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In Silico Research in Drug Delivery Systems

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Book cover Drug Delivery Systems: Advanced Technologies Potentially Applicable in Personalised Treatment

Part of the book series: Advances in Predictive, Preventive and Personalised Medicine ((APPPM,volume 4))

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Abstract

Like in many other research fields, scientific simulation has been established as a crucial element in the design technology of drug delivery systems. Modern multi-scale modeling and simulation techniques, supported by advanced and high-performance computational resources, form a cost-effective complement and/or alternative to the experimentally based trial-and-error approach traditionally used in the development of new drugs. This chapter gives a short overview of the application of modern modeling and simulation techniques within the context of drug delivery systems. Different approaches will be considered depending on the quality and the scale of organization of matter, ranging from picometers to nanoscale and beyond. Molecular modeling and simulation tools will be put in the perspective of their important role in the development of new drugs and in the simulation of their behavior. Such approach enables the engineering of tailored carriers for a specific drug, the optimization of its effectiveness, as well as the understanding at an atomistic level of how they interact with the surroundings. The application of computational flow models to drug delivery systems will be systematically addressed for hydrophobic and hydrophilic molecules. The current development of drug transport modeling by applying state-of-art computational fluid dynamics will also be described based on the drug release mechanism for diffusion, swelling and erosion-controlled systems. Finally, a brief prospective view on the high-performance scientific techniques underlying the advanced scientific simulation methods will be given.

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Notes

  1. 1.

    The complexity of the wavefunction based methods is usually emphasized through an example like the following. For a single oxygen atom, having eight electrons, its wavefunction ψ(r 1, r 2, ⋯ , r 8) is a function of 24 coordinates. Considering that just the modest number of 10 ψ values are to be stored for each coordinate, a total of 1024 values need to be stored. Could this be done on DVDs with a capacity of 5 GB, more than 1014 DVDs would be necessary. With a weight of 10 g per DVD, this would correspond to more than 109 ton DVDs!

References

  1. Acevedo O, Jorgensen WL (2010) Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions. Acc Chem Res 43(1):142–151. doi:10.1021/ar900171c

    Google Scholar 

  2. Alwarawrah M, Dai J, Huang J (2010) A molecular view of the cholesterol condensing effect in DOPC lipid bilayers. J Phys Chem B 114(22):7516–23. doi:10.1021/jp101415g

    Google Scholar 

  3. Annapragada A, Mishchiy N (2007) In silico modeling of aerosol deposition in lungs. Drug Disc Today 4(3):155–161. doi:10.1016/j.ddmod.2007.11.004

    Google Scholar 

  4. Arcamone F, Animati F, Capranico G, Lombardi P, Pratesi G, Manzini S, Supino R, Zunino F (1997) New developments in antitumor anthracyclines. Pharmacol Ther 76(1–3):117–124. doi:10.1016/S0163-7258(97)00096-X

    Google Scholar 

  5. Arifin DY, Lee LY, Wang CH (2006) Mathematical modeling and simulation of drug release from microspheres: implications to drug delivery systems. Adv Drug Deliver Rev 58(12–13):1274–325. doi:10.1016/j.addr.2006.09.007

    Google Scholar 

  6. Barth TJ, Griebel M, Keyes DE, Nieminen RM, Roose D, Schlick T, Knapek S, Zumbusch G (2007) Numerical simulation in molecular dynamics. Springer, Berlin

    Google Scholar 

  7. Cohen AJ, Mori-Sánchez P, Yang W (2012) Challenges for density functional theory. Chem Rev 112(1):289–320. doi:10.1021/cr200107z

    Google Scholar 

  8. Coote ML (2011) Ab initio kinetic modeling of free-radical polymerization. In: DaCosta H (ed) Rate constant calculation for thermal reactions: methods and applications. Wiley, New York

    Google Scholar 

  9. Crane M, Hurley N, Crane L, Healy A, Corrigan O, Gallagher K, McCarthy L (2004) Simulation of the USP drug delivery problem using CFD: experimental, numerical and mathematical aspects. Simul Model Pract Th 12(2):147–158. doi:10.1016/S1569-190X(03)00089-3

    Google Scholar 

  10. DaCosta H (ed) (2011) Rate constant calculation for thermal reactions. Wiley, New York

    Google Scholar 

  11. de Jong WA, Bylaska E, Govind N, Janssen CL, Kowalski K, Muller T, Nielsen IMB, van Dam HJJ, Veryazov V, Lindh R (2010) Utilizing high performance computing for chemistry: parallel computational chemistry. Phys Chem Chem Phys 12(26):6896–6920

    Google Scholar 

  12. Dorkoosh FA, Verhoef JC, Borchard G, Rafiee-Tehrani M, Junginger HE (2001) Development and characterization of a novel peroral peptide drug delivery system. J Control Release 71(3):307–318. doi:10.1016/S0168-3659(01)00232-2

    Google Scholar 

  13. Dorkoosh FA, Borchard G, Rafiee-Tehrani M, Verhoef JC, Junginger HE (2002) Evaluation of superporous hydrogel (SPH) and SPH composite in porcine intestine ex-vivo: assessment of drug transport, morphology effect, and mechanical fixation to intestinal wall. Eur J Pharm Biopharm 53(2):161–166

    Google Scholar 

  14. Dudukovic M (2002) Opaque multiphase flows: experiments and modeling. Exp Therm Fluid Sci 26(6–7):747–761. doi:10.1016/S0894-1777(02)00185-1

    Google Scholar 

  15. Engquist B, Ltstedt P, Runborg O (eds) (2009) Multiscale modeling and simulation in science. Springer, Berlin/Heidelberg

    Google Scholar 

  16. Fonseca AC, Jarmelo S, Carvalho RA, Fausto R, Gil MH, Simões PN (2010) H-1 NMR spectroscopic and quantum chemical studies on a poly(ester amide) model compound: Nα-benzoyl-L-argininate ethyl ester chloride. Structural preferences for the isolated molecule and in solution. J Phys Chem B 114(18):6156–6164. doi:10.1021/jp9114749

    Google Scholar 

  17. Fonseca AC, Jarmelo S, Silva MR, Beja AMM, Fausto R, Gil MH, Simões PN (2011) Study of Nα-benzoyl-L-argininate ethyl ester chloride, a model compound for poly(ester amide) precursors: x-ray diffraction, infrared and Raman spectroscopies, and quantum chemistry calculations. J Chem Phys 134(12):124505. doi:10.1063/1.3565966

    Google Scholar 

  18. Fredenberg S, Wahlgren M, Reslow M, Axelsson A (2011) The mechanisms of drug release in poly(lactic-co-glycolic acid)-based drug delivery systems-A review. Int J Pharm 415(1–2):34–52. doi:10.1016/j.ijpharm.2011.05.049

    Google Scholar 

  19. Friedrichs MS, Eastman P, Vaidyanathan V, Houston M, Legrand S, Beberg AL, Ensign DL, Bruns CM, Pande VS (2009) Accelerating molecular dynamic simulation on graphics processing units. J Comput Chem 30(6):864–872. doi:10.1002/jcc.21209

    Google Scholar 

  20. Friesner RA (2005) Ab initio quantum chemistry: methodology and applications. PNAS 102(19):6648–6653. doi:10.1073/pnas.0408036102

    Google Scholar 

  21. Garland M, Le Grand S, Nickolls J, Anderson J, Hardwick J, Morton S, Phillips E, Zhang Y, Volkov V (2008) Parallel computing experiences with CUDA. IEEE Micro 28(4):13–27. doi:10.1109/MM.2008.57

    Google Scholar 

  22. Gauss J (2000) Molecular properties. In: Grotendorst J (ed) NIC symposium 2000, Graphische Betriebe, Forschungszentrum Jülich, NIC series, vol 3, pp 541–592

    Google Scholar 

  23. Gordon MS, Fedorov DG, Pruitt SR, Slipchenko LV (2012) Fragmentation methods: a route to accurate calculations on large systems. Chem Rev 112(1):632–672. doi:10.1021/cr200093j

    Google Scholar 

  24. Gurtovenko Aa, Anwar J, Vattulainen I (2010) Defect-mediated trafficking across cell membranes: insights from in silico modeling. Chem Rev 110(10):6077–6103. doi:10.1021/cr1000783

    Google Scholar 

  25. Haddish-Berhane N, Nyquist C, Haghighi K, Corvalan C, Keshavarzian A, Campanella O, Rickus J, Farhadi A (2006) A multi-scale stochastic drug release model for polymer-coated targeted drug delivery systems. J Control Release 110(2):314–322. doi:10.1016/j.jconrel.2005.09.046

    Google Scholar 

  26. Han C, Wang B (2005) Factors that impact the developability of drug candidates: an overview. Wiley, Hoboken, chap 1, pp 1–14. doi:10.1002/0471475734.ch1

    Google Scholar 

  27. Hsu Y, Harris TJ, Hettiarachchi H, Penn R, Linninger AA (2011) Three dimensional simulation and experimental investigation of intrathecal drug delivery in the spinal canal and the brain. In: EN Pistikopoulos MG, Kokossis A (eds) 21st European symposium on computer aided process engineering. Elsevier, Amsterdam/Boston

    Google Scholar 

  28. Hu J, Liu S (2010) Responsive polymers for detection and sensing applications: current status and future developments. Macromolecules 43(20):8315–8330. doi:10.1021/ma1005815

    Google Scholar 

  29. Isse AA, Gennaro A, Lin CY, Hodgson JL, Coote ML, Guliashvili T (2011) Mechanism of carbon halogen bond reductive cleavage in activated alkyl halide initiators relevant to living radical polymerization: theoretical and experimental study. J Am Chem Soc 133(16):6254–6264. doi:10.1021/ja110538b

    Google Scholar 

  30. IUPAC (1997) Compendium of chemical terminology, 2nd edn. (the “Gold Book”). Compiled by A. D. McNaught and A. Wilkinson. Blackwell Scientific Publications, Oxford. URL http://goldbook.iupac.org. Accessed Dec 2011

  31. Izvekov S, Voth Ga (2005) A multiscale coarse-graining method for biomolecular systems. J Phys Chem B 109(7):2469–2473. doi:10.1021/jp044629q

    Google Scholar 

  32. Jarmelo S, Marques DAS, Simões PN, Carvalho RA, Batista CMSG, Araujo-Andrade C, Gil MH, Fausto R (2012) Experimental (IR/Raman and 1H/13C NMR) and theoretical (DFT) studies of the preferential conformations adopted by l-lactic acid oligomers and poly(l-lactic acid) homopolymer. J Phys Chem B 116(1):9–21. doi:10.1021/jp205033c

    Google Scholar 

  33. Jayaram B, Sprous D, Beveridge DL (1998) Solvation free energy of biomacromolecules: parameters for a modified generalized Born model consistent with the AMBER force field. J Phys Chem B 102(47):9571–9576. doi:10.1021/jp982007x

    Google Scholar 

  34. Jorgensen WL, Tirado-Rives J (1988) The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin. J Am Chem Soc 110(6):1657–1666. doi:10.1021/ja00214a001

    Google Scholar 

  35. Jorgensen WL, Maxwell DS, Tirado-Rives J (1996) Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J Am Chem Soc 118(45):11,225–11,236. doi:10.1021/ja9621760

    Google Scholar 

  36. Klein ML, Shinoda W (2008) Large-scale molecular dynamics simulations of self-assembling systems. Science 321(5890):798–800. doi:10.1126/science.1157834

    Google Scholar 

  37. Kleven M, Melaaen M, Reimers M, Røtnes J, Aurdal L, Djupesland P (2005) Using computational fluid dynamics (CFD) to improve the bi-directional nasal drug delivery concept. Food Bioprod Process 83(2):107–117. doi:10.1205/fbp.04403

    Google Scholar 

  38. Koch W, Holthausen MC (2001) A chemist’s guide to density functional theory. Wiley-VCH Verlag GmbH, Weinheim/New York

    Google Scholar 

  39. Kukol A (2009) Lipid models for united-atom molecular dynamics simulations of proteins. J Chem Theory Comput 5(3):615–626. doi:10.1021/ct8003468

    Google Scholar 

  40. Landau DP (2005) The future of simulation in materials science. In: Yip S (ed) Handbook of materials modeling. Springer, Dordrecht

    Google Scholar 

  41. Lao LL, Peppas Na, Boey FYC, Venkatraman SS (2010) Modeling of drug release from bulk-degrading polymers. Int J Pharm 418(1):28–41. doi:10.1016/j.ijpharm.2010.12.020

    Google Scholar 

  42. Li J, Futera Z, Li H, Tateyama Y, Higuchi M (2011) Conjugation of organic-metallic hybrid polymers and calf-thymus DNA. Phys Chem Chem Phys 13(11):4839–4841. doi:10.1039/c0cp02037k

    Google Scholar 

  43. Lin H, Truhlar D (2007) Qm/mm: what have we learned, where are we, and where do we go from here? Theor Chem Accounts Theor Comput Model Theor Chim Acta 117:185–199. doi:10.1007/s00214-006-0143-z

    Google Scholar 

  44. Linninger Aa (2011) Biomedical systems research? New perspectives opened by quantitative medical imaging. Comput Chem Eng 36:1–9. doi:10.1016/j.compchemeng.2011.07.010

    Google Scholar 

  45. Lins RD, Hünenberger PH (2005) A new GROMOS force field for hexopyranose-based carbohydrates. J Comput Chem 26(13):1400–1412. doi:10.1002/jcc.20275

    Google Scholar 

  46. Lipkowitz KB, Cundari TR (eds) (2010) Reviews in computational chemistry, vol 27. Wiley, Hoboken

    Google Scholar 

  47. Longest PW, Hindle M (2010) CFD simulations of enhanced condensational growth (ECG) applied to respiratory drug delivery with comparisons to in vitro data. J Aerosol Sci 41(8):805–820. doi:10.1016/j.jaerosci.2010.04.006

    Google Scholar 

  48. Longest PW, Holbrook LT (2011) In silico models of aerosol delivery to the respiratory tract –  development and applications. Adv Drug Deliver Rev. doi:10.1016/j.addr.2011.05.009

    Google Scholar 

  49. Loverde SM, Klein ML, Discher DE (2011) Nanoparticle shape improves delivery: rational coarse grain molecular dynamics (rCG-MD) of taxol in worm-like PEG-PCL micelles. Adv Mater. doi:10.1002/adma.201103192

    Google Scholar 

  50. Lu D, Aksimentiev A, Shih AY, Cruz-Chu E, Freddolino PL, Arkhipov A, Schulten K (2006) The role of molecular modeling in bionanotechnology. Phys Biol 3(1):S40–S53. doi:10.1088/1478-3975/3/1/S05

    Google Scholar 

  51. Maginn EJ, Elliott JR (2010) Historical perspective and current outlook for molecular dynamics as a chemical engineering tool. Ind Eng Chem Res 49(7):3059–3078. doi:10.1021/ie901898k

    Google Scholar 

  52. Malde AK, Zuo L, Breeze M, Stroet M, Poger D, Nair PC, Oostenbrink C, Mark AE (2011) An automated force field topology builder (ATB) and repository: version 1.0. J Chem Theory Comput 7(12):4026–4037. doi:10.1021/ct200196m

    Google Scholar 

  53. Marrink SJ, de Vries AH, Mark AE (2004) Coarse grained model for semiquantitative lipid simulations. J Phys Chem B 108(2):750–760. doi:10.1021/jp036508g

    Google Scholar 

  54. Marrink SJ, Risselada HJ, Yefimov S, Tieleman DP, de Vries AH (2007) The MARTINI force field: coarse grained model for biomolecular simulations. J Phys Chem B 111(27):7812–7824. doi:10.1021/jp071097f

    Google Scholar 

  55. McQuarrie DA (2007) Quantum chemistry, 2nd edn. University Science Books, Sausalito

    Google Scholar 

  56. Monticelli L, Kandasamy SK, Periole X, Larson RG, Tieleman DP, Marrink SJ (2008) The MARTINI coarse-grained force field: extension to proteins. J Chem Theory Comput 4(5):819–834. doi:10.1021/ct700324x

    Google Scholar 

  57. Mortier STFC, De Beer T, Gernaey KV, Remon JP, Vervaet C, Nopens I (2011) Mechanistic modelling of fluidized bed drying processes of wet porous granules: a review. Eur J Pharm Biopharm 79:205–225. doi:10.1016/j.ejpb.2011.05.013

    Google Scholar 

  58. Odoh SO, Walker SM, Meier M, Stetefeld J, Schreckenbach G (2011) QM and QM/MM studies of uranyl fluorides in the gas and aqueous phases and in the hydrophobic cavities of tetrabrachion. Inorg Chem 50(7):3141–3152. doi:10.1021/ic2001706

    Google Scholar 

  59. Oostenbrink C, Villa A, Mark AE, van Gunsteren WF (2004) A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J Comput Chem 25(13):1656–1676. doi:10.1002/jcc.20090

    Google Scholar 

  60. Oostenbrink C, Soares TA, van Der Vegt NFA, van Gunsteren WF (2005) Validation of the 53A6 GROMOS force field. Eur Biophys J 34(4):273–284. doi:10.1007/s00249-004-0448-6

    Google Scholar 

  61. Owens J, Houston M, Luebke D, Green S, Stone J, Phillips J (2008) GPU computing. Proc IEEE 96(5):879–899. doi:10.1109/JPROC.2008.917757

    Google Scholar 

  62. Patel S, Brooks CL (2004) CHARMM fluctuating charge force field for proteins: I parameterization and application to bulk organic liquid simulations. J Comput Chem 25(1):1–15. doi:10.1002/jcc.10355

    Google Scholar 

  63. Patel S, Mackerell AD, Brooks CL (2004) CHARMM fluctuating charge force field for proteins: II protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model. J Comput Chem 25(12):1504–1514. doi:10.1002/jcc.20077

    Google Scholar 

  64. Paun IA, Moldovan A, Luculescu CR, Dinescu M (2011) Biocompatible polymeric implants for controlled drug delivery produced by MAPLE. Appl Surf Sci 257(24):10,780–10,788. doi:10.1016/j.apsusc.2011.07.097

    Google Scholar 

  65. Poger D, Mark AE (2010) On the validation of molecular dynamics simulations of saturated and cis -monounsaturated phosphatidylcholine lipid bilayers: a comparison with experiment. J Chem Theory Comput 6(1):325–336. doi:10.1021/ct900487a

    Google Scholar 

  66. Prabhakarpandian B, Shen MC, Pant K, Kiani MF (2011) Microfluidic devices for modeling cell-cell and particle-cell interactions in the microvasculature. Microvasc Res 82(3):210–220. doi:10.1016/j.mvr.2011.06.013

    Google Scholar 

  67. Praprotnik M, Site LD, Kremer K (2008) Multiscale simulation of soft matter: from scale bridging to adaptive resolution. Annu Rev Phys Chem 59(1):545–571. doi:10.1146/annurev.physchem.59.032607.093707

    Google Scholar 

  68. Puoci F, Iemma F, Picci N (2008) Stimuli-responsive molecularly imprinted polymers for drug delivery: a review. Curr Drug Del 5(2):85–96. doi:10.2174/156720108783954888

    Google Scholar 

  69. Rosen H, Abribat T (2005) The rise and rise of drug delivery. Nat Rev Drug Discov 4(5):381–385

    Google Scholar 

  70. Ross R, Mohanty S (eds) (2008) Multiscale simulation methods for nanomaterials. Wiley, Hoboken

    Google Scholar 

  71. Sajeesh S, Sharma CP (2006) Cyclodextrin-insulin complex encapsulated polymethacrylic acid based nanoparticles for oral insulin delivery. Int J Pharm 325(1–2):147–154. doi:10.1016/j.ijpharm.2006.06.019

    Google Scholar 

  72. Schlichting I, Berendzen J, Chu K, Stock AM, Maves SA, Benson DE, Sweet RM, Ringe D, Petsko GA, Sligar SG (2000) The catalytic pathway of cytochrome p450cam at atomic resolution. Science 287(5458):1615–1622. doi:10.1126/science.287.5458.1615

    Google Scholar 

  73. Schüttelkopf AW, van Aalten DMF (2004) PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr D 60(Pt 8):1355–1363. doi:10.1107/S0907444904011679

    Google Scholar 

  74. Shelley JC, Shelley MY, Reeder RC, Bandyopadhyay S, Klein ML (2001) A coarse grain model for phospholipid simulations. J Phys Chem B 105(19):4464–4470. doi:10.1021/jp010238p

    Google Scholar 

  75. Shi J, Votruba AR, Farokhzad OC, Langer R (2010) Nanotechnology in drug delivery and tissue engineering: from discovery to applications. Nano Lett 10(9):3223–3230. doi:10.1021/nl102184c

    Google Scholar 

  76. Soares Ta, Daura X, Oostenbrink C, Smith LJ, van Gunsteren WF (2004) Validation of the GROMOS force-field parameter set 45A3 against nuclear magnetic resonance data of hen egg lysozyme. J Biomol NMR 30(4):407–422. doi:10.1007/s10858-004-5430-1

    Google Scholar 

  77. Soares Ta, Hünenberger PH, Kastenholz Ma, Kräutler V, Lenz T, Lins RD, Oostenbrink C, van Gunsteren WF (2005) An improved nucleic acid parameter set for the GROMOS force field. J Comput Chem 26(7):725–737. doi:10.1002/jcc.20193

    Google Scholar 

  78. Stepniewski M, Pasenkiewicz-Gierula M, Róg T, Danne R, Orlowski A, Karttunen M, Urtti A, Yliperttula M, Vuorimaa E, Bunker A (2011) Study of PEGylated lipid layers as a model for PEGylated liposome surfaces: molecular dynamics simulation and Langmuir monolayer studies. Langmuir 27(12):7788–7798. doi:10.1021/la200003n

    Google Scholar 

  79. Stewart JJP (2007) Semiempirical molecular orbital methods. In: Lipkowitz KB, Boyd DB (eds) Reviews in computational chemistry. Wiley, New York

    Google Scholar 

  80. Stone JE, Saam J, Hardy DJ, Vandivort KL, Hwu WmW, Schulten K (2009) High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs. Proceedings of 2nd workshop on general purpose processing on graphics processing units –  GPGPU-2 pp 9–18. doi:10.1145/1513895.1513897

    Google Scholar 

  81. Stone JE, Hardy DJ, Ufimtsev IS, Schulten K (2010) GPU-accelerated molecular modeling coming of age. J Mol Graphics Model 29(2):116–125. doi:10.1016/j.jmgm.2010.06.010

    Google Scholar 

  82. Subashini M, Devarajan PV, Sonavane GS, Doble M (2011) Molecular dynamics simulation of drug uptake by polymer. J Mol Model 17(5):1141–1147. doi:10.1007/s00894-010-0811-8

    Google Scholar 

  83. Szabo A, Ostlund NS (1989) Modern quantum chemistry. McGraw-Hill, Inc., New York

    Google Scholar 

  84. Teo CS, Hor Keong Tan W, Lee T, Wang CH (2005) Transient interstitial fluid flow in brain tumors: effect on drug delivery. Chem Eng Sci 60(17):4803–4821. doi:10.1016/j.ces.2005.04.008

    Google Scholar 

  85. Thassu D, Pathak Y, Deleers M (2007) Nanoparticulate drug-delivery systems: an overview. In: Thassu D, Pathak Y, Deleers M (eds) Nanoparticulate drug delivery systems. Informa Healthcare, New York

    Google Scholar 

  86. Timko BP, Whitehead K, Gao W, Kohane DS, Farokhzad O, Anderson D, Langer R (2011) Advances in drug delivery. Annu Rev Mater Res 41(1):1–20. doi:10.1146/annurev-matsci-062910-100359

    Google Scholar 

  87. Truhlar DG (2008) Molecular modeling of complex chemical systems. J Am Chem Soc 130(50):16,824–16,827. doi:10.1021/ja808927h

    Google Scholar 

  88. Utkov H, Livengood M, Cafiero M (2010) Using density functional theory methods for modeling induction and dispersion interactions in ligand-protein complexes. In: Wheeler RA (ed) Annual reports in computational chemistry. Elsevier, Amsterdam/Boston

    Google Scholar 

  89. Vaidya A, Wigent R, Moore J, Schwartz J (2007) Protective effect of Carbopol on enzymatic degradation of a peptide-like substrate. I: effect of various concentrations and grades of Carbopol and other reaction variables on trypsin activity. Pharm Dev Technol 12(1):89–96. doi:10.1080/10837450601168656

    Google Scholar 

  90. Vasapollo G, Del Sole R, Mergola L, Lazzoi MR, Scardino A, Scorrano S, Mele G (2011) Molecularly imprinted polymers: present and future prospective. Int J Mol Sci 12(9):5908–5945. doi:10.3390/ijms12095908

    Google Scholar 

  91. Wang J, Wolf RM, Caldwell JW, Kollman Pa, Case Da (2004) Development and testing of a general amber force field. J Comput Chem 25(9):1157–1174. doi:10.1002/jcc.20035

    Google Scholar 

  92. Wang Q, Keffer DJ, Petrovan S, Thomas JB (2010) Molecular dynamics simulation of poly(ethylene terephthalate) oligomers. J Phys Chem B 114(2):786–795. doi:10.1021/jp909762j

    Google Scholar 

  93. Wheeler RA (ed) (2011) Annual reports in computational chemistry, vol 7. Elsevier, Amsterdam/London

    Google Scholar 

  94. Winter ND, Schatz GC (2010) Coarse-grained molecular dynamics study of permeability enhancement in DPPC bilayers by incorporation of lysolipid. J Phys Chem B 114(15):5053–5060. doi:10.1021/jp911309s

    Google Scholar 

  95. Xiang TX, Anderson BD (2006) Liposomal drug transport: a molecular perspective from molecular dynamics simulations in lipid bilayers. Adv Drug Deliver Rev 58(12–13):1357–1378. doi:10.1016/j.addr.2006.09.002

    Google Scholar 

  96. Xinhuai Z (2006) Three leading molecular dynamics simulation packages. SVU/Academic Computing, Computer Centre, National University of Singapore

    Google Scholar 

  97. Yang L, Alexandridis P (2000) Physicochemical aspects of drug delivery and release from polymer-based colloids. Curr Opin Colloid Interface Sci 5(1–2):132–143. doi:10.1016/S1359-0294(00)00046-7

    Google Scholar 

  98. Yip S (ed) (2005) Handbook of materials modeling. Springer, Dordrecht

    Google Scholar 

  99. Zoete V, Cuendet MA, Grosdidier A, Michielin O (2011) SwissParam: a fast force field generation tool for small organic molecules. J Comput Chem 32(11):2359–2368. doi:10.1002/jcc.21816

    Google Scholar 

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  1. Department of Chemical Engineering, University of Coimbra, Pólo II, Pinhal de Marrocos, Coimbra, 3030-790, Portugal

    André Filipe Ferreira, Rodrigo José Lopes & Pedro Nuno Simões

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    Jorge Coelho

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Ferreira, A.F., Lopes, R.J., Simões, P.N. (2013). In Silico Research in Drug Delivery Systems. In: Coelho, J. (eds) Drug Delivery Systems: Advanced Technologies Potentially Applicable in Personalised Treatment. Advances in Predictive, Preventive and Personalised Medicine, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6010-3_10

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