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Journal Abstract Search

143 related items for PubMed ID: 25361075

  • 21. Molecular mobility of amorphous S-flurbiprofen: a dielectric relaxation spectroscopy approach.
    Rodrigues AC, Viciosa MT, Danède F, Affouard F, Correia NT.
    Mol Pharm; 2014 Jan 06; 11(1):112-30. PubMed ID: 24215236
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  • 22. Correlation between glass-forming ability and fragility of pharmaceutical compounds.
    Kawakami K, Harada T, Yoshihashi Y, Yonemochi E, Terada K, Moriyama H.
    J Phys Chem B; 2015 Apr 09; 119(14):4873-80. PubMed ID: 25781503
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  • 23. An investigation into the influence of counterion on the properties of some amorphous organic salts.
    Towler CS, Li T, Wikström H, Remick DM, Sanchez-Felix MV, Taylor LS.
    Mol Pharm; 2008 Apr 09; 5(6):946-55. PubMed ID: 19434850
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  • 25. Novel descriptors from main and side chains of high-molecular-weight polymers applied to prediction of glass transition temperatures.
    Palomba D, Vazquez GE, Díaz MF.
    J Mol Graph Model; 2012 Sep 09; 38():137-47. PubMed ID: 23085161
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  • 26. Capturing the crystal: prediction of enthalpy of sublimation, crystal lattice energy, and melting points of organic compounds.
    Salahinejad M, Le TC, Winkler DA.
    J Chem Inf Model; 2013 Jan 28; 53(1):223-9. PubMed ID: 23215043
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  • 31. Scores of extended connectivity fingerprint as descriptors in QSPR study of melting point and aqueous solubility.
    Zhou D, Alelyunas Y, Liu R.
    J Chem Inf Model; 2008 May 28; 48(5):981-7. PubMed ID: 18465850
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  • 33. Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP-glucuronosyltransferase isoforms.
    Sorich MJ, Miners JO, McKinnon RA, Winkler DA, Burden FR, Smith PA.
    J Chem Inf Comput Sci; 2003 May 28; 43(6):2019-24. PubMed ID: 14632453
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  • 34. QSPR modelling for prediction of glass transition temperature of diverse polymers.
    Khan PM, Roy K.
    SAR QSAR Environ Res; 2018 Dec 28; 29(12):935-956. PubMed ID: 30392386
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  • 35. Machine learning analysis of a large set of homopolymers to predict glass transition temperatures.
    Casanola-Martin GM, Karuth A, Pham-The H, González-Díaz H, Webster DC, Rasulev B.
    Commun Chem; 2024 Oct 02; 7(1):226. PubMed ID: 39358434
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  • 36. Relationship between crystallization tendencies during cooling from melt and isothermal storage: toward a general understanding of physical stability of pharmaceutical glasses.
    Kawakami K, Harada T, Miura K, Yoshihashi Y, Yonemochi E, Terada K, Moriyama H.
    Mol Pharm; 2014 Jun 02; 11(6):1835-43. PubMed ID: 24731254
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  • 38. Development and validation of in silico models for estimating drug preformulation risk in PEG400/water and Tween80/water systems.
    Crivori P, Morelli A, Pezzetta D, Rocchetti M, Poggesi I.
    Eur J Pharm Sci; 2007 Nov 02; 32(3):169-81. PubMed ID: 17714921
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  • 39. Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature.
    Tao L, Varshney V, Li Y.
    J Chem Inf Model; 2021 Nov 22; 61(11):5395-5413. PubMed ID: 34662106
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  • 40. Skin permeation rate as a function of chemical structure.
    Katritzky AR, Dobchev DA, Fara DC, Hür E, Tämm K, Kurunczi L, Karelson M, Varnek A, Solov'ev VP.
    J Med Chem; 2006 Jun 01; 49(11):3305-14. PubMed ID: 16722649
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