Newly Developed Quantitative Spectrophotometric Analysis in the Visible Range (VIS) of Lisinopril that belongs to angiotensin-converting enzyme inhibitors

Lisinopril is a dipeptide containing an L-Proline group and an L-Lysine residue. It is an antiarrhythmic medication belonging to the family of angiotensin-converting enzyme (ACE) inhibitors . It effectively treats arterial hypertension (first-line treatment), heart failure, and heart attacks; it also prevents kidney problems in people with diabetes mellitus. The main purpose of this work consisted of the dosage of Lisinopril as a single active substance from pharmaceutical tablets. A new method for the quantitative analysis of Lisinopril using visible spectrophotometry (VIS) was found, optimized, and applied in laboratory practice. This method was based on the diazotization of the free primary amino group -NH₂ of Lisinopril in cold conditions for 25 minutes at 1-5 degrees Celsius, in the presence of sodium nitrite 5 % and hydrochloric acid 10%-15%, followed by the quantitative coupling of the obtained diazonium salt with alpha-naphthol from an alkalized 0.2 % alcoholic solution. An intense orange azo dye with a reddish shade was dosed at the wavelength corresponding to the absorption maximum, λ = 489 nm, in relation to double-distilled water, which was used as a blank. The amount of pure Lisinopril found per tablet was 19.60 mg / coated tablet .This value was very close to the official reference value of 20 mg pure Lisinopril/tablet. The average percentage deviation was only 2.00% compared to the officially declared content of the active substance; this fell perfectly within the normal limits of the average percentage deviation allowed by the Romanian Pharmacopoeias 10th Edition and European Pharmacopoeias (± 7.5%). The method proposed to be applied for the visible spectrophotometric analysis of Lisinopril from pharmaceutical tablets presented a very good linearity over the entire chosen concentration range of 0.41 μg/mL - 12.24 μg/mL. The linear regression coefficient was R² = 0.999085, which fit perfectly within the normal range of values, R² ≥ 0.9990. The proposed method was then statistically validated.