Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma.

Abstract

Background: Leptomeningeal metastasis in medulloblastoma poses challenges for effective treatments due to the blood-brain barrier (BBB), which may be addressed through intrathecal or intraventricular drug delivery. However, the lack of pharmacokinetic modeling for pathological cerebrospinal fluid (CSF) geometries has limited the ability to predict effective intrathecal and intraventricular drug exposure.

Methods: A patient-specific computational fluid dynamics "in silico" trial was conducted to simulate CSF movement to examine the tumor microenvironment in terms of drug-target exposure over time following intraventricular delivery via Omaya Reservoir. Simultaneously, we conducted cellular adhesion experiments to test the therapeutic potential of IGF1R inhibition on metastasis under patient-specific flow conditions generated by computational analysis.

Results: A 3-dimensional computational fluid dynamics (CFD) model based on patient-specific conditions was obtained to predict an efficacious drug concentration, providing guidance for therapeutic drug exposure at targeted sites. Microfluidic experiments for IGF1R inhibition of cellular adhesion showed the potential for reduced attachment of medulloblastoma to leptomeningeal cells to prevent metastasis.

Conclusions: This study offers insights from patient-specific in silico trials for the precision delivery of small-molecule drugs for the treatment of central nervous system (CNS) malignancies.