Characterization of the in vitro metabolic profile of nazartinib in HLMs using UPLC-MS/MS method: In silico metabolic lability and DEREK structural alerts screening using StarDrop software

Abstract

The orally given, irreversible, third-generation inhibitor of the epidermal growth factor receptor (EGFR), known as Nazartinib (EGF816), is now undergoing investigation in Phase II clinical trials conducted by Novartis for Non-Small Cell Lung Cancer. The primary aim of the current research was to establish a rapid, specific, environmentally friendly, and highly versatile UPLC-MS/MS methodology for the determination of nazartinib (NZT) levels in human liver microsomes (HLMs). Subsequently, same approach was used to examine the metabolic stability of NZT. The UPLC-MS/MS method employed in HLMs was validated as stated in the bioanalytical method validation criteria outlined by the US- FDA. The evaluation of the metabolic stability of NZT and the identification of potentially structural alarms were performed using the StarDrop software package that includes the P450 and DEREK software. The calibration curve for NZT showed a linearity in the range from 1 to 3000 ng/mL. The inter-day accuracy and precision exhibited a range of values between -4.33 % and 4.43 %, whereas the intra-day accuracy and precision shown a range of values between -2.78 % and 7.10 %. The sensitivity of the developed approach was verified through the determination of a LLOQ of 0.39 ng/mL. The intrinsic clearance and in vitro half-life of NZT were assessed to be 46.48 mL/min/kg and 17.44 min, respectively. In our preceding inquiry, we have effectively discerned the bioactivation center, denoted by the carbon atom between the unsaturated conjugated system and aliphatic linear tertiary amine. In the context of computational software, making minor adjustments or substituting the dimethylamino-butenoyl moiety throughout the drug design process may increase the metabolic stability and safety properties of new synthesized derivatives. The efficiency of utilizing different in silico software approaches to conserve resources and reduce effort was proved by the outcomes attained from in vitro incubation experiments and the use of NZT in silico software.

Keywords: DEREK program; Greenness; Metabolic stability; Nazartinib; StarDrop software; UPLC-MS/MS.

Graphical abstract

Fig. 1

Chemical structures of nazartinib and selpercatinib (IS).

Fig. 2

The CSL (0.9999) demonstrates the significant susceptibility of NZT to metabolic processes. The assessment of the outcomes was done using WhichP450 (the StarDrop software package).

Fig. 3

DEREK software results showing structural alerts of NZT chemical structure marked in red colour. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

MRM mass spectrum of NZT [M+H]+ showing daughter ions scan (A) and SLP (B) [M+H]+ showing daughter ions scan. The observed fragmentation patterns are demonstrated.

Fig. 5

(A) HLMs matrix (Negative-control) exhibiting small carry over effect of NZT and SLP (IS) at the triple quadrupole mass analyzer; (B) MRM chromatogram of positive-control (Blank HLMs plus SLP; 1000 ng/mL). (C) Overlaid MRM chromatograms of NZT QCs and CSs revealing the NZT chromatographic peaks (0.48 min) and SLP chromatographic peaks (1000 ng/mL; 0.74 min).

Fig. 6

The sensitivity of the current UPLC-MS/MS methodology is exemplified by its ability to estimate the NZT analytical peak at 1 ng/mL (A), that resembles the LOQ. Furthermore, the analytical peak of the SLP is detected at 1000 ng/mL (B).

Fig. 7

The results are graphically shown using a circular diagram, that showcases a diverse spectrum of colors ranging from red (indicating absence of greenness) to dark green (indicating the maximum degree of greenness). The colors listed above are related to 12 separate features, as illustrated in the accompanying diagram. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 8

The NZT metabolic stability curve (A). The linear part of the logarithm (ln) curve showing the linear regression equation that was employed to assess the NZT metabolism rate (B).

Fig. 9

(NZT metabolic lability score (blue color), NZT DEREK toxicity predictions (red color) and NZT phase I metabolites (black color) revealing that dimethylamino and the butenoyl groups are accountable for the metabolic instability of NZT. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)