|Year : 2021 | Volume
| Issue : 4 | Page : 414-417
Precision medicine in public health in India: Nascent but poised in the right direction
Arun Kumar Yadav1, Ram Sagar2
1 Professor, Department of Community Medicine, Armed Forces Medical College, Pune, Maharashtra, India
2 Post Doc trg, Department of Genetic Medicine, School of Medicine, John Hopkins University, Maryland, USA
|Date of Submission||31-Aug-2021|
|Date of Decision||17-Oct-2021|
|Date of Acceptance||19-Oct-2021|
|Date of Web Publication||29-Dec-2021|
Arun Kumar Yadav
Department of Community Medicine, Armed Forces Medical College, Pune, Maharashtra
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Precision medicine (PM) in public health offers a new paradigm. Over a past few decades, there has been very rapid development in science and technology, especially in medical-clinical research to enhance the likelihood of preventive treatment which is personalized to an individual. This combined with digital health and accessibility of environmental and behavioral data offers a unique opportunity for specific prevention advice to individuals and thus to population at large. Indian with its 1.3 billion population and its ethnic diversity with high burden of disease offers a unique opportunity for the role of PM in public health. The article further explores the status and way forward for PM in India.
Keywords: India, India genomic project, precision medicine
|How to cite this article:|
Yadav AK, Sagar R. Precision medicine in public health in India: Nascent but poised in the right direction. Indian J Public Health 2021;65:414-7
|How to cite this URL:|
Yadav AK, Sagar R. Precision medicine in public health in India: Nascent but poised in the right direction. Indian J Public Health [serial online] 2021 [cited 2022 Jan 22];65:414-7. Available from: https://www.ijph.in/text.asp?2021/65/4/414/333974
| Introduction|| |
The variability of clinical presentation and response to preventive and therapeutic measures call for paradigms shift in traditional medicine approach. Precision medicine (PM) which can be understood as the right drug at the right time to the right patient is becoming popular. The US national academy of sciences first used the term PM in 2011 and defines it as an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.
| Progress in Precision Medicine – Development in Science and Technology|| |
PM has been possible due to the scientific and technical development over the past two decades. The basic framework of PM is given in [Figure 1].
The human genome project took 13 years to complete. However, with newer techniques such as next-generation sequencing, the genomic studies' time and cost have reduced drastically. Different cell type gives rise to variety of gene expression as they have distinct set of transcription regulators. Hence, the avenues beyond genes are explored, and newer branches of epigenomics, transcriptomes, proteomics, and metabolomics are developed for molecular characterization and interactions among various level of expression of genes.
Digitization of health with wearable devices, electronic health records, health information systems have made large amount of longitudinal and clinical data about individual available. The simultaneous development in Big data analytics, Machine learning, and Artificial Intelligence makes it possible to analyze a large amount of data generated through omics and digital health. Development of techniques such as RNA interference, transcription activator-like effector, or clustered regularly interspaced short palindromic repeat techniques makes it possible for the specific gene or interaction at the molecular level to be targeted.
PM has been successful particularly in the field of oncology in characterizing the heterogeneity of the disease and making the treatment individualized, based on the pharmacogenomics and omics. However, the targeted therapy is developing in other areas of medical sciences also such as hematology, infectious diseases, cardiovascular diseases, pulmonary diseases, renal diseases, endocrine diseases, neurology, psychiatry, and ophthalmology. This is substantiated by the fact that increasing number of targeted therapy are being approved by Center for Drug Evaluation and Research, FDA in recent years.
| Precision Medicine, Preventive Medicine, and Public Health|| |
PM as a concept seems in contravention to public health. However, long-term goal of both PM and public health is to keep population healthy. In fact, PM by identifying the individual at risk at the earliest and instituted personalized preventive measure may prevent or delay the risk factor or disease. This is what preventive medicine and public health strive to do. However, there are many skepticism of its utility at population level due to its predictive value limited to rare diseases, which would not affect the health of the population at large. Data from two large cohort studies observed only marginal gain in the identification of disease as compared to convention risk factors using PM approach.,
PM can help in better understanding the response of the host to infections or varied response of the antibiotics/antivirals in different individuals in communicable diseases. The whole-genome sequencing of the micro-organism can be used for the identification of genetic relatedness and mapping of the organism and thus helps in genomic surveillance. Drug susceptibility testing before giving antibiotics to individual so as to prevent multidrug resistance and mapping of the same is essential public health activity.
A scoping review of the cost-effectiveness of PM reviewed 83 studies done on cardiovascular diseases (23), cancer (36), and other diseases. Majority of studies (57) concluded that PM intervention is cost-effective compared to usual care while 14 studies concluded that PM is not cost-effective. However, the evidence is weak due to heterogeneity among the economic outcome, no pooled analysis, prevalence of the genetic factors in the population can vary, cost of genetic testing and companion treatment and the probability of complications or mortality were not taken into account.
| Development in India|| |
India with its 1.3 billion population and disease burden of both noncommunicable and communicable disease offers unique opportunity for PM. The Indian Genome Variation database project was started as early as 2003. It aimed to provide data on reported and novel, single nucleotide polymorphisms and repeats in over a thousand genes in 15,000 individuals from different regions of India. As early as 2012, India government started drafting of the Human DNA profiling bill, the bill was produced in monsoon session of 2015 and reintroduced in 2019 as DNA technology bill in 2019. The bill provides for the regulation of use of DNA technology to ascertain the identity of certain persons.
One of the exciting developments is the launch of “Genome India Project” on January 03, 2020, by department of biotechnology with the aim to collect 10,000 genetic samples from citizens across India to build a reference genome. Through whole-genome sequencing, the project would build an exhaustive catalog of genetic variation for the Indian populations and open new areas for advancing next-generation personalized or PM. Another research area developing is combination of Ayurveda and Genomics, known as Ayurgenomics for PM. The Indian Cancer Genome Atlas has been started with collaboration with the cancer genome atlas and department of biotechnology with the aim to create database of omics among Indian cancer patients. The government of India also launched a program Unique Methods of Management and treatment of Inherited disorders in 2019 for the prevention and management of inherited genetic disorders. The program aims to establish NIDAN Kendra, skilled clinicians in Human genetics, and undertakes screening of pregnant women and newborn babies. Similarly, Indian-specific databases have been developed such as Indian proteomic database under the flagship human protein reference database and other platforms such as Human Proteinpedia. Besides these collaborative projects, Individual researchers are also involved in delineating the genomics to proteomics of specific diseases in India.
Besides omics, the country has made a rapid stride in digitalization of health. National health policy 2017 aims to provide the affordable, accessible, and quality care to its population, leveraging the power of information and communication technologies. Some of the programs which provide health services such as Ayushman Bharat are already operational on robust IT platform. Health schemes are already leveraging IT platform such as maternal and child health, NIKSHAY, and others which are delivering services to people at the right time. The National Tuberculosis Elimination program has already started using benefits of PM for diagnosis and multidrug treatment. In the future, more and more national program algorithm for diagnosis and treatment would be based on PM.
The national digital health mission was launched in 2019 to establish state-of-the-art digital health system and promote the use of Clinical decision support systems by the health professionals and practitioners. Recently, PM launched Ayushman Bharat digital mission. The digital mission will have health data of individuals subsumed in health ID and would also give a boost to research and PM as well as to intraoperability of hospital services across various echelons.
Hence, India has progressed over the past decade in the field of PM. However, to make it routine into clinical and public health decision making, we have long way to go in terms of availability of meaningful data, clinician and public health specialist who understands the application of complex data, also awareness and acceptance of PM by society as large.
What We Need To Do?
New paradigm in medical education is required to enable students to understand, accept, and apply an integrative approach to health care in accordance with PM. The medical graduate must have handy knowledge of omics and its application. Research by undergraduate in the field of omics should be incentivized so that in their later years, they can continue doing research for application of PM in their respective areas.
PM is based on data. The more genetic variation, gene–gene interaction, epigenomics, and other variables are known, the more precise and predictive it would become. As Indian Genome Project is doing whole-genome sequencing of only 10,000 participants, however, for large population like ours, we would be required sequencing of large number of people. Further, this data is to be linked in such a way that the individual has access and can transfer the data to an individual where the decision would be made.
PM requires collaboration with people with multiple expertise, clinician, bioinformatics, programmers, biostatistician, etc., to come together. Making sense of data and presenting the data to clinician and public health specialist in a simple and actionable form would require an interface between doctors and the data.
The storage and retrieval of the data at the site of clinical care are essential. Innovations are required for easy accessibility and point-of-care applicability of the data. Artificial intelligence, machine learning, and deep learning would be required to handle the data. The algorithm for the identification of genetic variation and other data would be required to be developed for Indian-specific contents. Innovation would also be required for diagnostic, management, and public health use of the PM.
The government needs to come out with a policy on PM, clearly laying down the road map ahead for coming decades. Although we are moving in the right direction, a policy will consolidate all that we have achieved and show us the way forward.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Annas GJ. Personalized medicine or public health? Bioethics, human rights, and choice. Rev Port Saúde Pública 2014;32:158-63.
National Research Council (US) Committee on a Framework for Developing a New Taxonomy of Disease. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. Washington (DC): National Academies Press (US); 2011. Available from: http://www.ncbi.nlm.nih.gov/books/NBK91503/
. [Last accessed on 2021 Apr 06].
Iriart JA. Precision medicine/personalized medicine: A critical analysis of movements in the transformation of biomedicine in the early 21st
century. Cad Saude Publica 2019;35:e00153118.
Alberts B, Johnson A, Lewis J, Raff M, Roberts K, Walter P. Studying gene expression and function. In: Mol Biol Cell. 4th ed. New York: Garland Science; 2002. ISBN-10: 0-8153-4072-9.
Vatansever S, Schlessinger A, Wacker D, Kaniskan HÜ, Jin J, Zhou MM, et al.
Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions. Med Res Rev 2021;41:1427-73.
Boettcher M, McManus MT. Choosing the right tool for the job: RNAi, TALEN, or CRISPR. Mol Cell 2015;58:575-85.
Jameson JL, Longo DL. Precision medicine – Personalized, problematic, and promising. N Engl J Med 2015;372:2229-34.
Wang W, Sun Q. Novel targeted drugs approved by the NMPA and FDA in 2019. Signal Transduct Target Ther 2020;5:65.
Vaithinathan AG, Asokan V. Public health and precision medicine share a goal. J Evid Based Med 2017;10:76-80.
Ramaswami R, Bayer R, Galea S. Precision medicine from a public health perspective. Annu Rev Public Health 2018;39:153-68.
Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al.
Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet 2018;50:1219-24.
Inouye M, Abraham G, Nelson CP, Wood AM, Sweeting MJ, Dudbridge F, et al.
Genomic risk prediction of coronary artery disease in 480,000 adults: Implications for primary prevention. J Am Coll Cardiol 2018;72:1883-93.
Salipante SJ, SenGupta DJ, Cummings LA, Land TA, Hoogestraat DR, Cookson BT. Application of whole-genome sequencing for bacterial strain typing in molecular epidemiology. J Clin Microbiol 2015;53:1072-9.
Kasztura M, Richard A, Bempong NE, Loncar D, Flahault A. Cost-effectiveness of precision medicine: A scoping review. Int J Public Health 2019;64:1261-71.
Wallace RK. Ayurgenomics and modern medicine. Medicina (Kaunas) 2020;56:E661.
Gamulin S. The forthcoming era of precision medicine. Acta Med Acad 2016;45:152-7.