The United States Pharmacopeia convention. The United States Pharmacopeia, chapter 232: elemental impurities—limits, in: Revision Bulletin, Official January 1, 2018.

[10] The United States Pharmacopeia convention. The United States Pharmacopeia, chapter 233: elemental impurities—procedures, in: Revision Bulletin, Official January 1, 2018.

[11] J.S. Barin, P.A. Mello, M.F. Mesko, F.A. Duarte, E.M.M. Flores, Determination of elemental impurities in pharmaceutical products and related matrices by ICP-based methods: a review, Anal. Bioanal. Chem. 408 (2016) 4547–4566, https://doi.org/10.1007/s00216-016-9471-6.

[12] N. Lewen, Preparation of pharmaceutical samples for elemental impurities analysis: some potential approaches, Spectroscopy 31 (2016) 36–43.

[13] A.G. Althoff, C.B. Williams, T. McSweeney, D.A. Gonçalves, G.L. Donati, Microwave-induced plasma optical emission spectrometry (MIP OES) and standard dilution analysis to determine trace elements in pharmaceutical samples, Appl. Spectrosc. 71 (2017) 2692–2698, https://doi.org/10.1177/0003702817721750.

[14] L. Fischer, B. Zipfel, G. Koellensperger, J. Kovac, S. Bilz, A. Kunkel, C. Venzago, S. Hann, Flow injection combined with ICP-MS for accurate high throughput analysis of elemental impurities in pharmaceutical products according to USP <232>/<233>, J. Pharm. Biomed. Anal. 95 (2014) 121–129, https://doi.org/10.1016/j.jpba.2014.02.016.

[15] K. Van Hoecke, C. Catry, F. Vanhaecke, Optimization of sample preparation and a quadrupole ICP-MS measurement protocol for the determination of elemental impurities in pharmaceutical substances in compliance with USP guidelines, J. Anal. At. Spectrom. 27 (2012) 1909–1919, https://doi.org/10.1039/C2JA30128H.

[16] O. Chahrou, J. Malone, M. Collins, V. Salmon, C. Greenan, A. Bombardier, Z. Ma, N. Dunwoody, Development and validation of an ICP-MS method for the determination of elemental impurities in TP-6076 active pharmaceutical ingredient (API) according to USP <232>/<233>, J. Pharm. Biomed. Anal. 145 (2017) 84–90, https://doi.org/10.1016/j.jpba.2017.06.045.

[17] X. Gu, S. Zhu, L. Yan, L. Cheng, P. Zhu, J. Zheng, Development of a sample preparation method for accurate analysis of 24 elemental impurities in oral drug products by ICP-MS according to USP/ICH guidelines, J. Anal. At. Spectrom. 36 (2021) 512–517, https://doi.org/10.1039/d0ja00519c.

[18] E. Holmfred, A. Alrijjal, C.P. Chamberlain, K. Maher, S. Stürup, Determination of trace elements in ibuprofen drug products using microwave-assisted acid digestion and inductively coupled plasma-mass spectrometry, Heliyon 10 (2024) e23566, https://doi.org/10.1016/j.heliyon.2023.e23566.

[19] M. Riisom, B. Gammelgaard, I.H. Lambert, S. Stürup, Development and validation of an ICP-MS method for quantification of total carbon and platinum in cell
samples and comparison of open-vessel and microwave-assisted acid digestion methods, J. Pharm. Biomed. Anal. 158 (2018) 144–150, https://doi.org/10.1016/j.jpba.2018.05.038.

[20] F.C. Pinheiro, A.I. Barros, J.A. Nóbrega, Microwave-assisted sample preparation of medicines for determination of elemental impurities in compliance with United States Pharmacopeia: how simple can it be? Anal. Chim. Acta 1065 (2019) 1–11, https://doi.org/10.1016/j.aca.2019.03.016.

[21] U. Wollein, B. Bauer, R. Habernegg, N. Schramek, Potential metal impurities in active pharmaceutical substances and finished medicinal products—a market surveillance study, Eur. J. Pharm. Sci. 77 (2015) 100–105, https://doi.org/10.1016/j.ejps.2015.05.028.

[22] C.A. Bizzi, M.F. Pedrotti, J.S. Silva, J.S. Barin, J.A. Nóbrega, E.M.M. Flores, Microwave-assisted digestion methods: towards greener approaches for plasma-based analytical techniques, J. Anal. At. Spectrom. 32 (2017) 1448–1466, https://doi.org/10.1039/c7ja00108h.

[23] T. Pluháček, J. Hanzal, J. Hendrych, D. Milde, Microwave-assisted digestion using nitric acid for heavy metals and sulfated ash testing in active pharmaceutical ingredients, Pharmazie 71 (2016) 177–180, https://doi.org/10.1691/ph.2016.5140.

[24] K.H. Nam, R. Isensee, G. Infantino, K. Putyera, X. Wang, Microwave-induced combustion for ICP-MS: a generic approach to trace elemental analyses of pharmaceutical products, Spectroscopy 26 (2011) 36–41.

[25] L. Whitecotton, G. Gilleland, E. Kulikov, A. Liba, Elemental Impurities in Aspirin: USP <232>/<233> and ICH Q3D Methods Using ICP-OES, Application note Agilent, 2021.

[26] C. Venzago, M. Popp, J. Kovac, A. Kunkel, Pharmacopeial requirements for elemental impurities: a novel approach to the trace determination of osmium by oxidative pressure vessel sample digestion and measurement using inductively coupled plasma mass spectrometry (ICP-MS) after complexation and stabilisation, J. Anal. At. Spectrom. 28 (2013) 1125–1129, https://doi.org/10.1039/c3ja50040c.

[27] G. Li, D. Schoneker, K.L. Ulman, J.J. Sturm, L.M. Thackery, J.F. Kauffman, Elemental impurities in pharmaceutical excipients, J. Pharm. Sci. 104 (2015) 4197–4206, https://doi.org/10.1002/jps.24650.

[28] G. Grindlay, J. Mora, M. de Loos-Vollebregt, F. Vanhaecke, A systematic study on the influence of carbon on the behavior of hard-to-ionize elements in inductively coupled plasma-mass spectrometry, Spectrochim. Acta B 86 (2013) 42–49, https://doi.org/10.1016/j.sab.2013.05.002.

[29] J.A. Carter, A.I. Barros, J.A. Nóbrega, G.L. Donati, Traditional calibration methods in atomic spectrometry and new calibration strategies for inductively coupled plasma mass spectrometry, Front. Chem. 6 (2018) 504, https://doi.org/10.3389/fchem.2018.00504.

[30] K.E. Jarvis, A.L. Gray, R.S. Houk, I. Jarvis, J.W. MacLaren, J.G. Williams, Handbook of Inductively Coupled Plasma Mass Spectrometry, Springer, New York, 1992.

[31] J. Vogl, W. Pritzkow, Isotope dilution mass spectrometry — a primary method of measurement and its role for RM certification, Mapan - J. Metrol. Soc. India 25 (2010) 135–164, https://doi.org/10.1007/s12647-010-0017-7.

[32] International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use, ICH harmonised guideline, guideline for elemental impurities Q3D(R1), March 22, 2019.

[33] J.I. Garcia Alonso, P. Rodriguez-Gonzalez, Isotopic Mass Dilution Spectrometry, Royal Society of Chemistry, Cambridge, 2013.

[34] K. Simitchiev, V. Stefanova, V. Kmetov, G. Andreev, N. Kovachev, A. Canals, Microwave-assisted cloud point extraction of Rh, Pd and Pt with 2-mercaptobenzothiazole as preconcentration procedure prior to ICP-MS analysis of pharmaceutical products, J. Anal. At. Spectrom. 23 (2008) 717–726, https://doi.org/10.1039/B715133K.

[35] A. Krejcová, I. Ludvikova, T. Cernohorsky, M. Pouzar, Elemental analysis of nutritional preparations by inductively coupled plasma mass and optical emission spectrometry, Food Chem. 132 (2012) 588–596, https://doi.org/10.1016/j.foodchem.2011.10.076.

[36] S. Ghattavi, A. Nezamzadeh-Ejhieh, GC-MASS detection of methyl orange degradation intermediates by AgBr/g-C₃N₄: experimental design, bandgap study, and characterization of the catalyst, Int. J. Hydrog. Energy 45 (2020) 24636–24656, https://doi.org/10.1016/j.ijhydene.2020.06.207.

[37] S. Salesi, A. Nezamzadeh-Ejhieh, An experimental design study of photocatalytic activity of the Z-scheme silver iodide/tungstate binary nano photocatalyst, Environ. Sci. Pollut. Res. Int. 48 (2023) 105440–105456, https://doi.org/10.1007/s11356-023-29730-z.

[38] M. Nosuhi, A. Nezamzadeh-Ejhieh, High catalytic activity of Fe(II)-clinoptilolite nanoparticales for indirect voltammetric determination of dichromate: experimental design by response surface methodology (RSM), Electrochim. Acta 223 (2017) 47–62, https://doi.org/10.1016/j.electacta.2016.12.011.

[39] L.V. Candioti, M.M. De Zan, M.S. Cámara, H.C. Goicoechea, Experimental design and multiple response optimization. Using the desirability function in analytical methods development, Talanta 124 (2014) 123–138, https://doi.org/10.1016/j.talanta.2014.01.034.

[40] S. Sharafzadeh, J. Zolgharnein, A. Nezamzadeh-Ejhieh, A co-precipitation synthesized Zn(II)/Ni(II) magnetic heterostructure ferrite for photocatalytic degradation of metronidazole: charge carriers transfer mechanism, kinetics and thermodynamic aspects, Int. J. Hydrog. Energy 106 (2025) 1429–1442, https://doi.org/10.1016/j.ijhydene.2025.02.031.

[41] H. Derikvandi, A. Nezamzadeh-Ejhieh, Designing of experiments for evaluating the interactions of influencing factors on the photocatalytic activity of NiS and SnS₂: Focus on coupling, supporting and nanoparticles, J. Colloid Interface Sci. 490 (2017) 628–641, https://doi.org/10.1016/j.jcis.2016.11.102.

[42] H.M. Kingston, L.B. Jassie, Microwave energy for acid decomposition at elevated temperatures and pressures using biological and botanical samples, Anal. Chem. 58 (1986) 2534–2541, https://doi.org/10.1021/ac00125a038.