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The Theme - Precision Medicine Revolution

(The University of Chicago - Alvin Wei-Cheng Wong)



Smart, Precision and Preventive Medicine in the Era of Big Data


1. Overview

- The Medical Model of Precision Medicine (or Personalized Medicine)

Precision medicine is an emerging approach for disease prevention and treatment that takes individual variability into account. To achieve “individual variability” requires analyzing multiple genes with little amounts of specimen inexpensively, quickly and sensitively.

"Precision medicine aims to collect, connect, and apply vast amounts of scientific research data and information about our health to understand why individuals respond differently to treatments and therapies, and help guide more precise and predictive medicine worldwide." -- [Precision Medicine at UCSF]

Personalized medicine is not a new paradigm or a revolution, it’s simply the natural evolution of healthcare. The medical model of precision medicine (personalized medicine) aims to customize the treatment based on the three governing factors (genome structure, lifestyle and environmental condition), which characterizes an individual’s response to the disease. The use of system biology and panomics aids this process by diagnosing the illness at a molecular level. Once the cause is determined, customized medication could be prescribed to them. Such personalized medicine moves from the one-size-fits-all model that doctors have previously adhered to.

- From Big Data to Precision Medicine

For over a decade the term Big data has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, Big data no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Technologies such as data analytics and data science have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises Big Advances, significant challenges remain.

- The Age of Precision Medicine is Here

As defined by the National Research Council, precision medicine refers to the tailoring of medical treatment to the individual characteristics of each patient. The availability of the human genome, large amounts of data on individual genetic variations, environmental interactions, influence of lifestyle, and cutting-edge tools and technologies for big-data analysis have led to the age of precision medicine (also referred to as personalized medicine). 

Imagine receiving a full diagnosis from a simple blood test, or the ability to tailor the perfect treatment to each person's own genetic makeup, taking into account an individual patient's specific susceptibilities to side effects. What if we could apply a patient’s genetic information to gain insights into the genetic variations of diseases and expedite drug development, to create more precise therapies. Welcome to the world of precision medicine. That sounds futuristic, like science fiction, or a cool exhibit, something that promises great things for tomorrow, something that’s not here yet. But this is different. After years of research, therapies tailored to the genomes of individual patients are reaching maturity. Precision medicine is already here. We have revolutionary new knowledge which has given us new targets for a smarter, more scientific approach that is helping all patients - but particularly those who need it most.


2. What is Precision Medicine?

- Precision Medicine Can Be a Game Changer 

The field of precision medicine, while still in its infancy, holds the promise of transforming health care delivery. 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. Precision approach to medicine includes an individual’s genetic profile to guide decisions made in regard to the prevention, better diagnoses, earlier interventions, more-efficient drug therapies, and customized treatment plans. Precision medicine can also be defined as a predictive, preventive, personalized, and participatory healthcare service delivery model. For example, precision medicine is a particular game-changer for cancers, so many of which are responding well to new immunotherapies - treatments that engineer a patients’ own immune cells to better fight disease. 

- An Emerging Approach for Disease Treatment and Prevention

The goal of precision medicine is to provide drugs and therapies that are uniquely suited to individual patients based on their genetics and other distinguishing health information. However, it does not literally mean the creation of drugs or medical devices that are unique to a patient. Precision medicine is able to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology and/or prognosis of those diseases they may develop, or in their response to a specific treatment.

Personalized, cell-based therapies and personalized drug selection constitute two important facets of precision medicine, treatments specifically tailored to the individual receiving them. It is transforming the way diseases like cancer, diabetes, cardiovascular and chronic respiratory diseases are treated by tailoring medical care to the person’s genetic makeup, or the genetic profile of an individual’s tumour. In precision medicine, the focus is on identifying the approaches that will be effective for patients based on genetics as well as environmental and lifestyle factors, and concentrate preventive or therapeutic interventions on those who most benefit, sparing expense and side effects for those who will not.

- One-Size-Doesn't-Fit-All

According to the National Institutes of Health (NIH), 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. 


3. Standards of Care

- Modern Medicine and One-Size-Fits All Medical Approach

Most often today, you go to your doctor with your symptoms, and you get an evaluation, maybe have a few tests run.  If you are lucky, you’re on your way to a diagnosis and a path to feeling better. However, your treatment plan doesn’t have all that much to do with you specifically. It’s identical to what doctors would hand over to essentially anyone with the same condition. That’s because medicine as we know it revolves around “standards of care,” the best courses of prevention or treatment for the general population, or the average person on the street. With breast cancer, for example, those standards mean self-exams and mammograms after a set age and the usual chemotherapy to treat a tumor if one is found. If the first treatment doesn’t work, doctors and patients move on to the next one and the next. It’s trial and error, with life on the line.

It is estimated that more than half of all cancer deaths could be prevented, and it is well established that early detection of cancer improves cancer mortality. Thus, The sooner these emerging early-detection tools and interventions become standard universal care, the sooner we will see higher survival rates. We can stop cancer before it starts because Precision Prevention doesn’t wait for the diagnosis. 

- Expanding Precision Medicine: The Path to Higher Value Care

Precision medicine is a new approach to disease prevention and treatment that takes into account a patient’s genes, environment and lifestyle, and customizes medical decisions based on that information. This is a departure from traditional medicine, wherein medical decisions were made for patients based on the typical characteristics of the disease they have, rather than their bodies’ unique characteristics in relation to that disease.

The one-size-fits-all medical approach is a thing of the past. Advances in genomics, precision medicine and machine learning have led to powerful new discoveries. Hospitals, networks and the federal government can use precision medicine to drive expenses out of the system, better understand disease and prevent people from getting sick in the first place. So we like to think of precision medicine as the right treatment for the right patient at the right time for the right cost.


(Duke University - Cheng-Yu Chen)

4. Personalized Healthcare

- Focusing Precision Medicine through Unravelling Genetic Variation

Precision medicine is an approach that emphasizes the ways in which your disease risks are unique and different, just like your other, more obvious characteristics. Those disease risks are based on the predispositions written into your genome at birth, combined with your lifestyle and environment. 

Like unique fingerprints, human genes can vary distinguishably among individuals. Thus, we can monitor each person's health by understanding and characterizing his or her genes. Primary physicians can classify the genetic information of each patient and provide advice regarding prevention or predict diseases that have a greater probability of occurring. When the disease appears, physicians can also effectively provide tailored medications and therapies, ensuring that the most optional treatment is given to the right patient in the right dose at the right time. 

- The Promise of Precision Medicine in Cancer Treatment 

In the case of cancer, the disease has its own genetic makeup, lending each tumor a unique character with unique tendencies and vulnerabilities. And perhaps there is, or soon will be, a drug or treatment or tailored combination of the two that will work better for you than it would for someone else. 

Today, when you are diagnosed with cancer, you usually receive the same treatment as others who have same type and stage of cancer. Even so, different people may respond differently, and, until recently, doctors didn’t know why. After decades of research, scientists now understand that patients’ tumors have genetic changes that cause cancer to grow and spread. They have also learned that the changes that occur in one person’s cancer may not occur in others who have the same type of cancer. And, the same cancer-causing changes may be found in different types of cancer.

"The hope of precision medicine is that treatments will one day be tailored to the genetic changes in each person’s cancer. Scientists see a future when genetic tests will help decide which treatments a patient's tumor is most likely to respond to, sparing the patient from receiving treaments that are not likely to help. Research studies are going on now to test whether treating patients with treatments that target the cancer-causing genetic changes in their tumors, no matter where the cancer develops in the body, will help them. Many of these treatments are drugs known as targeted therapies. 

Targeted therapy is the foundation of precision medicine. It is a type of cancer treatment that targets the changes in cancer cells that help them grow, divide, and spread. As researchers learn more about the cell changes that drive cancer, they are better able to design promising therapies that target these changes or block their effects." -- [NIH-National Cancer Institute]

- Genetics, Disease Prevention and Treatment

It is now appreciated that some cancers run in families due to an inherited predisposition to cancer development. Due to the widespread availability of genetic testing, we now have the opportunity to successfully identify these families and the affected individuals. Because early detection and prevention can also improve mortality in individuals with an inherited predisposition to cancer, these individuals are an important target population for cancer prevention and early detection strategies. With appropriate attention to implementation, identification of at-risk individuals may empower them to make and act upon informed, cancer-preventing health decisions.

Precision medicine promises to increase patient-centered care, personalized patient-provider relationships, and treatments targeted to individual concerns and needs. However, such advantages come with certain ethical, legal and social controversies. 


5. Genetic Markers and Next-generation Sequencing (NGS)

- Next Generation Sequencing: A Revolution in Technology. 

Next Generation DNA Sequencing (NGS) is a revolutionary new technology that provides biologists and medical scientists with the ability to collect massive amounts of DNA sequence data both rapidly and cheaply.

Precision medicine relies on an advanced DNA testing process known as next-generation sequencing (NGS). Today, developments in NGS and information technology have made precision medicine possible, with massive amounts of genetic, "omics," clinical, environmental, and lifestyle data now available. The tech­nology is still being developed, but NGS can map almost all of a person’s genome in a single run, making it much faster and cheaper than earlier methods. 

- Biomarkers and Clinical Research

In genetics, a biomarker (identified as genetic marker) is a DNA sequence that causes disease or is associated with susceptibility to disease. They can be used to create genetic maps of whatever organism is being studied. A genetic marker is a DNA sequence with a known physical location on a chromosome. Genetic markers can help link an inherited disease with the responsible gene. Biomarkers have the extra potential to identify individuals susceptible to particular diseases.

By detecting genetic markers for diseases, it can be used to inform prevention efforts, improve diagnoses, and suggest which treatments are likely to work best for each patient. The discovery of genetic biomarkers and their subsequent application in oncology research are paving the path toward a future in targeted therapy development, linking genes to disease states and prognosis and, ultimately, more effective treatments.


6. From Hype to Reality: Data Science Enabling Personalized Medicine

- Personalized Medicine: Unleash The Power of Health Data

Precision medicine aims to integrate personalized health data both from direct and indirect sources probing the deepest mysteries affecting individual health and well-being. Data integration means bringing together data from diverse sources, turning complex data into coherent and more useful information (i.e., knowledge), and turning it into something you can make use of programmatically. Moreover, integration of datasets significantly reduces the overall data complexity. The data becomes more available for use and unified as a system of its own. Such a streamlined and integrated data system can increase the collaboration between different parts of your data systems. Each part can now clearly see how their data is integrated into the overall system, including the user scenarios and the security and privacy processes around it. In order to do precision medicine we need all the patient’s diverse data in a common repository. It requires data utility ranging from collection and management (data storage, sharing, and privacy) to analytics (data mining, integration, and visualization). 

- From Data Gathering to Actionable Insights

Because of rapid advances in biotechnologies, highly complex biomedical data are becoming available in huge volumes. Where does all this diverse data come from? If we could look at labeled data streams, we might see research and development (R&D), physicians and clinics, patients, caregivers, etc. The array of (at present) disparate origins is part of the issue in synchronizing this information and using it to improve healthcare infrastructure and treatments. Hence, the present-day core issue at the intersection of machine learning and healthcare: finding ways to effectively collect and use lots of different types of data for better analysis, prevention, and treatment of individuals. To make sense of these heterogeneous data, big data analytics, including data quality control, analysis, modeling, interpretation, and validation, is needed to cover application areas such as bioinformatics, health informatics, imaging informatics, and sensor informatics.

- Seamless Integration of Personalized Health Data

Implementing precision medicine in a clinical setting requires seamless integration of diverse data from clinical evaluations and biomedical investigations with genomics and other physiological profiling to characterize an individual patient’s disease progression. Implementing precision medicine practices in clinical settings requires coordinated efforts to integrate data from both healthy and disease states in individuals. The ideas behind precision medicine are not new, but the development of big data analytics, biobanking, new methods for categorizing and representing patients, and computational tools for analyzing large datasets have provided opportunities for more widespread use.


7. The Precision Medicine Ecosystem

- Emerging New Technology to Advance Personalized Medicine

Modern biomedical sciences are data-driven, and depend on many reliable databases of biomedical knowledge, or simply "knowledge bases". Knowledge bases are particularly important for precision medicine. knowledge bases are essential for clinicians to look up what treatment is known to be effective for their patients.

"Precision medicine consists of seven overlapping and intersecting elements, including basic, clinical, and social/behavioral discovery, plus the enabling tools of digital health, 'omic technologies, and computational health sciences. These elements are integrated by a knowledge network, creating a sort of "Google maps for health," which informs new research and technologies, and leads to more precise and predictive care." -- (UCSF)

- Data-driven Precision Medicine Ecosystem

"The precision medicine ecosystem contains building blocks that optimally connect patients, clinicians, researchers and clinical laboratories to one another. Patients and clinicians access information through patient portals or EHRs. The ecosystem can include Displays or Clinical Decision Support (CDS) tools augmented by curated knowledge that is supplied and shared by multiple stakeholders. Case-level databases (genotypes, phontypes and outcome, family and medical history, environment and exposures) and biobanks (patient samples) receive case data and samples from clinical and research workflows. Researchers benefit from all of these information sources and also contribute to knowledge sources. Clinical laboratories leverage data and inform the clinical community as they assess genomic variation and its impact on human health." -- (NATURE)

For example, by integrating genomic, phylogenetic, population genetic, statistical and machine-learning, computer vision, and medical imaging techniques, clinicians and biomedical scientists investigate clinical and molecular signatures of human diseases, and develop novel computational methods to discover biomarkers (eg., imaging/biomarkers) for early diagnosis and accurate prediction of therapeutic responses for individual patients.

- An Integrated Precision Medicine Knowledge Base for Interpreting Relationships Between Diseases, Genes, Variants and Drugs

As genetic testing and interpretation advance, precision medicine stands to move medicine away from the population-based knowledge that grounds evidence-based medicine (EBM) to the treatment of patients “based on a deep understanding of health and disease attributes unique to each individual. Such understanding requires a different and broader concept of medical knowledge, the development of new methods for generating such knowledge, and approaches for incorporation into clinical practice. As precision medicine advances, for some decisions it will replace the population-based “best evidence” of EBM with specific and detailed understanding of what makes an individual patient different from others. To practice precision medicine, clinicians should reconsider current notions regarding the relative value of evidence, as case-based reasoning and understanding of mechanisms will figure more prominently.


8. Interdisciplinary Training for Precision Medicine

- Interdisciplinary Training to Build an Informatics Workforce for Precision Medicine.

Recent developments in molecular biology and information technology make precision medicine a reality today through the use of massive amounts of genetic, 'omics, clinical, environmental, and lifestyle data. Precision medicine has the potential to profoundly improve the practice of medicine, but requires a health care workforce that understands the complexities of this field. One of the most critical is an informatics workforce that has broad interdisciplinary training in basic science, applied research and clinical implementation. However, the advances required will take time to implement.

- Healthcare Workers Need Retraining to Keep Up With Technological Change

One important component of precision medicine is the use of an individual’s genomic information to offer targeted treatment, tailored to the individual. Genomics is a branch of molecular biology focused on studying all aspects of a genome, or the complete set of genes within a particular organism. Genomic technologies are generating an extraordinary amount of information. Genetics is already being used to direct clinical decision-making and its contribution is likely to increase. 

To accelerate these advances, fundamental changes are needed in the infrastructure and mechanisms for data collection, storage and sharing. This will create a continuously learning health-care system with seamless cycling between clinical care and research. Patients must be educated about the benefits of sharing data. If precision medicine approaches are to become part of routine healthcare, doctors and other healthcare providers will need to know more about molecular genetics and biochemistry. They will increasingly find themselves needing to interpret the results of genetic tests, understand how that information is relevant to treatment or prevention approaches, and convey this knowledge to patients. 


9. Bioinformatics: The Key to a Precision Medicine Future

- Bioinformatics Models, Methods and Algorithms

Bioinformatics, the key to a precision medicine future, aims to store, organize, explore, extract, analyze, interpret, and utilize information from biological data. Bioinformatics optimizes translational medicine through the transformation of data into diagnostics, prognostics and therapeutics. 

Bioinformatics has revolutionized the growth in the scale and complexity of biological data of the healthcare industry. There is a tremendous need to explore how mathematical, statistical and computational techniques can be used to better understand biological processes and systems, while developing new methodologies and tools to analyze the massive currently-available biological data. Recent developments in the strategies and technologies like big data, NGS, has changed the pace and driven the industry of genomics and molecular medicine towards commercially viability and impromptu outcomes.

Bioinformatics has increasingly shifted its focus from individual genes, proteins, and search algorithms to large-scale networks often denoted as 'omes such as biome, interactome, genome and proteome.

- Translational Medicine: Leveraging Bioinformatics

Translational medicine is becoming ever-more interdisciplinary. The ability to collect, store and analyze massive amounts of molecular and clinical data is fundamentally transforming the scientific method and its application in translational medicine. Biomedical researchers need new computational approaches to deal with the large amounts of data pouring in from genomics and other fields, and as new advances in physics and materials science offer new approaches to study or diagnose medical conditions.

Translational bioinformatics is a rapidly emerging field of biomedical data sciences and informatics technologies that efficiently translate basic molecular, genetic, cellular, and clinical data into clinical products or health implications. Its focus is on applying informatics methodology to the increasing amount of biomedical and genomic data to formulate knowledge and medical tools, which can be utilized by scientists, clinicians, and patients. Furthermore, it involves applying biomedical research to improve human health through the use of computer-based information system. Translational bioinformatics employs data mining and analyzing biomedical informatics in order to generate clinical knowledge for application. Clinical knowledge includes finding similarities in patient populations, interpreting biological information to suggest therapy treatments and predict health outcomes.


10. The 'Omics Universe and Its Future

- The Influence of 'OMICS in Shaping Precision Medicine 

Precision medicine is quickly emerging as an exciting new medical model in which patient information is extracted from their lifestyle, environmental, and genetic data. These data will be used to augment and refine traditional medical data to provide a higher level of specificity for disease prevention and patient care. One important aspect of precision medicine aims to deliver the right medicine to the right patient at the right dose at the right time based on the unique 'omics features of each individual patient, thus maximizing drug efficacy and minimizing adverse drug reactions. Born in basic research, ‘omics have become a powerful contributor across precision medicine.

The term 'omics is used to describe the collective research efforts of molecular biology for various subdomains (e.g., genomics, proteomics, metabolomics). Such a varied array of research avenues is believed to propel our understanding of diseases, leading to powerful new discoveries and treatments that can be tailored to individuals. It also gives medical professionals the resources needed to design specific treatments for individuals.  

- Advanced 'Omics Technologies and Approaches

The advance of precision medicine heavily relies on the ability to study biological phenomena at 'omics levels. Patients can be treated according to their own molecular characteristics. Individual omes as well as the integrated profiles of multiple omes, such as the genome, the epigenome, the transcriptome, the proteome, the metabolome, the antibodyome, and other 'omics information are expected to be valuable for health monitoring, preventative measures, and precision medicine. Moreover, 'omics technologies have the potential to transform medicine from traditional symptom-oriented diagnosis and treatment of diseases towards disease prevention and early diagnostics.  

A major objective of 'omics technologies is to understand genetic causality of complex traits of human diseases. New 'omics technologies have made it possible to obtain high-resolution molecular snapshots of organisms, tissues, and even individual cells at various disease states and experimental conditions. It is hoped that these developments will usher in a new era of personalized medicine in which an individual's molecular measurements are used to diagnose disease, guide therapy, and perform other tasks more accurately and effectively than is possible using standard approaches.

-  'Omics Technologies and Their Application to Medicine

Disease progression and drug response may vary significantly from patient to patient. Fortunately, the rapid development of high-throughput 'omics technologies has allowed for the identification of potential biomarkers that may aid in the understanding of the heterogeneities in disease development and treatment outcomes. High-throughput 'omics technologies and their application to medicine open up remarkable opportunities for realising optimised medical treatment for individuals. Integrated 'omics investigations will be critical in piecing together targetable mechanisms of action for both drug development and monitoring of therapy in order to fully apply precision medicine to the clinic.

In the future, newborns could be assessed from an ‘omic perspective, looking at genes, proteins, gut microbes, metabolic markers and the like. Beginning even before birth, practitioners would be able to see how these elements of health change as people progress through the course of their lives.

-'Omics, Big Data, Precision Medicine, and Personalized Medicine

The two fields, genomics and bioinformatics, have been facing enormous challenges and chances in the past three decades. Development of high-throughput technologies, such as next generation sequencing, have also brought us into an “'omics” era, where not only genomics, but transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics data can be generated in real time, enabling scientists and clinicians to examine for the first time the effect of multi-omics on disease pathogenesis in unprecedented detail. The combined 'omics information leads to a global profiling of health and disease, and provides new approaches for personalized health monitoring and preventative medicine.

'Omics data, mobile Internet real-time data and electronic health record data are the top three areas for big data in medical research. Precision medicine will use all of these three big data.


11. Molecular Pathology and Precision Medicine

- New Molecular Pathology Tests Advance Precision Medicine

Molecular pathology is another major tool in precision medicine. Molecular pathology is an emerging discipline within pathology which is focused in the study and diagnosis of disease through the examination of molecules within organs, tissues or bodily fluids. Tiny samples of blood or tissue are taken from the patient and analysed for levels of large molecules such as proteins and DNA. Combining these results with other information, such as imaging and clinical data, enables us to precisely divide patients into subgroups and optimise their treatment. Molecular pathology will take molecular diagnostics to new heights by adding important precision medicine tests to help patients. Molecular pathology will also modernize how we manage genomic information. It is commonly used in diagnosis of cancer and infectious diseases. 

- Molecular Pathology: A Requirement for Precision Medicine in Cancer.

Since almost all the biomarkers to be specifically detected are tissue based, a precise and reliable diagnostic is absolutely crucial. Reading a patient's tissue as deeply as possible and obtaining information on the morphological, genetic, proteomic and epigenetic background are the tasks of pathologists and molecular biologists and provide the clinicians with information relevant for precision medicine. 

Intensified cooperation between clinicians and pathologists will provide the basis of improved clinical drug selection and guide development of new cancer gene therapies and molecularly targeted drugs by research units and the pharmaceutical industry.

- The Changing Role of Pathologists in the Age of Precision Medicine

Developments in diagnostic technology and the rise of precision medicine mean pathologists are more involved in clinical decisions than ever. Clinical applications in molecular pathology have grown exponentially, and the field has evolved to become a focal point of precision medicine.

In general, as the amount of information coming from increasingly large numbers of sources continues to increase, pathologists will be spending more and more time on each case, integrating this into a complete, clinically-relevant report. Much of this will require the use of algorithmic analysis of the data to determine the best course of action for each individual patient. Developments in digital pathology will also allow more accurate and reproducible assessment of quantitative data.


12. Systems and Network-Based Approaches for Precision Medicine

- Networks and Systems Biology 

Networks and systems biology is the study of complex systems by a holistic approach where the 'omics approaches such as transcriptomics, glycomics and lipidomics find wide use. Networks and systems biology aims to understand the networks of interactions and effects of those interactions on a global scale, involving hundreds of different biological molecules simultaneously.

- Systems Biology-Powered Precision Medicine

The field of systems biology has far reaching impact on the disciplines of biology, medicine, and drug discovery. It offers great potential for the betterment of human life and cure against diseases. The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology is the study of systems of biological components, which may be molecules, cells, organisms or entire species. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. 

One important aspect of systems biology is data mining. Data management and access can become a daunting task given the tremendous amount of data generated with current high-throughput technologies, and the data size is constantly increasing with time. Challenges exist computationally in each step to handle, process and annotate high-throughput data, integrate data from different sources and platforms, and pursue clinical interpretation of the data. These steps can be quite computationally intensive and require significant computational hardware.

Systems biology is actively transforming the field of modern healthcare from symptom-based disease diagnosis and treatment to precision medicine in which patients are treated based on their individual characteristics. Development of high-throughput technologies such as high-throughout sequencing and mass spectrometry has enabled scientists and clinicians to examine genomes, transcriptomes, proteomes, metabolomes, and other omics information in unprecedented detail. The combined 'omics information leads to a global profiling of health and disease, and provides new approaches for personalized health monitoring and preventative medicine.

- Network Biology in Medicine and Beyond 

Clinical research and medical treatments are poised to experience a dramatic change in the next decade, thanks to the advent of population-wide 'omics profiling, electronic medical records, and artificial intelligence. The interpretation of such massive amounts of data and its relationship to disease is a major challenge when trying to make actionable predictions that can lead to effective patient-specific therapeutics. Network biology provides a conceptual framework and toolkit to integrate and interpret large data sets and to generate hypotheses about gene function, gene–disease associations, drug efficacy, and disease prognosis.

The explosion of large-scale, high-throughput technologies in the biological sciences demands a comprehensive view of biological systems. Integrative network biology will be the use of novel experimental and computational approaches to study signalling networks, and how network models can be applied to the study of complex diseases such as cancer. It includes following multiple topics: developing and applying sophisticated models and algorithms carefully tuned to extract relevant biological and medical knowledge from systems-level real-world molecular and medical data, including whole genome sequences, epigenetic data, protein-protein interaction networks, signaling networks, metabolic networks, transcriptional regulation networks, gene and disease ontologies, drug similarity networks, drug-target interactions, drug-drug interactions, patient records, lifestyle data, electronic health records etc. The aim of integrative network biology is to mine these inter-linked heterogeneous networked data for new biological and medical insight that would lead to improving diagnostics, discovering new biomarkers, improving patient stratification and treatment, personalizing treatment and facilitate rational drug development.


(McGraw Tower - Photo Courtesy of Cornell University)

13. Pharmacogenomics (Drug-Gene Testing)

- The Current "Test and React" Approach

Current practices for prescribing medication within classes of drugs are relatively arbitrary - performed using the ineffective "test and react" approach - and many patients do not respond to the first medication they are prescribed. Diagnostic tests to identify whether a person will respond positively to a given drug, or have a potentially life-threatening reaction to the medication or dose, could save billions of dollars, increase the quality of care and prevent fatalities.

- The "Drug-Gene Testing" Approach

Pharmacogenomics (or drug-gene testing), a relatively new field, is the study of the way genetic differences between individuals influence patient drug responses and drug disposition. Significant interindividual variation exists within the measured human genomes. This variability can have a major impact on the effectiveness of the many therapeutic drugs that require activation or inactivation by the affected enzymes. Therefore, Pharmacogenomics can play a major role in dosage adjustment to ensure effectiveness and/or prevent toxicity.

Pharmacogenomics is the study of how your genes affect the way your body processes and responds to medications. It combines pharmacology (the science of drugs) and genomics (the study of genes and their functions) to develop effective, safe medications and doses that will be tailored to a person’s genetic makeup. Pharmacogenetics is the science of determining how genetic variability influences physiological responses to drugs, from absorption and metabolism to pharmacologic action and therapeutic effect.

The field of pharmacogenomics is still in its infancy. In the future, pharmacogenomics will allow the development of tailored drugs to treat a wide range of health problems, including cardiovascular disease, Alzheimer disease, cancer, HIV/AIDS, and asthma. 

- What Pharmacogenomics Testing Does

Pharmacogenomic testing is one tool that can help your health care provider determine the best medication for you. Your health care provider also considers other factors such as your age, lifestyle, other medications you are taking and your overall health when choosing the right treatment for you.

The purpose of pharmacogenomic testing is to find out if a medication is right for you. A small blood or saliva sample can help determine: whether a medication may be an effective treatment for you; what the best dose of a medication is for you; whether you could have serious side effects from a medication. The laboratory looks for changes or variants in one or more genes that can affect your response to certain medications.

Someday, it should be possible for doctors to send individual cancer patients in for a genomic analysis and, based on the results, prescribe the drug they know will be the most effective. While the promise of this kind of personalized medicine is still distant, many researchers worldwide are working on it now, interpreting the genomes of individual cancer patients and searching for clues to how they will respond to various treatments. Pharmacogenomics and a new era of genomic testing will identify and hopefully treat inherited cancer. 

- The Role of Pharmacogenetics in Precision Medicine

Many drugs that are currently available are “one size fits all,” but they don’t work the same way for everyone. Whether used to explain a patient’s response or lack thereof to a treatment, or act as a predictive tool, precision medicine hopes to achieve better treatment outcomes, greater efficacy, minimization of the occurrence of drug toxicities and adverse drug reactions (ADRs). Adverse drug reactions are a significant cause of hospitalizations and deaths in the United States. With the knowledge gained from the human genome project, researchers are learning how inherited differences in genes affect the body’s response to medications. These genetic differences will be used to predict whether a medication will be effective for a particular person and to help prevent adverse drug reactions. Pharmacogenomics testing will play a growing role in guiding medication decisions.

- Precision Vaccines 

Vaccines have been the key to preventing disease outbreaks in the United States, including polio, measles, and whooping cough. Vaccination protects not only our children, but our friends who may be immunocompromised. The field of pharmacogenomics and pharmacogenetics provides a promising science base for vaccine research and development. A broad range of phenotype/genotype data combined with high-throughput genetic sequencing and bioinformatics are increasingly being integrated into this emerging field of vaccinomics.

"Growing realization that vaccine responses vary with an individual’s characteristics including age, sex, and environmental setting. Thus in an era of precision medicine, several emerging approaches and technologies will allow more accurate development of vaccines tailored for distinct populations: In vitro modeling of human immune responses to characterize sub-population-specific responses and identify new adjuvants and adjuvanted vaccine formulations as benchmarked to licensed vaccines. Heterologous/trained immunity: Live attenuated vaccines such as BCG (Mycobacterium bovis) activate multiple PRRs and may have possible beneficial heterologous effects, especially in early life. Use of big data/global molecular/OMIC approaches to characterize molecular signatures corresponding to vaccine correlates of protection." -- [Boston Children's Hospital]


14. Mass Spectrometry in Precision Medicine

- Application of Mass Spectrometry in Pharmaceutical and Biomedical Analysis 

Mass spectrometry, a new tool for precision medicine, is an analytical laboratory technique to separate the components of a sample by their mass and electrical charge. The instrument used in MS is called mass spectrometer. It produces a mass spectrum that plots the mass-to-charge (m/z) ratio of compounds in a mixture. Mass spectrometry is fast becoming an indispensable field for medical professionals. 

The mass spectrometric analysis of metabolites and proteins promises to revolutionize medical research and clinical diagnostics. Mass spectrometry is a powerful analytical tool with many applications in pharmaceutical and biomedical field. The increase in sensitivity and resolution of the instrument has opened new dimensions in analysis of pharmaceuticals and complex metabolites of biological systems. With the tremendous advances of modern mass spectrometry techniques, Mass spectrometry has become one of the essential analytical tools to biological and biomedical research. Mass spectrometry provides rapid and sensitive qualitative and quantitative analysis of biomolecules (proteins, peptides, oligosaccharides, lipids, DNA, and RNA), drugs, and metabolites.

- Mass Spectrometry Data 

The large volume of data produced in a typical mass spectrometry experiment requires that computers be used for data storage and processing. Over the years, different manufacturers of mass spectrometers have developed various proprietary data formats for handling such data which makes it difficult for academic scientists to directly manipulate their data. To address this limitation, several open, XML-based data formats have recently been developed by the Trans-Proteomic Pipeline at the Institute for Systems Biology to facilitate data manipulation and innovation in the public sector. 

- Bringing Precision and Clarity to Precision Medicine

Precision medicine increases the quality of clinical practice and targeted care pathways and ultimately reduces the overall healthcare costs. There is a growing popularity of using clinical mass spectrometers in the development of precision medicine for the early detection of diseases and the selection of accurate treatment methods that can reduce mortality rates. Such developments will drive the growth of the market.

Mass spectrometry, an analytical technology capable of measurements with high levels of reproducibility, precision and accuracy, brings precision and clarity to precision medicine. Mass spectrometry systems are helping biomedical researchers gain deeper insight into the mechanisms of disease progression and therapeutic intervention.

- The Rise in Aging Population Contributing to the Growth of the Global Clinical Mass Spectrometry Market

The use of mass spectrometry can provide an understanding of how a drug is interacting with the patient, and is orthoganol to the information provided by pharmacogenomic assays. Further, the speed and relatively low expense of drug monitoring by mass spectrometry makes it an ideal test for precision medicine patient management.

One of the key factors contributing to the growth of the global clinical mass spectrometry market is the rise in aging population: As the elderly generally have low immunity and metabolism, they need to undergo diagnostic tests such as microbial testing on a regular basis. This results in an increased demand for clinical mass spectrometry that reveals details about the casual microorganisms, based on which, the physician decides the best course of treatment. 


15. Radiology (Imaging) in the Age of Precision Medicine

- Radiology (Imaging) and Imaging-guided Interventions

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. During the last few decades various three-dimensional medical imaging techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound, have become available that allow a physician to see and diagnose disease that is hidden from normal view. Three-dimensional biomedical images are now being used not only for diagnosis, but for planning and conducting treatment strategies and surgeries, a concept referred to as image-guided interventions. Advances in computer technology, coupled with an increase in the accuracy and sensitivity of imaging technologies, will make it possible to seamlessly integrate diagnosis and treatment. Future image-guided interventions will enable medical practitioners to detect critical illnesses at their most curable stage - oftentimes at the cellular level, before any symptoms or signs are noticeable. 

- Characterization of Phenotypes

Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues.

- Radiomics and Imaging Genomics in Precision Medicine 

Imaging plays an important role in the diagnosis and staging of cancer, as well as in radiation treatment planning and evaluation of therapeutic response. Recently, there has been significant interest in extracting quantitative information from clinical standard-of-care images, i.e. radiomics, in order to provide a more comprehensive characterization of image phenotypes of the tumor. 

Radiomics, a field of study in which high-throughput data is extracted and large amounts of advanced quantitative imaging features are analyzed from medical images. A number of studies have demonstrated that a deeper radiomic analysis can reveal novel image features that could provide useful diagnostic, prognostic or predictive information, improving upon currently used imaging metrics such as tumor size and volume. Furthermore, these imaging-derived phenotypes can be linked with genomic data, i.e. radiogenomics, in order to understand their biological underpinnings or further improve the prediction accuracy of clinical outcomes. 

"Imaging genomics, also known as radiogenomics, is a growing field and application area in multi-scale data fusion whereby macroscopic phenotypes from medical imaging are linked with molecular phenotypes. The main idea is to discover imaging biomarkers that can identify the genomics of diseases, especially cancer, without the need for a biospy. This growing field draws from advances in quantitative imaging to increasingly extract more quantitative information from medical images. On the molecular biology side, bioinformatics algorithms are needed to summarize and extract meaningful information out of high dimensional genome wide data." -- (Stanford Medicine)

- How Artificial Intelligence (AI) is Changing Medical Imaging
AI in radiology is in its infancy. AI will completely change how we practice, from ordering exams and checking the appropriateness of an exam to how information is presented on the workstation for us to read and report. It will help us quantify data and make diagnoses. For example, using AI can make MRI scans up to 10 times faster. It may be possible to capture less data using AI, resulting in shorter scans, as well as potentially enhancing the rich information content of MR images. 

Artificial neural networks will be trained to recognize the underlying image structure and fill in the view omitted from the accelerated scan. These images will then be compared to traditional image reconstructions. Medical images can be compressed, which removes data without impacting the image appearance. If we can remove data, why not just under sample and then create the image that we want, In MR we can save time; in CT we can reduce radiation exposure.

AI can guide and inform our decisions by generating new insights from tedious quantification tasks, such as ejection fraction computation in cardiac exams. Of course, AI is also adept at mining complex multi-dimensional data from multiple systems. Imaging-based AI may also prove to be more accurate than genomics in predicting cancer for specific genetic subtypes, as we’ve seen in the fascinating brain imaging research in glioblastoma. Overall, identifying a patient’s risk of disease or preventing catastrophic events using imaging phenotypes will likely have a significant positive impact on a patient’s outcomes.

Current AI can answer specific questions, but it is still a far cry from human intelligence. In the diagnostic world of enterprise imaging, radiologists have been extensively trained to identify disease and are skilled at making efficient predictions, thus limiting the value of AI. In specific cases, AI algorithms could overcome the intrinsic limitations of human perception, such as skin cancer detection, diabetic retinopathy, or difficult-to-discern diseases on chest X-rays. Beyond these instances, the immediate future of AI lies more in aiding medically underserved areas.


16. From Biobanking to Precision Medicine

- The Road to Precision Medicine

The term biobank commonly refers to a large collection of tissue samples (with associated biological and medical data), such as surgical biopsies (fresh frozen or in paraffin sections), blood and serum samples, different cell types, DNA, RNA; all carefully collected for research purposes. The science of biobanking is very broad and covers collections of plant, animal, or human specimens. For the purposes of the precision medicine, we will focus on human biobanks. Since the late 1990s biobanks have become an important resource in medical research, supporting many types of contemporary research like genomics and precision medicine. 

Biobanks are an important compound of precision medicine. They are an essential tool for new drug discoveries and drug development. Biobanks play an important role in the whole process of patient prevention and prediction, follow-up, and therapy monitoring and optimalization. Biobanks have the specificity in that they cover multidisciplinary approach to the human health combining biological and medical approaches, as well as informative bioinformatics technologies, computationing, and modeling. 

- The Classical Biobanks and The Virtual Biobanks

A biobank is a biorepository that accepts, processes, stores and distributes biospecimens and associated data for use in research and clinical care. The field of biobanking has changed tremendously over the past thirty years. It started with small, predominantly university-based repositories that were developed for the research needs of specific projects. There gradually evolved institutional and government supported repositories, commercial (for profit) biorepositories, population based biobanks and most recently, virtual biobanks. 

A virtual biobank is a virtual repository (an online platform), housing 2D and 3D microscopy datasets of valuable clinical biopsy samples, which provides data extracted from and characterizing samples stored at classical biobanks. The recent advance of 3D tissue clearing technology has allowed to produce and display 3D image datasets alongside traditional 2D micrographs used by pathologists and researchers.

Virtual biobanks are large databases and can provide high-resolution images of samples as well as other characteristic data. These virtual biobanks can be accessed via specialized software or web portals. Samples are stored in a decentralized manner. The use of virtual biobanks provides access, in the form of pre-collected data, without requiring access to the physical sample. This allows the sample's data to be more readily shared without fear of contaminating/destroying/transporting the sample. Virtual biobanks are often used in bioinformatics.

- Biobanks in The Era of Precision Medicine

The data associated with stored biospecimens have increased in complexity from basics, such as date of collection and the diagnosis, to extensive information sets encompassing many aspects of participant or patient phenotype, now rapidly extending into genetic, proteomic, and other “omics” information. Data from biological samples combined with information from lifestyle and health questionnaires, medication history, electronic health records, physical exams, and environmental exposures and real time physiology tracked through digital technologies, will help researchers examine individual differences in health and disease.

Biobanks give researchers access to data representing a large number of people. Samples in biobanks and the data derived from those samples can often be used by multiple researchers for cross purpose research studies. For example, many diseases are associated with single-nucleotide polymorphisms, and performing genome-wide association studies using large collections of samples which represent tens or hundreds of thousands of individuals can help to identify disease biomarkers. Many researchers struggled to acquire sufficient samples prior to the advent of biobanks. 

- Ethics in Biobanking

Biobanks have provoked questions on privacy, research ethics and medical ethics. While viewpoints on what constitutes appropriate biobank ethics diverge, consensus has been reached that operating biobanks without establishing carefully considered governing principles and policies could be detrimental to communities that participate in biobank programs. 


17. Main Barriers to Greater Implementation of Precision Medicine

- Precision Medicine Rises, Data Management Still a Barrier 

Precision medicine is a young and growing field. Many of the technologies are in the early stages of development or have not yet been developed. Precision medicine is vital to advancing medicine, and critical to its success is the underlying technology needed to manage the large volumes of data it requires. For example, researchers will need to find ways to standardize the collection of clinic and hospital data from a huge number of volunteers around the country. They will also need to design databases to store large amounts of patient data efficiently. Drugs that are developed to target a person's genetic or molecular characteristics are likely to be expensive, just to name a few. 

- Two Main Barriers: High Costs and Technology Limitation

Currently, there are two main barriers to greater implementation of precision medicine: High costs and technology limitations. Fortunately the cost of sequencing a genome continues to drop year-over-year. Advances in the speed, accuracy, and cost of next-generation gene sequencing making it possible for clinical labs to create thousands of new tests. Artificial Intelligence (AI) can speed up precision medicine. To tackle the vast amount of patient data that must be collected and analyzed, and to help cut down on costs many researchers are implementing machine learning techniques. Today, machine learning is playing an integral role in the evolution of the field of genomics. The potential for AI in precision medicine is big. 


18. The Future of Precision Medicine 

- Potential Impacts for Health Technology Assessment

Precision medicine will dramatically change the health care landscape by improving upon current knowledge of such things as disease progression and drug efficacy. Imagine a world where your disease is immediately treated with a drug, designed uniquely for you, making it incredibly efficient. Even better, imagine a technology which, after inputting the parameters of your body, outputs a prediction and hence prevents a future illness. This is the dream of precision medicine.

The future of precision medicine will enable health care providers to tailor treatment and prevention strategies to people’s unique characteristics, including their genome sequence, microbiome composition, health history, lifestyle, and diet. To get there, we need to incorporate many different types of data, from metabolomics (the chemicals in the body at a certain point in time), the microbiome (the collection of microorganisms in or on the body), and data about the patient collected by health care providers and the patients themselves. Success will require that health data is portable, that it can be easily shared between providers, researchers, and most importantly, patients and research participants. 

Massive and growing databases of gene sequencing data promise long-sought breakthroughs in medicine. How will we balance the pursuit of better health with ethical questions raised by this fast-moving field, from defining acceptable applications to establishing ownership of our genetic data?

- The Challenges + Opportunities Ahead

Though challenging, the benefits to adopting a precision therapy model are readily clear. Precision medicine has the ability to more accurately diagnose disease states, detect the onset of diseases earlier, target treatments, and increase the overall efficiency and effectiveness of the healthcare system. Apart from these direct benefits, precision medicine will have ancillary value by reducing R&D expense, decreasing costs related to ineffective treatment, and enhancing focus on previously unmet disease states.

While significant advances in precision medicine have been made for select cancers, the practice is not currently in use for most diseases. Many efforts are underway to help make precision medicine the norm rather than the exception. The vision holds enormous promise for the future but healthcare still has huge ground to cover when it comes to making precision and personalized medicine an everyday part of primary care.

We can see now that the future of medicine is near and will be mediated through the integration of technologies across multiple disciplines, such as genetics, genomics, big data, and deep learning.


<updated by hhw: 2/17/20>






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