Advancing Precision Medicine Through Agile Governance

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Definition: Precision Medicine

According to the Precision Medicine Initiative, precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” This approach will allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people. It is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals.

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Although the term “precision medicine” is relatively new, the concept has been a part of healthcare for many years. For example, a person who needs a blood transfusion is not given blood from a randomly selected donor; instead, the donor’s blood type is matched to the recipient to reduce the risk of complications. Although examples can be found in several areas of medicine, the role of precision medicine in day-to-day healthcare is relatively limited. Researchers hope that this approach will expand to many areas of health and healthcare in coming year.


Health care has changed 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. We must now transition from traditional reactive medicine based on symptoms, diagnosis and treatment to a system that targets the disease before it occurs and, if it cannot be avoided, treats the disease in a personalized manner. Precision Medicine is that new way of thinking about medicine. In this paper, we performed a thorough review of the literature to present an updated review on the subject, discussing the impact of the use of genetics and genomics in the care process as well as medical education, clinical research and ethical issues.

Applications of precision medicine

  • What is already happening: The cases of oncology and psychiatry

Cancer is a leading cause of death worldwide, accounting for 8.8 million deaths in 2015 19. Research examining the mechanisms involved in the pathogenesis of cancer, including the understanding of oncogenes and epigenetic clues in oncogenesis, has been performed continuously and at an increasing pace over the last several decades 20. Therefore, the discovery of potential targets for drug development – aiming to block the expression of those oncogenes by inactivating them or their pathways – is one of the promising aspects of precision medicine. One example of this concept, which is already being clinically applied, is the treatment of chronic myeloid leukemia (CML). Allogeneic bone-marrow transplants had long been considered the best treatment option, but they were indicated only for younger patients and continued to cause significant mortality 21. However, the discoveries of molecular predispositions that generate a variety of diseases, such as CML, made possible the development of more specific medications aimed at new molecular targets. Currently, the administration of a competitive inhibitor of the Bcr/Abl tyrosine kinase – an oncoprotein expressed in 95% of patients with CML and the molecular target for this disease – is able to achieve an 80% success rate of a complete cytogenetic response in newly diagnosed patients 22.

  • What is going to happen: Tissue engineering and regenerative medicine

Tissue engineering and regenerative medicine are fields that can make important contributions to developments in precision medicine. Among the innumerable possibilities within these research areas, there are two topics of interest: organs-on-a-chip and personalized stem cell therapies.

  • Initiatives in precision medicine worldwide

The development of algorithms to predict and treat diseases based on a subpopulation-specific set of characteristics, such as genetics, drug responses, lifestyles, and social demands, requires a vast amount of information. Thus, instead of performing a series of separate and independent research protocols, initiatives aiming to create and integrate data from different medical centers are necessary. Using currently available tools, such as cloud computing, artificial intelligence, and big data, the collection and analysis of different databases will allow the creation of algorithms to direct clinical practice.

Precision Medicine Leveraging AI, Machine Learning in Early Stage - AI  Trends

Machine learning and artificial intelligence can improve precision medicine

The recent big data revolution, accompanied with the generation of continuously collected large data set from various molecular profiling (genetic, genomic, proteomic, epigenomic and others) efforts of patient samples by the development and deployment of wearable medical devices (e.g. wearable watches) and mobile health applications, and clinical outcome data has enabled the biomedical community to apply artificial intelligence (AI) and machine learning algorithms to vast amounts of data. These technological advancements have created new research opportunities in predictive diagnostics, precision medicine, virtual diagnosis, patient monitoring, and drug discovery and delivery for targeted therapies. These advancements have awoken the interests of academic, industry researchers, and regulatory agencies alike and are already providing new tools to physicians.

An example is the application of precision immunoprofiling by image analysis and artificial intelligence to biology and disease. This was demonstrated in a recent paper where the authors used immunoprofiling data to assess immuno-oncology biomarkers, such as PD-L1 and immune cell infiltrates as predictors of patient’s response to cancer treatment. Through spatial analysis of tumor-immune cell interactions, multiplexing technologies, machine learning, and AI tools these authors demonstrated the utility of pattern-recognition in large and complex datasets and deep learning approaches for survival analysis .

Technological Developments precision medicine

Three major types of precision medicine technology likely to emerge over the next decade were identified: complex algorithms, digital health applications (‘health apps’) and ‘omics’-based tests. These are summarized in the following sections and, alongside existing precision medicine tool.

  • Complex Algorithms

The experts anticipated increased use of algorithms that use artificial intelligence (AI) to aid clinical decision-making over the next decade. These algorithms require large datasets (‘knowledge bases’) that include a large number of variables, such as genetic information, sociodemographic characteristics and electronic health records. Using this information, the algorithms provide clinicians and patients with predictions on expected prognosis and optimal treatment choices using patient-level characteristics.

Health app use increases by 37% during pandemic - survey - Med-Tech  Innovation

  • Health Apps

Health apps include a wide range of tools that provide disease management advice, receive and process patient-inputted data, and record physical activity and physiological data such as heart rate. A subset of apps will likely fall under precision medicine, with the most advanced also utilizing AI-based technology as described in Sect. 3.3.1. Numbers of health apps are expected to increase significantly over the next decade. Digital health experts predicted that principal developments in this area would involve apps that analyze social or lifestyle determinants of health such as socioeconomic status or physical activity in order to stratify patients, including apps linked to activity monitoring devices (or wearable technologies). In November 2017 NICE published briefings on mobile technology health apps that were developed by the NICE medical technologies evaluation programme as a proof-of-concept activity, known as ‘Health App Briefings’. One of the first to be published concerned Sleepio, an app shown in placebo-controlled clinical trials to improve sleep through a virtual course of cognitive behavioral therapy.


  • Omics’-Based Biomarkers

Many current precision medicine tools use genetic and genomic information to estimate disease prognosis and predict treatment response. A senior health economist predicted the use of other ‘omics’-based biomarkers, such as proteomics, metabolomics and lipidomic would become more common and partially replace genomics over the next decade.Footnote1

‘Omics’-based testing is expected to increase in complexity and scope, with single tests informing treatment pathway, therapy choice or disease risk for multiple diseases simultaneously [24]. This was described by one expert as “multi-parametric testing”. Whole-genome sequencing is at the broadest end of this scale and could feasibly provide information on risks and treatment decisions for hundreds of diseases

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In this era of precision medicine, new technologies, novel study designs, and innovative therapeutic entities will challenge and elicit change within the entire spectrum of clinical research. As precision medicine advances, the IRB will continue to confront new applications that require fresh approaches to the protection of research subjects. Input from all involved in the research process is necessary for the system to move forward and successfully navigate this evolving field.

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Craig Hill

Craig began writing for in 2005, resulting in engaging and fascinating editorials about science and wellness progress. Craig’s inspirational and accurate science and health articles have made her very popular with the viewers. Craig graduated at the University of Illinois at Urbana-Champaign with a Bachelor of Arts degree at October in 2004. He then completed a science college internship in Fermilab, followed using a communications internship in Caterpillar. Ever since that moment, he has been writing in an independent capability for several science, health, technology, along with other books.

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