DoE-assisted HPLC method development and validation of enzalutamide and repaglinide in rat plasma
Creators: name: Reddy, Gangireddy Navitha
name: Jogvanshi, Akanksha
name: Reddy, Dannarm Srinivas
name: Chenkual, Laltanpuii
name: Sonti, Rajesh
Publisher: name: Taylor & Francis
Year: 2024
Subjects: subject: Biochemistry
subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Pharmacology
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified

description: <b>Aim:</b> A simple and rapid HPLC technique was developed and validated to simultaneously estimate enzalutamide (ENZ) and repaglinide (REP) in rat plasma. <b>Methods:</b><i>In silico</i> predictions using DDinter and DDI-Pred indicated possible drug–drug interactions between ENZ and REP. A central composite design was used to identify factors influencing the separation of the drugs. Interactions between chromatographic parameters were studied through 51 experiments, followed by illustration with three-dimensional response surface plots. The four factors optimized for the separation of the two drugs are column temperature (A), % organic strength (B), pH (C) and column type (D). <b>Results:</b> Plate count(R1), tailing factor (R2) and resolution (R3) responses in the experimental design were analyzed with the favorable chromatographic conditions predicted to be 0.1% formic acid and acetonitrile as mobile phases on a Phenomenex C18 LC column (250 × 4.6 mm, 5 μm). The method was applied to estimate the drugs in rat plasma using a simple protein-precipitation step and found to be linear, accurate and precise within the ranges of 0.5–16 and 5–50 μg/ml for ENZ and REP, respectively. <b>Conclusion:</b> The optimized method can be used in future bioanalytical workflow for drug quantification and drug–drug compatible studies. Owing to multiple complications in the elderly population, they are forced to take different combinations of drugs, leading to an undesired situation, i.e., polypharmacy resulting in drug–drug interactions (DDI). These DDIs primarily occur through pharmacokinetic and pharmacodynamic mechanisms, including the role of cytochrome P450 (CYP) enzymes. Enzalutamide (ENZ), a second-generation androgen receptor inhibitor, is used to treat castration-resistant prostate cancer. It is a non-steroidal, small-molecule inhibitor that obstructs androgen receptor (AR) signaling. Repaglinide (REP), an insulin secretagogue, rapidly lowers postprandial glucose levels in type 2 diabetes patients. Combining ENZ with REP may significantly reduce REP's area under the curve (AUC), leading to DDIs. Therefore, developing and validating an optimized method for their simultaneous determination in biofluids is practically advantageous. The Central Composite Design (CCD) is a flexible approach for simultaneous drug estimation via HPLC. This work presents the analytical and bioanalytical methods for ENZ and REP with an internal standard (IS) Bicalutamide (BCT) in rat plasma, employing Design of Experiments (DoE) principles to optimize various parameters and achieve the best HPLC separation conditions. The possible drug–drug interactions are predicted by <i>in silico</i> tools DDInter and DDI-pred. The DoE-assisted method, which used a central composite design for the analytical separation of two analytes, helped to assess the factors affecting HPLC separation. DoE was performed with design expert software version 13.0.5.0. The CCD design was conducted using 51 runs, which were further investigated, and the response was interpreted using 3D surface and all-factor plots. The study aimed to explore how independent variables (factors) such as column temperature (A), % organic strength (B), pH (C) and column type (D) impact dependent variables, including plate count (R1), tailing (R2) and resolution (R3). A simple and efficient method of protein precipitation was employed for sample extraction using acetonitrile solvent. An HPLC system (WatersTM e2695) with a photodiode array detector (2998 series) and Empower 3 software was used. HPLC chromatographic separation was performed on a Phenomenex C18 column (250 × 4.6 mm, 5 μm) with a 10-minute run time and 1.0 ml/min flow rate. Gradient elution with 0.1% formic acid in H2O (A) and ACN (B) was employed. LC-MS/MS analysis was conducted using a Thermo Scientific<sup>TM</sup> Quantis Plus. DDInter scores, ranging from 0 to 1, depicted possible metabolic interactions and in DDI-pred, the major risk level value was identified as 0.224, using this combination. Among the various CYP450 isoforms, CYP2C8 showed a ΔP (ΔP = Pa-Pi) value of 0.163, indicating a probability of interaction through this isoform, given that both drugs are metabolized by it. In DoE, the lack of fit for the responses was found to be non-significant, which determines whether the models are suitable for the evaluation of the factors. We utilized polynomial equations to predict the actual relationships between the factors and responses. The optimized method allowed for rapid quantitative analysis within 7 min in analytical solution and rat plasma. The method was validated according to US-FDA guidelines in the range of 5–50 and 0.5–16 μg/ml for repaglinide and enzalutamide, respectively.