In silico algorithm for optimization of pharmacokinetic studies of [25Mg2+]porphyrin-fullerene nanoparticles

Fursov VV1,2, Zinchenko DI1, Namestnikova DD2, Kuznetsov DA2,3
About authors

1 Mendeleev University of Chemical Technology, Moscow, Russia

2 Pirogov Russian National Research Medical University, Moscow, Russia

3 Semenov Federal Research Center for Chemical Physics, Moscow, Russia

Correspondence should be addressed: Valentin V. Fursov
Ostrovityanova, 1, Moscow, 117997, Russia; ur.liam@vosrufv

About paper

Funding: the study was funded by by the Ministry of Science and Higher Education of the Russian Federation, grant No. 075-15-2020-792 (Unique identifier RF-190220X0031)

Author contribution: Fursov VV — in silico study supervision, concept, hypothesis, structure, modeling, manuscript writing; Zinchenko DI — modeling, code, manuscript writing; Namestnikova DD — in vivo experiments; Kuznetsov DA — general supervision, data interpretation and analysis, planning of experiments.

Compliance with ethical standards: the study was approved by the ethical review board at the Pirogov Russian National Research Medical University (protocol № 140 of 15 December 2014) and the local committee for surveillance of the maintenance and use of laboratory animals (protocol № 13/2020 of 08 October 2020, protocol № 24/2021 of 10 December 2021).

Received: 2022-07-05 Accepted: 2022-07-18 Published online: 2022-07-22

The search for effective pharmacophores to treat ischemic stroke is precipitated by the prevalence and high mortality of the condition. Optimization of preclinical scenarios for promising neuroprotectants by mathematical modeling using up-to-date computational platforms is a well-defined and urgent task. This study aimed to develop a drug-oriented model represented by an ordinary differential equation system to study pharmacokinetics of 25Mg2+-releasing porphyrin-fullerene nanocationite PMC16 in silico using MATLAB and adjust computating model's adequatness using in vivo rat model. The developed five-compartment model predicts the distribution of nanoparticles in organs and tissues (e.g. the brain, the heart and the liver) for the purpose of experimental parameters optimization. The in silico produced pharmacokinetic curves show good agreement with the data obtained using in vivo rat model of ischemic stroke. The in silico and in vivo results indicate that PMC16 nanoparticles effectively cross the blood-brain barrier.

Keywords: ischemic stroke, mathematical modeling, nanocationites, pharmacokinetics, penumbra, 25Mg2+, differential equations