APPLICATION OF STATISTICAL SOFTWARE TRENDS IN REAL-WORLD IMPLEMENTATION WITHIN CLINICAL AND PRE-CLINICAL TRIALS

Main Article Content

Gowtham.K
Surya prakash.T
Nandhini.R
Sineka.P
Mohankumar.S
Chidambar.P
Mohamed anas.S
Ranjith.T
Santhosh.M
Surendra kumar.M

Keywords

Statistical software, Preclinical, Clinical trials, SPSS

Abstract

The use of statistical software has become a revolutionary force in the quickly changing world of clinical and pre-clinical trials, enabling data-driven decision-making, improving research outcomes, and stimulating innovation. This review paper examines the most recent developments and trends in the practical application of statistical software tools, highlighting their critical influence on the design of clinical and pre-clinical studies. We explore the many features of statistical software and how they affect data administration, analysis, visualization, teamwork, and legal compliance. This article explains the significant impact of statistical software on the quality, effectiveness, and dependability of clinical and pre-clinical trials by a thorough study of recent studies, case studies, and industry insights. We also talk about the new trends, problems, and opportunities that promise to further revolutionize the industry.The contemporary landscape witnesses a proliferation of diverse statistical software solutions, including SPSS Statistics, JMP, Grapher, Minitab, OriginPro, TIMi Suite

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References

1. Zahir H, Javaid A, Rehman R, Hussain Z. Statistical concepts in biology and health sciences. Journal of Ayub Medical College Abbottabad. 2014 Mar 1;26(1):95-7.
2. Kern SE. Inferential statistics, power estimates, and study design formalities continue to suppress biomedical innovation. arXiv preprint arXiv:1411.0919. 2014 Nov 4.
3. Vrijens B, Urquhart J. Methods for measuring, enhancing, and accounting for medication adherence in clinical trials. Clinical Pharmacology & Therapeutics. 2014 Jun;95(6):617-26.
4. Denny KH, Stewart CW. Acute, subacute, subchronic, and chronic general toxicity testing for preclinical drug development. InA comprehensive guide to toxicology in nonclinical drug development 2017 Jan 1 (pp. 109-127). Academic Press.
5. Liu Z, HuiMingalone CK, Gnanatheepam E, Hollander JM, Zhang Y, Meng J, Zeng L, Georgakoudi I. Label-free, multi-parametric assessments of cell metabolism and matrix remodeling within human and early-stage murine osteoarthritic articular cartilage. Communi-cations Biology. 2023 Apr 13; 6(1):405.
6. Shah N, Engineer S, Bhagat N, Chauhan H, Shah M. Research trends on the usage of machine learning and artificial intelligence in advertising. Augmented Human Research. 2020 Dec;5:1-5.
7. Japec L, Kreuter F, Berg M, Biemer P, Decker P, Lampe C, Lane J, O’Neil C, Usher A. Big data in survey research: AAPOR task force report. Public Opinion Quarterly. 2015 Jan 1;79(4):839-80.
8. Farrell, D., 2016. DataExplore: An application for general data analysis in research and education. Journal of Open Research Software, 4(1).
9. Arribas J, Bernal D, Fernández-Prades C, Closas P, Fernández-Rubio JA. A novel real-time platform for digital beamforming with GNSS software defined receivers. InProceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009) 2009 Sep 25 (pp. 2329-2343).
10. Mo L. Examining the reliability of logistic regression estimation software (Doctoral dissertation, Kansas State University).
11. Swift ML. GraphPad prism, data analysis, and scientific graphing. Journal of chemical informa-tion and computer sciences. 1997 Mar 24;37(2):411-2.
12. Dudley WN, Benuzillo JG, Carrico MS. SPSS and SAS programming for the testing of mediation models. Nursing Research. 2004 Jan 1;53(1):59-62.
13. Horton NJ, Kleinman K. Using R and RStudio for data management, statistical analysis, and graphics. CRC Press; 2015 Mar 10.
14. Divisi D, Di Leonardo G, Zaccagna G, Crisci R. Basic statistics with Microsoft Excel: a review. Journal of thoracic disease. 2017 Jun;9(6):1734.
15. Helsel DR. Statistics for censored environmental data using Minitab and R. John Wiley & Sons; 2011 Dec 14.
16. You S, Xie X, Chen Y. Statistical analysis of educational testing data based on SCILAB. In2009 IEEE International Workshop on Open-source Software for Scientific Computation (OSSC) 2009 Sep 18 (pp. 81-84). IEEE.
17. Hansen JS. GNU Octave: Beginner's Guide: Become a proficient octave user by learning this high-level scientific numerical tool from the ground up. Packt Publishing Ltd; 2011 Jun 21.
18. Xu TT, Peng JL, Ding F. Linkage Relationship between Port Logistics and Regional Economy based on Eviews Software. J. Softw.. 2013 Apr 1;8(4):971-8.
19. 19.Kremelberg D. Practical statistics: A quick and easy guide to IBM® SPSS® Statistics, STATA, and other statistical software. SAGE publications; 2010 Mar 18.
20. Sall J, Stephens ML, Lehman A, Loring S. JMP start statistics: a guide to statistics and data analysis using JMP. Sas Institute; 2017 Feb 21.
21. Stevenson KJ. Review of originpro 8.5. Journal of the American Chemical Society. 2011 Apr 13;133(14):5621.
22. Chen DG, Peace KE. Applied meta-analysis with R. Crc press; 2013 May 3.
23. Van den Ende J, Kemp R. Technological transformations in history: how the computer regime grew out of existing computing regimes. Research policy. 1999 Nov 1;28(8):833-51.\
24. Kuleto V, Ilić M, Dumangiu M, Ranković M, Martins OM, Păun D, Mihoreanu L. Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability. 2021 Sep 18;13(18):10424.
25. Ramya R, Rajeswari G. CLOUD TECHNOLOGIES IN EDUCATIONAL RESEARCH. EDUCATION 5.0: REVOLUTIONIZING LEARNING FOR THE FUTURE. 2023:90.
26. Larsson S, Anneroth M, Felländer A, Felländer-Tsai L, Heintz F, Ångström RC. Sustainable AI: An inventory of the state of knowledge of ethical, social, and legal challenges related to artificial intelligence.
27. Pugh SL, Torres-Saavedra PA. Fundamental statistical concepts in clinical trials and diagnostic testing. Journal of Nuclear Medicine. 2021 Jun 1; 62(6):757-64.
28. Morandat F, Hill B, Osvald L, Vitek J. Evaluating the design of the R language: Objects and functions for data analysis. InECOOP 2012–Object-Oriented Programming: 26th European Conference, Beijing, China, June 11-16, 2012. Proceedings 26 2012 (pp. 104-131). Springer Berlin Heidelberg.
29. Truong K (13 August 2019). "GraphPad acquires University of Chicago spinout SnapGene". MedCity News. Breaking Media. Retrieved 23 August 2021.
30. Mitteer DR, Greer BD, Fisher WW, Cohrs VL. Teaching behavior technicians to create publication‐quality, single‐case design graphs in graphpad prism 7. Journal of Applied Behavior Analysis. 2018 Oct; 51(4):998-1010.
31. Harris S, Harris D. Digital design and computer architecture. Morgan Kaufmann; 2015 Apr 9.
32. Kaeslin H. Digital integrated circuit design: from VLSI architectures to CMOS fabrication. Cambridge University Press; 2008 Apr 28.
33. Ramirez-Lassepas M, Espinosa CE, Cicero JJ, Johnston KL, Cipolle RJ, Barber DL. Predictors of intracranial pathologic findings in patients who seek emergency care because of headache. Archives of neurology. 1997 Dec 1; 54(12):1506-9.