Makine Öğrenmesi ile Hedefe Yönelik Nanoterapötiklerin Üretim Parametrelerinin Optimizasyonu

Year 2022, , 693 - 700, 31.03.2022

Naim Karasekreter , Şeyda Gündüz , Sadık Kağa , Süleyman Yaman

https://doi.org/10.31590/ejosat.1084311

Abstract

Etkin ilaç dağıtımı, daha güvenli ve verimli terapötik sonuçlar elde etmek için bir ilacın belirli bir hastalık bölgesine verilmesini ifade etmektedir. Son zamanlarda geleneksel ilaç dağıtım yöntemleri yerine ilacın etkin bir şekilde dağıtımını hedefleyen nanopartikül temelli ilaç dağıtım yöntemleri kullanılmaktadır. Etkin ilaç dağıtımını sınırlandıran nanoparçacığın yapısından ve farmakokinetik sınırlamalardan kaynaklı çeşitli faktörler bulunmaktadır. Bu faktörler nanoterapötiklerin özellikle hastalıklı kısımlarda başarılı bir şekilde birikmesini engeller ve hastalık sürecinde etkin yanıtı sınırlar. Nanoterapötik ilaçların vücuttaki dağılımında karşılaşılan temel problem, nanopartiküllerin hastalık bölgelerinde terapötik ilaç seviyelerine ulaşamamasıdır. Spesifik bir hedefe yapılamayan ilaç dağıtımı ve terapötiklerin hastalıklı bölgede yetersiz birikimi gibi engeller, ilaç geliştiricileri için zorluk olmaya devam etmektedir. İlaç dağıtımına yönelik bu engelleri başarılı şekilde aşmak için geleneksel nanoparçacıkların yeniden tasarlanılmasına ihtiyaç vardır. Nanoparçacıkların intravenöz uygulamada karşılaştığı engeller göz önüne alındığında, hedefe yönelik terapötiklerin birikimini, kandaki dolaşım süresini ve hücre membran etkileşimlerini etkileyen birçok faktör olduğu anlaşılmaktadır. Bu parametrelerden başlıcaları; nanoparçacık yüzey yapısı ve yüzey yükü, nanoparçacık boyutu, nanoparçacık şekli, nanoparçacık uygulama yöntemi ve dozudur. Bu parametreler akciğer, karaciğer, dalak ve böbrekler dahil olmak üzere farklı organlar arasındaki biyolojik dağılımı belirler. Üretilen terapötik nanoparçacıkların farmakokinetik özelliklerinin belirlenmesi, uzun zaman isteyen, yüksek teknoloji ve uzmanlık gerektiren, yüksek maliyetli testlerle mümkün olmaktadır. Bu durum ar-ge aşamasında olan çalışmalar için hem zaman hem maliyet açısından ciddi bir engel oluşturmaktadır. Bu çalışmada biyolojik dağılımı etkileyen parametrelerle ilgili yapılan çalışmalardan elde edilen veriler ele alınarak nanotıp, ilaç sektörü, biyoteknoloji gibi birçok bölümde ilerde yapılacak çalışmalar için bir veri seti oluşturulmuştur. Ayrıca istenen özelliklere göre üretilecek olan nanoparçacığın üretim parametrelerinin optimum şekilde hesaplanmasını sağlayacak akıllı bir sistem tasarlanmıştır.

Keywords

Nanopartikül, Nanoterapötik, Makine Öğrenmesi, Veri Seti, Optimizasyon

Optimizing Production Parameters of Targeted Nanotherapeutics with Machine Learning

Abstract

Effective drug delivery refers to the delivery of a drug to a specific disease site to achieve safer and more efficient therapeutic results. Recently, nanoparticle-based drug delivery methods aiming at effective drug delivery have been used instead of traditional drug delivery methods. There are several factors that limit the effective drug delivery due to the structure of the nanoparticle and pharmacokinetic limitations. These factors prevent the successful deposition of nanotherapeutics, especially in diseased parts, and limit the effective response in the disease process. The main problem encountered in the distribution of nanotherapeutic drugs in the body is that nanoparticles cannot reach therapeutic drug levels at disease sites. Barriers such as inability to deliver drugs to a specific target and insufficient accumulation of therapeutics at the diseased site remain challenges for drug developers. To successfully overcome these barriers to drug delivery, traditional nanoparticles need to be redesigned. Given the barriers nanoparticles face in intravenous administration, it appears that there are many factors that influence the accumulation of targeted therapeutics, circulation time in the blood, and cell membrane interactions. The main ones among these parameters are; nanoparticle surface structure and surface charge, nanoparticle size, nanoparticle shape, nanoparticle application method and dose. These parameters determine the biodistribution between different organs, including the lung, liver, spleen, and kidneys. Determination of the pharmacokinetic properties of the produced therapeutic nanoparticles is possible with high cost tests that require long time, high technology and expertise. This situation creates a serious obstacle in terms of both time and cost for studies that are in the R&D stage. In this study, a data set was created for future studies in many departments such as nanomedicine, pharmaceutical industry, biotechnology, by considering the data obtained from the studies on the parameters affecting the biological distribution. In addition, an intelligent system has been designed to optimally calculate the production parameters of the nanoparticle to be produced according to the desired properties.

Keywords

Nanoparticle, Nanotherapeutic, Machine Learning, Dataset, Optimization

References

• Freitas R. A., Jr (2002). The future of nanofabrication and molecular scale devices in nanomedicine. Studies in health technology and informatics, 80, 45–59.
• Torchilin V. P. (2005). Recent advances with liposomes as pharmaceutical carriers. Nature reviews. Drug discovery, 4(2), 145–160.
• Patel, H. M., & Moghimi, S. M. (1998). Serum-mediated recognition of liposomes by phagocytic cells of the reticuloendothelial system - The concept of tissue specificity. Advanced drug delivery reviews, 32(1-2), 45–60.
• Baeza, A., Ruiz-Molina, D., & Vallet-Regí, M. (2017). Recent advances in porous nanoparticles for drug delivery in antitumoral applications: inorganic nanoparticles and nanoscale metal-organic frameworks. Expert opinion on drug delivery, 14(6), 783–796.
• a b c d e 1.Doğrulama 9 1 0 0 0 2. Doğrulama 2 5 0 0 0 3. Doğrulama 3 1 2 1 1 4. Doğrulama 1 0 0 0 2 5. Doğrulama 0 0 0 2 1 Chen, W., Zhang, S., Yu, Y., Zhang, H., & He, Q. (2016). Structural-Engineering Rationales of Gold Nanoparticles for Cancer Theranostics. Advanced materials (Deerfield Beach, Fla.), 28(39), 8567–8585.
• Dykman, L. A., & Khlebtsov, N. G. (2016). Biomedical Applications of Multifunctional Gold-Based Nanocomposites. Biochemistry. Biokhimiia, 81(13), 1771–1789.
• N. Salah, S. Habib, A. Azam, M.S. Ansari, W.M. AL-Shawafi. (2016). Formation of Mn-doped SnO2Nanoparticles Via the MicrowaveTechnique: Structural, Optical andElectrical Properties. Nanomaterials and Nanotechnology.
• R.M. Patil, P.B. Shete, N.D. Thorat, S.V. Otari, K.C. Barick, A. Prasad. (2014) Superparamagnetic iron oxide/chitosan core/shells for hyperthermia application: Improved colloidal stability and biocompatibility. Journal of magnetism and magnetic materials.355.
• P.B. Shete, R.M. Patil, N.D. Thorat, A. Prasad, R.S. Ningthoujam, S.J. Ghosh. (2014) Magnetic chitosan nanocomposite for hyperthermia therapy application: Preparation, characterization and in vitro experiments. Applied Surface Science. 288. 149-157.
• R.M. Patil, P.B. Shete, S.V. Otari, N.D. Thorat, A. Prasad, R.S. Ningthoujam. (2014). Non-aqueous to aqueous phase transfer of oleic acid coated iron oxide nanoparticles for hyperthermia application. Royal Society of Chemistry. 4515-4522.
• P.B. Shete, R.M. Patil, R.S. Ningthoujam, S.J. Ghosh, S.H. Pawar. (2013). Magnetic core–shell structures for magnetic fluid hyperthermia therapy application. New Journal of Chemistry. 37. 3784-3792
• Sailor, M. J., & Park, J. H. (2012). Hybrid nanoparticles for detection and treatment of cancer. Advanced materials (Deerfield Beach, Fla.), 24(28), 3779–3802.
• Shah, M. A., Ali, Z., Ahmad, R., Qadri, I., Fatima, K., & He, N. (2015). DNA Mediated Vaccines Delivery Through Nanoparticles. Journal of nanoscience and nanotechnology, 15(1), 41–53.
• Ur Rehman, F., Mazhar, K., Malik, A., Naz, S. S., Shah, K. U., Khan, A., Khan, S., Ahmed, R., & Qaisar, S. (2021). Surface modified multifaceted nanocarriers for oral non-conventional cancer therapy; synthesis and evaluation. Materials science & engineering. C, Materials for biological applications, 123, 111940.
• Aryal, S., Park, H., Leary, J. F., & Key, J. (2019). Top-down fabrication-based nano/microparticles for molecular imaging and drug delivery. International journal of nanomedicine, 14, 6631–6644.
• Moghimi, S. M., Hedeman, H., Muir, I. S., Illum, L., & Davis, S. S. (1993). An investigation of the filtration capacity and the fate of large filtered sterically-stabilized microspheres in rat spleen. Biochimica et biophysica acta, 1157(3), 233–240.
• R. M. Patil, P. B. Shete, (2019) Chapter 4- Biodistribution and Cellular Interaction of Hybrid Nanostructures, Hybrid Nanostructures for Cancer Theranostics, Micro and Nano Technologies, 63-86.
• Zaki NM, Nasti A, Tirelli N. (2011). Nanocarriers for cytoplasmic delivery: cellular uptake and intracellular fate of chitosan and hyaluronic acid-coated chitosan nanoparticles in a phagocytic cell model. Macromol Biosci. 11(12):1747–1760
• Chouly, C., Pouliquen, D., Lucet, I., Jeune, J. J., & Jallet, P. (1996). Development of superparamagnetic nanoparticles for MRI: effect of particle size, charge and surface nature on biodistribution. Journal of microencapsulation, 13(3), 245–255.
• Choi, H. S., Liu, W., Misra, P., Tanaka, E., Zimmer, J. P., Itty Ipe, B., Bawendi, M. G., & Frangioni, J. V. (2007). Renal clearance of quantum dots. Nature biotechnology, 25(10), 1165–1170.
• Bourrinet, P., Bengele, H. H., Bonnemain, B., Dencausse, A., Idee, J. M., Jacobs, P. M., & Lewis, J. M. (2006). Preclinical safety and pharmacokinetic profile of ferumoxtran-10, an ultrasmall superparamagnetic iron oxide magnetic resonance contrast agent. Investigative radiology, 41(3), 313–324.
• Yoo, J. W., Chambers, E., & Mitragotri, S. (2010). Factors that control the circulation time of nanoparticles in blood: challenges, solutions and future prospects. Current pharmaceutical design, 16(21), 2298–2307.
• Cilliers, C., Nessler, I., Christodolu, N., & Thurber, G. M. (2017). Tracking Antibody Distribution with Near-Infrared Fluorescent Dyes: Impact of Dye Structure and Degree of Labeling on Plasma Clearance. Molecular pharmaceutics, 14(5), 1623–1633.
• Ji, Z., Guo, W., Sakkiah, S., Liu, J., Patterson, T. A., & Hong, H. (2021). Nanomaterial Databases: Data Sources for Promoting Design and Risk Assessment of Nanomaterials. Nanomaterials (Basel, Switzerland), 11(6), 1599.
• Hancock, J. T., & Khoshgoftaar, T. M. (2020). CatBoost for big data: an interdisciplinary review. Journal of big data, 7(1), 94.
• Çerçi, Ç. (2017). Emg İşaretlerinin Özniteliklerinin Çıkarılması, Knn Ve Ysa Yöntemleri İle Sınıflandırılması. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi.
• Özkaya, U., & Seyfi, L. (2021). Yere Nüfuz Eden Radar B Tarama Görüntülerinin Az Parametreye Sahip Konvolüsyonel Sinir Ağı İle Değerlendirilmesi. Geomatik, 6(2), 84-92.
• Huang, X. L., Zhang, B., Ren, L., Ye, S. F., Sun, L. P., Zhang, Q. Q., Tan, M. C., & Chow, G. M. (2008). In vivo toxic studies and biodistribution of near infrared sensitive Au-Au(2)S nanoparticles as potential drug delivery carriers. Journal of materials science. Materials in medicine, 19(7), 2581–2588.
• Huang, X. L., Zhang, B., Ren, L., Ye, S. F., Sun, L. P., Zhang, Q. Q., Tan, M. C., & Chow, G. M. (2008). In vivo toxic studies and biodistribution of near infrared sensitive Au-Au(2)S nanoparticles as potential drug delivery carriers. Journal of materials science. Materials in medicine, 19(7), 2581–2588 . Takeuchi, I., Onaka, H., & Makino, K. (2018). Biodistribution of colloidal gold nanoparticles after intravenous injection: Effects of PEGylation at the same particle size. Bio-medical materials and engineering, 29(2), 205–215.
• Akiyama, Y., Mori, T., Katayama, Y., & Niidome, T. (2009). The effects of PEG grafting level and injection dose on gold nanorod biodistribution in the tumor-bearing mice. Journal of controlled release : official journal of the Controlled Release Society, 139(1), 81–84.
• Cho, W. S., Cho, M., Jeong, J., Choi, M., Cho, H. Y., Han, B. S., Kim, S. H., Kim, H. O., Lim, Y. T., Chung, B. H., & Jeong, J. (2009). Acute toxicity and pharmacokinetics of 13 nm-sized PEG-coated gold nanoparticles. Toxicology and applied pharmacology, 236(1), 16–24.
• Fent, G. M., Casteel, S. W., Kim, D. Y., Kannan, R., Katti, K., Chanda, N., & Katti, K. (2009). Biodistribution of maltose and gum arabic hybrid gold nanoparticles after intravenous injection in juvenile swine. Nanomedicine : nanotechnology, biology, and medicine, 5(2), 128–135.
• Terentyuk, G. S., Maslyakova, G. N., Suleymanova, L. V., Khlebtsov, B. N., Kogan, B. Y., Akchurin, G. G., Shantrocha, A. V., Maksimova, I. L., Khlebtsov, N. G., & Tuchin, V. V. (2009). Circulation and distribution of gold nanoparticles and induced alterations of tissue morphology at intravenous particle delivery. Journal of biophotonics, 2(5), 292–302.
• Zhang, G., Yang, Z., Lu, W., Zhang, R., Huang, Q., Tian, M., Li, L., Liang, D., & Li, C. (2009). Influence of anchoring ligands and particle size on the colloidal stability and in vivo biodistribution of polyethylene glycol-coated gold nanoparticles in tumor-xenografted mice. Biomaterials, 30(10), 1928–1936.
• Bourrinet, P., Bengele, H. H., Bonnemain, B., Dencausse, A., Idee, J. M., Jacobs, P. M., & Lewis, J. M. (2006). Preclinical safety and pharmacokinetic profile of ferumoxtran-10, an ultrasmall superparamagnetic iron oxide magnetic resonance contrast agent. Investigative radiology, 41(3), 313–324.
• Lawaczeck, R., Bauer, H., Frenzel, T., Hasegawa, M., Ito, Y., Kito, K., Miwa, N., Tsutsui, H., Vogler, H., & Weinmann, H. J. (1997). Magnetic iron oxide particles coated with carboxydextran for parenteral administration and liver contrasting. Pre-clinical profile of SH U555A. Acta radiologica (Stockholm, Sweden : 1987), 38(4 Pt 1), 584–597.
• Chen, H., Wang, L., Yeh, J., Wu, X., Cao, Z., Wang, Y. A., Zhang, M., Yang, L., & Mao, H. (2010). Reducing non-specific binding and uptake of nanoparticles and improving cell targeting with an antifouling PEO-b-PgammaMPS copolymer coating. Biomaterials, 31(20), 5397–5407.
• Zhao, Y., Sultan, D., Detering, L., Luehmann, H., & Liu, Y. (2014). Facile synthesis, pharmacokinetic and systemic clearance evaluation, and positron emission tomography cancer imaging of ⁶⁴Cu-Au alloy nanoclusters. Nanoscale, 6(22), 13501–13509.
• Bergen, J. M., von Recum, H. A., Goodman, T. T., Massey, A. P., & Pun, S. H. (2006). Gold nanoparticles as a versatile platform for optimizing physicochemical parameters for targeted drug delivery. Macromolecular bioscience, 6(7), 506–516.
• Balogh, L., Nigavekar, S. S., Nair, B. M., Lesniak, W., Zhang, C., Sung, L. Y., Kariapper, M. S., El-Jawahri, A., Llanes, M., Bolton, B., Mamou, F., Tan, W., Hutson, A., Minc, L., & Khan, M. K. (2007). Significant effect of size on the in vivo biodistribution of gold composite nanodevices in mouse tumor models. Nanomedicine : nanotechnology, biology, and medicine, 3(4), 281–296.