Comparative pharmacokinetics of osmotic-controlled and immediate-release Eperisone tablet formulation in healthy human subjects using a sensitive plasma LC-ESI-MS/MS method.
Kamran AhmedMuhammad Harris ShoaibRabia Ismail YousufFahad SiddiquiFaaiza QaziJaveria IftikharFarrukh Rafiq AhmedMuhammad Iqbal NasiriPublished in: Scientific reports (2020)
To evaluate and compare the pharmacokinetic (PK) characteristics of a newly developed oral osmotically controlled drug delivery system of Eperisone 150 mg tablets with Eperisone immediate release (IR) marketed tablet brand as a reference formulation. It was a single dose, two treatment, two sequence, randomized, crossover study, involving 12 healthy human subjects. A modified, sensitive LC-ESI-MS/MS method was developed and validated as per FDA guidelines for estimation of Eperisone in plasma using a simple extraction and quick protein precipitation method. Non-compartmental pharmacokinetic model was used for PK analysis. Results were statistically compared using logarithmically transformed data, where p > 0.05 was considered as non-significant with 90% CI limit of 0.8-1.25. The bio-analytical method used for estimating drug plasma concentration was found to be simple, selective, linear, accurate and precise with 0.01 ng/ml as limit of detection. The comparative PK analysis revealed an insignificant difference in AUC0-∞, AUC0-t, Vz/F, Cl/F and t1/2λz, whereas a significant difference in Cmax, Tmax and MTTs were found. The relative bioavailability of Eperisone osmotic tablet was 109.7%. The osmotic controlled release drug formulation was found to release Eperisone for an extended period with less inter individual fluctuation in pharmacokinetic variables.
Keyphrases
- ms ms
- endothelial cells
- drug delivery
- liquid chromatography tandem mass spectrometry
- open label
- mass spectrometry
- simultaneous determination
- pluripotent stem cells
- clinical trial
- machine learning
- single cell
- amino acid
- adverse drug
- clinical practice
- label free
- combination therapy
- study protocol
- protein protein
- deep learning
- replacement therapy