Primena višekriterijumske optimizacije na bazi verovatnoće u pripremi enkapsulacije lekova pomoću dizajniranog eksperimenta

Ključne reči: teorija verovatnoće, višekriterijumska optimizacija, poželjna verovatnoća, dizajn testa, enkapsulacija lekova

Sažetak


Uvod/cilj: U radu je predstavljena višekriterijumska optimizacija zasnovana na verovatnoći (probability based multi  objective optimization –PMOO) za objektivno  proučavanje problema optimizacije enkapsulacije lekova pomoću hitozana rastvorljivog u vodi (water-soluble chitosan ‒ WSC)/gama poliglutaminske kiseline ((g-PGA) – tanšinona    IIA (TA) pomoću dizajna površine odgovora i glicerozoma ‒ triptolida pomoću ortogonalnog dizajna eksperimenta.

Metode: U višekriterijumskoj optimizaciji, zasnovanoj na verovatnoći, uveden je koncept poželjne verovatnoće kako bi se opisao stepen poželjnosti korisnosti neke performanse. Svaki korisni ili nekorisni indeks korisnosti linearno doprinosi delimičnoj poželjnoj verovatnoći u pozitivnom, odnosno u negativnom smislu, a svi pokazatelji korisnosti performansi tretiraju se podjednako i jednovremeno. Ukupna poželjna verovatnoća kandidata proizvod je svih parcijalnih poželjnih verovatnoća, čime se višekriterijumski problem prevodi u jednokriterijumski.

Rezultati: 1. Do optimalne enkapsulacije WSC / g-PGA-TA dolazi kada je WSC 5.755 mg×ml−1, TA 1.0275 mg×ml−1, odnos TA i nosećeg materijala 1:4.9, a vreme reakcije 1.302h. 2. Optimalni uslovi pripreme glicerozoma – triptolida su  pri koncentraciji glicerina od 20%, masenom odnosu fosfolipida i holesterola 30:1 i masenom odnosu fosfolipida i triptolida 5:1.

Zaključak: Rezultati pokazuju primenljivost višekriterijumske optimizacije zasnovane na verovatnoći u optimizaciji enkapsulacije kompozita pomoću dizajniranih testova.

Reference

Chen, M., Lu, X., Zhu, Q., et al. all authors 2021. Evaluation of common chemotherapy regimens in advanced non-small cell lung adenocarcinoma based on multi-attribute utility theory. Chinese Journal of Drug Application and Monitoring, 18(1-4) [online]. Available at: https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2021&filename=YWYY202101002&uniplatform=NZKPT&v=bxMFiGTbK1mKlUPOMD8CABdj_4W49AosAMR0bBe8QhpzpDFJjv_sLq5Z-owj3pLW [Accessed: 20 May 2022].

Mandal, J.K., Mukhopadhyay, S., Dutta, P. 2018. Multi-Objective Optimization. Evolutionary to Hybrid Framework. Springer Nature Singapore. Available at: https://doi.org/10.1007/978-981-13-1471-1>

Mankowski, M. & Moshkov, M. 2021. Dynamic Programming Multi-Objective Combinatorial Optimization. Springer Nature Switzerland AG. Available at: https://doi.org/10.1007/978-3-030-63920-4>

Mirjalili, S. & Dong, J.S. 2020. Multi-Objective Optimization using Artificial Intelligence Techniques. Springer Nature Switzerland AG. Available at:  https://doi.org/10.1007/978-3-030-24835-2>

Song, Z., Feng, D., Xu J. & Bi, K. 1992. Study on the compatibility and therapeutical basis of composite herbal medicines of Lingguishugan Decoction. Chinese Traditional Patent Medicine, 12 [online]. Available at: https://pesquisa.bvsalud.org/portal/resource/pt/wpr-681963?lang=en [Accessed: 20 May 2022].

Wu, X., Li, F. & Liu, C. 2013. Multi-objective Optimize Based on Nondominated Sorting Genetic Algorithm - Uniform multi-objective optimization of extraction conditions of drug application. Chinese Journal of Health Statistics, 30, pp.177-181. Available at: https://t.cnki.net/kcms/detail?v=A52pXWg201CVo-Bo_keKquLNBjXQW5azyK-dnK-Tg2yMGDd8AG1A-thCUodt_QLVWFdF3kinUwKyIaDkGQqZNDnqC2lLF9k4s732XQLo4VS_cgxPny7Oyw==&uniplatform=NZKPT [Accessed: 20 May 2022].

Yu, J., Wu, N., Zheng, X. & Zheng, M. 2020. Preparation of water-soluble chitosan/poly-gama-glutamic acid—tanshinone IIA encapsulation composite and its in vitro/in vivo drug release properties. Biomedical Physics & Engineering Express,  6(4), art.number:045020. Available at: https://doi.org/10.1088/2057-1976/ab9ab2>

Zheng, M., Wang, Y. & Teng, H. 2021. A New "Intersection" Method for Multi-Objective Optimization in Material Selection. Tehnički glasnik, 15(4), pp.562-568. Available at: https://doi.org/10.31803/tg-20210901142449>

Zheng, M., Wang, Y. & Teng H. 2022a. A novel method based on probability theory for simultaneous optimization of multi - object orthogonal test design in material engineering. Kovove Materialy/Metallic Materials, 60(1), pp.45-53. Available at: https://doi.org/10.31577/km.2022.1.45

Zheng, M., Wang, Y. & Teng, H. 2022b. Hybrid of “Intersection” Algorithm for Multi - Objective Optimization with Response Surface Methodology and its Application. Tehnički glasnik, 16(4). Available at: https://doi.org/10.31803/tg-20210930051227 (in press).

Zhu, C., Zhang, Y., Wu, T., He, Z., Guo, T. & Feng, N. 2022. Optimizing glycerosome formulations via an orthogonal experimental design to enhance transdermal triptolide delivery. Acta Pharmaceutica, 72(1), pp.135-146 [online]. Available at: https://acta.pharmaceutica.farmaceut.org/wp-content/uploads/2021/08/13522.pdf [Accessed 20 May 2022]

Objavljeno
2022/10/14
Rubrika
Originalni naučni radovi