Personalized medicine: Time for One person, one medicine

Authors

  • Prithvirajsinh Parmar Babaria institute of Pharmacy, Vadodara, Gujarat, 391240, India
  • Himan Patel Babaria institute of Pharmacy, Vadodara, Gujarat, 391240, India
  • Ashvin Mishra Sigma institute of Pharmacy, Vadodara, Gujarat, 390019, India
  • Miteshkumar Malaviya Shree Dhanvntary Pharmacy Collage, Kim, Gujarat, 394110, India
  • Keyur Parmar Faculty of Pharmacy,The Maharaja Sayajirao University, Vadodara,390001, India

DOI:

https://doi.org/10.47957/ijpda.v9i2.462

Keywords:

Personalized medicine, Precision medicine, Artificial intelligence in Pharmaceutical industry, Genomics, PM in healthcare

Abstract

It’s becoming clearer that medicine is not one-size-fits-all. The problem with the traditional or present way of medical treatment is that they are created for and tested on a large group of people. The medicines are prescribed so broadly that they don’t work for everyone. Some drugs work very well for certain people and some not. In ancient times, medicine was practiced according to the signs and symptoms presented by the patient and were solely based on the individual knowledge of the physician and thus were called intuition medicine. Nowadays, medicine is based on the evidence produced by scientific research, including clinical trials, which is designated as evidence-based medicine. In the future, medicine will be practiced according to algorithms that will take into consideration the patient's characteristics, such as their genome, epigenetics, and lifestyle, constituting personalized medicine. Doctors use information about you -- your genes, lifestyle, and environment -- along with the characteristics of your disease to select treatments that are most likely to work for you. Health care has transmuted since the decline in mortality caused by infectious diseases as well as chronic and non-contagious diseases, with a direct impact on the cost of public health and individual health care. The evolution of medicine has increased the life expectancy of humans. Personalized medicine is the new way of thinking about medicines. In this review, we will see how Personalized medicine will transform healthcare, how Artificial intelligence and personalized medicine working together towards better healthcare, personalized medicine in the pharmaceutical industry, its vision for the future, and its application in various diseases.

Downloads

Download data is not yet available.

References

Kishorbhai VT, Malaviya, M. . Overview of an ovarian cancer and its treatment aspects. International Journal of Pharmaceutical and Biological Science Archive. 2021;9(2):24-30.

Hamburg MA, Collins FS. The Path to Personalized Medicine. New England Journal of Medicine. 2010;363(4):301-4.

Vogenberg FR, Isaacson Barash C, Pursel M. Personalized medicine: part 1: evolution and development into theranostics. P & T : a peer-reviewed journal for formulary management. 2010;35(10):560-76.

Mancinelli L, Cronin M, Sadée W. Pharmacogenomics: the promise of personalized medicine. AAPS PharmSci. 2000;2(1):E4-E.

Mathur S, Sutton J. Personalized medicine could transform healthcare (Review). Biomed Rep. 2017;7(1):3-5.

Rose N. Personalized Medicine: Promises, Problems and Perils of a New Paradigm for Healthcare. Procedia - Social and Behavioral Sciences. 2013;77:341-52.

Vicente AM, Ballensiefen W, Jönsson J-I. How personalised medicine will transform healthcare by 2030: the ICPerMed vision. Journal of Translational Medicine. 2020;18(1):180.

Javaid M, Haleem A. Industry 4.0 applications in medical field: A brief review. Current Medicine Research and Practice. 2019;9(3):102-9.

Ayers A. Personalized Medicine – Future Impact, Pharma Industry Perspective. J Biomol Tech. 2010;21(3 Suppl):S5-S.

Molyneux D, Nantulya V. Public-private partnerships in blindness prevention: Reaching beyond the eye. Eye (London, England). 2005;19:1050-6.

Bhatt P, Narvekar P, Lalani R, Chougule MB, Pathak Y, Sutariya V. An in vitro Assessment of Thermo-Reversible Gel Formulation Containing Sunitinib Nanoparticles for Neovascular Age-Related Macular Degeneration. AAPS PharmSciTech. 2019;20(7):281.

Uddin M, Wang Y, Woodbury-Smith M. Artificial intelligence for precision medicine in neurodevelopmental disorders. npj Digital Medicine. 2019;2(1):112.

Jigar Vyas HP, Himan Patel. . Comparative Study of Etoricoxib Loaded Solid Dispersion and Beta-cyclodextrin Complexes for improvement of Dissolution Profile, Research Journal of Pharmaceutical Dosage Forms and Technology. 2020;12(2):63-7.

Mathur S, Sutton J. Personalized medicine could transform healthcare. Biomed Rep. 2017;7(1):3-5.

Varnäs K, Varrone A, Farde L. Modeling of PET data in CNS drug discovery and development. Journal of pharmacokinetics and pharmacodynamics. 2013;40(3):267-79.

Patil S, Lalani R, Bhatt P, Vhora I, Patel V, Patel H, et al. Hydroxyethyl substituted linear polyethylenimine for safe and efficient delivery of siRNA therapeutics. RSC Advances. 2018;8(62):35461-73.

van Tinteren H, Hoekstra OS, Smit EF, van den Bergh JHAM, Schreurs AJM, Stallaert RALM, et al. Effectiveness of positron emission tomography in the preoperative assessment of patients with suspected non-small-cell lung cancer: the PLUS multicentre randomised trial. Lancet. 2002;359(9315):1388-93.

van Dongen GA, Poot AJ, Vugts DJ. PET imaging with radiolabeled antibodies and tyrosine kinase inhibitors: immuno-PET and TKI-PET. Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine. 2012;33(3):607-15.

Malaviya M, Shiroya M. Systemic gene delivery using lipid envelope systems and its potential in overcoming challenges. International Journal of Pharmaceutics and Drug Analysis. 2021;9(1):46-55.

Vanpariya F, Shiroya M, Malaviya M. Emulgel: A Review. International Journal of Science and Research (IJSR). 2021;10:847.

Bhatt P, Lalani R, Mashru R, Misra A. Abstract 2065: Anti-FSHR antibody Fab’ fragment conjugated immunoliposomes loaded with cyclodextrin-paclitaxel complex for improved in vitro efficacy on ovarian cancer cells. Cancer research. 2016;76(14 Supplement):2065.

Ramsey BW, Davies J, McElvaney NG, Tullis E, Bell SC, D?evínek P, et al. A CFTR Potentiator in Patients with Cystic Fibrosis and the G551D Mutation. New England Journal of Medicine. 2011;365(18):1663-72.

Narvekar P, Bhatt P, Fnu G, Sutariya V. Axitinib-Loaded Poly(Lactic-Co-Glycolic Acid) Nanoparticles for Age-Related Macular Degeneration: Formulation Development and In Vitro Characterization. ASSAY and Drug Development Technologies. 2019;17(4):167-77.

Bhatt P, Patel D, Patel A, Patel A, Nagarsheth A. Oral Controlled Release Systems: Current Strategies and Challenges. In: Misra A, Shahiwala A, editors. Novel Drug Delivery Technologies: Innovative Strategies for Drug Re-positioning. Singapore: Springer Singapore; 2019. p. 73-120.

Published

2021-07-06
Statistics
98 Views | 104 Downloads
Citatons

How to Cite

Parmar, P., H. Patel, A. Mishra, M. Malaviya, and K. Parmar. “Personalized Medicine: Time for One Person, One Medicine”. International Journal of Pharmaceutics and Drug Analysis, vol. 9, no. 2, July 2021, pp. 86-92, doi:10.47957/ijpda.v9i2.462.

Issue

Section

Review Articles
Share |