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...
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Nature Portfolio
2025-05-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-00925-4 |
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| author | Alyssa G. Almer Samuel V. Rasmussen Dina Kats Matthew N. Svalina Bonnie L. Cole Mohammadreza Khani Sonja Chen Samuel H. Cheshier Bryn A. Martin Noah E. Berlow Charles Keller |
| author_facet | Alyssa G. Almer Samuel V. Rasmussen Dina Kats Matthew N. Svalina Bonnie L. Cole Mohammadreza Khani Sonja Chen Samuel H. Cheshier Bryn A. Martin Noah E. Berlow Charles Keller |
| author_sort | Alyssa G. Almer |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e316e026118e4aaebdf5f0be5f208184 |
| institution | DOAJ |
| issn | 2730-664X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Medicine |
| spelling | doaj-art-e316e026118e4aaebdf5f0be5f2081842025-08-20T03:22:11ZengNature PortfolioCommunications Medicine2730-664X2025-05-015111110.1038/s43856-025-00925-4Computational and biological modeling of IGF1R inhibition for multifocal medulloblastomaAlyssa G. Almer0Samuel V. Rasmussen1Dina Kats2Matthew N. Svalina3Bonnie L. Cole4Mohammadreza Khani5Sonja Chen6Samuel H. Cheshier7Bryn A. Martin8Noah E. Berlow9Charles Keller10Children’s Cancer Therapy Development InstituteChildren’s Cancer Therapy Development InstituteChildren’s Cancer Therapy Development InstituteChildren’s Cancer Therapy Development InstituteDepartment of Pathology, Seattle Children’s HospitalDepartment of Biological Engineering, University of IdahoDepartment of Pathology, Nationwide Children’s HospitalDivision of Pediatric Neurosurgery, Department of Neurosurgery, Huntsman Cancer Institute, Intermountain Primary Children’s Hospital, University of UtahDepartment of Biological Engineering, University of IdahoChildren’s Cancer Therapy Development InstituteChildren’s Cancer Therapy Development InstituteAbstract 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.https://doi.org/10.1038/s43856-025-00925-4 |
| spellingShingle | Alyssa G. Almer Samuel V. Rasmussen Dina Kats Matthew N. Svalina Bonnie L. Cole Mohammadreza Khani Sonja Chen Samuel H. Cheshier Bryn A. Martin Noah E. Berlow Charles Keller Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma Communications Medicine |
| title | Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma |
| title_full | Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma |
| title_fullStr | Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma |
| title_full_unstemmed | Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma |
| title_short | Computational and biological modeling of IGF1R inhibition for multifocal medulloblastoma |
| title_sort | computational and biological modeling of igf1r inhibition for multifocal medulloblastoma |
| url | https://doi.org/10.1038/s43856-025-00925-4 |
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