The impact of twenty-first century personalized medicine versus twenty-first century medicine's impact on personalization

Individualisation, personalisation and person-centredness in mental healthcare: a scoping review of concepts and linguistic network visualisation

BACKGROUND

Targeted mental health interventions are increasingly described as individualised, personalised or person-centred approaches. However, the definitions for these terms vary significantly. Their interchangeable use prevents operationalisations and measures.

OBJECTIVE

This scoping review provides a synthesis of key concepts, definitions and the language used in the context of these terms in an effort to delineate their use for future research.

STUDY SELECTION AND ANALYSIS

Our search on PubMed, EBSCO and Cochrane provided 2835 relevant titles. A total of 176 titles were found eligible for extracting data. A thematic analysis was conducted to synthesise the underlying aspects of individualisation, personalisation and person-centredness. Network visualisations of co-occurring words in 2625 abstracts were performed using VOSViewer.

FINDINGS

Overall, 106 out of 176 (60.2%) articles provided concepts for individualisation, personalisation and person-centredness. Studies using person-centredness provided a conceptualisation more often than the others. A thematic analysis revealed medical, psychological, sociocultural, biological, behavioural, economic and environmental dimensions of the concepts. Practical frameworks were mostly found related to person-centredness, while theoretical frameworks emerged in studies on personalisation. Word co-occurrences showed common psychiatric words in all three network visualisations, but differences in further contexts.

CONCLUSIONS AND CLINICAL IMPLICATIONS

The use of individualisation, personalisation and person-centredness in mental healthcare is multifaceted. While individualisation was the most generic term, personalisation was often used in biomedical or technological studies. Person-centredness emerged as the most well-defined concept, with many frameworks often related to dementia care. We recommend that the use of these terms follows a clear definition within the context of their respective disorders, treatments or medical settings.

SCOPING REVIEW REGISTRATION

Open Science Framework: osf.io/uatsc.

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology

More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.

Ethical implications of epigenetics in the era of personalized medicine

Given the increasing research activity on epigenetics to monitor human diseases and its connection with lifestyle and environmental expositions, the field of epigenetics has attracted a great deal of interest also at the ethical and societal level. In this review, we will identify and discuss current ethical, legal and social issues of epigenetics research in the context of personalized medicine. The review covers ethical aspects such as how epigenetic information should impact patient autonomy and the ability to generate an intentional and voluntary decision, the measures of data protection related to privacy and confidentiality derived from epigenome studies (e.g., risk of discrimination, patient re-identification and unexpected findings) or the debate in the distribution of responsibilities for health (i.e., personal versus public responsibilities). We pay special attention to the risk of social discrimination and stigmatization as a consequence of inferring information related to lifestyle and environmental exposures potentially contained in epigenetic data. Furthermore, as exposures to the environment and individual habits do not affect all populations equally, the violation of the principle of distributive justice in the access to the benefits of clinical epigenetics is discussed. In this regard, epigenetics represents a great opportunity for the integration of public policy measures aimed to create healthier living environments. Whether these public policies will coexist or, in contrast, compete with strategies reinforcing the personalized medicine interventions needs to be considered. The review ends with a reflection on the main challenges in epigenetic research, some of them in a technical dimension (e.g., assessing causality or establishing reference epigenomes) but also in the ethical and social sphere (e.g., risk to add an epigenetic determinism on top of the current genetic one). In sum, integration into life science investigation of social experiences such as exposure to risk, nutritional habits, prejudice and stigma, is imperative to understand epigenetic variation in disease. This pragmatic approach is required to locate clinical epigenetics out of the experimental laboratories and facilitate its implementation into society.

Measuring Exercise-Induced Secreted Protein Acidic and Rich in Cysteine Expression as a Molecular Tool to Optimize Personalized Medicine

The numerous exercise benefits for health as well as applications for diseases has lead to exercise being prescribed in many pathological conditions. Secreted protein acidic and rich in cysteine (SPARC) gene expression is stimulated by exercise and SPARC has been suggested as a molecular mediator of exercise. Therefore, we suggest using this property for personalized medicine. This can be achieved by prescribing the exercise with a pattern (duration, intensity, etc.) that corresponds to the optimum SPARC/Sparc expression. We expect this approach to optimize the exercise therapy in both the preventive and curative contexts. In the research field, measuring exercise -dependent expression of Sparc would represent a molecular tool to further optimize the selection of exercise animal models as well.