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    <Journal>
      <PublisherName>isfcppharmaspire</PublisherName>
      <JournalTitle>Pharmaspire</JournalTitle>
      <PISSN>C</PISSN>
      <EISSN>o</EISSN>
      <Volume-Issue>Volume 14,Issue 2, 2022 </Volume-Issue>
      <PartNumber/>
      <IssueTopic>Multidisciplinary</IssueTopic>
      <IssueLanguage>English</IssueLanguage>
      <Season>April-June</Season>
      <SpecialIssue>N</SpecialIssue>
      <SupplementaryIssue>N</SupplementaryIssue>
      <IssueOA>Y</IssueOA>
      <PubDate>
        <Year>-0001</Year>
        <Month>11</Month>
        <Day>30</Day>
      </PubDate>
      <ArticleType>Pharmaceutics</ArticleType>
      <ArticleTitle>Prediction of excipient-excipient incompatibility: A latent threat to pharmaceutical product development</ArticleTitle>
      <SubTitle/>
      <ArticleLanguage>English</ArticleLanguage>
      <ArticleOA>Y</ArticleOA>
      <FirstPage>65</FirstPage>
      <LastPage>75</LastPage>
      <AuthorList>
        <Author>
          <FirstName>Junaid Ul</FirstName>
          <LastName>Hamid</LastName>
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
          <FirstName>Sunil</FirstName>
          <LastName>Gupta</LastName>
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
        </Author>
      </AuthorList>
      <DOI>10.56933/Pharmaspire.2022.14208</DOI>
      <Abstract>The importance of pharmaceutical excipients in the creation of any dosage form is critical. These excipients are occasionally to blame for product underperformance and dosage form deterioration. Product deterioration and underperformance could be attributed to incompatibilities between drug and excipient or sometimes excipient and excipient either due to the presence of reactive impurities in the excipients or a reaction between the functional groups present on the excipients. Although the drug and excipient incompatibilities are monitored and reported, excipient-excipient incompatibilities are overlooked due to a paucity of the literature. Pharmaceutical companies used to work in a controlled environment (compatibility&#13;
tests between excipients to determine the best excipients for dosage form creation) and utilize mitigation measures to suppress any incompatibilities between excipients when necessary. These tactics take time and money to implement, and they increase the cost of developing a dosage form. However, the primary goal of this review is to highlight some of the most prevalent excipient-excipient incompatibilities that can occur during dosage form development, possible incompatibility reactions, as well as a potential method for predicting excipient-excipient incompatibilities based on structural information. The structure incompatibility relationship strategy to forecast incompatibilities between diverse excipients is an idea based on the reactivity of pharmaceutical excipients, and it might be a useful tool in reducing the time, cost, and product failures during the product development due to excipient-excipient incompatibilities.</Abstract>
      <AbstractLanguage>English</AbstractLanguage>
      <Keywords>Excipient-excipient incompatibility, Reactive impurities, Functional groups, Degradation reactions, Quantitative structure-property relationship</Keywords>
      <URLs>
        <Abstract>https://isfcppharmaspire.com/ubijournal-v1copy/journals/abstract.php?article_id=14110&amp;title=Prediction of excipient-excipient incompatibility: A latent threat to pharmaceutical product development</Abstract>
      </URLs>
      <References>
        <ReferencesarticleTitle>References</ReferencesarticleTitle>
        <ReferencesfirstPage>16</ReferencesfirstPage>
        <ReferenceslastPage>19</ReferenceslastPage>
        <References>1. Carlin B, Collins GK. Composition Guide for Pharmaceutical Excipients. The Internationational Pharmaceutical Excipients Council; 2020. p. 1-16.&#13;
2. Zhang K, Pellett JD, Narang AS, Wang YJ, Zhang YT. Reactive impurities in large and small molecule pharmaceutical excipients a review. Trends Anal Chem 2018;101:34-42.&#13;
3. Bari SB, Kadam BR, Jaiswal YS, Shirkhedkar AA. Impurity profile: Significance in active pharmaceutical ingredient. Eur J Anal Chem 2007;2:32-53.&#13;
4. Jenke DR, Stults CL, Paskiet DM, Jenke DR, Stults CL, Paskiet DM, et al. Materials in manufacturing and packaging systems as sources of elemental impurities in packaged drug products: A literature review. PDA J Pharm Sci Technol 2015;69:1-48.&#13;
5. Knowles DB, Shkel IA, Phan NM, Sternke M, Lingeman E, Cheng X, et al. Chemical interactions of polyethylene glycols (PEGs) and glycerol with protein functional groups: Applications to effects of PEG and glycerol on protein processes. Biochemistry 2015;54:3528-42.&#13;
6. Bindra DS, Stein D, Pandey P, Barbour N. Incompatibility of croscarmellose sodium with alkaline excipients in a tablet formulation. Pharm Dev Technol 2014;19:285-9.&#13;
7. Thakral S, Thakral NK, Majumdar DK. Eudragit: A technology evaluation. Expert Opin Drug Discov 2013;10:131-49.&#13;
8. Rowe RC, Sheskey PJ, Quinn ME. Handbook of Pharmaceutical Excipients. Vol. 6th ed. London, United Kingdom: Pharmaceutical Press; 2009. p. 917.&#13;
9. Pramod K, Suneesh CV, Shanavas S, Ansari SH, Ali J. Unveiling the compatibility of eugenol with formulation excipients by systematic drug-excipient compatibility studies. J Anal Sci Technol. 2015;6:34.&#13;
10. Clarancia S, Dhanjal JK, Malik V, Hospital W, Radhakrishnan N. Quantitative Structure-activity Hamid and Gupta: Prediction of excipient incompatibility Pharmaspire | Vol. 14 | No. 2 | 2022 74 Relationship (QSAR): Modeling Approaches to Encyclopedia of Bioinformatics and Computational Biology: Quantitative Structure-activity Relationship (QSAR): Modeling Approaches to Biological Applications; 2018. p. 40.&#13;
11. Plante M, Zhang Q, Zhang Q, Scientific TF, High T, High T. Determination of Proteins and Carbohydrates by 2D HPLC (RPLC and HILIC) with Charged Aerosol and Ultraviolet Detection; 2015. p. 2-4.&#13;
12. Huang T, Garceau ME, Gao P. Liquid chromatographic determination of residual hydrogen peroxide in pharmaceutical excipients using platinum and wired enzyme electrodes. J Pharm Biomed Anal 2003;31:1203-10.&#13;
13. Yue H, Bu X, Huang MH, Young J, Raglione T. Quantitative determination of trace levels of hydrogen peroxide in crospovidone and a pharmaceutical product using high performance liquid chromatography with coulometric detection. Int J Pharm 2009;375:33-40.&#13;
14. Nielsen NS, Timm-Heinrich M, Jacobsen C. Comparison of wet-chemical methods for determination of lipid hydroperoxides. J Food Lipids 2003;10:35-50.&#13;
15. Li Z, Jacobus LK, Wuelfing WP, Golden M, Martin GP, Reed RA. Detection and quantification of low-molecularweight aldehydes in pharmaceutical excipients by headspace gas chromatography. J Chromatogr A 2006;1104:1-10.&#13;
16. Daoudy BD, Al-Khayat MA, Karabet F, Al-Mardini MA. A robust static headspace GC-FID method to detect and quantify formaldehyde impurity in pharmaceutical excipients. J Anal Methods Chem 2018;2018:13-7.&#13;
17. Tian J. Application of static headspace gas chromatography for determination of acetaldehyde in beer. J Food Compos Anal 2010;23:475-9.&#13;
18. Prabhu P. Detection and Quantification of Formaldehyde by Derivatization with Pentafluorobenzylhydroxyl Amine in Pharmaceutical Excipients by Static Headspace GC/MS. Vol. 4. PerkinElmer Inc.; 2011.&#13;
19. Sugaya N, Nakagawa T, Sakurai K, Morita M, Onodera S. Analysis of aldehydes in water by head space-GC/MS. J Health Sci 2001;47:21-7.&#13;
20. Schiller M, Von Der Heydt H, Mand;auml;rz F, Schmidt PC. Quantification of sugars and organic acids in hygroscopic pharmaceutical herbal dry extracts. J Chromatogr A 2002;968:101-11.&#13;
21. Li X, Meng D, Zhao J, Yang Y. Simultaneous determination of nitrate and nitrite in wrapper by highperformance liquid chromatography with cloud-point extraction. Asian J Chem 2014;26:4363-6.&#13;
22. Menoutis J, Parisi A, Verma N. Study of the use of axial viewed inductively coupled plasma atomic emission spectrometry with ultrasonic nebulization for the determination of select elemental impurities in oral drug products. J Pharm Biomed Anal 2018;152:12-6.&#13;
23. Wirth DD, Baertschi SW, Johnson RA, Maple SR, Miller MS, Hallenbeck DK, et al. Maillard reaction of lactose and fluoxetine hydrochloride, secondary amine. J. Pharm. Sci. 1998;87:31-9.&#13;
24. Kishore RS, Kiese S, Fischer S, Pappenberger A, Grauschopf U, Mahler HC. The degradation of&#13;
polysorbates 20 and 80 and its potential impact on the stability of biotherapeutics. Pharm Res 2011;28:1194-210.&#13;
25. Paul D. Pharmaceutical water treatment. Ultrapure Water 2010;27:26-9.&#13;
26. Grodowska K, Parczewski A. Organic solvents in the pharmaceutical industry. Acta Pol Pharm Drug Res 2010;67:3-12.&#13;
27. Waterman KC, Adami RC, Alsante KM, Antipas AS, Arenson DR, Carrier R, et al. Hydrolysis in pharmaceutical formulations. Pharm Dev Technol 2002;7:113-46.&#13;
28. Hutchinson SA, Ho GS, Ho CT. Stability and degradation of the high-intensity sweeteners: Aspartame, alitame, and sucralose. Food Rev Int 1999;15:249-61.&#13;
29. Yue C, Li G, Pidko EA, Wiesfeld JJ, Rigutto M, Hensen EJ. Dehydration of glucose to 5-Hydroxymethylfurfural using Nb-doped tungstite. ChemSusChem 2016;9:2421-9.&#13;
30. Raut DM, Allada R, Pavan KV, Deshpande G, Patil D, Patil A, et al. Dehydration of lactose monohydrate: Analytical and physical characterization. Pharm Lett\ 2011;3:202-12.&#13;
31. Hartyanszky I, Kalasz H, Adeghate E, Gulyas Z, Hasan MY, Tekes K, et al. Active metabolites resulting from decarboxylation, reduction and ester hydrolysis of parent drugs. Curr Drug Metab 2012;13:835-62.&#13;
32. Lopalco A, Dalwadi G, Niu S, Schowen RL, Douglas J, Stella VJ. Mechanism of decarboxylation of pyruvic acid in the presence of hydrogen peroxide. J Pharm Sci 2016;105:705-13.&#13;
33. Shi W, Lv H, Yuan S, Huang H, Liu Y, Kang Z. Nearinfrared light photocatalytic ability for degradation of tetracycline using carbon dots modified Ag/AgBr nanocomposites. Sep Purif Technol 2017;174:75-83.&#13;
34. Tashtoush BM, Jacobson EL, Jacobson MK. UVA is the major contributor to the photodegradation of tretinoin and isotretinoin: Implications for development of improved pharmaceutical formulations. Int J Pharm 2008;352:123-8.&#13;
35. Ahmad I, Anwar Z, Ahmed S, Sheraz MA, Bano R, Hafeez A. Solvent effect on the photolysis of riboflavin. AAPS PharmSciTech 2015;16:1122-8.&#13;
36. Jin X, Xu H, Qiu S, Jia M, Wang F, Zhang A. Influence of initial concentration, pH and temperature. J Photochem Photobiol A Chem 2017;332:224-31.&#13;
37. Rering C, Williams K, Hengel M, Tjeerdema R. Comparison of direct and indirect photolysis in imazosulfuron photodegradation. J Agric Food Chem 2017;65:3103-8.&#13;
38. Ahmad I, Ahmed S, Anwar Z, Sheraz MA, Sikorski M. Photostability and photostabilization of drugs and drug products. Int J Photoenergy 2016;2016:8135608.&#13;
39. Kulkarni AS, Kasabe AJ, Bhatia MS, Bhatia NM, Gaikwad VL. Quantitative structure property relationship approach in formulation development: An overview. AAPS PharmSciTech 2019;20:268.&#13;
40. Ivanciuc O, Ivanciuc T, Balaban AT. Quantitative structure-property relationship evaluation of structural descriptors derived from the distance and reverse wiener matrices. Internet Electron J Mol Des 2002;1:467-87.&#13;
41. Grisoni F, Ballabio D, Todeschini R, Consonni V Molecular descriptors for structure activity applications: A hands-on approach. Methods Mol Biol 2018;1800:3-53.&#13;
42. Goodarzi M, Funar-timofei S, Vander HY. Towards better understanding of feature-selection or reduction techniques for quantitative structure activity relationship models. Trends Anal Chem 2013;42:49-63.&#13;
43. Xue L, Bajorath J. Molecular descriptors in chemoinformatics, computational combinatorial chemistry, and virtual screening. Comb Chem High Throughput Screen 2000;3:363-72.&#13;
44. Karelson M, Lobanov VS, Katritzky AR. Quantumchemical descriptors in QSAR/QSPR studies. Chem Rev 1996;96:1027-43.&#13;
45. Thanikaivelan P, Subramanian V, Rao JR, Nair BU. Application of quantum chemical descriptor in quantitative structure activity and structure property relationship. Chem Phys Lett 2000;323:59-70.46. Gaillard P, Carrupff PA, Testa B, Boudon A. Molecular lipophilicity potential, a tool in 3D QSAR: Method and applications. J Comput Aided Mol Des 1994;8:83-96.&#13;
47. Prasanna S, Doerksen RJ. Topological polar surface area: A useful descriptor in 2D-QSAR. Curr Med Chem 2009;16:21-41.&#13;
48. Katritzky AR, Slavov SH, Dobchev DA, Karelson M. Rapid QSPR model development technique for prediction of vapor pressure of organic compounds. Comput Chem Eng 2007;31:1123-30.&#13;
49. Gaikwad VL, Bhatia MS, Singhvi I. Experimental and chemoinformatics evaluation of some physicochemical properties of excipients influencing release kinetics of the acidic drug ibuprofen. Chemosphere 2015;138:494-502.&#13;
50. Kasabe AJ, Kulkarni AS, Gaikwad VL. QSPR modeling of biopharmaceutical properties of hydroxypropyl methylcellulose (cellulose ethers) tablets based on its degree of polymerization. AAPS PharmSciTech 2019;20:308.&#13;
51. Gaikwad VL, Bhatia NM, Singhvi I, Mahadik KR, Bhatia MS. Computational modeling of polymeric physicochemical properties for formulation development of a drug containing basic functionality. J Pharm Sci 2017;106:3337-45.&#13;
52. Luo X, Yang X, Qiao X, Wang Y, Chen J, Wei X, et al. Development of a QSAR model for predicting aqueous reaction rate constants of organic chemicals with hydroxyl radicals. Environ Sci Process Impacts 2017;19:350-6.&#13;
53. Baylon JL, Cilfone NA, Gulcher JR, Chittenden TW. Deep learning using multiscale reaction classification enhancing retrosynthetic reaction prediction with deep learning using multiscale reaction classification. J Chem Inf Model 2019;59:673-88.&#13;
54. Toropov AA, Kudyshkin VO, Voropaeva NL, Ruban IN, Rashidova SS. QSPR modeling of the reactivity&#13;
parameters of monomers in radical copolymerizations. J Struct Chem 2004;45:945-50.&#13;
55. Saraf SR, Rogers WJ, Mannan MS. Prediction of reactive hazards based on molecular structure. J Hazard Mater 2003;98:15-29.&#13;
56. Oland;aacute;h J, Alsenoy C Van, Sannigrahi AB. Condensed Fukui functions derived from stockholder charges: Assessment of their performance as local reactivity descriptors. J Phys Chem A 2002;106:3885-90.&#13;
57. Frau J, Glossman-Mitnik D. Chemical reactivity theory applied to the calculation of the local reactivity descriptors of a colored maillard reaction product. Chem Sci Int J 2018;22:1-14.&#13;
58. Hemmateenejad B, Sanchooli M. Substituent electronic descriptors for fast QSAR/QSPR. J Chemom 2007;21:96-107.&#13;
59. Liu S, Rong C, Lu T. Electronic forces as descriptors of nucleophilic and electrophilic regioselectivity and stereoselectivity. Phys Chem Chem Phys 2017;19:1496-503.&#13;
60. Liu P, Long W. Current mathematical methods used in QSAR/QSPR studies. Int J Mol Sci 2009;10:1978-98.&#13;
61. Shen M, Xiao Y, Golbraikh A, Gombar VK, Tropsha A. Development and validation of and;kappa;-nearest-neighbor QSPR models of metabolic stability of drug candidates. J Med Chem 2003;46:3013-20.&#13;
62. Veerasamy R, Rajak H, Jain A, Sivadasan S, Varghese CP, Agrawal RK. Validation of QSAR models strategies and importance. Int J Drug Des Disocov 2011;2:511-9.</References>
      </References>
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