Personalized medicine: what are the challenges for health services?

The advent of personalized medicine

Science and technology contribute to improvements in health by increasing our understanding and developing innovations to prevent, diagnose and treat diseases.^1,2 In recent years, the prospect of ‘personalized medicine’ has been realized by developments in genomics, ³ other biotechnologies and digital technologies, including e-health and m-health (use of mobile technology). The combination of powerful scientific tools and information, set in a sociopolitical context that celebrates and empowers the individual within health care systems that treat them, is expected to change health services in the next few years. ⁴

Personalized approaches are proposed as solutions to the problems faced by health care systems, including prevention and treatment of chronic complex diseases such as cardiovascular and endocrine disorders, obesity, neurodegenerative diseases and cancer. ⁵ In addition, recent years have seen an increase in studies of rare variants of both common and rare diseases. Furthermore, there is increasing awareness of pharmacogenomics as a key component in personalized medicine. ³ A recent evaluation of all 517 medications labelled by the European Medicines Agency between 1995 and 2014 demonstrated that 15% – predominantly anticancer drugs – include pharmacogenomics information which covers pharmacokinetic and pharmacodynamic targets. ⁶ Clinical practice in many areas of medicine is shifting toward personalized treatment and, in theory, personalization of treatment should lead to lower health care costs.

The challenge of personalized medicine

Technological advances, together with demographic changes and increased patient expectations, are the main drivers of increased expenditure in health care. The response of governments and other funders to such rising costs has been to put pressure on service providers, demanding of them greater efficiency. ¹ Health care leaders acknowledge that part of the solution to tackling funding gaps is to more effectively use technologies to transform health care. To achieve this, digital technologies together with molecular science that enables earlier and more precise detection of disease, will need to be balanced against false-positive and unnecessary additional interventions. Additionally, reaping the benefits of the vast amounts of data generated by new technologies requires concomitant developments in our ability to interpret it.^1,4

The example of substance abuse

In mental health, the situation is seemingly particularly challenging. The cause of most psychiatric conditions is probably heterogeneous, which makes the search for biomarkers imperative, as few treatments are universally effective. ⁷ One subject for research has been impulsivity-related genetic factors. These traits have a complex background that is influenced by genetic and non-genetic factors. Genetic variants associated with the dopaminergic and serotonergic systems may have key roles in impulsivity.^8–10 The offspring of parents with substance-use disorders have increased impulsivity ¹¹ and this may be transmitted as a general risk factor for substance abuse. Thus, genetic factors play a role in the development of dependence and represent a vulnerability factor. ¹² In addition, specific genes for each substance of abuse have been identified, including significant genetic influences on aspects of smoking behaviour. ¹³

Disease pathogenesis is particularly complex for behavioural diseases. While impulsivity does have genetic susceptibility, ¹⁴ it is not entirely due to genetic determinants. Recent studies examining epigenetic changes in gene expression as a result of drug or alcohol consumption are helping elucidate the interaction between genes and environment. In the field of addictions, the contribution of genetics is much less robust than the contribution of behavioural and social factors. Small genetic effects are further complicated by the link between genotype and phenotype, with incomplete penetrance and differential expression of particular genes. These findings do not diminish the potential to elucidate the mechanistic pathways that can shed light on disease pathogenesis. Even though the results from genetic epidemiology studies are promising, the translation of such findings to inform precise alcohol, smoking and drug misuse prevention strategies is still at the beginning.

Consequences for health care systems

These developments mean that health care systems have to be redesigned. Technologies and practice that enable the move of health care from hospital into the community and shift responsibility from the professional to the citizen will need to be implemented. We need to seek the proper balance between the advantages created by the stratification and personalization of health care and the need to ensure solidarity and equity in populations, while ensuring there is a regulatory framework and public policies that respond adequately to these challenges.^1,2

A role for public health practitioners

Public health practitioners have an important role to play in achieving these changes but regrettably most have not yet embraced this agenda. They have a responsibility to help implement change in the organization of health services and public policy to ensure that genomic and other technologies are used to best effect. As reported in Beyond public health genomics: A framework for future personalized health care, ¹ a central task will be to ensure that health care systems, as well as shifting priorities from hospital to community and from diagnosis and treatment to prediction and prevention, need to embrace knowledge of genomics to make personalized medicine a reality. Implementation must be grounded in the transformation of health care, fitting a system that is sustainable ethically, environmentally and financially. Within this system, personal prevention must find its place. Financial constraints, the appropriate balance between individual autonomy and community solidarity, and its acceptability to citizens will all affect the eventual model of care. Clarity about the balance between state and private provision, between state and private funding, and between the public and commercial sectors needs to be addressed. There will be many barriers to implementation to overcome such as costs, vested interests, professional paternalism, rejection of private sector involvement, bureaucratic delays around sharing of data and low tolerance of risk that places so many obstacles in the way of innovation.