A comprehensive study on nanoparticle drug delivery to the brain: application of machine learning techniques

Yousfan, A., Al Rahwanji, M. J. ORCID: https://orcid.org/0000-0001-8181-752X, Hanano, A. and Al-Obaidi, H. ORCID: https://orcid.org/0000-0001-9735-0303 (2024) A comprehensive study on nanoparticle drug delivery to the brain: application of machine learning techniques. Molecular Pharmaceutics, 21 (1). pp. 333-345. ISSN 1543-8392 doi: 10.1021/acs.molpharmaceut.3c00880

Abstract/Summary

The delivery of drugs to specific target tissues and cells in the brain poses a significant challenge in brain therapeutics, primarily due to limited understanding of how nanoparticle (NP) properties influence drug biodistribution and off-target organ accumulation. This study addresses the limitations of previous research by using various predictive models based on collection of large data sets of 403 data points incorporating both numerical and categorical features. Machine learning techniques and comprehensive literature data analysis were used to develop models for predicting NP delivery to the brain. Furthermore, the physicochemical properties of loaded drugs and NPs were analyzed through a systematic analysis of pharmacodynamic parameters such as plasma area under the curve. The analysis employed various linear models, with a particular emphasis on linear mixed-effect models (LMEMs) that demonstrated exceptional accuracy. The model was validated via the preparation and administration of two distinct NP formulations via the intranasal and intravenous routes. Among the various modeling approaches, LMEMs exhibited superior performance in capturing underlying patterns. Factors such as the release rate and molecular weight had a negative impact on brain targeting. The model also suggests a slightly positive impact on brain targeting when the drug is a P-glycoprotein substrate.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/114414
Identification Number/DOI	10.1021/acs.molpharmaceut.3c00880
Refereed	Yes
Divisions	Life Sciences > School of Chemistry, Food and Pharmacy > School of Pharmacy > Pharmaceutics Research Group
Uncontrolled Keywords	Drug Discovery, Pharmaceutical Science, Molecular Medicine
Publisher	American Chemical Society (ACS)
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