Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 35, 26 April 2024


Open Access | Article

Genomics-driven pharmacodynamics: A new frontier in personalized medicine

Yaode Shao * 1
1 University of Sydney

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 35, 164-172
Published 26 April 2024. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yaode Shao. Genomics-driven pharmacodynamics: A new frontier in personalized medicine. TNS (2024) Vol. 35: 164-172. DOI: 10.54254/2753-8818/35/20240938.

Abstract

Personalized medicine is an emerging, rapidly evolving approach to clinical practice where he uses new technologies to provide decision-making for the prediction, prevention, diagnosis and treatment of disease. Personalized medicine is rooted in the idea that because individuals have subtle and unique characteristics at the molecular, physiological, environmental exposure and behavioral levels, they may need to target the diseases they have to accommodate these subtle and unique characteristics. The goal of personalized medicine is often thought to be to provide the right treatment to the right person at the right time. Genomics has great potential in the development of personalized medicine. Pharmacokinetics provides a quantitative way to understand drug behavior in humans and is the scientific basis for realizing personalized medicine. This article aims to explore the impact of genomics on pharmacokinetics and apply these insights to personalized medicine.

Keywords

personalized medicine, genomics, pharmacodynamics, Pharmacogenetics

References

1. Offit, K Personalized medicine: new genomics, old lessons. Hum. Genet. 2011, 130, 3–14.

2. Evans, J J Schentag, W J Jusko (Eds.), Applied Therapeutics (third ed.), Wiley Online Library (1992)

3. Isaac S Chan and Geoffrey S Ginsburg Annual Review of Genomics and Human Genetics 2011 12:1, 217-244

4. Evans, J J Schentag, W J Jusko (Eds.), Applied Therapeutics (third ed.), Wiley Online Library (1992)

5. Iriart J A B (2019). Precision medicine/personalized medicine: a critical analysis of movements in the transformation of biomedicine in the early 21st century. Cadernos de saúde publica, 35.

6. Hayes D F Markus, H S, Leslie R D et al. Personalized medicine: risk prediction, targeted therapies and mobile health technology. BMC Med 12, 37 (2014). https://doi.org/10.1186/1741-7015-12-37

7. European Science Foundation. Personalized medicine for the European citizen. Towards more precise medicine for the diagnosis, treatment and prevention of disease (IPM). Strasbourg: European Science Foundation; 2012.

8. Ghazi, I M, & Cawley, M J (2021). The science of pharmacokinetics: an overview and applications. Remington, 207-218.

9. Hayes D F Markus, H S, Leslie R D et al. Personalized medicine: risk prediction, targeted therapies and mobile health technology. BMC Med 12, 37 (2014). https://doi.org/10.1186/1741-7015-12-37

10. S Kubrick, A C Clarke, K Dullea, G Lockwood, W Sylvester, Copyright Collection (Library of Congress), et al. (1988). 2001, a space odyssey. In Criterion collection Criterion collection edit., pp. 3 videodiscs of 3 (optical) (149 min). The Voyager Company, USA.

11. Hall MA, McEwen JE, Barton JC, Walker AP, Howe EG, et al. 2005. Concerns in a primary care population about genetic discrimination by insurers. Genet. Med. 7: 311–16

12. Michael, J, Joyner, M D, & SW, R. (2015). Seven Questions for Personalized Medicine

13. F Sanger, S Nicklen and A R Coulson, Proc. Natl. Acad. Sci. U. S. A., 1977, 74, 5463–5467.

14. A M Maxam and W Gilbert, Proc. Natl. Acad. Sci. U. S. A., 1977, 74, 560–564

15. M Margulies, M Egholm, W E Altman, S Attiya, J S Bader and L A Bemben, et al., Nature, 2005, 437, 376–380

16. C Luo, D Tsementzi, N Kyrpides, T Read and K T Konstantinidis, PLoS One, 2012, 7, e30087

17. H Bayley, Nature, 2010, 467, 164–165

18. Seib KL, Dougan G, Rappuoli R. 2009. The key role of genomics in modern vaccine and drug design for emerging infectious diseases. PLoS Genet. 5: e1000612

19. B Rabbani, N Mahdieh, K Hosomichi, H Nakaoka and I Inoue, J Hum Genet, 2012, 57, 621–632

20. Rasko D A, Rosovitz M J, Myers GS, Mongodin E F, Fricke W F, et al. 2008. The pangenome structure of Escherichia coli: comparative genomic analysis of E. coli commensal and pathogenic isolates. J. Bacteriol. 190: 6881–93

21. Rabbani, B, Nakaoka, H, Akhondzadeh, S, Tekin, M, & Mahdieh, N (2016). Next generation sequencing: implications in personalized medicine and pharmacogenomics. Molecular biosystems, 12(6), 1818-1830.

22. Di Sanzo, M, Cipolloni, L, Borro, M, La Russa, R, Santurro, A, Scopetti, M, ... & Frati, P. (2017). Clinical applications of personalized medicine: a new paradigm and challenge. Current pharmaceutical biotechnology, 18(3), 194-203.

23. Shuldiner, A R.; Palmer, K.; Pakyz, R E.; Alestock, T D.; Maloney, K A; O'Neill, C.; Bhatty, S; Schub, J; Overby, C L; Horenstein, R B ; Pollin, T I ; Kelemen, M D ; Beitelshees, A L; Robinson, S W; Blitzer, M G; McArdle, P F; Brown, L; Jeng, L J.; Zhao, R Y; Ambulos, N; Vesely, M R Implementation Of Pharmacogenetics: The University Of Maryland Personalized Anti-Platelet Pharmacogenetics Program. Am. J. Med. Genet. C. Semin., 2014, 166C (1), 76-84.

24. Beitelshees, A L; Voora, D; Lewis, J P Personalized anti-platelet and anti-coagulation therapy: applications and significance of pharmacogenomics. Pharmgenomics Pers. Med., 2015, 8, 43-61.

25. Pulley, J M; Denny, J C; Peterson, J F; Bernard, G R; VnencakJones, C L; Ramirez, A H; Delaney, J T; Bowton, E; Brothers, K; Johnson, K; Crawford, D C; Schildcrout, J; Masys, D R; Dilks, H H; Wilke, R A; Clayton, E W ; Shultz, E.; Laposata, M; McPherson, J; Jirjis, J N; Roden, D M Operational implementation of prospective genotyping for personalized medicine: The design of the Vanderbilt PREDICT project. Clin. Pharmacol. Ther., 2012, 92(1), 87–95.

26. Picard N, Marquet P The influence of pharmacogenetics and cofactors on clinical outcomes in kidney transplantation. Expert Opin Drug Metab Toxicol 2011; 7:731–43.

27. Haufroid V, Mourad M, Van Kerckhove V, Wawrzyniak J, De Meyer M, Eddour DC, et al. The effect of CYP3A5 and MDR1 (ABCB1) polymorphisms on cyclosporine and tacrolimus dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenetics 2004; 14:147–54

28. Wallemacq P, Armstrong VW, Brunet M, Haufroid V, Holt DW, Johnston A, et al. Opportunities to optimize tacrolimus therapy in solid organ transplantation: report of the European consensus conference. Ther Drug Monit 2009; 31:139–52

29. Gómez-Bravo MA, Salcedo M, Fondevila C, Suarez F, Castellote J, Rufian S, et al. Impact of donor and recipient CYP3A5 and ABCB1 genetic polymorphisms on tacrolimus dosage requirements and rejection in Caucasian Spanish liver transplant patients. J Clin Pharmacol 2013; 53:1146–54.

30. Mourad M, Wallemacq P, De Meyer M, Malaise J, De Pauw L, Eddour DC, et al. Biotransformation enzymes and drug transporters pharmacogenetics in relation to immunosuppressive drugs: impact on pharmacokinetics and clinical outcome. Transplantation 2008;85: S19–24.

31. Hesselink DA, van Schaik RH, van Agteren M, de Fijter JW, Hartmann A, Zeier M, et al. CYP3A5 genotype is not associated with a higher risk of acute rejection in tacrolimus-treated renal transplant recipients. Pharmacogenet Genomics 2008; 18:339–48.

32. Thervet E, Loriot MA, Barbier S, Buchler M, Ficheux M, Choukroun G, et al. Optimization of initial tacrolimus dose using pharmacogenetic testing. Clin Pharmacol Ther 2010; 87:721–6.

33. Van Gelder T, Hesselink DA. Dosing tacrolimus based on CYP3A5 genotype: will it improve clinical outcome? Clin Pharmacol Ther 2010; 87:640–1.

34. Quteineh L, Verstuyft C Pharmacogenetics in immunosuppressants: impact on dose requirement of calcineurin inhibitors in renal and liver pediatric transplant recipients. Curr Opin Organ Transplant 2010; 15:601–7.

35. Li L, Li C-J, Zheng L, Zhang Y-J, Jiang H-X, Si-Tu B, et al. Tacrolimus dosing in Chinese renal transplant recipients: a population-based pharmacogenetics study. Eur J Clin Pharmacol 2011; 67:787–95.

36. Rahsaz M, Azarpira N, Nikeghbalian S, Aghdaie MH, Geramizadeh B, Moini M, et al. Association between tacrolimus concentration and genetic polymorphisms of CYP3A5 and ABCB1 during the early stage after liver transplant in an Iranian population. Exp Clin Transplant 2012; 10:24–9.

37. Hauser I A, Schaeffeler E, Gauer S, Scheuermann EH, Wegner B, Gossmann J, et al. ABCB1 genotype of the donor but not of the recipient is a major risk factor for cyclosporine-related nephrotoxicity after renal transplantation. J Am Soc Nephrol 2005; 16:1501–11.

38. Woillard J-B, Rerolle J-P, Picard N, Rousseau A, Guillaudeau A, Munteanu E, et al. Donor P-gp polymorphisms strongly influence renal function and graft loss in a cohort of renal transplant recipients on cyclosporine therapy in a long-term follow-up. Clin Pharmacol Ther 2010; 88:95–100.

39. Lv R, Hu X, Bai Y, Long H, Xu L, Liu Z, et al. Association between IL-6-174G/C polymorphism and acute rejection of renal allograft: evidence from a meta-analysis. Transpl Immunol 2012; 26:11–8.

40. Hu X, Bai Y, Li S, Zeng K, Xu L, Liu Z, et al. Donor or recipient TNF-A-308G/A polymorphism and acute rejection of renal allograft: a meta-analysis. Transpl Immunol 2011; 25:61–71.

41. Hwang Y-H, Ro H, Choi I, Kim H, Oh K-H, Hwang J-I, et al. Impact of polymorphisms of TLR4/CD14 and TLR3 on acute rejection in kidney transplantation. Transplantation 2009; 88:699–705

42. Singh R, Manchanda PK, Kesarwani P, Srivastava A, Mittal RD. Influence of genetic polymorphisms in GSTM1, GSTM3, GSTT1 and GSTP1 on allograft outcome in renal transplant recipients. Clin Transplant 2009; 23:490–8.

43. Lloberas N, Torras J, Cruzado JM, Andreu F, Oppenheimer F, Sánchez-Plumed J, et al. Influence of MRP2 on MPA pharmacokinetics in renal transplant recipients-results of the Pharmacogenomic Substudy within the Symphony Study. Nephrol Dial Transplant 2011; 26:3784–93.

44. García-González, X, Cabaleiro, T, Herrero, M, McLeod, H & López-Fernández, L. (2016). Clinical implementation of pharmacogenetics. Drug Metabolism and Personalized Therapy, 31(1), 9-16.

45. Donnan G.A., Fisher M., Macleod M. and Davis S.M.: "Stroke". Lancet 2008; 371: 1612.

46. Hunter D J, Altshuler D and Rader D J: "From Darwin’s finches to canaries in the coal mine—mining the genome for new biology". N Engl J Med 2008; 358: 2760

47. Read SJ, Parsons AA, Harrison D C, et al. Stroke Genomics: Approaches to Identify, Validate, and Understand Ischemic Stroke Gene Expression. Journal of Cerebral Blood Flow & Metabolism. 2001;21(7):755-778. doi:10.1097/00004647-200107000-00001

48. Lapham E V, Kozma C, Weiss J O, Benkendorf JL, Wilson M A. 2000. The gap between practice and genetics education of health professionals: HuGEM survey results. Genet. Med. 2: 226–31

49. Metcalfe S, Hurworth R, Newstead J, Robins R. 2002. Needs assessment study of genetics education for general practitioners in Australia. Genet. Med. 4: 71–77

50. Hall MA, McEwen J E, Barton J C, Walker A P, Howe E G, et al. 2005. Concerns in a primary care population about genetic discrimination by insurers. Genet. Med. 7: 311–16

51. Apse KA, Biesecker B B, Giardiello F M, Fuller B P, Bernhardt BA. 2004. Perceptions of genetic discrimination among at-risk relatives of colorectal cancer patients. Genet. Med. 6: 510–16

52. Vastag B. 2006. New clinical trials policy at FDA. Nat. Biotechnol. 24: 1043

53. Ginsburg GS, Burke T W, Febbo P. 2008. Centralized biorepositories for genetic and genomic research. JAMA 299: 1359–61

54. Westfall J M, Mold J, Fagnan L. 2007. Practice-based research: “Blue Highways” on the NIH roadmap. JAMA 297: 403–6

55. Offit, K Personalized medicine: new genomics, old lessons. Hum. Genet. 2011, 130, 3–14.

56. Inst. Med. Comm. Comp. Eff. Res. Prioritization. 2009. Initial National Priorities for Comparative Effectiveness Research. Washington, DC: National Academies. 227 pp.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 2nd International Conference on Modern Medicine and Global Health
ISBN (Print)
978-1-83558-395-1
ISBN (Online)
978-1-83558-396-8
Published Date
26 April 2024
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/35/20240938
Copyright
26 April 2024
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated