In vitro PK/PD modeling of tyrosine kinase inhibitors in non‐small cell lung cancer cell lines

• Main Authors: Linda Wanika (Author), Neil D. Evans (Author), Martin Johnson (Author), Helen Tomkinson (Author), Michael J. Chappell (Author)
• Format: Book
• Published: Wiley, 2024-03-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1752-8062; 1752-8054; 10.1111/cts.13714
• Keywords: Therapeutics. Pharmacology; RM1-950; Public aspects of medicine; RA1-1270
• Source: Clinical and Translational Science, Vol 17, Iss 3, Pp n/a-n/a (2024)

Abstract Tyrosine kinase inhibitors (TKIs) are routinely prescribed for the treatment of non‐small cell lung cancer (NSCLC). As with all medications, patients can experience adverse events due to TKIs. Unfortunately, the relationship between many TKIs and the occurrence of certain adverse events remains unclear. There are limited in vivo studies which focus on TKIs and their effects on different regulation pathways. Many in vitro studies, however, that investigate the effects of TKIs observe additional changes, such as changes in gene activations or protein expressions. These studies could potentially help to gain greater understanding of the mechanisms for TKI induced adverse events. However, in order to utilize these pathways in a pharmacokinetic/pharmacodynamic (PK/PD) framework, an in vitro PK/PD model needs to be developed, in order to characterize the effects of TKIs in NSCLC cell lines. Through the use of ordinary differential equations, cell viability data and nonlinear mixed effects modeling, an in vitro TKI PK/PD model was developed with estimated PK and PD parameter values for the TKIs alectinib, crizotinib, erlotinib, and gefitinib. The relative standard errors for the population parameters are all less than 25%. The inclusion of random effects enabled the model to predict individual parameter values which provided a closer fit to the observed response. It is hoped that this model can be extended to include in vitro data of certain pathways that may potentially be linked with adverse events and provide a better understanding of TKI‐induced adverse events.