|dc.description.abstract||Introduction: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKIs) are standard of care in EGFR-postive NSCLC patients. The issue uptake of NSCLC can be determined using radiolabeled EGFR TKI PET/CT. However, recent research has shown a significant difference between image quality (i.e. tumor-to-lung contrast) in in three generation EGFR TKIs: 11C-erlotinib, 18F-afatinib and 11C-osimertinib. In this research we aim to develop a mechanistical model to predict the tumor-to-lung contrast and uptake of healthy tissue of the three tracers.
Methods: Relevant physicochemical & drug specific properties (e.g. pKa, lipophilicity, EGFR binding) for each TKI were collected and used in established base models. Key hallmarks of NSCLC: immune tumor deprivation, unaltered tumor perfusion and erratic neovascularization. Analysis was performed by excluding each key component and comparing the PE with the final mechanistical PBPK-model predictions. Model accuracy was demonstrated by calculating the prediction error (PE) between predicted tissue to blood ratios (TBR) and measured, PET image derived, TBR.
Results: The fitted models were able to predict the tumor-to-lung contrast for all EGFR-TKIs within 3-fold of observed PET image ratios (PE Tumor-to-lung ratio of -93%, +43% and-7.4 % for erlotinib, osimertinib and afatinib respectively). Furthermore, the models depicted agreeable whole-body distribution for osimertinib and afatinib, showing high tissue distribution and an underprediction and low tissue distribution at high blood concentrations for erlotinib (mean PE, of -4.4%, range -156% - +187%, for all tissues).
Conclusion: The developed models adequately predicted the image quality of afatinib, osimertinib and erlotinib. Some deviations in predicted whole-body TBR lead to new hypotheses such increased affinity for mutated EGFR and active influx transport (erlotinib into excreting tissues) or active efflux (afatinib from brain), which is currently unaccounted for. In the future, the models may be used to predict the image quality of new tracers.||