Computationally guided design and synthesis of dual-drug loaded polymeric nanoparticles for combination therapy

Song Jin , Zhenwei Lan , Guangze Yang , Xinyu Li , Javen Qinfeng Shi , Yun Liu , Chun-Xia Zhao

Aggregate ›› 2024, Vol. 5 ›› Issue (5) : e606

PDF
Aggregate ›› 2024, Vol. 5 ›› Issue (5) : e606 DOI: 10.1002/agt2.606
RESEARCH ARTICLE

Computationally guided design and synthesis of dual-drug loaded polymeric nanoparticles for combination therapy

Author information +
History +
PDF

Abstract

Single-drug therapies or monotherapies are often inadequate, particularly in the case of life-threatening diseases like cancer. Consequently, combination therapies emerge as an attractive strategy. Cancer nanomedicines have many benefits in addressing the challenges faced by small molecule therapeutic drugs, such as low water solubility and bioavailability, high toxicity, etc. However, it remains a significant challenge in encapsulating two drugs in a nanoparticle. To address this issue, computational methodologies are employed to guide the rational design and synthesis of dual-drugloaded polymer nanoparticles while achieving precise control over drug loading. Based on the sequential nanoprecipitation technology, five factors are identified that affect the formulation of drug candidates into dual-drug loaded nanoparticles, and then screened 176 formulations under different experimental conditions. Based on these experimental data, machine learning methods are applied to pin down the key factors. The implementation of this methodology holds the potential to significantly mitigate the complexities associated with the synthesis of dual-drug loaded nanoparticles, and the co-assembly of these compounds into nanoparticulate systems demonstrates a promising avenue for combination therapy. This approach provides a new strategy for enabling the streamlined, high-throughput screening and synthesis of new nanoscale drug-loaded entities.

Keywords

combination therapy / machine learning / polymeric nanoparticle

Cite this article

Download citation ▾
Song Jin, Zhenwei Lan, Guangze Yang, Xinyu Li, Javen Qinfeng Shi, Yun Liu, Chun-Xia Zhao. Computationally guided design and synthesis of dual-drug loaded polymeric nanoparticles for combination therapy. Aggregate, 2024, 5(5): e606 DOI:10.1002/agt2.606

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

a) L. A. Jackson, E. J. Anderson, N. G. Rouphael, P. C. Roberts, M. Makhene, R. N. Coler, M. P. McCullough, J. D. Chappell, M. R. Denison, L. J. Stevens, N. Engl. J. Med. 2020, 383, 1920;b) M. J. Mulligan, K. E. Lyke, N. Kitchin, J. Absalon, A. Gurtman, S. Lockhart, K. Neuzil, V. Raabe, R. Bailey, K. A. Swanson, Nature 2020, 586, 589.

[2]

Y. C. Barenholz, Nanomed.: Des., Delivery Detect. 2016, 51, 315.

[3]

Y. Liu, G. Yang, Y. Hui, S. Ranaweera, C.-X. Zhao, Small 2022, 18, 2106580.

[4]

M. B. McGuckin, J. Wang, R. Ghanma, N. Qin, S. D. Palma, R. F. Donnelly, A. J. Paredes, J. Controlled Release 2022, 345, 334.

[5]

a) E. Bernabeu, M. Cagel, E. Lagomarsino, M. Moretton, D. A. Chiappetta, Int. J. Pharm. 2017, 526, 474;b) M. Imran, S. Saleem, A. Chaudhuri, J. Ali, S. Baboota, J. Drug Delivery Sci. Technol. 2020, 60, 101959.

[6]

J. Wu, Y.-J. Zhu, F. Chen, X.-Y. Zhao, J. Zhao, C. Qi, Dalton Trans. 2013, 42, 7032.

[7]

B. Wang, W. Meng, M. Bi, Y. Ni, Q. Cai, J. Wang, Dalton Trans. 2013, 42, 8918.

[8]

Y. Liu, G. Yang, S. Jin, L. Xu, C.-X. Zhao, ChemPlusChem 2020, 85, 2143.

[9]

Y. Liu, G. Yang, T. Baby, Tengjisi, D. Chen, D. A. Weitz, C.-X. Zhao, Angew. Chem. Int. Ed. 2020, 59, 4720.

[10]

C. Núñez, J. L. Capelo, G. Igrejas, A. Alfonso, L. M. Botana, C. Lodeiro, Biomaterials 2016, 97, 34.

[11]

L. Fan, F. Li, H. Zhang, Y. Wang, C. Cheng, X. Li, C.-h. Gu, Q. Yang, H. Wu, S. Zhang, Biomaterials 2010, 31, 5634.

[12]

M. Li, P. Liu, G. Gao, J. Deng, Z. Pan, X. Wu, G. Xie, C. Yue, C. H. Cho, Y. Ma, L. Cai, ACS Appl. Mater. Interfaces 2015, 7, 8005.

[13]

Y. Liu, J. Fang, Y.-J. Kim, M. K. Wong, P. Wang, Mol. Pharmaceutics 2014, 11, 1651.

[14]

Y. Fan, Q. Wang, G. Lin, Y. Shi, Z. Gu, T. Ding, Acta Biomater. 2017, 62, 257.

[15]

A. Zielińska, F. Carreiró, A. M. Oliveira, A. Neves, B. Pires, D. N. Venkatesh, A. Durazzo, M. Lucarini, P. Eder, A. M. Silva, A. Santini, E. B. Souto, Molecules 2020, 25, 3731.

[16]

Y. Liu, G. Yang, S. Jin, R. Zhang, P. Chen, Tengjisi, L. Wang, D. Chen, D. A. Weitz, C.-X. Zhao, Angew. Chem. Int. Ed. 2020, 59, 20065.

[17]

E. A. O’Reilly, L. Gubbins, S. Sharma, R. Tully, M. H. Z. Guang, K. Weiner-Gorzel, J. McCaffrey, M. Harrison, F. Furlong, M. Kell, A. McCann, The fate of chemoresistance in triple negative breast cancer (TNBC), BBA Clinical, 2015, 3, 257.

[18]

S. Bochum, S. Berger, U. M. Martens, in Small Molecules in Oncology (Ed: U. M. Martens), Springer International Publishing, Cham 2018, p.217.

[19]

J. Murai, S.-Y. N. Huang, A. Renaud, Y. Zhang, J. Ji, S. Takeda, J. Morris, B. Teicher, J. H. Doroshow, Y. Pommier, Mol. Cancer Ther. 2014, 13, 433.

[20]

a) J. Wang, C. Gan, R. W. Sparidans, E. Wagenaar, S. van Hoppe, J. H. Beijnen, A. H. Schinkel, Pharmacol. Res. 2018, 129, 414;b) Y. B. Patil, S. K. Swaminathan, T. Sadhukha, L. Ma, J. Panyam, Biomaterials 2010, 31, 358.

[21]

H. Zhang, W. Jiang, R. Liu, J. Zhang, D. Zhang, Z. Li, Y. Luan, ACS Appl. Mater. Interfaces 2017, 9, 19687.

[22]

K. Zhang, X. Tang, J. Zhang, W. Lu, X. Lin, Y. Zhang, B. Tian, H. Yang, H. He, J. Controlled Release 2014, 183, 77.

[23]

a) J. Cheng, B. A. Teply, I. Sherifi, J. Sung, G. Luther, F. X. Gu, E. Levy-Nissenbaum, A. F Radovic-Moreno, R. Langer, O. C. Farokhzad, Biomaterials 2007, 28, 869;b) G. Yang, Y. Liu, Y. Hui, Tengjisi, D. Chen, D. A. Weitz, C.-X. Zhao, Angew. Chem. Int. Ed. 2021, 60, 15426.

[24]

G. Yang, Y. Liu, S. Jin, Y. Hui, X. Wang, L. Xu, D. Chen, D. Weitz, C.-X. Zhao, Aggregate 2023, 4, e314.

[25]

L. Xu, X. Wang, G. Yang, Z. Zhao, Y. Weng, Y. Li, Y. Liu, C.-X. Zhao, Aggregate 2023, 4, e369.

[26]

C. J. M Rivas, M. Tarhini, W. Badri, K. Miladi, H. Greige-Gerges, Q. A. Nazari, S. A. G. Rodríguez, R. Á. Román, H. Fessi, A. Elaissari, Int. J. Pharm. 2017, 532, 66.

[27]

D. Reker, Y. Rybakova, A. R. Kirtane, R. Cao, J. W. Yang, N. Navamajiti, A. Gardner, R. M. Zhang, T. Esfandiary, J. L’Heureux, T. von Erlach, E. M. Smekalova, D. Leboeuf, K. Hess, A. Lopes, J. Rogner, J. Collins, S. M. Tamang, K. Ishida, P. Chamberlain, D. Yun, A. Lytton-Jean, C. K. Soule, J. H. Cheah, A. M. Hayward, R. Langer, G. Traverso, Nat. Nanotechnol. 2021, 16, 725.

[28]

a) C. Lampe, I. Kouroudis, M. Harth, S. Martin, A. Gagliardi, A. S. Urban, Adv. Mater. 2023, 35, 2208772; b) E. Vargo, J. C. Dahl, K. M. Evans, T. Khan, P. Alivisatos, T. Xu, Adv. Mater. 2022, 34, 2203168; c) L. Breiman, Mach. Learn. 2001, 45, 5.

[29]

J. Mockus, V. Tiesis, A. Zilinskas, in Towards Global Optimization, Vol. 2, Elsevier, North Holland 1978, p.117.

[30]

R. Mannhold, G. I. Poda, C. Ostermann, I. V. Tetko, J. Pharm. Sci. 2009, 98, 861.

[31]

MATLAB version:9.13.0 (R2022b), The MathWorks Inc., Natick, Massachusetts, United States 2022.

RIGHTS & PERMISSIONS

2024 The Author(s). Aggregate published by SCUT, AIEI, and John Wiley & Sons Australia, Ltd.

AI Summary AI Mindmap
PDF

142

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/