Pharmacokinetic-pharmacodynamic integration of shikimic acid in broilers: An indirect effect modeling approach

Abstract

Shikimic acid (SA), a natural polyhydroxy cyclic organic acid, possesses significant anti-inflammatory and antioxidant activities; however, its pharmacokinetic (PK) profile and pharmacodynamic (PD) relationship in poultry remain poorly characterized. This study aimed to elucidate the PK characteristics of SA in broilers and its PD regulatory patterns on serum antioxidant indices. Sixteen healthy 5-week-old broilers were randomly assigned to intravenous (IV) and oral (PO) groups (50 mg/kg BW). Plasma SA concentrations were dynamically monitored via HPLC-MS/MS, while serum malondialdehyde (MDA), superoxide dismutase (SOD), and total antioxidant capacity (T-AOC) were quantified simultaneously. PK parameters were calculated using non-compartmental analysis (NCA), and PK-PD integration was performed using an indirect effect model.

The results showed that after IV administration, SA was extensively distributed and rapidly eliminated, with an apparent volume of distribution (V_z) of 0.35 ± 0.08 L/kg and an elimination half-life (t_1/2) of 1.61 ± 0.54 h. PO administration demonstrated moderate absorption characteristics, with a T_max of 3.38 ± 0.74 h and a C_max of 32.68 ± 7.15 µg/mL. Notably, the absolute bioavailability (F) of SA reached 40.37 % ± 7.22 %, which appears higher than values previously reported in mammals. Although a single dose significantly improved the oxidative status, the peak effect lagged behind the peak plasma concentration, exhibiting a typical hysteresis loop. Indirect effect model fitting yielded a low equilibrium rate constant (k_e0), strongly suggesting that SA may exert its antioxidant effects via indirect mechanisms rather than acting primarily as a direct scavenger. In conclusion, SA exhibits favorable absorption characteristics and moderate oral bioavailability in broilers, with an antioxidant profile characterized by indirect regulation, likely involving the activation of endogenous signaling pathways for sustained protection. This study provides an important scientific basis for the precision dosing of SA in poultry and the development of plant-derived anti-stress additives.

Introduction

Shikimic acid (SA; 3,4,5-trihydroxy-1-cyclohexene-1-carboxylic acid) is a naturally occurring polyhydroxy cyclic organic acid (Fig. 1). As a key intermediate in the shikimate pathway for the biosynthesis of aromatic amino acids in plants (Herrmann and Weaver, 1999), SA serves as an essential precursor for lignin, alkaloids, and polyphenols (Maeda and Dudareva, 2012). Currently, the pericarp of star anise (Illicium verum) is the primary industrial source of SA, with a dry weight content ranging from 3 % to 7 % (Just et al., 2015). While SA has gained prominence as the starting material for the synthesis of the anti-influenza drug oseltamivir, emerging basic medical research has revealed its significant and independent pharmacological value. Specifically, SA exhibits superior antioxidant and anti-inflammatory activities. Unlike traditional free radical scavengers, SA operates primarily through an "indirect antioxidant" mechanism. It activates the Nrf2/Keap1 signaling pathway, promoting the nuclear translocation of Nrf2 and its subsequent binding to the antioxidant response element (ARE), which induces the expression of endogenous antioxidant enzymes such as heme oxygenase-1 (HO-1) and superoxide dismutase (SOD) (Bao et al., 2023; Su et al., 2025). Regarding its anti-inflammatory properties, SA effectively inhibits the activation of the lipopolysaccharide (LPS)-induced NF-κB signaling pathway by blocking IκB-α phosphorylation and p65 nuclear translocation, thereby significantly reducing the release of pro-inflammatory cytokines, including TNF-α, IL-1 β, and IL-6 (Rabelo et al., 2016; Li et al., 2023).

Fig. 1.

Chemical structure of shikimic acid (molecular formula: C₇H₁₀O₅, molecular weight: 174.15 g/mol).

Modern poultry production, particularly broiler farming, faces formidable biological challenges. The rapid growth rate of broilers often imposes intense metabolic pressure, leading to an imbalance in free radical homeostasis and triggering oxidative stress and "cytokine storms." This oxidative damage can compromise the intestinal mucosal barrier, resulting in increased intestinal permeability (the "leaky gut" syndrome), which subsequently impairs nutrient absorption, elevates the feed conversion ratio (FCR), and even induces muscular myopathies, such as white striping and woody breast. These conditions seriously jeopardize poultry welfare and industry profitability (Surai et al., 2019). Although nutritional interventions for oxidative stress have been explored, there is an increasingly urgent demand for safe and efficient plant-derived additives capable of multi-target regulation of both antioxidant and anti-inflammatory pathways (Mishra and Jha, 2019).

A comprehensive understanding of the disposition kinetics of a drug within the animal body is a prerequisite for evaluating its clinical potential. Previous studies have indicated that the pharmacokinetic (PK) profile of SA in mammals is characterized by low absorption and rapid elimination. In rats, the absolute oral bioavailability of SA is approximately 10 % (Noh et al., 2020); in mice, it fluctuates between 11.09 % and 20.44 % (Liang et al., 2025); and in growing pigs, it is approximately 21.68 % (Mo et al., 2024). This low bioavailability is typically attributed to the high hydrophilicity of SA, which hinders transmembrane absorption, and its metabolism by gut microbiota into by-products such as hippuric acid (Adamson et al., 1970). To date, pharmacokinetic studies of SA in poultry remain absent. Although the application of crude star anise extracts has been reported, the complexity of their constituents (e.g., anethole) makes it difficult to precisely define the effective exposure of SA as the active ingredient (Bampidis et al., 2023). The lack of key PK parameters (AUC, C_max, CL, and V_z) specifically for poultry has significantly restricted the precision dosing and clinical development of SA as a botanical veterinary drug.

Consequently, the present study utilized high-sensitivity HPLC-MS/MS to systematically delineate the disposition of SA in broilers through parallel IV and PO administration trials for the first time. Furthermore, PK-PD correlations were established using an indirect effect model. This study not only fills the gap in interspecies PK data but also aims to suggest potentially distinct absorption features in broilers, providing an important scientific basis for formulating precise dosing regimens and developing novel plant-derived veterinary medicines.

Materials and methods

Chemicals and reagents

Shikimic acid (SA API; batch no. FKSA2401007) was purchased from Fukang Pharmaceutical Co., Ltd. (Fuzhou, China). The SA analytical standard (batch no. 2354349) was obtained from Shanghai ANPEL Laboratory Technologies Inc. (Shanghai, China). The purity of both the bulk SA and the analytical standard was determined to be > 99 %. Liquid chromatography-mass spectrometry (LC-MS) grade acetonitrile, methanol, and formic acid were sourced from Thermo Fisher Scientific (Waltham, MA, USA). Dichloromethane was supplied by Guangzhou Chemical Reagent Factory (Guangzhou, China). Ultrapure water used throughout the study was generated using a Milli-Q water purification system (Millipore, Billerica, MA, USA).

Ethical statement

Experimental procedures were conducted in strict accordance with the guidelines for the care and use of laboratory animals and were approved by the Animal Ethics Committee of South China Agricultural University (Approval No. 2025a016).

Animals

Sixteen healthy 5-week-old yellow-feathered broilers (equal numbers of males and females, mean initial body weight of 1.98 ± 0.11 kg) were obtained from Xinxing Dahuanong Poultry and Egg Co., Ltd. (Xinxing, China). The birds were randomly housed in four standardized wire cages (100 × 80 × 80 cm), with four birds (two males and two females) per cage. The broilers were acclimated for 1 week prior to the start of the experiment, during which they were provided ad libitum access to water and an antibiotic-free standard basal diet. The environment was well-ventilated and well-illuminated, with the ambient temperature maintained at 25 ± 1 °C. Following a 12 h fast (with free access to water), the 16 broilers were randomly allocated into two experimental groups—intravenous (IV) and oral (PO) administration (n = 8 per group)—using the SAS statistical software package (version 9.4; SAS Institute Inc., Cary, NC, USA) based on a completely randomized design.

Dosing and sample collection

The SA dosing solution was freshly prepared by dissolving the SA bulk powder (purity > 99 %) in sterile deionized water to a final concentration of 0.1 g/mL. For both intravenous (IV) and oral (PO) routes, the drug was administered as a simple aqueous solution to avoid potential interference from excipients. The mixture was vortexed for 2 min and filtered through a 0.22 μm membrane to ensure complete dissolution and sterility. The dosing solution was prepared within 30 min before administration and was visually inspected prior to dosing, showing a clear appearance without visible precipitation. The administration volume was adjusted according to body weight. Although the pH of the dosing solution was not measured, no abnormal clinical signs or adverse reactions were observed in broilers after intravenous administration. For the intravenous (IV) group, a single dose of 50 mg/kg BW was administered via the left brachial vein (wing vein). For the oral (PO) group, a single dose of 50 mg/kg BW was administered by oral gavage using a standardized gavage needle. The moment of administration was designated as 0 h. All blood samples (approximately 2 mL per collection) were obtained from the right brachial vein. At the specific time points designated for antioxidant determination (0, 1, 2, 4, 8, and 12 h post-administration), the collected blood was immediately divided into two equal aliquots. One aliquot was transferred into a heparinized tube containing sodium heparin as the anticoagulant to obtain plasma for pharmacokinetic analysis. The other aliquot was placed in a non-anticoagulant plain tube and allowed to clot at room temperature for 20 min before centrifugation to obtain serum for the determination of antioxidant biomarkers. For all other sampling points, the blood was processed solely for plasma collection. The complete blood sampling schedule was as follows: IV group: 5, 15, 30, and 45 min, and 1, 2, 3, 4, 6, 8, 12, and 24 h post-administration; PO group: 15, 30, and 45 min, and 1, 2, 3, 4, 6, 8, 12, and 24 h post-administration. Immediately after collection or clotting, all blood samples were centrifuged at 4,000 rpm for 10 min to separate the plasma or serum. The supernatants were then transferred into 1.5 mL microcentrifuge tubes and stored at −20 °C for subsequent HPLC-MS/MS analysis and antioxidant assays.

Plasma sample pretreatment

An aliquot of 500 μL plasma was transferred into a 5 mL centrifuge tube, followed by the addition of 2 mL of ultrapure water and vortex-mixing. Subsequently, 2 mL of dichloromethane was added, and the mixture was further vortexed to facilitate liquid-liquid extraction. After centrifugation at 12,000 rpm for 10 min at 4 °C, the upper aqueous phase was collected and subjected to purification using a MAX solid-phase extraction (SPE) column (Anpel Laboratory Technologies Inc., Shanghai, China). The column was eluted with methanol containing 15 % formic acid, and the eluate was evaporated to dryness under a gentle stream of nitrogen. The resulting residue was reconstituted in 500 μL of the initial mobile phase and filtered through a 0.22 μm nylon membrane (Anpel, Shanghai, China) prior to HPLC-MS/MS analysis.

A stock solution of SA (1 mg/mL) was prepared by dissolving 10 mg of the SA analytical standard in 10 mL of water. Working solutions (0.5, 1, 2, 5, 10, 20, and 50 μg/mL) were prepared through serial dilution of the stock solution. Calibration standards (0.05, 0.1, 0.2, 0.5, 1, 2, and 5 μg/mL) were generated by spiking 450 μL of blank plasma with 50 μL of the respective working solutions and processed following the pretreatment method described above. Linear regression was performed by plotting the peak area (Y) against the corresponding concentration (X) to determine the regression equation and the coefficient of determination (R²). The accuracy (relative error, RE%) and precision (relative standard deviation, RSD%) of the method were evaluated using quality control (QC) samples at three concentrations: low-level (LQC, 0.15 μg/mL), medium-level (MQC, 2.5 μg/mL), and high-level (HQC, 4 μg/mL), along with the limit of quantification (LOQ, 0.05 μg/mL). Six replicates were analyzed for each concentration (n = 6). Intra-day precision and accuracy were assessed within a single day, while inter-day precision and accuracy were determined over three consecutive days.

The stability of SA in broiler plasma was further evaluated using low- and high-QC samples (0.15 and 4 μg/mL, respectively). Short-term stability was assessed after storage at room temperature for 12 h. Autosampler stability was evaluated by keeping processed samples in the autosampler at 4 °C for 24 h prior to analysis. Freeze-thaw stability was determined after three freeze-thaw cycles. Long-term stability was assessed after storage at −20 °C for 15 d. Six replicates were analyzed under each condition.

HPLC-MS/MS analytical conditions

The quantification of SA was performed using a Shimadzu 8045 HPLC-MS/MS system (Shimadzu Corp., Kyoto, Japan) equipped with an electrospray ionization (ESI) source. Chromatographic separation was achieved on a Synergi Fusion-RP column (100 × 3.0 mm, 2.5 μm, 100 Å; Phenomenex, Torrance, CA, USA). The mobile phase consisted of 0.01 % formic acid in ultrapure water (solvent A) and acetonitrile (solvent B). The detailed liquid chromatography and mass spectrometry parameters are summarized in Table 1, Table 2, respectively.

Table 1.

Mobile phase gradient elution program for HPLC analysis.

Time (min)	Flow rate (mL/min)	A (%)	B (%)
0.0	0.5	100	0
2.0		100	0
2.5		30	70
3.5		30	70
3.6		100	0
5		100	0

Note:.

Solvent A: 0.01 % formic acid in ultrapure water.

Solvent B: LC-MS grade acetonitrile.

The total run time was 5 min with a flow rate of 0.5 mL/min.

Table 2.

Optimized MRM parameters for the mass spectrometric detection of shikimic acid (SA).

Analyte	Precursor ion	Fragment ion	DP/V	CE/V
SA	173.0	92.9	−55	−24
		136.9	−55	−14

Note:.

SA: Shikimic acid.

DP: Declustering potential.

CE: Collision energy.

Parameters were optimized using an electrospray ionization (ESI) source in negative mode.

Determination of serum antioxidant indices

Serum MDA, SOD, and T-AOC were selected as pharmacodynamic endpoints because they reflect complementary dimensions of oxidative status that are relevant to the reported antioxidant action of shikimic acid. MDA is a widely used indicator of lipid peroxidation and oxidative damage, SOD represents a key enzymatic antioxidant defense component, and T-AOC provides an integrated estimate of the overall antioxidant capacity of the biological system. These biomarkers are commonly used in poultry studies to evaluate systemic oxidative stress and antioxidant responses and were therefore considered suitable for characterizing the time-dependent pharmacodynamic effects of SA in broilers. In addition, previous studies suggest that SA may exert antioxidant effects mainly through modulation of endogenous defense pathways, including Nrf2-related signaling, rather than acting exclusively as a direct free-radical scavenger. On this basis, a combined endpoint panel including MDA, SOD, and T-AOC was used to capture both oxidative injury and compensatory antioxidant responses following SA administration.

Serum samples were collected at 0, 1, 2, 4, 8, and 12 h following SA administration. Antioxidant biomarkers were evaluated only following oral administration to better reflect practical exposure conditions relevant to the application of SA as a plant-derived veterinary drug in poultry production. The levels of oxidative stress and antioxidant capacity in the serum were determined using commercial biochemical assay kits (Beijing Boxbio Science & Technology Co., Ltd., Beijing, China) according to the manufacturer’s protocols. The malondialdehyde (MDA) content was measured using the thiobarbituric acid (TBA) assay. Briefly, serum was reacted with the TBA working solution in a boiling water bath, followed by centrifugation, and the absorbance of the resulting supernatant was measured at 532 nm. Superoxide dismutase (SOD) activity was determined via the nitroblue tetrazolium (NBT) method. Serum was mixed with the reaction solution and incubated under specific light conditions; the absorbance was then measured at 560 nm, and the enzymatic activity was calculated based on the percentage of inhibition. The total antioxidant capacity (T-AOC) was assessed using the ferric reducing antioxidant power (FRAP) assay. Samples were incubated with the FRAP working solution at 37 °C, and the absorbance was measured at 593 nm. T-AOC values were calculated using a FeSO₄ standard curve. All absorbance readings were obtained using a multimode microplate reader (BioTek, Winooski, VT, USA), and the final data were calculated based on the formulas provided with each kit.

Statistical analysis and PK-PD modeling

Data were organized using Excel 2019 and analyzed using GraphPad Prism 8.0.1 (GraphPad Software, San Diego, CA, USA) and Phoenix WinNonlin version 8.1.0 (Certara, Princeton, NJ, USA). Antioxidant biomarker data are presented as mean ± SD. Differences in serum antioxidant indices at each post-dose time point relative to the pre-dose baseline (0 h) were assessed using one-way analysis of variance (ANOVA) followed by Duncan's multiple range test, and a value of P < 0.05 was considered statistically significant. Pharmacokinetic parameters following intravenous (IV) and oral (PO) administration were calculated by non-compartmental analysis (NCA) using Phoenix WinNonlin.

PK-PD integration was performed to characterize the temporal relationship between plasma SA exposure and serum antioxidant responses (T-AOC, SOD, and MDA). Because the peak pharmacodynamic effects lagged behind the plasma concentration peak, the concentration-effect relationship showed hysteresis, indicating that the observed antioxidant response could not be adequately described by plasma concentrations alone. Therefore, an effect-compartment link model was introduced to account for the delay between plasma exposure and biophase distribution. The drug concentration in the effect compartment (C_e) was linked to the measured plasma concentration (C_p) according to the following equation:

$$\frac{d{C}_e}{dt}=k_{e0}·(C_p-C_e)$$

where k_e0 is the first-order equilibrium rate constant governing drug distribution between the plasma and effect compartments.

Based on the direction of the observed biomarker changes, indirect response models were used to describe the pharmacodynamic effects of SA. For T-AOC and SOD, SA was assumed to stimulate the zero-order production rate (k_in), and the response was described as

$$\frac{dE}{dt}=k_{in}·(1+S·C_e)-k_{out}·E$$

For MDA, because SA administration was associated with a reduction in biomarker levels, the drug effect was modeled as stimulation of the first-order loss process (k_out):

$$\frac{dE}{dt}=k_{in}-k_{out}·(1+S·C_e)·E$$

where E represents the observed biomarker response, k_in and k_out are the zero-order production and first-order loss rate constants, respectively, and S is the linear sensitivity coefficient describing the effect of C_e on the response. The baseline response (E₀) in the absence of drug effect was defined as E₀ = k_in/k_out. Model fitting and parameter estimation were performed using the Phoenix Model module in Phoenix WinNonlin 8.1 (Certara, Princeton, NJ, USA). Individual modeling was applied, and the PK-PD model was developed using individual plasma concentration and serum biomarker data from the PO group. For PK-PD integration, the pharmacokinetic component was described by a one-compartment model with extravascular input and clearance parameterization, and an effect-compartment link model was incorporated through the k_e0 parameter. For T-AOC and SOD, SA was modeled as linearly stimulating the zero-order input process (k_in), whereas for MDA, the drug effect was modeled as stimulation of the first-order loss process (k_out), consistent with the observed decrease in this biomarker after treatment. Parameter estimation was performed by maximum likelihood estimation. Different residual error structures were specified for PK and PD observations: a multiplicative error model was used for plasma concentration data, whereas an additive error model was used for pharmacodynamic response data. The initial standard deviation values were set to 0.1 for PK and 1.0 for PD. Model adequacy was evaluated using the Akaike Information Criterion (AIC).

In addition, the relationship between systemic exposure (AUC_plasma) and cumulative pharmacodynamic effect (AUEC, expressed as the percentage change from baseline) was analyzed by linear regression analysis. AUEC values over 0–12 h were calculated using the Linear Trapezoidal Linear/Log Interpolation method, and the coefficient of determination (R²) was used to assess the strength of the exposure-effect relationship.

Results

Method validation

The HPLC-MS/MS method developed in this study exhibited excellent linearity over the concentration range of 0.05 to 5 μg/mL, with a coefficient of determination (R²) exceeding 0.99. For SA in broiler plasma, the intra-day accuracy ranged from 94.28 % to 98.23 %, while the inter-day accuracy ranged from 94.99 % to 97.02 %. The intra-day and inter-day precision (RSD%) values were 3.74 %–6.98 % and 3.68 %–6.18 %, respectively. The limit of detection (LOD) was 0.025 μg/mL, and the limit of quantification (LOQ) was 0.05 μg/mL. Stability testing further showed that SA remained stable in broiler plasma after storage at room temperature for 12 h, storage in the autosampler at 4 °C for 24 h, three freeze-thaw cycles, and long-term storage at −20 °C for 15 d, with accuracy ranging from 91.28 % to 103.58 % and precision values ranging from 3.72 % to 5.43 % (Tables S1 and S2).

Pharmacokinetic profiles of SA in broilers

Following a single dose of 50 mg/kg BW, the mean and individual plasma concentration-time profiles of SA are presented in Fig. 2. The primary pharmacokinetic parameters are summarized in Table 3 (IV) and Table 4 (PO).

Fig. 2.

Plasma concentration-time profiles of shikimic acid (SA) in broilers following a single intravenous (A) and oral (B) administration (50 mg/kg BW). Main curves represent mean ± SD (n = 8); insets display individual data to illustrate inter-individual variability.

Table 3.

Pharmacokinetic parameters of shikimic acid in broilers after a single intravenous (IV) administration (50 mg/kg BW).

Parameter	1	2	3	4	5	6	7	8	mean ± SD
C0 (μg/mL)	464.29	387.27	397.75	447.74	601.06	534.52	426.20	329.09	448.49 ± 86.19
t1/2 (h)	1.19	1.45	1.49	1.30	1.28	2.37	2.57	1.24	1.61 ± 0.54
AUC (h·μg/mL)	360.19	286.98	285.14	326.47	346.18	413.46	383.98	264.07	333.31 ± 52.36
Vz (L/kg)	0.24	0.37	0.38	0.29	0.27	0.41	0.48	0.34	0.35 ± 0.08
CL (L/h/kg)	0.14	0.17	0.18	0.15	0.14	0.12	0.13	0.19	0.15 ± 0.02
Vss (L/kg)	0.16	0.20	0.20	0.18	0.13	0.15	0.20	0.20	0.18 ± 0.03
MRT (h)	1.13	1.16	1.16	1.20	0.90	1.25	1.55	1.07	1.18 ± 0.18

Note:.

Data are expressed as mean ± SD (n = 8).

C₀: initial plasma concentration at time zero, determined by back-extrapolation of the plasma concentration-time curve.

t_1/2: elimination half-life.

AUC: area under the concentration-time curve from zero to infinity.

V_z: apparent volume of distribution during the terminal phase.

CL: systemic clearance.

V_ss: steady-state volume of distribution.

MRT: mean residence time.

Table 4.

Pharmacokinetic parameters of shikimic acid in broilers after a single oral (PO) administration (50 mg/kg BW).

Parameter	1	2	3	4	5	6	7	8	mean ± SD
Cmax (μg/mL)	38.36	27.02	33.74	25.93	40.18	21.91	41.29	33.00	32.68 ± 7.15
Tmax (h)	2.00	3.00	3.00	4.00	4.00	3.00	4.00	4.00	3.38 ± 0.74
t1/2 (h)	0.94	1.65	3.38	1.51	1.28	1.33	2.60	1.74	1.80 ± 0.80
AUC (h·μg/mL)	128.96	122.65	146.87	131.26	148.01	84.41	159.28	154.9	132.04 ± 22.48
MRT (h)	3.62	4.00	4.09	4.65	4.94	3.76	5.66	4.92	4.45 ± 0.70
F (%)	38.69	36.80	44.06	39.38	44.40	25.33	47.79	46.47	40.37 ± 7.22

Note:.

Data are expressed as mean ± SD (n = 8).

C_max: maximum observed plasma concentration.

T_max: time to reach C_max.

F: absolute bioavailability, calculated as (AUC_PO/AUC_IV) × 100 %.

Values for individual broilers (1–8) were calculated using non-compartmental analysis (NCA).

After IV administration (Fig. 2A), The initial plasma concentration (C₀) of SA, extrapolated to time zero, was 448.49 ± 86.19 μg/mL, followed by a multi-exponential decay. SA underwent a rapid systemic distribution and elimination process during the first 4 h post-dosing; by 24 h, concentrations in all birds had fallen below the limit of quantification (LOQ). Non-compartmental analysis (NCA) revealed an elimination half-life (t_1/2) of 1.61 ± 0.54 h and a systemic clearance CL of 0.15 ± 0.02 L/h/kg, indicating rapid drug elimination in broilers. The apparent volume of distribution (V_z) was 0.35 ± 0.08 L/kg, suggesting that SA is likely distributed predominantly within extracellular fluid and well-perfused tissues of the central compartment.

Following a single PO administration (Fig. 2B), the plasma concentration-time curve exhibited distinct absorption, distribution, and elimination phases. SA was rapidly absorbed from the gastrointestinal tract of the broilers, with a mean time to reach peak concentration (T_max) of 3.38 ± 0.74 h and a peak concentration (C_max) of 32.68 ± 7.15 μg/mL. Compared to the IV group, the PO group showed a significantly delayed peak and a longer mean residence time (MRT) of 4.45 h, resulting in a markedly flatter curve profile. Notably, the absolute bioavailability (F) of SA in broilers was calculated to be 40.37 % ± 7.22 %.

Antioxidant effects of SA on serum biomarkers in broilers

The time-course profiles of serum antioxidant biomarkers following a single PO administration of 50 mg/kg BW SA are illustrated in Fig. 3. The concentration of malondialdehyde (MDA) in the serum exhibited an initial decline followed by a gradual recovery. Starting from 1 h post-administration, MDA levels decreased steadily, reaching a trough at 6–8 h, where the MDA content was significantly lower than the baseline (0 h) level (P < 0.05). By 12 h, although the MDA levels began to rise, they remained within a low-fluctuation range (Fig. 3C). In contrast, both serum total antioxidant capacity (T-AOC) (Fig. 3A) and superoxide dismutase (SOD) activity (Fig. 3B) displayed a "rise-then-fall" dynamic. These indices increased progressively after dosing and peaked between 6 h and 8 h, reaching levels significantly higher than the baseline (P < 0.05). Notably, a distinct time-lag was observed between the time to reach peak plasma SA concentration (T_max) and the time of peak antioxidant effects, indicating a delayed pharmacodynamic response relative to systemic drug exposure.

Fig. 3.

Serum antioxidant biomarker dynamics in broilers following oral shikimic acid (SA) administration (50 mg/kg BW). (A) Total antioxidant capacity (T-AOC); (B) superoxide dismutase (SOD); (C) malondialdehyde (MDA). Data are presented as mean ± SD (n = 8). Different letters indicate significant differences (P < 0.05) among time points.

PK-PD integration and modeling

Hysteresis analysis and model selection

By constructing the exposure-response relationship between plasma SA concentrations and antioxidant biomarkers (T-AOC, SOD, and MDA), the temporal characteristics of SA’s biological effects were systematically evaluated. As shown in the concentration-effect plots, T-AOC (Fig. 4A) and SOD (Fig. 4B) exhibited typical counter-clockwise hysteresis loops, whereas MDA (Fig. 4C) displayed a clockwise hysteresis loop.

Fig. 4.

Concentration-effect hysteresis loops for antioxidant biomarkers in broilers after oral shikimic acid (SA) administration (50 mg/kg BW). (A) Total antioxidant capacity (T-AOC); (B) superoxide dismutase (SOD); (C) malondialdehyde (MDA). Data points represent mean values (n = 8) connected chronologically to illustrate the temporal delay between plasma SA concentration and biological response.

This pronounced delay qualitatively is consistent with the physiological responses of antioxidant markers lag significantly behind changes in plasma drug concentrations, which is a hallmark of indirect pharmacodynamic (PD) characteristics. Consequently, an indirect effect model was employed to quantitatively characterize this process.

Parameter estimation and model fitness

The goodness of fit for each biomarker was assessed using the Akaike Information Criterion (AIC). The low AIC values across all indices (Table 5) indicated that the indirect effect model accurately captured the dynamic induction of antioxidant changes by SA in broilers.

Table 5.

PD parameters of indirect effect models for T-AOC, SOD, and MDA in broilers after oral administration of SA.

Parameter	AIC	S	ke0	kout	kin
T-AOC	−15.22 ± 9.52	0.01 ± 0.007	0.44 ± 0.42	0.14 ± 0.06	0.37 ± 0.16
SOD	33.50 ± 10.11	0.04 ± 0.02	0.89 ± 0.74	0.31 ± 0.16	8.98 ± 4.55
MDA	−13.85 ± 3.54	0.01 ± 0.007	1.06 ± 0.82	0.24 ± 0.13	0.84 ± 0.45

Note:.

AIC: Akaike Information Criterion, used to evaluate model fitness (lower values indicate better fit).

S: linear stimulation coefficient, representing the potency of SA in enhancing or inhibiting the biomarker.

k_e0: equilibrium rate constant for the effect compartment.

k_in: zero-order production rate constant of the effect.

k_out: first-order elimination rate constant of the effect.

The estimated equilibrium rate constants for the effect compartment (k_e0) for T-AOC, SOD, and MDA were consistently low, further validating the significant delay in the transport of SA from the systemic circulation to the effect site and the subsequent induction of biomarker alterations. The sensitivity coefficients (S) for all three indices were less than 0.05. This suggests that under the high-efficiency redox homeostasis of healthy birds, the fluctuations in antioxidant markers induced by exogenous SA are moderate and physiologically consistent with a healthy animal model.

Correlation between systemic exposure and cumulative effect

The quantitative relationship between SA exposure and the cumulative biological response was further explored using non-compartmental analysis (NCA). Regression analysis revealed a strong correlation between the systemic exposure of SA (AUC_plasma) and the area under the effect-time curve (AUEC, calculated as the percentage change relative to the 0 h baseline) (Fig. 5).

Fig. 5.

Linear regression between shikimic acid systemic exposure (AUC_plasma) and cumulative antioxidant effects (AUEC) in broilers. (A) Total antioxidant capacity (T-AOC); (B) superoxide dismutase (SOD); (C) malondialdehyde (MDA). AUEC is calculated as the percentage change relative to the 0 h baseline. R² represents the coefficient of determination.

The coefficients of determination for T-AOC (R² = 0.8696) (Fig. 5A), SOD (R² = 0.6728) (Fig. 5B), and MDA (R² = 0.6825) (Fig. 5C) collectively indicate that the systemic exposure levels of SA are significantly and positively correlated with the overall enhancement of antioxidant capacity in broilers.

Discussion

Shikimic acid (SA), characterized as a highly polar, hydrophilic, and small-molecule cyclic organic acid, possesses physicochemical properties strikingly similar to those of various endogenous organic acids in plasma. This similarity frequently leads to severe matrix suppression and significant background interference during HPLC-MS/MS analysis (Matuszewski et al., 2003). To ensure high sensitivity and analytical accuracy in complex biological matrices, we implemented a strategic refinement of the existing pretreatment protocol (Mo et al., 2024).

Specifically, a liquid-liquid extraction (LLE) step using dichloromethane was introduced following the initial aqueous extraction phase. This step leveraged polarity differentials to precisely eliminate lipophilic interferences from the plasma. Subsequently, selective enrichment and purification were achieved via mixed-mode anion-exchange solid-phase extraction (MAX - SPE), utilizing methanol containing 15 % formic acid as the eluant. The high concentration of formic acid not only neutralized the basic functional groups of the MAX sorbent to ensure the complete desorption of SA but also significantly enhanced the extraction recovery. This multi-stage purification strategy effectively mitigated signal suppression and ensured the robustness of SA quantification in avian plasma.

The absolute bioavailability (F) of SA in broilers was measured at 40.37 % ± 7.22 %, indicating moderate oral bioavailability and a value higher than those reported in several mammalian species, such as rats (10 %) (Noh et al., 2020), mice (11.09 %–20.44 %) (Liang et al., 2025), and growing pigs (21.68 %) (Mo et al., 2024). It should be noted that cross-species comparisons of absolute bioavailability should be interpreted with caution, given differences in formulation, dose levels, gastrointestinal physiology, and analytical methodologies among studies. Nevertheless, this pronounced species-dependent disparity likely stems from the synergistic promotion of organic acid transport by the unique gastrointestinal anatomy and physiological characteristics of poultry.

Firstly, the crop, an organ exclusive to poultry, maintains a slightly acidic environment (pH 4.5 −6.0) and serves as a pre-absorptive reservoir that extends the residence time of SA in the proximal digestive tract (Classen et al., 2016). As a polar organic acid, SA exists primarily in a non-dissociated molecular state under these low-pH conditions, which not only facilitates transmembrane absorption via passive diffusion but may also promote uptake through specific carriers, such as monocarboxylate transporters (MCTs), into intestinal epithelial cells (Sadr et al., 2025). In contrast, the gastric emptying rates and pH gradient evolution in monogastric mammals (e.g., pigs) differ significantly from those in poultry, potentially limiting the exposure time of SA within its optimal "absorption window" (Moran, 1982).

Secondly, species-specific intestinal microbial metabolism is a critical determinant of systemic exposure. In mammals, SA is susceptible to microbial conversion into metabolites such as hippuric acid (Adamson et al., 1970), resulting in a significant microbial "first-pass effect." Although the avian ceca possess a highly developed microbiota, SA is primarily absorbed in the upper small intestine. Due to the relatively short gastrointestinal tract and rapid digesta transit in poultry, the prototype drug enters the systemic circulation before reaching the high-density microbial zones of the ceca, thereby largely bypassing the loss of exposure associated with microbial degradation.

Furthermore, the significantly delayed peak time observed in broilers (T_max = 3.38 ± 0.74 h) compared to mammals suggests a prolonged absorption phase, potentially attributed to the reservoir effect of the avian crop or a specialized carrier-mediated transport system within the avian gastrointestinal tract. Future studies should focus on delineating the expression profiles and transport kinetics of specific organic acid transporters in the avian intestinal epithelium to further elucidate the molecular mechanisms underlying the superior absorption of SA in poultry.

In this study, the dynamic relationship between plasma SA concentrations and serum antioxidant biomarkers (T-AOC, SOD, and MDA) was simultaneously monitored. These complementary biomarkers allowed the assessment of oxidative injury, enzymatic antioxidant defense, and overall antioxidant capacity in an integrated manner. Following oral administration, although distinct regulatory trends were observed—characterized by increases in T-AOC and SOD and a decrease in MDA—the overall magnitude of these fluctuations was relatively moderate. This phenomenon is likely attributable to the low baseline oxidative stress in the healthy broilers utilized in this study. Under the constraints of redox homeostasis, biological systems tend to maintain antioxidant levels within a precise physiological homeostatic range. Any exogenous intervention typically triggers endogenous feedback mechanisms, thereby limiting drastic oscillations of these biomarkers in a basal physiological state (Surai et al., 2021).

Nevertheless, by constructing an indirect effect model and analyzing the exposure-response curves, this study revealed a significant temporal delay between SA exposure and its antioxidant effects. Specifically, T-AOC and SOD exhibited clear counter-clockwise hysteresis loops, while MDA showed a clockwise hysteresis loop. This pronounced effect delay, coupled with the low equilibrium rate constant (k_e0), provides robust evidence that SA does not function merely as a simple direct free radical scavenger in broilers. Instead, it acts as a significant indirect antioxidant. Although the sample size was relatively limited, it is consistent with exploratory PK-PD studies in veterinary pharmacology, and model robustness was supported by goodness-of-fit diagnostics and AIC-based model selection. This study focused on characterizing the PK-PD relationship at a representative dose rather than establishing a dose–response profile, which will be addressed in future studies.

This perspective is strongly supported by recent cross-species research (Su et al., 2025). In murine models, SA has been shown to significantly alleviate deoxynivalenol (DON)-induced jejunal barrier injury, primarily by activating the Nrf2/HO-1/NQO1 signaling pathway to bolster the host's antioxidant defense system. These molecular findings align closely with our PK-PD modeling results: upon entering the systemic circulation, SA does not exert an immediate effect but instead serves as a signaling molecule to trigger endogenous responses.

There is an inherent time span associated with this complex genomic regulatory cascade, which involves SA acting on target cells, the dissociation of Nrf2 from Keap1, its subsequent nuclear translocation, binding to the antioxidant response element (ARE) sequence, and the eventual transcription and translation of downstream antioxidant enzymes such as HO-1, SOD, and NQO1. The fact that the peak effect significantly lags behind the peak plasma concentration is the holistic kinetic manifestation of these underlying molecular processes. This indirect antioxidant mode implies that SA may build a durable defense barrier by "empowering" the body to autonomously synthesize antioxidant enzymes. Consequently, even as systemic drug concentrations decline, the induced endogenous protective proteins may continue to provide sustained protection.

Conclusion

In conclusion, this study provides the first systematic evaluation of the pharmacokinetic (PK) profile and pharmacodynamic (PD) regulation of shikimic acid (SA) in broilers through parallel IV and PO administration trials. Our findings indicate that SA exhibits moderate oral bioavailability in broilers, with values higher than those reported in several mammalian species. Integrated PK-PD modeling revealed a characteristic hysteresis effect on serum antioxidant markers (T-AOC, SOD, and MDA), and the low equilibrium rate constant (k_e0) supports the view that SA acts primarily through indirect antioxidant mechanisms, likely involving the activation of endogenous signaling pathways.

These findings provide new data for avian PK-PD evaluation and offer a basis for further investigation of SA as a plant-derived antioxidant candidate in poultry.

CRediT authorship contribution statement

Yue Shen: Writing – original draft, Software. Kaibin Mo: Validation, Methodology. Hui Zhao: Formal analysis. Yicheng Zhang: Investigation. Xianhui Huang: Writing – review & editing, Supervision, Project administration.

Disclosures

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.