LC-MS/MS method for co-estimation of doxorubicin and piperine: formulation development and pharmacokinetic studies

ABSTRACT

Introduction

Oral metronomic chemotherapy employs a low-dose combination of chemotherapeutics administered regularly to minimize toxicity while enhancing anticancer efficacy. The clinical utility of Doxorubicin (DOX) is limited due to severe cardiotoxicity. Interestingly, Piperine (PIP) has been explored to mitigate DOX-induced toxicity while enhancing its therapeutic efficacy. Solid lipid nanoparticles (SLNs) offer an efficient drug delivery approach to improve oral bioavailability and controlled release of DOX and PIP.

Areas Covered

LC-MS/MS method was developed and validated per US-FDA bioanalytical guidelines to quantify DOX and PIP in plasma simultaneously. SLNs were developed and optimized using design expert software and exhibited particle size of 151.56 ± 0.32 nm, polydispersity index (PDI) of 0.172 ± 0.02, and surface charge of −22.83 ± 0.66 mV. Pharmacokinetic evaluation in female Sprague-Dawley rats showed enhanced AUC₀–∞ for DOX (31911.78 ± 226.92 ng/mL) and PIP (7377.66 ± 655.78 ng/mL), indicating improved systemic exposure.

Expert Opinion

The findings highlight the potential of SLN-based co-delivery of DOX and PIP for oral metronomic chemotherapy. The validated LC-MS/MS method ensures precise pharmacokinetic assessment, which is crucial for future clinical translation. This study provides a promising strategy for enhancing oral chemotherapy efficacy.

Plain Language Summary

This study focuses on improving cancer treatment by using a special type of oral chemotherapy that involves giving low doses of drugs regularly to reduce side effects. Doxorubicin (DOX) is a common cancer drug but can harm the heart. Piperine (PIP), a natural compound found in black pepper, may help reduce this damage and make DOX work better. To deliver these drugs more effectively, scientists used tiny fat-based particles called solid lipid nanoparticles (SLNs). These SLNs were carefully designed and tested, showing they can carry both drugs in the body more efficiently. A highly sensitive testing method was also developed to measure the drug levels in the blood. The results showed that the SLNs helped both DOX and PIP stay in the body longer, which could make the treatment more effective. This approach may offer a safer and more efficient way to deliver chemotherapy drugs by mouth in the future.

TWEETABLE ABSTRACT

Solid lipid nanoparticles co-delivering doxorubicin and piperine improved oral bioavailability and reduced toxicity. A validated LC-MS/MS method enabled accurate plasma quantification.

GRAPHICAL ABSTRACT

Mechanistic scheme depicting the pharmacokinetic study of doxorubicin and piperine loaded solid lipid nanoparticles. Created with Biorender.com.

1. Introduction

Breast cancer is still a major worldwide health problem because of its rising prevalence and complex management and treatment options. It is the leading cause of mortality, especially among women worldwide [1]. Doxorubicin (DOX), a chemotherapeutic agent, is active against several cancers such as breast, lung, liver, and multiple myeloma. However, it has been noted that DOX possesses several adverse effects, such as cardiotoxicity, hepatotoxicity, and neurotoxicity [2]. Phytochemicals obtained from natural sources have shown great promise in combination therapy because of their low toxicity profiles and variety of bioactive characteristics. In recent years, exploring combinatorial therapies that minimize the adverse effects of chemotherapeutics and improve their anti-cancer efficacy has drawn more attention [3]. Piperine (PIP) manifests several pharmacological activities; anticancer activity has been widely explored. Interestingly, PIP has been reported to be effective against the cardiotoxicity induced by DOX [4].

The liquid chromatography-mass spectrometry (LC-MS/MS) method is an essential pharmaceutical analysis technique that guarantees the precision, consistency, and repeatability of quantitative findings for therapeutically active agents. Simultaneous quantification of DOX and PIP presents a substantial challenge due to differences in their chemical characteristics. The chemical structure of DOX and PIP are shown in Figure S1. As far as we know, no single bioanalytical technique has been developed to determine DOX and PIP utilizing LC-MS/MS simultaneously. However, bioanalytical methods for the quantification of DOX, along with other therapeutic agents, have been reported. Qi et al. developed a simultaneous LC-MS/MS method for quantifying pirarubicin, DOX, cyclophosphamide, and vincristine. The method was applied to quantify these drugs in clinical patients with non-Hodgkin lymphoma [5]. Likewise, Altalal et al. developed a simultaneous LC-MS/MS method for quantifying DOX and sorafenib in rat plasma. Improved C_max and Area under the curve (AUC) were obtained when both drugs were administered simultaneously [6]. Similarly, PIP has been quantified simultaneously using LC-MS/MS with other therapeutic agents such as curcumin, demethoxycurcumin, bisdemethoxycurcumin, and tetrahydrocurcumin. A gradient method containing methanol in 0.1% formic acid was used to resolve these compounds [7]. Basu et al. developed an LC-MS/MS method for the simultaneous estimation of PIP, cinnamic acid, and gallic acid. A polarity switch technique was employed to estimate piperine in the positive mode, whereas cinnamic acid and gallic acid were quantified in the negative mode [8].

Despite extensive reports on the individual or combined quantification of DOX and PIP with other agents, there is currently no validated LC-MS/MS method available for their simultaneous estimation. The distinct physicochemical properties of DOX (a hydrophilic chemotherapeutic agent with a high molecular weight and polar functional groups) and PIP (a lipophilic phytochemical with poor aqueous solubility) make their simultaneous extraction and detection particularly challenging [9,10]. This analytical incompatibility complicates chromatographic separation, ionization efficiency, and matrix effects. Therefore, the development of a robust, sensitive, and selective LC-MS/MS method capable of simultaneously quantifying both drugs in a single run addresses a critical gap in current bioanalytical methodologies.

Nanotechnology has transformed drug delivery by utilizing nanocarriers such as liposomes, nanoparticles, micelles, and nanoemulsions to deliver therapeutic agents at the target site [11]. Drugs can be loaded onto the surface or inside the matrix of these nanocarriers, allowing for controlled release and extended circulation within the body. Solid lipid nanoparticles (SLNs) are one such nanocarrier composed of solid lipids dispersed in the aqueous phase, which offer a promising platform for encapsulation of dual drugs such as DOX and PIP [12].

In the present work, a bioanalytical LC-MS/MS method for simultaneous quantification of DOX and PIP has been developed and validated. Subsequently, we formulated and optimized solid lipid nanoparticles for oral delivery of DOX and PIP. The applicability of the method was demonstrated by performing pharmacokinetic studies using the optimized nanoformulation to obtain a better bioavailability profile.

2. Materials and methods

2.1. Chemicals

DOX was received as a gift sample from Alembic Pharmaceuticals Pvt. Ltd., Vadodara, India. PIP was purchased from Tokyo Chemical Industry Co., Ltd. (TCI), India. Phenacetin (internal standard), formic acid (≥98%), and LC-MS/MS-grade solvents (methanol and acetonitrile) were obtained from Sigma-Aldrich, Merck Life Science Private Limited, Bengaluru, India, originally sourced from Sigma-Aldrich, CA, USA. Milli-Q water was produced using an in-house water purification system (EMD Millipore, Billerica, MA, USA). Precirol® ATO 5 was provided as a complimentary sample by Gattefossé India Pvt. Ltd., Mumbai, India. Tween 80 and propylene glycol were procured from Sigma-Aldrich, Merck Life Science Private Limited, Bengaluru, India.

2.2. Animals

Young female Sprague-Dawley (SD) rats (weight range: 240–260 g), non-genetically modified, were obtained from the Animal Laboratory Facility, CSIR-Central Drug Research Institute, India, and acclimatized for 7 days prior to the experiment under standard laboratory conditions. All experimental procedures were approved by the Institutional Animal Ethics Committee (IAEC/2023/109) of CSIR-Central Drug Research Institute, India, following the guidelines of the Committee for the Purpose of Control and Supervision of Experiments on Animals (CCSEA), Government of India. The study was conducted in accordance with the ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) to ensure transparency and humane animal research practices. Rats were housed in polypropylene cages (3 rats per cage) under controlled environmental conditions. Commercially available pelleted feed and potable drinking water were provided to the animals ad libitum. The temperature in the experimental animal room was maintained at 22°C ±3°C, and the relative humidity was within 30–70%. The lighting was artificial, and the photoperiod was maintained at a 12-hour light and 12-hour dark cycle. Appropriate cleaning and hygiene were maintained.

2.3. LC-MS/MS conditions

A liquid chromatographic system (ABSciex QTRAP, LC-MS/MS, Framingham, MA, USA) with an autosampler (Shimadzu Corporation, Kyoto, Japan), a column oven (CTO-20AC; Shimadzu), and an LC-20AD binary pump were used for the method development. 4000 Q TRAP-, mass spectrometer instrument in positive mode was used for the quantification of both drugs. Multiple reaction monitoring (MRM) mode was utilized for the analysis. DOX, PIP, and Phenacetin as internal standard (IS) were isolated using Zorbax SB C18 column (4.6 × 100 mm, 3.5 µm; Agilent Technologies Inc., Santa Clara, CA, USA) having a mobile phase of 0.1% formic acid (FA) in methanol and milli-Q water (80:20, %v/v). The injection volume was kept at 20 µL, and the analysis’s flow rate and total run time were 0.6 mL/min and 5 minutes, respectively. The column oven and autosampler temperature were set at 4°C and 30°C, respectively. Data acquisition and quantification were performed using Analyst® software version 1.6 (Applied Biosystems, MDS Sciex, Toronto, Canada).

2.4. Preparation of calibration standards and quality control samples

The Primary DOX, PIP, and IS stock solution was prepared in acetonitrile (ACN). Various working stock solutions were prepared using ACN from the primary stock solution. The calibration stock solutions were prepared for DOX and PIP in the range 100, 200, 500, 1000, 2000, 4000, 6000, and 10,000 ng/mL using ACN. Similarly, working stock solutions for quality control samples were prepared using 100, 300, 3900, and 7500 ng/mL of DOX and PIP in ACN. The plasma samples for various calibrators and quality control samples were prepared by spiking 5 µL of working stock solutions to 45 µL of fresh SD rat plasma [13]. The final calibration standards were prepared in the range of 10, 20, 50, 100, 200, 400, 600, and 1000 ng/mL. The final QC samples of DOX and PIP were prepared at different concentration levels, such as LLOQ, indicated as the lower limit of quantification (10 ng/mL), LQC indicated as lower-quality-control (30 ng/mL), MQC indicated as medium-quality-control (390 ng/mL), and HQC indicated as high-quality-control (750 ng/mL). Samples were stored in the refrigerator until further use [14].

2.5. Extraction and sample processing

A simple protein precipitation method was used to process the plasma samples [15]. Briefly, various calibrators, quality control samples, and IS solution were spiked into fresh rat plasma and then vortexed for about 20–25 seconds. Afterward, 100 µL of 0.1% FA in ACN was added to each radioimmunoassay (RIA) tube. The obtained mixtures were vortexed for 5 minutes and then centrifuged for 10 minutes at 4500 rotations per minute (rpm). After centrifugation, 50 µL of the supernatant was collected and injected into the LC-MS/MS for analysis [16].

2.6. Validation of the developed LC-MS/MS method

Following US-FDA requirements enabled the developed LC-MS/MS technique to be validated [17]. As per the guidelines, the developed method was validated by analyzing the analytes’ linearity, accuracy, precision, extraction recovery, carryover effect, dilution integrity, and stability profile [18].

2.6.1. Selectivity and specificity of the analytes

The analytes’ specificity was assessed to confirm that no exogenous or endogenous interference was present [19]. Plasma samples were spiked with DOX, PIP, and IS (n = 6) to determine the presence of chromatographic noise or any interference from the biological matrix [20].

2.6.2. Linearity curve of the analytes and limit of detection

The calibration curve of the analytes was plotted by using the average peak area ratio of DOX and PIP to IS against the nominal calibration standard strengths. The calibration standards were produced with final concentrations of 10, 20, 50, 100, 200, 400, 600, and 1000 ng/mL. The results obtained were fitted using $1\mathit{x}2\mathit{x}2$ Weighted factor in least-square regression analysis. The acceptable limit for calibration standards as per guidelines is ± 15%. The limit of detection and quantitation were determined using the signal-to-noise (S/N) ratio method, where an S/N ratio greater than 3 was used for the limit of detection (LOD) and greater than 10 for the limit of quantification (LOQ) [21].

2.6.3. Accuracy and precision

Analyzing replicates of various concentrations of quality control samples throughout the assay range is a crucial step during the validation of the developed method. This is done by evaluating the accuracy and precision over the quantitation range during method development [22]. Various quality control samples, LLOQ, LQC, MQC, and HQC, with concentrations of 10, 30, 390, and 750 ng/mL, were analyzed (n = 6). As per guidelines, the acceptable limit for all the quality control samples is ± 15%, except LLOQ, which should not exceed ± 20%.

2.6.4. Recovery and matrix effect of the analytes

The recovery of DOX and PIP along with IS was calculated from the plasma matrix by relating the peak area ratio of the analyte, which was pre-spiked before extraction, to the post-spiked extracted sample for all the quality control samples (LLOQ, LQC, MQC, and HQC, n = 3). Similarly, the matrix effect of all the quality control samples was analyzed by comparing the pre-spiked extracted samples with those of post-spiked extracted samples [23].

2.6.5. Carryover effect and dilution integrity

An analyte concentration of 1000 ng/mL was injected to investigate the carryover impact, followed by the injection of a blank plasma sample into the LC-MS/MS. The dilution integrity was verified by diluting the SD rat plasma sample (20 times, containing 20,000 ng/mL, n = 6) of DOX and PIP to obtain 1000 ng/mL. The acceptable limit as per US-FDA guidelines is ± 15% [24].

2.7. Stability studies

Following US-FDA criteria at different quality control levels, including LLOQ, LQC, MQC, and HQC, stability studies were conducted to evaluate the stability of analytes in the biological matrix [25]. Various stability study parameters were studied, such as autosampler stability, benchtop stability, freeze-thaw stability, and long-term stability [26]. For autosampler stability, the samples were kept at 4°C for 12 hours, at 25 ± 4°C for 8 hours for benchtop stability, and at −70 ± 10°C for 30 days to assess the long-term stability. The freeze-thaw stability was assessed after three cycles of freezing and thawing of the samples, which were then analyzed in LC-MS/MS. For all QC samples, the limit of % RSD should not exceed ± 15% [27].

2.8. Applicability of the developed LC-MS/MS method: formulation development and pharmacokinetics studies

The developed method was applied to the formulation development of solid lipid nanoparticles loaded with DOX and PIP and investigated its pharmacokinetic profile in female SD rats.

2.8.1. Optimization of SLNs loaded with DOX and PIP (DOX-PIP-SLN) using design-expert software

2.8.1.1. Ternary phase diagram of SLNs

A ternary phase diagram was employed using the water titration method to optimize the concentration range of surfactant, co-surfactant, and lipid. Briefly, Tween 80 and propylene glycol were mixed to form a surfactant/co-surfactant mixture (1:4). Thereafter, lipid Precirol® ATO 5 (Glyceryl palmitostearate) was heated at 85°C using a water bath and combined with the surfactant and co-surfactant mixture to produce a monophasic system. A ternary phase diagram comprising the solid lipid nanoparticles was created in relation to the lipid and surfactant/co-surfactant combination at weight ratios of 1:9 to 9:1. Following gentle titration with aliquots of distilled water, phase clarity was visually observed to determine the transparency, viscosity, and homogeneity. The phase diagram was examined in order to determine the requisite percentages of lipid, surfactant, and co-surfactant needed to formulate solid lipid nanoparticles.

2.8.1.2. Optimization of SLNs using design Expert software

Box – Behnken experimental design was employed for the optimization of SLNs. The independent variables chosen were concentration of Precirol® as lipid, surfactants, and co-surfactants (Tween 80 and propylene glycol), and sonication time (Table S1). The dependent variables were particle size (d.nm), polydispersity index (PDI), and zeta potential (mV). The selected independent variables, Precirol® concentration (lipid), Tween 80 and propylene glycol (surfactant/co-surfactant), and sonication time, were chosen due to their critical roles in influencing droplet formation, size, and formulation stability. These parameters directly affect the characteristics of lipid-based nanoformulations. The dependent variables particle size, PDI, and zeta potential were selected as they are key indicators of formulation performance, including stability, uniformity, and potential bioavailability. Optimizing these variables using Box – Behnken design helps in understanding the interactions among components and identifying the ideal conditions for a stable and effective formulation. This approach ensures quality by design (QbD)-driven development. The final formulation was developed using the processing factors at their optimal concentration, and it was then characterized [28]. The ultrasound method was employed to produce the SLNs [29]. Briefly, the optimized concentration of lipid Precirol® was heated along with the drug PIP in a water bath. Then, the aqueous phase containing Tween 80, propylene glycol, and drug DOX was vortexed and heated to 65°C [30]. Following the addition of the aqueous phase to the lipid phase, the pre-emulsion was homogenized for five minutes at a high speed (10,000 rpm) using an IKA homogenizer. The resulting emulsion was subjected to additional sonication using a probe sonicator. Following this, the dispersion was progressively cooled to obtain solid lipid nanoparticles [31].

2.8.2. Characterization of the prepared DOX-PIP-SLN

The DOX-PIP-SLN was characterized for its particle size distribution, PDI, and surface charge using a Malvern Zetasizer [32]. Moreover, the drug loading and entrapment efficiency were estimated using the developed LC-MS/MS method. Briefly, 1 mL of DOX-PIP-SLN was centrifuged at 8,000 rpm for 10 minutes, and the supernatant was analyzed in LC-MS/MS to get the unentrapped drug [33]. Entrapment efficiency (%) and drug loading (%) of DOX-PIP-SLN was calculated as follows

$$\%\mathit{Entrapment}\mathit{efficiency}=\frac{\mathit{Amount}\mathit{of}\mathit{drug}\mathit{in}\mathit{DOX}-\mathit{PIP}-\mathit{SLN}}{\mathit{Total}\mathit{amount}\mathit{of}\mathit{drug}\mathit{added}\mathit{in}\mathit{DOX}-\mathit{PIP}-\mathit{SLN}}\times 100$$

$$\mathit{Drug}\mathit{loading}\left(\mathrm{\%}\right)=\frac{\mathit{Amount}\mathit{of}\mathit{drug}\mathit{in}\mathit{DOX}-\mathit{PIP}-\mathit{SLN}}{\mathit{Total}\mathit{weight}\mathit{of}\mathit{the}\mathit{DOX}-\mathit{PIP}-\mathit{SLN}}\times 100$$

2.8.3. Pharmacokinetic studies

The oral pharmacokinetic study of free DOX and PIP in combination and DOX-PIP-SLN was performed on healthy female SD rats (240–260 g) that were on an overnight fast. Female SD rats were used as a well-established model for pharmacokinetic evaluation due to their physiological similarity to humans in oral drug absorption. The free drug suspension was prepared by dissolving both drugs in 0.25% sodium carboxymethyl cellulose. The dose was 10 mg/kg for both DOX and PIP, based on the animal’s body weight. For the pharmacokinetic study, the animals were divided into two groups (n = 6, each): group I (Free DOX-PIP) and group II (DOX-PIP-SLN). Two groups were compared: Group I received Free DOX-PIP (reference group), and Group II received DOX-PIP-SLN (test group). Group I served as the reference comparator to evaluate the pharmacokinetic profile of the developed nanoformulation. Sample size (n = 6 per group) was selected based on prior literature demonstrating adequate statistical power to detect pharmacokinetic differences in rats [34]. No randomization was performed, animals were assigned to groups based on body weight matching. No formal strategy was used to control confounders, but all animals were kept under identical housing conditions, and procedures were performed at the same time each day to reduce variability. No animals or data points were excluded during the experiment or analysis. After oral dosing of both free DOX-PIP and DOX-PIP-SLN, blood samples (200–250 µL/each rat) were collected at varying time points (0.08, 0.25, 0.5, 1, 2, 6, 12, 24, 48 hours) from the retro-orbital plexus. Light anesthesia (using isoflurane) was administered during blood collection to prevent discomfort. The collected blood samples were centrifuged to obtain plasma [35]. The PK profile was determined using a non-compartmental model using the software Pheonix 6.3 WinNonlin (Pharsight Corporation, Mountain View, CA, USA). Blinding was not applied during group allocation, experiment conduct, or data analysis. However, objective pharmacokinetic parameters (e.g., plasma drug concentration, AUC, C_max) were used as outcome measures, which minimized the risk of observer bias. The primary outcome measures assessed were pharmacokinetic parameters, including plasma concentration of DOX and PIP, AUC, maximum plasma concentration (C_max), time to reach maximum plasma concentration (T_max), half-life (t½), and clearance (CL). These parameters were calculated from plasma concentration-time data collected at predetermined time points following drug administration. No formal testing for statistical assumptions (normality or homogeneity of variance) was performed. Due to the descriptive nature of pharmacokinetic data, non-compartmental analysis was applied. Data were reported as mean ± SD (n = 6 per group) for all pharmacokinetic parameters. After the pharmacokinetic study, the carbon dioxide asphyxia euthanasia method was employed, ensuring a humane endpoint.

3. Results

3.1. Optimization of LC-MS/MS conditions

To quantify the drugs DOX and PIP, a 4000 QTRAP MS/MS equipped with an electrospray ionization (ESI) source was used. Other parameters of the MS were optimized by directly introducing pure samples of DOX, PIP, and IS into the MS source. Both positive and negative modes were tested for ionization during the optimization process. Based on the intensity, the positive polarity [M + 1]⁺ mode was selected for DOX, PIP, and IS quantification (Table 1). The m/z ratio indicating the precursor and product ions for DOX, PIP, and IS was optimized as 544.5 → 397.4, 286.3 →201.2, and 180.2 → 110.2, respectively (Figure 1). By modifying the pH, changing the mobile phase, and utilizing different columns, the LC parameters were optimized. A mobile phase containing 0.1% FA in methanol and 0.1% FA in milli-Q water (80:20%, v/v) showed an excellent drug peak shape. A Zorbax SB column (4.6 × 100 mm, 3.5 µm) was employed to separate DOX, PIP and IS. Phenacetin was preferred as the IS due to its suitable chromatographic retention, effective ionization, and favorable extraction behavior.

Table 1.

LC-MS/MS parameters for DOX, PIP, and IS.

Instrument variable
LC parameters	Injection volume	20 µL
	Column temperature	30º C
	Flow rate	0.6 mL/min
	Mode	Isocratic
Mobile phase		0.1% formic acid in methanol and 0.1% formic acid in Milli-Q water (80:20, %v/v)
MS/MS		DOX	PIP	Phenacetin (IS)
Precursor ion (Q1)		544.5	286.3	180.2
Product ion (Q3)		397.34	201.2	110.2
Declustering potential (DP)		90	100	80
Entrance potential (EP)		10	10	10
Collision energy (CE)		17	24	27
Collision exit potential (CXP)		20	10	19

Other Source parameters: Curtain gas = 20, Collision gas = High, Ion spray voltage = 5500 V, Temperature = 500°C, Ion source gas: (GS1 = 50 and GS2 = 70).

LC: Liquid chromatography; MS: Mass spectrometry; IS: Internal standard.

Figure 1.

MRM spectra of (A) DOX (m/z: 544.3 → 397.4), (B) PIP (m/z: 286.3 → 201.2), and (C) internal standard (Phenacetin, m/z: 180.2 → 110.2) obtained using LC-MS/MS in positive ion mode. Analytes were dissolved in methanol, and spectra were acquired under optimized conditions using a 4000 QTRAP mass spectrometer. MRM transitions represent the most abundant precursor-to-product ion pairs selected for quantification.

3.2. Optimization of the extraction protocol

The extraction of the analytes was achieved by protein precipitation method. Various organic solvents were tried to efficiently extract the analytes, such as methanol, ACN, diethyl ether, tert-butyl methyl ether, and ethyl acetate. Because of its effective extraction and recovery, acetonitrile with 0.1% FA was used for protein precipitation. Reduced biomatrix interference further suggested using this solvent. The absolute mean recovery of DOX and PIP was found to be 78.37 ± 4.91 and 87.65 ± 7.41%, respectively.

3.3. LC-MS/MS method validation

3.3.1. Selectivity and specificity

The retention time of DOX, PIP and IS were found to be 1.91, 3.29, and 2.05 minutes. During the analysis, no endogenous peaks were identified, confirming the selectivity and specificity of the developed LC-MS/MS method. Figure 2 depicts the chromatograms of DOX, PIP and IS at various quality control concentrations such as LLOQ, HQC and in blank plasma.

Figure 2.

Chromatograms of (A) blank plasma, (B) internal standard (IS), Phenacetin (zero) spiked plasma (C) DOX and PIP spiked plasma with is at lower limit of quantification (LLOQ) (D) DOX and PIP spiked plasma with is at lower quality control (LQC) (E) DOX and PIP spiked plasma with is at higher quality control (HQC).

3.3.2. Linearity plot and limit of detection

A calibration range of 10–1000 ng/mL showed that the DOX and PIP calibration curve was linear and reproducible (Figure S2). The coefficient of determination (R²) for DOX and PIP was found to be 0.997 and 0.994, respectively. Table 2 shows the accuracy and precision table of various calibration standards of DOX and PIP in rat plasma. The method was validated with a lower limit of detection and quantification of 5 ng/mL and 10 ng/mL, respectively, for DOX and PIP based upon their signal-to-noise ratio.

Table 2.

Accuracy and precision data of back-calculated concentrations of calibration samples of DOX and PIP in rat plasma (mean ± SD, n = 3). Both compounds were initially dissolved in methanol. Plasma samples were processed using protein precipitation with acetonitrile containing 0.1% formic acid.

Nominal conc. (ng/mL)	Observed conc. (ng/mL, mean ± SD)	% Accuracy	% Precision
DOX in combination (DOX+PIP)
10	9.60 ± 0.30	94.35	1.57
20	21.70 ± 0.72	110.00	1.29
50	49.63 ± 4.57	101.80	11.39
100	101.60 ± 5.13	104.00	4.08
200	190.00 ± 8.19	94.60	6.13
400	405.67 ± 21.94	103.10	6.72
600	594.00 ± 26.66	97.00	4.37
1000	991.00 ± 82.89	94.65	4.56
PIP in combination (DOX+PIP)
10	9.23 ± 0.15	92.27	1.64
20	22.30 ± 0.40	111.00	1.80
50	52.70 ± 3.86	105.33	7.25
100	111.33 ± 0.58	111.33	0.52
200	210.00 ± 3.61	104.67	1.99
400	387.33 ± 16.26	96.83	4.24
600	534.33 ± 27.43	89.07	5.19
1000	888.33 ± 12.2	88.83	1.38

3.3.3. Accuracy and precision

Interday and intraday accuracy and precision was calculated by analyzing quality control samples (LLOQ, LQC, MQC and HQC). The established method was determined to be accurate and precise with all the assay values within the acceptable variable limits (≤ ± 15%), except for LLOQ which is less than 20% (Table 3).

Table 3.

Accuracy and precision results of DOX and PIP in rat plasma (mean ± SD, n = 6).

DOX in combination (DOX+PIP)
Intraday (n = 6)					Interday (n = 18)
Level	Nominal conc.	Observed conc. (ng/mL, mean ± SD)	% Accuracy	% Precision	Nominal conc.(ng/mL)	Observed conc. (ng/mL, mean ± SD)	% Accuracy	% Precision
LLOQ	10	9.64 ± 0.28	96.43	7.16	10	9.87 ± 0.23	98.73	2.37
LQC	30	28.97 ± 1.15	96.53	1.54	30	28.40 ± 1.75	94.73	6.13
MQC	390	426.08 ± 8.65	109.17	2.38	390	418.50 ± 10.19	107.33	2.41
HQC	750	741.33 ± 40.08	98.79	3.66	750	791.00 ± 17.69	105.33	2.14
PIP in combination (DOX+PIP)
Intraday (n = 6)					Interday (n = 18)
Level	Nominal conc. (ng/mL)	Observed conc. (ng/mL, mean ± SD)	% Accuracy	% Precision	Nominal conc.(ng/mL)	Observed conc. (ng/mL, mean ± SD)	% Accuracy	% Precision
LLOQ	10	9.38 ± 0.23	94.27	4.60	10	9.68 ± 0.55	96.80	5.73
LQC	30	32.08 ± 0.74	107.00	1.10	30	31.18 ± 0.44	103.83	1.13
MQC	390	421.25 ± 7.38	107.92	1.86	390	421.33 ± 14.08	107.83	3.39
HQC	750	688.83 ± 9.76	89.15	0.13	750	698.67 ± 16.42	93.17	2.33

LLOQ: Lower limit of quantification; LQC: Lower quality control; MQC: Medium quality control; HQC: Higher quality control.

3.3.4. Recovery and matrix effect

The extraction recovery after pre- and post-extraction of the analytes DOX and PIP was found to be 78.37 ± 4.91 and 87.65 ± 7.41%, respectively. By examining the matrix effect, one may be sure that ion enhancement or suppression is not being caused by endogenous interference from biological matrices [36]. Unaffected ionization was confirmed by the absence of matrix impact during the analysis of DOX and PIP.

3.3.5. Dilution integrity results and carry-over effect

For DOX and PIP, the accuracy after 20 times dilution was determined to be 109.0 and 96.47%, respectively, which was within the acceptable limit. Furthermore, examining the injected blank plasma after evaluating a higher analyte concentration revealed no carryover effect.

3.3.6. Stability

DOX and PIP were stable in rat plasma throughout a range of storage conditions as per USFDA guidelines, which could be encountered during routine research sample analysis. Table 4 shows the % accuracy of DOX and PIP at various storage conditions. The % accuracy was found to be within acceptable limits as per USFDA guidelines.

Table 4.

Stability studies of DOX and PIP in rat plasma samples (mean ± SD, n = 6).

Storage conditions	Level	Nominal conc. (ng/mL)	Observed conc. (ng/mL, mean ± SD)	% Accuracy	% Precision
DOX in combination (DOX+PIP)
Autosampler stability (4°C, 24 h)	LLOQ	10	9.93 ± 0.64	95.42	6.75
	LQC	30	31.40 ± 1.07	101.27	3.54
	MQC	390	437.00 ± 12.78	107.83	2.84
	HQC	750	812.00 ± 31.41	104.87	3.91
Bench Top Stability (24 ± 4°C, 8 h)	LLOQ	10	10.40 ± 0.92	99.18	9.23
	LQC	30	31.40 ± 1.90	104.93	6.02
	MQC	390	441.00 ± 9.58	108.67	2.23
	HQC	750	801.00 ± 31.24	104.57	4.03
Freeze-thaw cycles stability (−70 ± 10°C, 3 cycles)	LLOQ	10	10.50 ± 0.70	97.15	7.23
	LQC	30	26.90 ± 1.52	91.90	5.60
	MQC	390	397.00 ± 12.80	106.17	3.12
	HQC	750	793.00 ± 29.01	103.70	3.64
Long term stability (−70 ± 10°C, 30 days)	LLOQ	10	9.00 ± 0.53	92.83	5.74
	LQC	30	31.40 ± 1.93	98.92	6.60
	MQC	390	428.00 ± 16.40	107.70	3.94
	HQC	750	689.00 ± 54.60	102.23	7.08
PIP in combination (DOX+PIP)
Autosampler stability (4°C, 24 h)	LLOQ	10	10.90 ± 0.42	105.00	4.04
	LQC	30	32.80 ± 1.36	103.33	4.27
	MQC	390	432.00 ± 11.72	106.83	2.93
	HQC	750	689.00 ± 19.58	94.33	2.75
Bench Top Stability (24 ± 4°C, 8 h)	LLOQ	10	10.30 ± 0.75	103.45	7.28
	LQC	30	33.10 ± 0.60	108.50	1.72
	MQC	390	428.00 ± 9.79	109.50	2.43
	HQC	750	687.00 ± 18.99	90.67	2.79
Freeze-thaw cycle stability (−70 ± 10°C, 3 cycles)	LLOQ	10	8.93 ± 0.30	90.05	3.28
	LQC	30	30.40 ± 2.11	96.78	7.12
	MQC	390	422.00 ± 16.98	107.33	4.24
	HQC	750	679.00 ± 22.47	93.20	3.22
Long-term stability (−70 ± 10°C, 30 days)	LLOQ	10	9.66 ± 0.71	102.35	6.92
	LQC	30	33.20 ± 2.29	104.33	7.42
	MQC	390	404.00 ± 15.59	102.45	3.94
	HQC	750	681.00 ± 11.14	88.85	1.63

3.4. Applicability of the developed LC-MS/MS method

3.4.1. Optimization and characterization of solid lipid nanoparticles

The ternary phase diagram shown in Figure 3(H), with the blue region, depicts the formation of microemulsion, and SLNs were formed with less than 20% lipid phase and more than 50% water phase. After optimizing the concentration range of lipid and surfactants, efforts were made to optimize the solid-lipid nanoparticles to get the minimum particle size, the lowest polydispersity index, and surface charge using Design-Expert software. A three-factor and three-level Box-Behnken design having 17 runs was selected to optimize the nanoformulation. The selected independent variables, including the amount of lipid precirol, concentration of surfactant and co-surfactant, and sonication time, had a substantial impact on the observed responses for zeta potential, PDI, and particle size (Figure 3). A decreased concentration of lipid precirol and surfactants yielded lower particle size, ranging nanoparticles, whereas no significant change was observed in the PDI values by altering the concentrations of lipid and surfactant. Similarly, no drastic change in the zeta potential was observed by varying the concentration of lipid and surfactant at a constant sonication time of 70 seconds. The Design-Expert software produced polynomial equations that clarified the key effects and interactions of each independent component on each dependent variable. Particle size, PDI, and zeta potential variables are related in the following ways, as indicated by multiple regression analysis performed on the experimental data:

Figure 3.

Optimization of solid lipid nanoparticles by using Box Behnken experimental design. (A) contour plot showing the effect of lipid and surfactant concentration on particle size. (B) three-dimensional surface response graph for particle size (C) contour plot showing the effect of lipid and surfactants on polydispersity index (PDI) of the nanoformulation (D) three-dimensional surface response graph for PDI (E) contour plot showing the effect of lipid and surfactants on zeta potential (F) three-dimensional surface response graph for zeta potential (G) contour plot showing the desirability of the optimized nanoformulation (H) ternary phase diagram of solid lipid nanoparticles.

Particle Size  144.722–2.87253 * A + 7.98714 * B + 8.59964 * C + −19.0367 * AB + 10.3216 * AC + 3.75761 * BC + −8.94858 * A² +8.2066 * B² +12.1316 * C²

PDI      0.17347 + −0.00534614 * A + −0.0307274 * B + −0.0313524 * C + −0.00702561 * AB + −0.0606089 * AC + 0.0302953 * BC + 0.0283605 * A² + −0.00700191 * B² +0.0512481 * C²

Zeta Potential  −24.29 + 0.509015 * A + 0.332947 * B + −1.31151 * C + −0.146887 * AB + −3.05664 * AC + 1.54723 * BC + 0.901738 * A² + −0.616058 * B² +2.17819 * C²

Asterisk (*) represents the multiplication symbol

After the optimization of nanoformulation, both drugs were loaded within the solid-lipid nanoparticles. The particle size of the developed nanoformulation was found to be 151.56 ± 0.32 d.nm, PDI 0.172 ± 0.02, and zeta potential of − 22.83 ± 0.66 mV. Additionally, the entrapment efficiency of DOX and PIP was found to be 90.4 ± 0.8% and 89.6 ± 0.8%, respectively (Figure 4).

Figure 4.

Development and characterization of solid lipid nanoparticles (A) method of preparation of solid lipid nanoparticles. (B & C) characterization of solid lipid nanoparticles. (D) and (E) entrapment efficiency and loading efficiency of DOX and PIP loaded in solid lipid nanoparticles, respectively. Created with Biorender.com.

3.4.2. Oral pharmacokinetics studies

The oral pharmacokinetic investigation and bioavailability evaluation in rats were both conducted using the developed and validated LC-MS/MS technique for both drugs. Figure 5, depicts the typical DOX and PIP plasma concentration-time curves after oral dosing in young female SD rats. The various pharmacokinetic parameters of DOX and PIP after oral administration is listed in Table 5. A dose of 10 mg/kg each of DOX and PIP was administered to the rats. An increased C_max (64.43 ± 7.50 ng/mL) for DOX in DOX-PIP-SLN was observed as compared to free DOX in DOX-PIP solution (31.80 ± 1.04 ng/mL). Similarly, the C_max for PIP in DOX-PIP-SLN was found to be 1775.00 ± 215.75 ng/mL as compared to free PIP in DOX-PIP solution (120.33 ± 9.85 ng/mL). After oral administration, an enhanced AUC_0-∞ was observed for both DOX and PIP 31,911.78 ± 226.92 ng/mL and 7377.66 ± 655.78 ng/mL, respectively, when loaded within solid-lipid nanoparticles as compared to their free drug in combination. Also, DOX and PIP exhibited a higher mean residence time of 47.28 ± 9.05 hours and 6.18 ± 0.35 hours, respectively, as compared to their free drug concentration in combination. The improved pharmacokinetic profile of SLN may be attributed to the nano-sized particles facilitating increased surface area for absorption, enhanced solubility and dissolution rate, protection of the drugs from enzymatic degradation in the gastrointestinal tract, and potential lymphatic uptake due to the lipidic nature of the SLNs. Furthermore, the sustained release behavior of the developed nanoparticles may have contributed to prolonged circulation time and improved drug plasma levels.

Figure 5.

The mean concentrations of DOX and PIP vs. time profile of (A) DOX in DOX +PIP combination and DOX-PIP-SLNs (B) PIP in DOX +PIP combination and DOX-PIP-SLNs.

Table 5.

Pharmacokinetic parameters of free DOX+PIP and DOX-PIP-SLNs after oral administration.

Parameters (unit)	Free DOX in (DOX+PIP) combination (10 mg/kg DOX +10 mg/kg PIP)	DOX in DOX-PIP-SLNs (10 mg/kg DOX +10 mg/kg PIP)	PIP in (DOX+PIP) combination (10 mg/kg DOX +10 mg/kg PIP)	PIP in DOX-PIP-SLNs (10 mg/kg DOX +10 mg/kg PIP)
Cmax(ng/mL)	31.80 ± 1.04	64.43 ± 7.50	120.33 ± 9.85	1775.00 ± 215.75
Tmax (h)	0.79 ± 0.10	0.75 ± 0.00	1.00 ± 0.00	0.75 ± 0.00
AUC0-∞ (h*ng/mL)	518.35 ± 19.50	31911.78 ± 226.92	336.66 ± 46.96	7377.66 ± 655.78
T1/2 (h)	11.07 ± 1.56	27.61 ± 7.48	3.30 ± 0.64	10.80 ± 1.78
Vd/F (L/Kg)	307.38 ± 35.71	205.75 ± 35.05	142.13 ± 27.28	21.39 ± 4.82
Cl/F (L/hr/Kg)	19.31 ± 0.73	5.29 ± 0.64	30.18 ± 4.15	1.37 ± 0.13
MRT (h)	16.53 ± 2.06	47.28 ± 9.05	4.34 ± 0.59	6.18 ± 0.35

C_max: Maximum plasma concentration; T_max: Time to reach maximum plasma concentration; AUC_0-∞ : Area under the plasma concentration-time curve from time zero to infinity; T_1/2: Elimination half-life; V_d/F: Apparent volume of distribution; Cl/F : Apparent clearance; MRT: Mean residence time.

4. Discussion

The present work focuses on the quantification of DOX and PIP simultaneously in the biological matrix through the development and validation of an LC-MS/MS method following USFDA guidelines. The developed LC-MS/MS technique allows for the simultaneous measurement of DOX and PIP in plasma samples using the same chromatographic approach and extraction process. The entire run time for the study was 5 minutes, with the retention times of DOX, PIP, and IS being 1.91, 3.29, and 2.05 minutes, respectively. The primary challenge in developing a LC-MS/MS technique for the simultaneous measurement of DOX and PIP in a single run was choosing the right mobile phase due to the variations in their molecular weights and polarity. As a result, preliminary experiments were carried out utilizing various ratios of solvents, including methanol, acetonitrile, and glacial acetic acid, to optimize the composition of the mobile phase. This was done to prevent tailing and interference from endogenous components while achieving good analyte separation. After several runs, the mobile phase 0.1% formic acid in methanol- 0.1% formic acid in milli-Q water (80:20, %v/v) was selected with a flow rate of 20 µL. Protein precipitation method was employed to extract DOX and PIP from plasma. Precipitating agents cause proteins to become denatured and aggregate. The proteins separate from the solution as a result of this process, making analysis easier [37]. 0.1% formic acid in acetonitrile was used as the precipitating agent to extract the analytes. To guarantee its robustness, the LC-MS/MS method for assessing DOX and PIP was verified in compliance with USFDA criteria. A number of crucial factors were included in the validation procedure, including recovery, stability, specificity, linearity, accuracy, and precision. Specificity of the method was determined by assessing any interference caused by endogenous matrix components during the elution of DOX and PIP. The calibration curves demonstrated a high correlation coefficient (r² > 0.99), indicating strong linear correlations between concentration and their response. By examining quality control samples at various concentrations throughout the range and maintaining intra- and inter-day variability within the allowable limits of ± 15%, accuracy and precision were assessed. Moreover, under various circumstances, such as long-term, freeze-thaw cycles, bench-top stability, and autosampler stability tests, ensured that DOX and PIP remained stable. The developed LC-MS/MS method was evaluated for its whiteness using the RGB12 model, which integrates analytical performance, environmental impact, and practical efficiency. The method achieved a high whiteness score of 88.1, indicating excellent overall balance, sustainability, and suitability for routine analysis in terms of sensitivity, eco-friendliness, and cost-effectiveness (Figure S3). We optimized the solid lipid nanoparticle formulation for loading DOX and PIP using Design Expert software. The application made it easier to explore formulation factors systematically, such as lipid content, surfactant concentration range, and sonication time. The developed solid lipid nanoparticles demonstrated homogeneous particle size, sustained drug release profiles, and increased encapsulation efficiency for both DOX and PIP. Pharmacokinetic studies were conducted on solid lipid nanoparticles loaded with DOX and PIP, as well as their free drug combinations, in order to evaluate the applicability of the developed LC-MS/MS approach. When compared to the free drug in combination, the solid lipid nanoparticles showed a markedly better pharmacokinetic profile, which was marked by increased bioavailability, extended circulation time, and decreased clearance rates. The enhanced pharmacokinetic characteristics indicate that DOX and PIP’s therapeutic potential is effectively increased by solid lipid nanoparticles encapsulation, which may result in better clinical outcomes with reduced dosing regimens. However, the study is limited by potential inter-animal variability and inherent differences between rat physiology and human pharmacokinetics. The findings suggest potential relevance to humans, though confirmation in higher animal models and clinical studies is needed.

5. Conclusion

To conclude, in compliance with USFDA criteria, we successfully developed and validated an LC-MS/MS technique for the simultaneous quantification of DOX and PIP in biological samples. By employing Design Expert software, we were able to optimize solid lipid nanoparticles to achieve better drug encapsulation and improved pharmacokinetic characteristics. The solid lipid nanoparticles showed better bioavailability and sustained release than free drug combinations, indicating their potential for higher therapeutic outcomes.

Funding Statement

The author Pooja Yadav thanks the Department of Science and Technology (DST), New Delhi, India, for financial support in the form of the DST-Inspire fellowship.

Article highlights

• A validated LC-MS/MS technique has been developed to simultaneously determine doxorubicin (DOX) and piperine (PIP) in rat plasma.

• Optimization of solid lipid nanoparticles was done by the Box-Behnken experimental approach.

• The optimized solid lipid nanoparticles demonstrated uniform particle distribution with a negative surface charge.

• Compared to free drug in combination, pharmacokinetic investigations indicated enhanced bioavailability.

• The developed method and improved formulation open new possibilities for clinical applications.

• This is a CSIR-CDRI communication 11031.

Disclosure statement

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing assistance

No writing assistance was utilized in the production of this manuscript

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contribution

PY conceptualization, Methodology, Writing – original draft, Formal analysis. DC Methodology, Data curation, Writing – review and editing. PKY Formal analysis, Writing – review and editing. AK Writing – review and editing. JRG Writing – review and editing, Visualization. MKC Supervision, Conceptualization, Validation, Visualization, Writing – review and editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper

Financial disclosures

The authors have no financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board approval or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17576180.2025.2548198