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Drug Delivery and Translational Research

, Volume 8, Issue 6, pp 1797–1806 | Cite as

Finding key nanoprecipitation variables for achieving uniform polymeric nanoparticles using neurofuzzy logic technology

  • Miguel O. Jara
  • Johanna Catalan-Figueroa
  • Mariana Landin
  • Javier O. Morales
Original Article

Abstract

Nanoprecipitation is a simple and fast method to produce polymeric nanoparticles (Np); however, most applications require filtration or another separation technique to isolate the nanosuspension from aggregates or polydisperse particle production. In order to avoid variability introduced by these additional steps, we report here a systematic study of the process to yield monomodal and uniform Np production with the nanoprecipitation method. To further identify key variables and their interactions, we used artificial neural networks (ANN) to investigate the multiple variables which influence the process. In this work, a polymethacrylate derivative was used for Np (NpERS) and a database with several formulations and conditions was developed for the ANN model. The resulting ANN model had a high predictability (> 70%) for NpERS characteristics measured (mean size, PDI, zeta potential, and number of particle populations). Moreover, the model identified production variables leading to polymer supersaturation, such as mixing time and turbulence, as key in achieving monomodal and uniform NpERS in one production step. Polymer concentration and type of solvent, modifiers of polymer diffusion and supersaturation, were also shown to control NpERS characteristics. The ANN study allowed the identification of key variables and their interactions and resulted in a predictive model to study the NpERS production by nanoprecipitation. In turn, we have achieved an optimized method to yield uniform NpERS which could pave way for polymeric nanoparticle production methods with potential in biological and drug delivery applications.

Keywords

Nanoprecipitation Artificial neural networks Polymeric nanoparticles Nanoparticle production Mixing time Homogeneous nanoparticles 

Notes

Funding information

The authors acknowledge the funding support from FONDECYT 11130235 and FONDAP 15130011.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

13346_2017_446_MOESM1_ESM.pdf (785 kb)
ESM 1 (PDF 784 kb)

References

  1. 1.
    Bunjes H. Lipid nanoparticles for the delivery of poorly water-soluble drugs. J Pharm Pharmacol. 2010;62(11):1637–45.  https://doi.org/10.1111/j.2042-7158.2010.01024.x.Google Scholar
  2. 2.
    Kipp JE. The role of solid nanoparticle technology in the parenteral delivery of poorly water-soluble drugs. Int J Pharm. 2004;284(1–2):109–22.  https://doi.org/10.1016/j.ijpharm.2004.07.019.Google Scholar
  3. 3.
    A. Kumar, H. M. Mansour, A. Friedman and E. R. Blough, Nanomedicine in drug delivery, CRC, 2013, doi:  https://doi.org/10.1201/b14802.
  4. 4.
    Merisko-Liversidge EM, Liversidge GG. Drug nanoparticles: formulating poorly water-soluble compounds. Toxicol Pathol. 2008;36(1):43–8.  https://doi.org/10.1177/0192623307310946.Google Scholar
  5. 5.
    M. M. de Villiers, P. Aramwit and G. S. Kwon, Nanotechnology in drug delivery. Springer, 2008.Google Scholar
  6. 6.
    Fessi H, Puisieux F, Devissaguet JP, Ammoury N, Benita S. Nanocapsule formation by interfacial polymer deposition following solvent displacement. Int J Pharm. 1989;55(1):R1–4.  https://doi.org/10.1016/0378-5173(89)90281-0.Google Scholar
  7. 7.
    Lepeltier E, Bourgaux C, Couvreur P. Nanoprecipitation and the “Ouzo effect”: application to drug delivery devices. Adv Drug Deliv Rev. 2014;71:86–97.  https://doi.org/10.1016/j.addr.2013.12.009.Google Scholar
  8. 8.
    Schubert S, Joseph J, Delaney T, Schubert US. Nanoprecipitation and nanoformulation of polymers: from history to powerful possibilities beyond poly(lactic acid). Soft Matter. 2011;7(5):1581–8.  https://doi.org/10.1039/C0SM00862A.Google Scholar
  9. 9.
    Baby T, Liu Y, Middelberg APJ, Zhao C-X. Fundamental studies on throughput capacities of hydrodynamic flow-focusing microfluidics for producing monodisperse polymer nanoparticles. Chem Eng Sci. 2017;169:128–39.  https://doi.org/10.1016/j.ces.2017.04.046.Google Scholar
  10. 10.
    Albisa A, Piacentini E, Sebastian V, Arruebo M, Santamaria J, Giorno L. Preparation of drug-loaded PLGA-PEG nanoparticles by membrane-assisted nanoprecipitation. Pharm Res. 2017;34(6):1296–308.  https://doi.org/10.1007/s11095-017-2146-y.Google Scholar
  11. 11.
    Allen S, Osorio O, Liu Y-G, Scott E. Facile assembly and loading of theranostic polymersomes via multi-impingement flash nanoprecipitation. J Control Release. 2017;262:91–103.  https://doi.org/10.1016/j.jconrel.2017.07.026.Google Scholar
  12. 12.
    Beck-Broichsitter M, Nicolas J, Couvreur P. Solvent selection causes remarkable shifts of the “Ouzo region” for poly(lactide-co-glycolide) nanoparticles prepared by nanoprecipitation. Nanoscale. 2015;7(20):9215–21.  https://doi.org/10.1039/C5NR01695A.
  13. 13.
    Yang Z, Foster D, Dhinojwala A. Continuous production of polymer nanoparticles using a membrane-based flow cell. J Colloid Interface Sci. 2017;501:150–5.  https://doi.org/10.1016/j.jcis.2017.04.044.Google Scholar
  14. 14.
    Vitale SA, Katz JL. Liquid droplet dispersions formed by homogeneous liquid−liquid nucleation: “The Ouzo Effect.” Langmuir. 2003;19(10):4105–10.  https://doi.org/10.1021/la026842o.
  15. 15.
    Aubry J, Ganachaud F, Cohen Addad J-P, Cabane B. Nanoprecipitation of polymethylmethacrylate by solvent shifting: 1. Boundaries. Langmuir. 2009;25(4):1970–9.  https://doi.org/10.1021/la803000e.Google Scholar
  16. 16.
    Legrand P, Lesieur S, Bochot A, Gref R, Raatjes W, Barratt G, et al. Influence of polymer behaviour in organic solution on the production of polylactide nanoparticles by nanoprecipitation. Int J Pharm. 2007;344(1-2):33–43.  https://doi.org/10.1016/j.ijpharm.2007.05.054.Google Scholar
  17. 17.
    Sommerfeld P, Schroeder U, Sabel BA. Long-term stability of PBCA nanoparticle suspensions suggests clinical usefulness. Int J Pharm. 1997;155(2):201–7.  https://doi.org/10.1016/S0378-5173(97)00153-1.Google Scholar
  18. 18.
    Gaumet M, Vargas A, Gurny R, Delie F. Nanoparticles for drug delivery: the need for precision in reporting particle size parameters. Eur J Pharm Biopharm. 2008;69(1):1–9.  https://doi.org/10.1016/j.ejpb.2007.08.001.Google Scholar
  19. 19.
    Di Pasquale N, Marchisio DL, Barresi AA. Model validation for precipitation in solvent-displacement processes. Chem Eng Sci. 2012;84:671–83.  https://doi.org/10.1016/j.ces.2012.08.043.Google Scholar
  20. 20.
    Horn D, Rieger J. Organic nanoparticles in the aqueous phase—theory, experiment, and use. Angew Chem Int Ed. 2001;40(23):4330–61.  https://doi.org/10.1002/1521-3773(20011203)40:23<4330::AID-ANIE4330>3.0.CO;2-W.Google Scholar
  21. 21.
    Lince F, Marchisio DL, Barresi AA. Strategies to control the particle size distribution of poly-ε-caprolactone nanoparticles for pharmaceutical applications. J Colloid Interface Sci. 2008;322(2):505–15.  https://doi.org/10.1016/j.jcis.2008.03.033.Google Scholar
  22. 22.
    Matteucci ME, Hotze MA, Johnston KP, Williams RO. Drug nanoparticles by antisolvent precipitation: mixing energy versus surfactant stabilization. Langmuir. 2006;22(21):8951–9.  https://doi.org/10.1021/la061122t.
  23. 23.
    Rao JP, Geckeler KE. Polymer nanoparticles: preparation techniques and size-control parameters. Prog Polym Sci. 2011;36(7):887–913.  https://doi.org/10.1016/j.progpolymsci.2011.01.001.Google Scholar
  24. 24.
    Bilati U, Allémann E, Doelker E. Strategic approaches for overcoming peptide and protein instability within biodegradable nano- and microparticles. Eur J Pharm Biopharm. 2005;59(3):375–88.  https://doi.org/10.1016/j.ejpb.2004.10.006.
  25. 25.
    Bodmeier R, Chen H, Tyle P, Jarosz P. Spontaneous formation of drug-containing acrylic nanoparticles. J Microencapsul. 1991;8(2):161–70.  https://doi.org/10.3109/02652049109071485.Google Scholar
  26. 26.
    Hoffart V, Lamprecht A, Maincent P, Lecompte T, Vigneron C, Ubrich N. Oral bioavailability of a low molecular weight heparin using a polymeric delivery system. J Control Release. 2006;113(1):38–42.  https://doi.org/10.1016/j.jconrel.2006.03.020.Google Scholar
  27. 27.
    Jiao Y, Ubrich N, Marchand-Arvier M, Vigneron C, Hoffman M, Lecompte T, et al. In vitro and in vivo evaluation of oral heparin-loaded polymeric nanoparticles in rabbits. Circulation. 2002;105(2):230–5.  https://doi.org/10.1161/hc0202.101988.Google Scholar
  28. 28.
    Pignatello R, Bucolo C, Ferrara P, Maltese A, Puleo A, Puglisi G. Eudragit RS100® nanosuspensions for the ophthalmic controlled delivery of ibuprofen. Eur J Pharm Sci. 2002;16(1-2):53–61.  https://doi.org/10.1016/S0928-0987(02)00057-X.Google Scholar
  29. 29.
    Gargouri M, Sapin A, Bouali S, Becuwe P, Merlin JL, Maincent P. Optimization of a new non-viral vector for transfection: Eudragit nanoparticles for the delivery of a DNA plasmid. Technol Cancer Res Treat. 2009;8(6):433–43.  https://doi.org/10.1177/153303460900800605.Google Scholar
  30. 30.
    Seremeta KP, Chiappetta DA, Sosnik A. Poly(ɛ-caprolactone), Eudragit® RS 100 and poly(ɛ-caprolactone)/Eudragit® RS 100 blend submicron particles for the sustained release of the antiretroviral efavirenz. Colloids Surf B Biointerfaces. 2013;102:441–9.  https://doi.org/10.1016/j.colsurfb.2012.06.038.Google Scholar
  31. 31.
    Agatonovic-Kustrin S, Beresford R. Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research. J Pharm Biomed Anal. 2000;22(5):717–27.  https://doi.org/10.1016/S0731-7085(99)00272-1.Google Scholar
  32. 32.
    Colbourn EA, Rowe RC. Novel approaches to neural and evolutionary computing in pharmaceutical formulation: challenges and new possibilities. Future Med Chem. 2009;1(4):713–26.  https://doi.org/10.4155/fmc.09.57.Google Scholar
  33. 33.
    Achanta AS, Kowalski JG, Rhodes CT. Artificial neural networks: implications for pharmaceutical sciences. Drug Dev Ind Pharm. 1995;21(1):119–55.  https://doi.org/10.3109/03639049509048099.Google Scholar
  34. 34.
    Díaz-Rodríguez P, Landin M. Smart design of intratumoral thermosensitive β-lapachone hydrogels by artificial neural networks. Int J Pharm. 2012;433(1–2):112–8.  https://doi.org/10.1016/j.ijpharm.2012.05.008.Google Scholar
  35. 35.
    Kazazi-Hyseni F, Landin M, Lathuile A, Veldhuis GJ, Rahimian S, Hennink WE, et al. Computer modeling assisted design of monodisperse PLGA microspheres with controlled porosity affords zero order release of an encapsulated macromolecule for 3 months. Pharm Res. 2014;31(10):2844–56.  https://doi.org/10.1007/s11095-014-1381-8.Google Scholar
  36. 36.
    Landin M, Rowe RC. In: Aguilar JE, editor. Formulation tools for pharmaceutical development. Oxford: Woodhead; 2013. p. 7–37.Google Scholar
  37. 37.
    Landín M, Rowe RC, York P. Advantages of neurofuzzy logic against conventional experimental design and statistical analysis in studying and developing direct compression formulations. Eur J Pharm Sci. 2009;38(4):325–31.  https://doi.org/10.1016/j.ejps.2009.08.004.Google Scholar
  38. 38.
    Rowe RC, Colbourn EA. Computers in pharmaceutical formulation. In: Ekins S, editor. Computer applications in pharmaceutical research and development. New York: Wiley; 2006. p. 677–701.Google Scholar
  39. 39.
    Colbourn E, Rowe RC. Encyclopedia of pharmaceutical technology. New York: Marcel Dekker; 2005. p. 145–57.Google Scholar
  40. 40.
    Johnson BK, Prud’homme RK. Mechanism for rapid self-assembly of block copolymer nanoparticles. Phys Rev Lett. 2003;91(11):118302.  https://doi.org/10.1103/PhysRevLett.91.118302.Google Scholar
  41. 41.
    Molpeceres J, Guzman M, Aberturas MR, Chacon M, Berges L. Application of central composite designs to the preparation of polycaprolactone nanoparticles by solvent displacement. J Pharm Sci. 1996;85(2):206–13.  https://doi.org/10.1021/js950164r.Google Scholar
  42. 42.
    Stepanyan R, Lebouille JGJL, Slot JJM, Tuinier R, Stuart MAC. Controlled nanoparticle formation by diffusion limited coalescence. Phys Rev Lett. 2012;109(13):138301.  https://doi.org/10.1103/PhysRevLett.109.138301.Google Scholar
  43. 43.
    Xu J, Zhang S, Machado A, Lecommandoux S, Sandre O, Gu F, et al. Controllable microfluidic production of drug-loaded PLGA nanoparticles using partially water-miscible mixed solvent microdroplets as a precursor. Sci Rep. 2017;7(1):4794.  https://doi.org/10.1038/s41598-017-05184-5.Google Scholar
  44. 44.
    Tan Y, Xu K, Li L, Liu C, Song C, Wang P. Fabrication of size-controlled starch-based nanospheres by nanoprecipitation. ACS Appl Mater Interfaces. 2009;1(4):956–9.  https://doi.org/10.1021/am900054f.Google Scholar
  45. 45.
    Badri W, Miladi K, Nazari QA, Fessi H, Elaissari A. Effect of process and formulation parameters on polycaprolactone nanoparticles prepared by solvent displacement. Colloids Surf Physicochem Eng Asp. 2017;516:238–44.  https://doi.org/10.1016/j.colsurfa.2016.12.029.Google Scholar
  46. 46.
    Choi S-W, Kwon H-Y, Kim W-S, Kim J-H. Thermodynamic parameters on poly(D,L-lactide-co-glycolide) particle size in emulsification-diffusion process. Colloids Surf Physicochem Eng Asp. 2002;201(1-3):283–9.  https://doi.org/10.1016/S0927-7757(01)01042-1.Google Scholar
  47. 47.
    Galindo-Rodriguez S, Allémann E, Fessi H, Doelker E. Physicochemical parameters associated with nanoparticle formation in the salting-out, emulsification-diffusion, and nanoprecipitation methods. Pharm Res. 2004;21(8):1428–39.  https://doi.org/10.1023/B:PHAM.0000036917.75634.be.Google Scholar
  48. 48.
    J. H. Kim, T. K. Ryu, K. Y. Jeong, D.-H. Paik, S.-K. Moon and S.-W. Choi, J Pharm Investig, 2014, 45, 157–161.Google Scholar
  49. 49.
    Van Krevelen DW, Te Nijenhuis K. In: Van Krevelen DW, Nijenhuis KT, editors. Properties of polymers (fourth edition). Amsterdam: Elsevier; 2009. p. 189–227.Google Scholar
  50. 50.
    Derlacki ZJ, Easteal AJ, Edge AVJ, Woolf LA, Roksandic Z. Diffusion coefficients of methanol and water and the mutual diffusion coefficient in methanol-water solutions at 278 and 298 K. J Phys Chem. 1985;89(24):5318–22.  https://doi.org/10.1021/j100270a039.Google Scholar
  51. 51.
    Wang C-C, Zhang G, Shah NH, Infeld MH, Waseem Malick A, McGinity JW. Influence of plasticizers on the mechanical properties of pellets containing Eudragit® RS 30 D. Int J Pharm. 1997;152(2):153–63.  https://doi.org/10.1016/S0378-5173(97)00080-X.Google Scholar
  52. 52.
    Ganachaud F, Katz JL. Nanoparticles and nanocapsules created using the Ouzo effect: spontaneous emulsification as an alternative to ultrasonic and high-shear devices. ChemPhysChem. 2005;6(2):209–16.  https://doi.org/10.1002/cphc.200400527.Google Scholar
  53. 53.
    Hornig S, Heinze T. Efficient approach to design stable water-dispersible nanoparticles of hydrophobic cellulose esters. Biomacromolecules. 2008;9(5):1487–92.  https://doi.org/10.1021/bm8000155.Google Scholar
  54. 54.
    Quintanar-Guerrero D, Allémann E, Fessi H, Doelker E. Preparation techniques and mechanisms of formation of biodegradable nanoparticles from preformed polymers. Drug Dev Ind Pharm. 1998;24(12):1113–28.  https://doi.org/10.3109/03639049809108571.Google Scholar
  55. 55.
    Sternling CV, Scriven LE. Interfacial turbulence: hydrodynamic instability and the marangoni effect. AICHE J. 1959;5(4):514–23.  https://doi.org/10.1002/aic.690050421.Google Scholar
  56. 56.
    Prasad KN, Luong TT, FlorenceJoelle Paris AT, Vaution C, Seiller M, Puisieux F. Surface activity and association of ABA polyoxyethylene–polyoxypropylene block copolymers in aqueous solution. J Colloid Interface Sci. 1979;69(2):225–32.  https://doi.org/10.1016/0021-9797(79)90151-6.Google Scholar

Copyright information

© Controlled Release Society 2017

Authors and Affiliations

  • Miguel O. Jara
    • 1
  • Johanna Catalan-Figueroa
    • 1
  • Mariana Landin
    • 2
  • Javier O. Morales
    • 1
    • 3
    • 4
  1. 1.Department of Pharmaceutical Science and Technology, School of Chemical and Pharmaceutical SciencesUniversity of ChileSantiagoChile
  2. 2.Department of Pharmacology, Pharmacy and Pharmaceutical TechnologyUniversity of SantiagoSantiago de CompostelaSpain
  3. 3.Advanced Center for Chronic Diseases (ACCDiS)SantiagoChile
  4. 4.Pharmaceutical Biomaterial Research Group, Department of Health SciencesLuleå University of TechnologyLuleåSweden

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