Personomics. From precision medicine to personalized medicine

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Personomics
Abstract model of man of DNA molecule. Eps 10

In recent years, medicine based on knowledge and on the treatment of patients, recognized as individuals with unique characteristics, has mainly focused on the characterization of their biological “uniqueness”, defined by the so-called -omics data. This approach, known as precision medicine, was the subject of a famous 2015 speech by Barack Obama. In essence, precision medicine represents the adaptation of medical treatment to the individual characteristics of each patient. The goal is to make the treatment process targeted to a specific person, in order to increase its effectiveness and decrease complications, failures and economic waste. Another name for this is approach is personomics.

Personomics

Using the information provided by -omics data in diagnosing and treating patients has enormous potential for improving human health. However, the concept of precision medicine typically does not take into account aspects of individual variability related to the person’s life experiences. This is where personomics comes in. The term was also coined in 2015 and proposed to the scientific community by Roy Ziegelstein of the Johns Hopkins University School of medicine on the columns of Jama International Medicine.

Personomics determines how the disease reveals itself phenotypically and how the disease and the affected individual respond to treatment. Basically, it takes into account the social, psychological, cultural, behavioral aspects, the economic factors that influence the patient’s health beliefs and his interactions with healthcare professionals. With personomics, importance is given to the individual’s personal preferences, to his or her values and objectives and to the support that the patient receives from the affections.

Precision medicine vs personalized medicine

  • Precision medicine characterizes individuals on the basis of biological and molecular aspects that can target the treatment process. It starts from large data sets, derived from -omics and supporting technologies, to obtain tailor-made diagnoses and therapies.
  • Personalized medicine considers the biological profile of the patient, his lifestyle and the influence of environmental factors, without necessarily relying on large data sets to redefine the disease.

Precision diagnostics

As mentioned, with the advent of -omics it has become possible to collect data on DNA, mRNA, proteins, metabolism and drug response. Current technological tools and the development of cell-level tests, such as rapid genetic assays and wearable sensors, also allow for the integration of -omic data with other clinical, lifestyle and treatment adherence information. The process of getting to know and applying the results is circular. The large sets of biological and digital health data are integrated into a network of knowledge that feeds both information useful for the evolution of science and information useful for the management and treatment of the individual.

Genomic medicine has an important impact in all those conditions in which the presence of mutations plays a causal role.

In the field of oncology, for example, the search for oncogenes that drive the disease is increasingly common to build and adjust a targeted treatment process. The methods of analysis are different and can be applied to a biological sample obtained from a biopsy of the investigated tissue, or from the more innovative liquid biopsy, or on the blood. The latter has the advantage of being non-invasive and highly repeatable, allowing the evolution of the disease to be monitored over time. In these cases, tumor DNA released into the bloodstream from primary tumors and metastases is sought. Other non-invasive approaches on biological fluids other than blood are also currently being studied to trace, in addition to circulating tumor DNA, also circulating tumor cells or exosomes.

Supporting technologies

  • Immunohistochemistry: the antigen is searched for in a portion of tissue on the basis of antigen-antibody reactions.
  • Fluorescent in situ hybridization: specific DNA sequences are identified from different biological samples using labeled nucleotide probes.
  • Next generation sequencing: millions of nucleic acid fragments are sequenced in parallel in a short time. It represents the technique with the greatest potential and also applies to liquid biopsy.

The contribution of Big Data

In recent years we have witnessed a real explosion in the volume, speed and variety of information available in the medical field: the so-called Big Data. It is a collection of biological, biometric and electronic data of millions of individuals, whose interpretation can provide important bases for the interpretation of the results obtained, for the prediction of future processes and for the identification of ad hoc therapies. Artificial intelligence (AI) and machine learning are both applicable to precision medicine. The target? To go beyond the current information capacity of Big Data and find ways to understand the data also in order to obtain pragmatic value for clinical practice.

When it comes to technology and medicine, it should be remembered that efforts are not solely about process validation. In fact, attention is also focused on security, ethical and privacy issues.

Clinical applications of AI and machine learning

Artificial Intelligence

  • Data collection, storage, normalization and tracking
  • Continuous monitoring of pharmacological therapy
  • Therapeutic adherence

Machine learning

  • Identification of a course of action without direct instructions
  • Management of drug combinations
  • Development of biomaterials
  • Dynamic and continuous monitoring of the pathology
  • Therapeutic adherence

A new era for clinical research

infographic clinical trialsThe current model of design and development of a clinical study risks being no longer adequate for the historical moment. If in fact it is true that, thanks to the research and identification of more and more biological markers, the treatment process can be individualized, it is equally true that a clinical study design that does not take into account this characterization of the disease risks not arriving to the goal: that of “tailor-made” care.

As a matter of fact, through a progressive segmentation, even frequent tumors are treated today as rare diseases and this makes the classic randomized clinical trial little applicable. For this reason, new designs have been proposed, the so-called master protocols, which include basket trials, umbrella trials and platform trials and have the aim of finding the right trial for the individual patient. To do so, they also integrate emerging realities such as machine learning, comprehensive molecular profiling and real world data into the trial. The emphasis on the role of biomarkers in these protocols requires a safe and thorough screening process.

Umbrella trials

In umbrella trials applied to the oncology field, patients with the same type of tumor (in other words, with the same organ of origin) are examined for the presence of a series of biomarkers. On this basis they are allocated to the treatment arms with the corresponding drugs, in which each drug is coupled to the specific biomarker. They are particularly indicated in cases where there are several therapeutic options. The “umbrella” study also evaluates the efficacy of the drugs on the individual tumor type. Tumor genotyping divides patients based on mutations to evaluate appropriate target therapies. Experimental drugs can be evaluated for different types of cancer with the same mutation within the same study or in a separate trial.

Basket trials

In basket trials applied to the oncology field, on the other hand, patients are recruited only on the basis of molecular characteristics, regardless of the origin of the tumor which therefore does not become a selective criterion. This type of study is ideal for the targeted evaluation of therapies with low prevalence targets. The basket trial is independent of the histological assessment and the treatment arms are based on mutations “shared” by the patients. Treatment cohorts may therefore be more inclusive of rare mutations. The responses can be evaluated for the entire cohort or for individual characteristics.

Platform trials

In all these studies it is also planned to introduce features of adaptive designs. Based on them, the preliminary results that gradually accumulate can be used to modify the course or structure of the trial. These are platform trials, generally randomized, multi-step and multi-arm studies, with a control arm and more experimental arms. The application normally consists in evaluating different targeted therapies for one or more diseases. This is done through changes in the course of the study, with flexibility based on the progress of the trial. In addition to this, other aspects of great importance must also be considered. They range from the ability to ensure the integrity of the conduct of clinical trials, to a robust structure capable of appropriately interpreting the results for application in clinical practice.

Personomics, the 5P healthcare

Quando si parla di medicina personalizzata in campo oncologico, è inevitabile ricordare l’approccio 4P. La sigla si riferisce a un modello di cura predittivo, personalizzato, preventivo e partecipativo per il trattamento dei pazienti. Gabriella Pravettoni – professore ordinario di psicologia generale e direttore del dipartimento di oncologia ed emato-oncologia dell’Unimi, e direttore della divisione di psiconcologia allo IEO – in un passaggio del “Libro bianco sulla medicina personalizzata in oncologia” sottolinea però come sia altrettanto importante dare rilevanza alla componente psicologica. P non solo come “psicologia”, ma anche come “persona” con una serie di bisogni. La personomica, quindi. Purtroppo, sebbene siano passati ormai 10 anni dall’introduzione del concetto della medicina 5P, siamo ancora molto indietro su questo approccio.

When it comes to personalized medicine in the oncology field, it is inevitable to remember the 4P approach. The acronym refers to a model of care for the treatment of patients that is:

  • predictive,
  • personalized,
  • preventive,
  • participatory.

Gabriella Pravettoni – full professor of general psychology and director of the department of oncology and hemato-oncology at the University of Milan, and director of the psycho-oncology division at IEO – underlines however how important it is in a passage from the White Book on personalized medicine in oncology give relevance to the psychological component. P not only as a “psychology”, but also as a “person” with a set of needs. Personomics, then. Unfortunately, although it has now been 10 years since the introduction of the 5P medicine concept, we are still far behind on this approach.