Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume :15 | Issue : 01 | Page : –

Tanujaa S R,

Student, Department of Biotechnology, Karunya Institute of Science of Technology, Coimbatore, Tamil Nadu, India

Abstract

document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_abs_153367’);});Edit Abstract & Keyword

Infectious diseases have a heavy impact on both public health and the world’s economies. In most diseases, antibiotic resistance has become widespread over time. A variety of diseases comprising pneumonia, tuberculosis, and gonorrhea go through the same evolutionary processes, which include the formation of drug-resistant pathogens in response to selection pressure from medications and their potential extinction when drug use is ceased. Since the occurrence of drug resistance in serious infections typically coincides with poverty, drug-resistant illnesses including Mycobacterium tuberculosis, and Neisseria gonorrhea pose a threat to widening health disparities worldwide. This affects healthcare significantly and seriously jeopardizes many of the breakthroughs in clinical medicine made in the 20th century, even in settings with ample resources. New tactics and technological platforms inclusive of genomics, proteomics, transcriptomics, nanotechnology, and bioinformatics approaches are desperately needed to address these threats and obstacles. The field of biotechnology and its many applications are crucial in addressing this problem. This study will concentrate on the most recent biotechnological developments such as the use of Monoclonal antibodies, CRISPR-Cas Technology 3D Bioprinting, and more to address the problem of drug resistance and the difficulties encountered in their effective commercialization.

Keywords: Antibiotic resistance, Infectious disease, AMR, Drug resistance, Pathogen, treatment, DNA, RNA, Molecular Methods

[This article belongs to Research & Reviews : A Journal of Biotechnology (rrjobt)]

How to cite this article:
Tanujaa S R. Breakthroughs in biotechnology for the regulation of infectious diseases. Research & Reviews : A Journal of Biotechnology. 2025; 15(01):-.

How to cite this URL:
Tanujaa S R. Breakthroughs in biotechnology for the regulation of infectious diseases. Research & Reviews : A Journal of Biotechnology. 2025; 15(01):-. Available from: https://journals.stmjournals.com/rrjobt/article=2025/view=0

document.addEventListener(‘DOMContentLoaded’,function(){frmFrontForm.scrollToID(‘frm_container_ref_153367’);});Edit

References

1. Founou LL, Founou RC, Essack SY. Antibiotic resistance in the food chain: a developing country-perspective. Frontiers in microbiology. 2016 Nov 23;7:1881.
2. Jindal AK, Pandya K, Khan ID. Antimicrobial resistance: A public health challenge. Med J Armed Forces India. 2015;71(2):178–81. doi:10.1016/j.mjafi.2014.04.011.
3. van Doorn HR. The epidemiology of emerging infectious diseases and pandemics. Medicine (Abingdon). 2021;49(10):659–62. doi:10.1016/j.mpmed.2021.07.011.
4. Nathwani D, Varghese D, Stephens J, et al. Value of hospital antimicrobial stewardship programs [ASPs]: a systematic review. Antimicrob Resist Infect Control. 2019;8:doi:10.1186/s13756-019-0471-0.
5. Fekadu G, Yao J, You JHS. Bedaquiline-based treatment for extensively drug-resistant tuberculosis in South Africa: A cost-effectiveness analysis. PLoS One. 2022;17(8):e0272770. doi:10.1371/journal.pone.0272770.
6. Saleem Z, Hassali MA, Godman B, et al. Point prevalence surveys of antimicrobial use: a systematic review and the implications. Expert Rev Anti Infect Ther. 2020;18(9):897–910. doi:10.1080/14787210.2020.1767593.
7. Jamrozik E, Selgelid M. Ethics and drug resistance: Collective responsibility for global public health. Cham: Springer International Publishing; 2020.
8. Silva-Santana G, Silva CMF, Olivella JGB, et al. Worldwide survey of Corynebacterium striatum increasingly associated with human invasive infections, nosocomial outbreak, and antimicrobial multidrug-resistance, 1976–2020. Arch Microbiol. 2021;203(5):1863–80. doi:10.1007/s00203-021-02246-1.
9. Rudrapal M, Paudel KR, Pangeni R. Editorial: Drug repurposing and polypharmacology: A synergistic approach in multi-target-based drug discovery. Front Pharmacol. 2022;13:doi:10.3389/fphar.2022.1101007.
10. Sautter RL, Halstead DC. Need of the hour: Addressing the challenges of multi-drug-resistant health care-associated infections and the role of the laboratory in lowering infection rates. Clin Microbiol Newsl. 2018;40(2):11–6. doi:10.1016/j.clinmicnews.2018.01.001.
11. Olaru ID, Tacconelli E, Yeung S, et al. The association between antimicrobial resistance and HIV infection: a systematic review and meta-analysis. Clin Microbiol Infect. 2021;27(6):846–53. doi:10.1016/j.cmi.2021.03.026.
12. Connor BA, Dawood R, Riddle MS, Hamer DH. Cholera in travellers: a systematic review. J Travel Med. 2019;26. doi:10.1093/jtm/taz085.
13. Singhai M, Dhar Shah Y, Gupta N, et al. Chronicle down memory lane: India’s sixty years of plague experience. Indian J Med Microbiol. 2021;39(3):279–85. doi:10.1016/j.ijmmb.2021.06.007.
14. Nicastri E, Kobinger G, Vairo F, et al. Ebola virus disease. Infect Dis Clin North Am. 2019;33(4):953–76. doi:10.1016/j.idc.2019.08.005.
15. Zheng R, Wang Q, Wu R, et al. Holobiont perspectives on tripartite interactions among microbiota, mosquitoes, and pathogens. ISME J. 2023;17(5):1143–52. doi:10.1038/s41396-023-01436-7.
16. Zheng W, Sun W, Simeonov A. Drug repurposing screens and synergistic drug‐combinations for infectious diseases. Br J Pharmacol. 2018;175(2):181–91. doi:10.1111/bph.13895.
17. Howard DH, Scott RD II, Packard R, Jones D. The global impact of drug resistance. Clin Infect Dis. 2003;36(Suppl 1):S4–S10. doi:10.1086/344656.
18. Snowden FM. Emerging and reemerging diseases: a historical perspective. Immunol Rev. 2008;225:9–26. doi:10.1111/j.1600-065x.2008.00677.x.
19. Morens DM, Fauci AS. Emerging infectious diseases: Threats to human health and global stability. PLoS Pathog. 2013;9(7):e1003467. doi:10.1371/journal.ppat.1003467.
20. Joy M, Krishnaveni M. A review of epidemic surveillance systems for infectious diseases. In: 2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS). IEEE; 2022.
21. Choi J, Cho Y, Shim E, Woo H. Web-based infectious disease surveillance systems and public health perspectives: a systematic review. BMC Public Health. 2016;16. doi:10.1186/s12889-016-3893-0
22. Carrion M, Madoff LC. ProMED-mail: 22 years of digital surveillance of emerging infectious diseases. Int Health. 2017;9(3):177-183. doi:10.1093/inthealth/ihx014
23. Gu Y, Zhang T, Chen H, et al. Mini review on flexible and wearable electronics for monitoring human health information. Nanoscale Res Lett. 2019;14. doi:10.1186/s11671-019-3084-x
24. Burnham JP, Olsen MA, Stwalley D, et al. Infectious diseases consultation reduces 30-day and 1-year all-cause mortality for multidrug-resistant organism infections. Open Forum Infect Dis. 2018;5. doi:10.1093/ofid/ofy026
25. O’Brien TF. Emergence, spread, and environmental effect of antimicrobial resistance: how use of an antimicrobial anywhere can increase resistance to any antimicrobial anywhere else. Clin Infect Dis. 2002;34(Suppl 3):S78-S84. doi:10.1086/340244
26. King DA, Peckham C, Waage JK, et al. Infectious diseases: preparing for the future. Science. 2006;313(5792):1392-1393. doi:10.1126/science.1129134
27. Maddah N, Verma A, Almashmoum M, Ainsworth J. Effectiveness of public health digital surveillance systems for infectious disease prevention and control at mass gatherings: systematic review. J Med Internet Res. 2023;25:e44649. doi:10.2196/44649
28. Sun G, Trung NV, Hoi LT, et al. Visualisation of epidemiological map using an Internet of Things infectious disease surveillance platform. Crit Care. 2020;24. doi:10.1186/s13054-020-03132-w
29. Kang W-T, Xu H, Liao Y, et al. Qualitative and quantitative detection of multiple sexually transmitted infection pathogens reveals distinct associations with cervicitis and vaginitis. Microbiol Spectr. 2022;10. doi:10.1128/spectrum.01966-22
30. Unemo M, Bradshaw CS, Hocking JS, et al. Sexually transmitted infections: challenges ahead. Lancet Infect Dis. 2017;17:e235-e279. doi:10.1016/s1473-3099(17)30310-9
31. Unemo M, Golparian D, Shafer WM. Challenges with gonorrhea in the era of multi-drug and extensively drug resistance – are we on the right track? Expert Rev Anti Infect Ther. 2014;12(6):653-656. doi:10.1586/14787210.2014.906902
32. Centers for Disease Control and Prevention. Basic information about ARG – STD information from CDC. CDC. Available from: https://www.cdc.gov/std/gonorrhea/drug-resistant/basic.htm. Accessed 27 Oct 2023.
33. Rice PA, Shafer WM, Ram S, Jerse AE. Neisseria gonorrhoeae: drug resistance, mouse models, and vaccine development. Annu Rev Microbiol. 2017;71:665-686. doi:10.1146/annurev-micro-090816-093530
34. Unemo M, Nicholas RA. Emergence of multidrug-resistant, extensively drug-resistant and untreatable gonorrhea. Future Microbiol. 2012;7(12):1401-1422. doi:10.2217/fmb.12.117
35. Phillips AN, Stover J, Cambiano V, et al. Impact of HIV drug resistance on HIV/AIDS-associated mortality, new infections, and antiretroviral therapy program costs in sub-Saharan Africa. J Infect Dis. 2017;215(9):1362-1365. doi:10.1093/infdis/jix089
36. Chinnambedu RS, Marimuthu RR, Sunil SS, et al. Changing antibiotic resistance profile of Staphylococcus aureus isolated from HIV patients (2012–2017) in Southern India. J Infect Public Health. 2020;13(1):75-79. doi:10.1016/j.jiph.2019.06.015
37. Donkor E, Kotey F, Dayie N, et al. Colonization of HIV-infected children with methicillin-resistant Staphylococcus aureus. Pathogens. 2019;8(1):35. doi:10.3390/pathogens8010035
38. Soroka M, Wasowicz B, Rymaszewska A. Loop-mediated isothermal amplification (LAMP): The better sibling of PCR? Cells. 2021;10:1931. doi:10.3390/cells10081931
39. ResearchGate. A critical review on PCR, its types, and applications. Available from: https://www.researchgate.net/publication/266971527_a_critical_review_on_PCR_its_types_and_applications. Accessed 27 Oct 2023.
40. Parashar D, Chauhan DS, Sharma VD, Katoch VM. Applications of real-time PCR technology to mycobacterial research. Indian J Med Res. 2006;124.
41. Rajalakshmi S. Different types of PCR techniques and their applications. Available from: https://faculty.ksu.edu.sa/sites/default/files/different_types_of_pcr_techniques_and_its_applications.pdf. Accessed 27 Oct 2023.
42. Elnifro EM, Ashshi AM, Cooper RJ, Klapper PE. Multiplex PCR: Optimization and application in diagnostic virology. Clin Microbiol Rev. 2000;13(4):559. doi:10.1128/cmr.13.4.559-570.2000
43. Green MR, Sambrook J. Inverse polymerase chain reaction (PCR). Cold Spring Harb Protoc. 2019;2019:db.prot095166. doi:10.1101/pdb.prot095166
44. Karunasagar I. Bacteria: Vibrio vulnificus. In: Encyclopedia of Food Safety. Elsevier; 2014. pp. 564–569.
45. Olsson M, Strålin K, Holmberg H. Clinical significance of nested polymerase chain reaction and immunofluorescence for detection of Pneumocystis carinii pneumonia. Clin Microbiol Infect. 2001;7(10):492–497. doi:10.1046/j.1469-0691.2001.00309.x
46. Bièche I, Onody P, Laurendeau I, et al. Real-time reverse transcription-PCR assay for future management of ERBB2-based clinical applications. Clin Chem. 1999;45.
47. Scanlon KJ, Kashani-Sabet M. Utility of the polymerase chain reaction in detection of gene expression in drug-resistant human tumors. J Clin Lab Anal. 1989;3(5):323–329. doi:10.1002/jcla.1860030512
48. Cason C, D’Accolti M, Soffritti I, et al. Next-generation sequencing and PCR technologies in monitoring the hospital microbiome and its drug resistance. Front Microbiol. 2022;13. doi:10.3389/fmicb.2022.969863
49. Kouamou V, Ndhlovu CE, Katzenstein D, Manasa J. Rapid HIV-1 drug resistance testing in a resource-limited setting: the Pan Degenerate Amplification and Adaptation assay (PANDAA). Pan Afr Med J. 2021;40. doi:10.11604/pamj.2021.40.57.28558
50. The Pan Degenerate Amplification and Adaptation (PANDAA) assay: a solution for HIV-1 drug resistance testing in a resource-limited setting? J Allergy Infect Dis. 2021;2. doi:10.46439/allergy.2.020
51. Denaro M, Ghandour H, Long JE, et al. Validation of PANDAA qDx HIVDR RTI: a simple and scalable real-time PCR-based HIV drug resistance genotyping kit for the management of NNRTI-based ART failure. Available from: https://programme.ias2019.org/PAGMaterial/eposters/2172.pdf. Accessed 28 Oct 2023.
52. Schmitt S, Stephan R, Huebschke E, et al. DNA microarray-based characterization and antimicrobial resistance phenotypes of clinical MRSA strains from animal hosts. J Vet Sci. 2020;21. doi:10.4142/jvs.2020.21.e54
53. Protonotariou E, Meletis G, Papadopoulou D, et al. Evaluation of the “AMR Direct Flow Chip Kit” DNA microarray for detecting antimicrobial resistance genes directly from rectal and nasopharyngeal clinical samples upon ICU admission. Enferm Infecc Microbiol Clin (Engl). 2021;39(5):276–278. doi:10.1016/j.eimce.2020.05.014
54. Marton MJ, DeRisi JL, Bennett HA, et al. Drug target validation and identification of secondary drug target effects using DNA microarrays. Nat Med. 1998;4(11):1293–1301. doi:10.1038/3282
55. Hughes TR, Roberts CJ, Dai H, et al. Widespread aneuploidy revealed by DNA microarray expression profiling. Nat Genet. 2000;25(3):333–337. doi:10.1038/77116
56. More M, Gutiérrez G, Rothschild M, et al. Evaluation of SNP genotyping in alpacas using the Bovine HD Genotyping Beadchip. Front Genet. 2019;10. doi:10.3389/fgene.2019.00361
57. Onogi A, Watanabe T, Ogino A, et al. Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size. BMC Genomics. 2021;22. doi:10.1186/s12864-021-07792-y
58. Jenkins CA, Schofield EC, Mellersh CS, et al. Improving the resolution of canine genome-wide association studies using genotype imputation: A study of two breeds. Anim Genet. 2021;52(6):703–713. doi:10.1111/age.13117
59. Single nucleotide polymorphisms in Bison bison identified by the GGP Bovine 50K SNP assay. Available from: https://buscaintegrada.ufrj.br/Record/oai:doaj.org-article:dfb8a45b920246c6a0316fb5b88d8b52. Accessed 28 Oct 2023.
60. Ferraz JBS, Wu X-L, Li H, et al. Development and evaluation of a low-density single-nucleotide polymorphism chip specific to Bos indicus cattle. Anim Prod Sci. 2020;60(12):1769. doi:10.1071/an19396
61. Gras MA, Grosu H. Informational steps and tools in genomic selection of livestock: A review. Available from: https://ibna.ro/arhiva/08-AZ-156-Mihail_Gras_28-02-2020.pdf. Accessed 28 Oct 2023.
62. Chartrand C, Leeflang MMG, Minion J, et al. Accuracy of rapid influenza diagnostic tests: A meta-analysis. Ann Intern Med. 2012;156(7):500. doi:10.7326/0003-4819-156-7-201204030-00403
63. Kim H, Kang H, Kim H-N, et al. Development of 6E3 antibody-mediated SERS immunoassay for drug-resistant influenza virus. Biosens Bioelectron. 2021;187:113324. doi:10.1016/j.bios.2021.113324
64. Yi Z, Xu X, Meng X, et al. Emerging markers for antimicrobial resistance monitoring. Chin Chem Lett. 2023;34:108238. doi:10.1016/j.cclet.2023.108238
65. Lee WS, Lee S, Kang T, et al. Detection of ampicillin-resistant E. coli using novel nanoprobe-combined fluorescence in situ hybridization. Nanomaterials (Basel). 2019;9(5):750. doi:10.3390/nano9050750
66. Dillon L, Dimonaco NJ, Creevey CJ. O04 Understanding the key role of accessory genes in AMR phenotype through interpretable machine learning techniques. JAC Antimicrob Resist. 2023;5:dlad066.004. doi:10.1093/jacamr/dlad066.004
67. Feldgarden M, Brover V, Haft DH, et al. Validating the AMRFinder tool and resistance gene database by using antimicrobial resistance genotype-phenotype correlations in a collection of isolates. Antimicrob Agents Chemother. 2019;63. doi:10.1128/aac.00483-19
68. Hendriksen RS, Bortolaia V, Tate H, et al. Using genomics to track global antimicrobial resistance. Front Public Health. 2019;7. doi:10.3389/fpubh.2019.00242
69. Peng B, Li H, Peng X. Proteomics approach to understand bacterial antibiotic resistance strategies. Expert Rev Proteomics. 2019;16(10):829–839. doi:10.1080/14789450.2019.1681978
70. Staub I, Sieber SA. β-lactam probes as selective chemical-proteomic tools for the identification and functional characterization of resistance-associated enzymes in MRSA. J Am Chem Soc. 2009;131(17):6271–6276. doi:10.1021/ja901304n
71. Horgan RP, Kenny LC. ‘Omic’ technologies: Genomics, transcriptomics, proteomics, and metabolomics. Obstet Gynaecol. 2011;13(3):189–195. doi:10.1576/toag.13.3.189.27672
72. Cabral-Marques O, Schimke LF, de Oliveira EB Jr, et al. Flow cytometry contributions for the diagnosis and immunopathological characterization of primary immunodeficiency diseases with immune dysregulation. Front Immunol
73. Ndagi U, Falaki AA, Abdullahi M, et al. Antibiotic resistance: bioinformatics-based understanding as a functional strategy for drug design. RSC Adv. 2020;10:18451–68. doi:10.1039/d0ra01484b
74. Kavvas ES, Yang L, Monk JM, et al. A biochemically-interpretable machine learning classifier for microbial GWAS. Nat Commun. 2020;11:1–11. doi:10.1038/s41467-020-16310-9
75. Melo MCR, Maasch JRMA, de la Fuente-Nunez C. Accelerating antibiotic discovery through artificial intelligence. Commun Biol. 2021;4:1–13. doi:10.1038/s42003-021-02586-0
76. Hunt M, Mather AE, Sánchez-Busó L, et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genom. 2017;3:. doi:10.1099/mgen.0.000131
77. Feldgarden M, Brover V, Haft DH, et al. Using the NCBI AMRFinder tool to determine antimicrobial resistance genotype-phenotype correlations within a collection of NARMS isolates. bioRxiv.
78. Crossette E, Gumm J, Langenfeld K, et al. Metagenomic quantification of genes with internal standards. MBio. 2021;12:. doi:10.1128/mbio.03173-20
79. Arango-Argoty G, Garner E, Pruden A, et al. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data. Microbiome. 2018;6:. doi:10.1186/s40168-018-0401-z
80. Zankari E, Allesøe R, Joensen KG, et al. PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens. J Antimicrob Chemother. 2017;72:2764–8. doi:10.1093/jac/dkx217
81. Zhang F, Wang M, Xi J, et al. A novel heterogeneous network-based method for drug response prediction in cancer cell lines. Sci Rep. 2018;8:1–9. doi:10.1038/s41598-018-21622-4
82. Qi R, Zou Q. Trends and potential of machine learning and deep learning in drug study at single-cell level. Research (Wash DC). 2023;6:. doi:10.34133/research.0050
83. Berglund F, Österlund T, Boulund F, et al. Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome. 2019;7:. doi:10.1186/s40168-019-0670-1
84. Marini S, Boucher C, Noyes N, Prosperi M. The K-mer antibiotic resistance gene variant analyzer (KARGVA). Front Microbiol. 2023;14:. doi:10.3389/fmicb.2023.1060891
85. Lakin SM, Kuhnle A, Alipanahi B, et al. Hierarchical Hidden Markov models enable accurate and diverse detection of antimicrobial resistance sequences. Commun Biol. 2019;2:1–11. doi:10.1038/s42003-019-0545-9
86. Doster E, Lakin SM, Dean CJ, et al. MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data. Nucleic Acids Res. 2020;48:D561–9. doi:10.1093/nar/gkz1010
87. Bortolaia V, Kaas RS, Ruppe E, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020;75:3491–500. doi:10.1093/jac/dkaa345
88. De R. Metagenomics: aid to combat antimicrobial resistance in diarrhea. Gut Pathog. 2019;11:. doi:10.1186/s13099-019-0331-8
89. Sahu T, Ratre YK, Chauhan S, et al. Nanotechnology-based drug delivery system: Current strategies and emerging therapeutic potential for medical science. J Drug Deliv Sci Technol. 2021;63:102487. doi:10.1016/j.jddst.2021.102487
90. Blecher K, Nasir A, Friedman A. The growing role of nanotechnology in combating infectious disease. Virulence. 2011;2:395–401. doi:10.4161/viru.2.5.17035
91. Jain S, Nehra M, Kumar R, et al. Internet of medical things (IoMT)-integrated biosensors for point-of-care testing of infectious diseases. Biosens Bioelectron. 2021;179:113074. doi:10.1016/j.bios.2021.113074
92. Dubey AK, Kumar Gupta V, Kujawska M, et al. Exploring nano-enabled CRISPR-Cas-powered strategies for efficient diagnostics and treatment of infectious diseases. J Nanostructure Chem. 2022;12:833–64. doi:10.1007/s40097-022-00472-7
93. Ahmed S, Ning J, Peng D, et al. Current advances in immunoassays for the detection of antibiotics residues: a review. Food Agric Immunol. 2020;31:268–90. doi:10.1080/09540105.2019.1707171
94. Ni Y, Rosier BJHM, van Aalen EA, et al. A plug-and-play platform of ratiometric bioluminescent sensors for homogeneous immunoassays. Nat Commun. 2021;12:1–12. doi:10.1038/s41467-021-24874-3
95. Sulovari A, Ninomiya MJ, Beck CA, et al. Clinical utilization of species-specific immunoassays for identification of Staphylococcus aureus and Streptococcus agalactiae in orthopedic infections. J Orthop Res. 2021;39:2141–50. doi:10.1002/jor.24935
96. Haddad NS, Nozick S, Kim G, et al. Novel immunoassay for diagnosis of ongoing Clostridioides difficile infections using serum and medium enriched for newly synthesized antibodies (MENSA). J Immunol Methods. 2021;492:112932. doi:10.1016/j.jim.2020.112932
97. Saylor C, Dadachova E, Casadevall A. Monoclonal antibody-based therapies for microbial diseases. Vaccine. 2009;27:G38–46. doi:10.1016/j.vaccine.2009.09.105
98. Thakare R, Dasgupta A, Chopra S. Bezlotoxumab for the treatment of Clostridium difficile-associated diarrhea. Drugs Today (Barc). 2017;53:385–92. doi:10.1358/dot.2017.53.7.2655240
99. Yamamoto BJ, Shadiack AM, Carpenter S, et al. Obiltoxaximab prevents disseminated Bacillus anthracis infection and improves survival during pre- and postexposure prophylaxis in animal models of inhalational anthrax. Antimicrob Agents Chemother. 2016;60:5796–805. doi:10.1128/aac.01102-16
100. Farahnik B, Beroukhim K, Zhu TH, et al. Ixekizumab for the treatment of psoriasis: A review of phase III trials. Dermatol Ther (Heidelb). 2016;6:25–37. doi:10.1007/s13555-016-0102-0
101. Blair HA. Emicizumab: A review in haemophilia A. Drugs. 2019;79:1697–707. doi:10.1007/s40265-019-01200-2
102. Wilcox MH, Gerding DN, Poxton IR, et al. Bezlotoxumab for prevention of recurrent Clostridium difficile infection. N Engl J Med. 2017;376:305–17. doi:10.1056/nejmoa1602615
103. Beccari MV, Mogle BT, Sidman EF, et al. Ibalizumab, a novel monoclonal antibody for the management of multidrug-resistant HIV-1 infection. Antimicrob Agents Chemother. 2019;63:. doi:10.1128/aac.00110-19
104. Shadman KA, Wald ER. A review of palivizumab and emerging therapies for respiratory syncytial virus. Expert Opin Biol Ther. 2011;11:1455–67. doi:10.1517/14712598.2011.608062
105. Shivalingaiah AH, Shankaraiah RH, Hanumanthaiah AND. Safety of new indigenous human Rabies Monoclonal Antibody (RMAb) for Post Exposure Prophylaxis. Indian J Community Health. 2018;30:196–201. doi:10.47203/ijch.2018.v30i03.004
106. Mueller SM, Itin P, Haeusermann P. Muckle-Wells syndrome effectively treated with canakinumab: Is the recommended dosing schedule mandatory? Dermatology. 2011;223:113–8. doi:10.1159/000331580
107. Navarra SV, Guzmán RM, Gallacher AE, et al. Efficacy and safety of belimumab in patients with active systemic lupus erythematosus: a randomised, placebo-controlled, phase 3 trial. Lancet. 2011;377:721–31. doi:10.1016/s0140-6736(10)61354-2
108. Scully M, Cataland SR, Peyvandi F, et al. Caplacizumab treatment for acquired thrombotic thrombocytopenic purpura. N Engl J Med. 2019;380:335–46. doi:10.1056/nejmoa1806311
109. Loftus EV Jr, Colombel J-F, Feagan BG, et al. Long-term efficacy of vedolizumab for ulcerative colitis. J Crohns Colitis. 2016;11:jjw177. doi:10.1093/ecco-jcc/jjw177
110. Munguia J, Nizet V. Pharmacological targeting of the host–pathogen interaction: Alternatives to classical antibiotics to combat drug-resistant superbugs. Trends Pharmacol Sci. 2017;38:473–83. doi:10.1016/j.tips.2017.02.003
111. Ramamurthy D, Nundalall T, Cingo S, et al. Recent advances in immunotherapies against infectious diseases. Immunother Adv. 2021;1:. doi:10.1093/immadv/ltaa007
112. Junaid M, Thirapanmethee K, Khuntayaporn P, Chomnawang MT. CRISPR-based gene editing in Acinetobacter baumannii to combat antimicrobial resistance. Pharmaceuticals (Basel). 2023;16:920. doi:10.3390/ph160709
113. Hille F, Charpentier E. CRISPR-Cas: biology, mechanisms and relevance. Philos Trans R Soc Lond B Biol Sci. 2016;371:20150496. doi:10.1098/rstb.2015.0496
114. Uthayakumar D, Sharma J, Wensing L, Shapiro RS. CRISPR-based genetic manipulation of Candida species: Historical perspectives and current approaches. Front Genome Ed. 2021;2:. doi:10.3389/fgeed.2020.606281
115. Stocco G, Lucafò M, Decorti G. Pharmacogenomics of antibiotics. Int J Mol Sci. 2020;21:5975. doi:10.3390/ijms21175975
116. Dlozi PN, Gladchuk A, Crutchley RD, et al. Cathelicidins and defensins antimicrobial host defense peptides in the treatment of TB and HIV: Pharmacogenomic and nanomedicine approaches towards improved therapeutic outcomes. Biomed Pharmacother. 2022;151:113189. doi:10.1016/j.biopha.2022.113189
117. Khaled SA, Burley JC, Alexander MR, et al. 3D printing of five-in-one dose combination polypill with defined immediate and sustained release profiles. J Control Release. 2015;217:308–14. doi:10.1016/j.jconrel.2015.09.028
118. Varghese R, Sood P, Salvi S, et al. 3D printing in the pharmaceutical sector: Advances and evidences. Sens Int. 2022;3:100177. doi:10.1016/j.sintl.2022.100177
119. Qureshi A, Niazi JH. Biosensors for detecting viral and bacterial infections using host biomarkers: a review. Analyst. 2020;145:7825–48. doi:10.1039/d0an00896f

Regular Issue Subscription Review Article

Research & Reviews : A Journal of Biotechnology

ISSN: 2231-3826

Volume	15
Issue	01
Received	04/09/2024
Accepted	13/12/2024
Published	01/02/2025

Total Visits: 20

Initiatives

Legal Information

Contact Us

STM Journals
An imprint of Consortium E-learning network Pvt. Ltd.
A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin-201301
(Tel) (+91) 0120- 4781 200
(Mob) (+91) 9810078958, +919667725932
[email protected]

Join Us

Submit Manuscript

Submit Topics

WEBSITE DISCLAIMER

Last updated: 2022-06-15

The information provided by STM Journals (“Company”, “we”, “our”, “us”) on https://journals.stmjournals.com/ (the “Site”) is for general informational purposes only. All information on the Site is provided in good faith, however, we make no representation or warranty of any kind, express or implied, regarding the accuracy, adequacy, validity, reliability, availability, or completeness of any information on the Site.

UNDER NO CIRCUMSTANCE SHALL WE HAVE ANY LIABILITY TO YOU FOR ANY LOSS OR DAMAGE OF ANY KIND INCURRED AS A RESULT OF THE USE OF THE SITE OR RELIANCE ON ANY INFORMATION PROVIDED ON THE SITE. YOUR USE OF THE SITE AND YOUR RELIANCE ON ANY INFORMATION ON THE SITE IS SOLELY AT YOUR OWN RISK.

EXTERNAL LINKS DISCLAIMER

The Site may contain (or you may be sent through the Site) links to other websites or content belonging to or originating from third parties or links to websites and features. Such external links are not investigated, monitored, or checked for accuracy, adequacy, validity, reliability, availability, or completeness by us.

WE DO NOT WARRANT, ENDORSE, GUARANTEE, OR ASSUME RESPONSIBILITY FOR THE ACCURACY OR RELIABILITY OF ANY INFORMATION OFFERED BY THIRD-PARTY WEBSITES LINKED THROUGH THE SITE OR ANY WEBSITE OR FEATURE LINKED IN ANY BANNER OR OTHER ADVERTISING. WE WILL NOT BE A PARTY TO OR IN ANY WAY BE RESPONSIBLE FOR MONITORING ANY TRANSACTION BETWEEN YOU AND THIRD-PARTY PROVIDERS OF PRODUCTS OR SERVICES.

PROFESSIONAL DISCLAIMER

The Site can not and does not contain medical advice. The information is provided for general informational and educational purposes only and is not a substitute for professional medical advice. Accordingly, before taking any actions based on such information, we encourage you to consult with the appropriate professionals. We do not provide any kind of medical advice.

Content published on https://journals.stmjournals.com/ is intended to be used and must be used for informational purposes only. It is very important to do your analysis before making any decision based on your circumstances. You should take independent medical advice from a professional or independently research and verify any information that you find on our Website and wish to rely upon.

THE USE OR RELIANCE OF ANY INFORMATION CONTAINED ON THIS SITE IS SOLELY AT YOUR OWN RISK.

AFFILIATES DISCLAIMER

The Site may contain links to affiliate websites, and we may receive an affiliate commission for any purchases or actions made by you on the affiliate websites using such links.

TESTIMONIALS DISCLAIMER

The Site may contain testimonials by users of our products and/or services. These testimonials reflect the real-life experiences and opinions of such users. However, the experiences are personal to those particular users, and may not necessarily be representative of all users of our products and/or services. We do not claim, and you should not assume that all users will have the same experiences.

YOUR RESULTS MAY VARY.

The testimonials on the Site are submitted in various forms such as text, audio, and/or video, and are reviewed by us before being posted. They appear on the Site verbatim as given by the users, except for the correction of grammar or typing errors. Some testimonials may have been shortened for the sake of brevity, where the full testimonial contained extraneous information not relevant to the general public.

The views and opinions contained in the testimonials belong solely to the individual user and do not reflect our views and opinions.

ERRORS AND OMISSIONS DISCLAIMER

While we have made every attempt to ensure that the information contained in this site has been obtained from reliable sources, STM Journals is not responsible for any errors or omissions or the results obtained from the use of this information. All information on this site is provided “as is”, with no guarantee of completeness, accuracy, timeliness, or of the results obtained from the use of this information, and without warranty of any kind, express or implied, including, but not limited to warranties of performance, merchantability, and fitness for a particular purpose.

In no event will STM Journals, its related partnerships or corporations, or the partners, agents, or employees thereof be liable to you or anyone else for any decision made or action taken in reliance on the information in this Site or for any consequential, special or similar damages, even if advised of the possibility of such damages.

GUEST CONTRIBUTORS DISCLAIMER

This Site may include content from guest contributors and any views or opinions expressed in such posts are personal and do not represent those of STM Journals or any of its staff or affiliates unless explicitly stated.

LOGOS AND TRADEMARKS DISCLAIMER

All logos and trademarks of third parties referenced on https://journals.stmjournals.com/ are the trademarks and logos of their respective owners. Any inclusion of such trademarks or logos does not imply or constitute any approval, endorsement, or sponsorship of STM Journals by such owners.

CONTACT US

Should you have any feedback, comments, requests for technical support, or other inquiries, please contact us by email: [email protected].