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Optimization of Lipid-Based Ceftriaxone Delivery System via Machine Learning †

Daniela R. P. Loureiro
José X. Soares
Cláudia Nunes
Carlos M. M. Afonso
1,2 and
Salette Reis
Laboratory of Organic and Pharmaceutical Chemistry, Department of Chemical Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
Interdisciplinary Center of Marine and Environmental Investigation (CIIMAR/CIMAR), 4450-208 Matosinhos, Portugal
LAQV, REQUIMTE, Department of Chemical Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal
Author to whom correspondence should be addressed.
Presented at the 8th International Electronic Conference on Medicinal Chemistry, 1–30 November 2022; Available online:
Med. Sci. Forum 2022, 14(1), 151;
Published: 1 November 2022
(This article belongs to the Proceedings of The 8th International Electronic Conference on Medicinal Chemistry)


Ceftriaxone (CTX) a third-generation cephalosporin, is a broad-spectrum antibiotic that can be administered via intramuscular or intravenous routes to treat various types of infection. However, CTX has poor cellular penetration and poor diffusion due to its high molecular weight and high hydrophilicity. To address these problems, we propose an innovative nanotherapy based on the encapsulation of CTX in a nanostructured lipid carrier. Usually, several attempts must be made, on a trial-and-error basis, before a formulation that guarantees high drug encapsulation and suitable physicochemical properties is found. Machine Learning (ML) has recently stirred great interest as a tool to model and predict nanoparticles’ biological activity. Herein, for the first time, the use of ML for the optimization of a nanoformulation is explored. Several variables were optimized simultaneously, namely, the amount of solid lipid, the percentage of liquid lipid, the surfactant solution, the water volume, the sonication amplitude, and the sonication time. To define the best nanoformulation, three different outcomes were considered: the encapsulation efficiency of CTX, the size of the nanoparticles, and their zeta potential. Our ML approach was able to find, with a low number of experiments, the conditions that provided formulations with the highest encapsulation efficiency of CTX and nanoparticles with suitable size and adequate zeta potential. Besides the impressive acceleration of the optimization process that was achieved, the optimization guided by our ML model also provided insights into the optimization of other nanoformulations.

Supplementary Materials

The following are available online at

Author Contributions

Conceptualization, D.R.P.L., C.N. and S.R.; methodology, D.R.P.L.; software, J.X.S.; validation, D.R.P.L. and J.X.S.; formal analysis, D.R.P.L. and J.X.S.; investigation, D.R.P.L.; writing—original draft preparation, D.R.P.L.; writing—review and editing, C.N., S.R. and C.M.M.A. All authors have read and agreed to the published version of the manuscript.


This research was funded by the project UIDB/50006/2020 | UIDP/50006/2020, funded by FCT/MCTES through national funds, by FCT/MCTES—Foundation for Science and Technology from the Minister of Science, Technology and Higher Education and European Regional Development Fund (ERDF) under the projects, co-financed by COMPETE 2020, Portugal 2020, PTDC/SAU-PUB/28736/2017 (POCI-01-0145-FEDER-028736), and PTDC/NANMAT/31444/2017 and within the scope of UIDB/04423/2020, UID/QUI/5000612019, and UIDP/04423/2020 (Group of Natural Products and Medicinal Chemistry). DRPL thanks FCT for her PhD grant (SFRH/BD/140844/2018).

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.
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MDPI and ACS Style

Loureiro, D.R.P.; Soares, J.X.; Nunes, C.; Afonso, C.M.M.; Reis, S. Optimization of Lipid-Based Ceftriaxone Delivery System via Machine Learning. Med. Sci. Forum 2022, 14, 151.

AMA Style

Loureiro DRP, Soares JX, Nunes C, Afonso CMM, Reis S. Optimization of Lipid-Based Ceftriaxone Delivery System via Machine Learning. Medical Sciences Forum. 2022; 14(1):151.

Chicago/Turabian Style

Loureiro, Daniela R. P., José X. Soares, Cláudia Nunes, Carlos M. M. Afonso, and Salette Reis. 2022. "Optimization of Lipid-Based Ceftriaxone Delivery System via Machine Learning" Medical Sciences Forum 14, no. 1: 151.

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