Gliomas are brain tumors mainly derived from glial cells that are difficult to treat and cause high mortality. Radiation, chemotherapy, and surgical excision are the conventionaltreatments for gliomas. Patients who have surgery or have undergone chemotherapy for glioma treatment have poor prognosis with tumor recurrence. In particular, for glioblastoma,the 5-year averagesurvival rateis 4-7%, and the median survival is 12-18months. Anumber of issues hinder effective treatmentsuch as, poor surgical resection, tumor heterogeneity, insufficient drug penetration across the blood-brain barrier, multidrug resistance, and difficulties with drug specificity. Nanotheranostic-mediated drug delivery is becoming a well-researched consideration, and an efficient non-invasive method for delivering chemotherapeutic drugs to the target area. Theranostic nanomedicines, which incorporate therapeutic drugs and imaging agents forpersonalized therapies, can be used for preventing overdose of non-responders. Through the identification of massive and complicated information from next-generation sequencing, machine learning enables for precise prediction of therapeutic outcomes and post-treatment management for patients with cancer. This article gives a thorough overview of nanocarrier-mediated drug delivery with a brief introduction to drug delivery challenges. In addition, this assessment offers a current summary of preclinical and clinical research on nanomedicines for gliomas. In the future, nanotheranostics will provide personalized treatment for gliomas and other treatable cancers.
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