# Assisted evaluation of aniline's in silico toxicity using artificial intelligence and its simultaneous determination as a toxic impurity with widely used cardiovascular drugs using a green micellar chromatographic method

## TL;DR

A new eco-friendly method uses AI and green chemistry to detect toxic aniline and salicylic acid impurities in cardiovascular drugs.

## Contribution

First AI-based molecular docking study of aniline toxicity combined with a green micellar HPLC method for simultaneous impurity detection.

## Key findings

- AI docking simulations identified cytochrome P450 binding sites linked to aniline-induced methemoglobinemia.
- A green micellar HPLC method accurately quantified aniline and salicylic acid alongside four cardiovascular drugs.
- The method met ICH guidelines with high accuracy and greenness scores of 0.80 and 0.85.

## Abstract

The safety of pharmaceutical products is critically influenced by the presence of impurities and degradation products. Aniline (ANN) is a very toxic degradation product of atorvastatin (ATN), which can cause life-threatening diseases such as methemoglobinemia. For the first time, a comprehensive artificial intelligence study using molecular docking was applied to assess the ANN-induced methemoglobinemia by simulating different binding energies in different pockets of cytochrome P450 (CYP 1A2), revealing the most suitable position leading to toxicity. Moreover, environmental concerns have become increasingly important due to the toxic effects of the excessive use of organic solvents in chromatographic separation systems. Accordingly, greener surfactant systems comprising sodium dodecyl sulfate (SDS) and polyoxyethylene-23-lauryl ether (Brij-35) were employed as safer alternatives were used for the quantitation of ANN in the presence of salicylic acid as an aspirin impurity alongside four widely used cardiovascular drugs of aspirin (APN), atenolol (AEN), atorvastatin calcium (ATN), and losartan potassium (LSN) in pure form and pharmaceuticals. The method validation was done according to the International Conference for Harmonisation (ICH) guidelines with linearity ranges of (10–200), (5–140), (5–100), (5–130), (0.5–40), and (0.5–30) µg mL−1 for APN, AEN, ATN, LSN, SAA, and ANN, respectively, and the results obtained were highly accurate. The greenness of the proposed method was ascertained using the green analytical procedure index: score (0.80), blue applicability grade index: score (0.85), and the Analytical GREEnness calculator. A statistical comparison between the results of our study and the reported method showed no significant difference in precision or accuracy.

An eco-friendly micellar HPLC method, integrated with an AI-assisted docking approach, enables the simultaneous determination of aniline and salicylic acid impurities with four cardiovascular drugs, to predict aniline toxicity.