Towards a computational prediction for the tumor selective accumulation of paramagnetic nanoparticles in retinoblastoma cells

• Published in: Bulletin of RSMU 2018-01 (6), p.68-73
• Main Authors: Johansen, R.J., Bukhvostov, A.A., Ermakov, K.V., Kuznetsov, D.A.
• Format: Article
• Language: English
• ISSN: 2500-1094; 2542-1204
• DOI: 10.24075/brsmu.2018.078

Retinoblastoma is a malignant growth affecting retina. An original combination of modified Non-Markov and Gompertzian computational approaches is proven of being a reliable tool for prediction of tumor selective accumulation of the bivalent metal isotopes (25Mg, 43Ca, 60Co, 67Zn, …) — releasing nanoparticles in human retinoblastoma cells. This mathematical model operates with a starting point of the discriminative drug uptake caused by a gap-like distinction between the neighboring malignant and normal cell proliferation rates. This takes into account both pharmacokinetic and pharmacodynamic peculiarities of PMC16, fullerene-C60 based nanoparticles, known for their unique capabilities for a cancer-targeted delivery of paramagnetic metal isotopes followed by an essential chemotherapeutic effect. Being dependent on a tumor growth rate but not on the neoplasm steady state mass, a randomized level of drug accumulation in retinoblastoma cells has been formalized as a predictive paradigm suitable to optimize an ongoing PMC16 preclinical research.