Healthcare is becoming more proactive and data-rich than anything before possible – and will increasingly focus on maintaining and enhancing wellness more than just reacting to disease. Lee Hood and I have recently launched a large-scale data-rich wellness project that integrates genomics, proteomics, metabolomics, microbiomes, clinical chemistries and wearable devices of the quantified self to monitor wellness and disease. The resulting dense, dynamic personal data clouds enable the creation of a field we term Scientific Wellness that aims to help individuals take informed actions to enhance their wellness and help reduce their risk for disease. Analyses of these data — individually and in aggregate — will enable us to identify scientifically-validated metrics for wellness, see early warning signs of disease, and develop approaches to reverse disease in its early stages (such as can currently be done for e.g. pre-diabetes). I will present results from our proof-of-concept pilot study in a set of 108 individuals (the Pioneer 100 study), showing how the interpretation of these data led to actionable findings for individuals to improve health and reduce risk drivers of disease — and well as give big picture views of how this endeavor relates to the future of health.

Cell growth and regulation involve vast networks of interacting DNAs, RNAs, proteins, lipids and sugars. Through a fundamental strategy of life, these interactions push multiple cellular processes by increasing local concentrations of key molecules. Now scientists can exploit these interactions with a new type of precision therapy called the Extracellular Drug Conjugate (EDC).

EDCs are a new type of ADC that use proximity to activate the drug’s potential. In the case of EDCs, a drugs activity is increased by over 1000-fold if both targets (antibody and drug) are within angstroms apart (i.e. they interact).   This talk will discuss how EDCs can exhibit low to mid-picomolar potencies, and with signal to noise ratios of > 1,000:1; both of which are dependent on the expression and interaction of two proteins.

Specifically, this talk will focus on proteins that interact with the human Na,K-ATPase (NKA). An active plasma membrane ion pump, the NKA is required for life. Without it, the cell cannot maintain a proper ion potential and the cells dies by a natural death process known as necrosis. You will learn about; 1) how a small naturally occurring steroid can be delivered to specific cell types and how this delivery can affect cell growth and cytokine production, 2) how this knowledge can be exploited in precision medicine, and 3) how a blockbuster antibody medicine can be constructed to kill B-cells while having no effect on other blood cells. This talk will therefore describe a new level of therapeutic precision that depends on protein-protein proximity and not simply the expression of a single protein.

In this era of precision molecular medicine, knowledge changes rapidly and is highly dispersed.  Physicians and patients are faced with conflicting expert opinions and a shortage of actionable data, buried within a tsunami of literature.  Patient outcomes and quality of life vary widely across physicians and institutions, often falling off dramatically from elite institutions to rural and disadvantaged communities, as well as in developing countries.

Not only do individual physicians not know the optimal way to treat any complex case; they don’t even how to find this out.  Advanced cancers are characterized by thousands of molecular aberrations, potentially creating tens of thousands of clinically distinct subtypes. Moreover, there are hundreds of approved therapies, which have never been tested head to head, or in combinations. Current clinical trial designs, including contemporary “adaptive” Bayesian designs, cannot efficiently search this huge combinatorial space, especially given the limited number of cancer patients.

In the absence of definitive clinical studies, the best way to help current patients achieve better outcomes is by aggregating and validating the insights, intuitions, and experiences of our best clinicians.  Every day, thousands of patients who have exhausted the standard of care are treated with off-label drugs and cocktails. These treatment decisions are based largely on the judgments and experience of individual physicians, but the results are seldom reported, so nothing is learned. Cancer Commons is building a platform that will coordinate these thousands of ad hoc “N of 1” experiments, capture their results, and rapidly share them.  Our goal is to transform the everyday practice of oncology into a global adaptive search for better treatments and cures.  Given the wide variation in treatment and outcomes, we are convinced that getting the right knowledge to the right patient and the right physician at the right time will save many lives.

Learning Objective 1: How to capture, validate and share the knowledge generated from the thousands of N-of-1 experiments that take place daily in oncology practices, far faster than journals and conferences.

Learning Objectives 2: How to coordinate these experiments across all patients and treatments to search for optimal combination therapies and regimens far more efficiently than clinical trials.  

Despite vast investment for decades in cancer research and development, cancer is still among the leading causes of death worldwide and its toll is expected to rise by about 70% over the next two decades. There are many aspects of cancer, including its complexity, diversity, and dynamic nature, which call for a radical change in the way we approach cancer study and management. For instance, the genetic profile of tumors affects patient tumor response while the tumor microenvironment plays a critical role in cancer development, progression, and control. Due to intra-tumoral heterogeneity, cancer cells extracted from the same tumor of a patient may be genetically heterogeneous. Tumor/host immune interactions influences disease outcome by altering the balance of suppressive versus cytotoxic responses in the vicinity of the tumor. In addition, biopsies often suffer from sample bias, and tumor sampling from some cancer types still remains difficult resulting in insufficient amount of tissue for genetic testing. Considering the high tumor heterogeneity from individual patients, it is increasingly recognized that a personalized medicine approach would help identifying the optimal treatment regimen for an individual patient, calibrated on his/her specific cancer signature, reducing toxicity from overtreatment and increasing efficacy of therapy.

However, in order to pursue personalized approaches, novel approaches capable of improving the care of cancer patients through earlier detection, better therapy monitoring, new drug development and rational treatment planning are urgently needed.

One of the challenges of personalized medicine is related to the so-called liquid biopsy, that is the extraction of circulating tumor cells (CTC) and cell-free or circulating tumor DNA (ctDNA) from peripheral blood, which is expected to revolutionize the way in which cancer care works nowadays, by providing easy and repeatable access to tumor biological material, and consequently to the information about disease state, prognosis and chemo-sensitivity contained in it. On the other hand, also because of the epithelial-to-mesenchymal transition, not much is known at present about how the peripheral blood samples the tumor material, adding urgency to the type of study discussed above. Another challenge of personalized medicine is represented by the assembly of suitable in vitro tumor models capable of predicting the response to specific chemotherapeutic agents for each patient. I will present to you today a new method to recognize, count, sort and analyze CTCs.

Clinical whole genome sequencing (cWGS) is rapidly gaining acceptance as cost is decreasing and success rates in identifying disease-causing variants are increasing. While the application of genomics in healthcare has historically centered around diagnosis of disease, the desire to apply genomics to risk assessment and disease prevention is growing. In the context of an educational program called Understand Your Genome, Illumina has offered cWGS in an ostensibly healthy population since 2012. To date, more than 1300 adults have been sequenced as part of this program, which has generated data about the motivations of this population, what medical findings can be seen in a generally healthy adult population and the value of genome sequencing over time. 

Learning Objective 1: Analyze the benefits of sequencing a healthy population, for the individual and for the contribution to genomics knowledge

Learning Objective 2: Identify the frequency of findings expected to be of clinical significance in a healthy adult

Abstract Coming Soon

Although there have been enormous advances in gene sequencing, the results give massive amounts of data that only point to disease risk. Major health factors, including diet, lifestyle, environment and genes, exert their influence by subtly changing our metabolic composition. Metabolomics provides a snapshot of the current state of health and provides new information to help with immediate clinical decision-making. 

Advances in metabolomics have made it a valuable first-line tool for assessing health. It can be used to identify perturbations of metabolic pathways associated with many diseases and quickly screen patients for health or disease status. In this session, we’ll discuss the technology and how it is guiding precision medicine today and its role in the future.

Psychiatric disorders are among the leading causes of disability worldwide. One fifth of the population will suffer from a psychiatric disorder in their lifetime. Antipsychotic and antidepressant drugs remain the cornerstone of treatment in schizophrenia and mood disorders. However, more than 50% of patients do not respond well to their initial treatment and much time is often spent until the right medication is found for the right patient.  In addition, some develop serious side-effects that cause them to discontinue the medication. Thus, predictive tools would be of enormous help to optimize and personalize medication treatment.

Genomics offer a tremendous opportunity to personalize medication treatment by use of preemptive genotyping selected genes known to be involved in drug metabolism, neurotransmission and occurrence of side effects. Over the past decade, evidence has emerged that assessing gene variants for drug metabolizing enzymes such CYP2D6 or CYP2C19   can be used to improve treatment with antidepressant and antipsychotics. In addition, various gene variants have been identified involved in psychotropic medication induced side effects such ads for carbamazepine-induced Steven-Johnsons Syndrome or antipsychotic-induced weight gain.

The presentation will review current recommendations provided by expert panels such as the Clinical Pharmacogenomics Implementation Consortium (CPIC) and regulatory agencies (e.g., FDA). Data from our own research studies in Toronto including more than 7,000 patients will be presented showing acceptance and benefits of genetic testing in clinical practice. In addition, implementation strategies and cost-benefits will be reviewed, and commercially available test kits will be critically discussed.    

Learning Objective 1:  Understanding principles of how genetics influences response and side effects in psychopharmacology      

Learning Objective 2:  Application of pharmacogenetics in clinical practice 

Best practices for developing precision medicine diagnostics can include completing a retrospective analysis.  Obtaining enough samples to have a statistically significant study typically requires going beyond an initial institution.  There are a multitude of impediments that can frustrate the ability to rapidly identify and obtain samples.  This presentation will review these impediments by segmenting institutions into three segments: major academic medical centers, biobanks, community practices and mid-tier cancer centers.  Within each of these segments, the presentation will discuss the typical impediments.  The presentation will close with some recommendations for improving the process for both requestors and providers.      

Liquid Biopsies are gaining acceptance in the Oncology community as a surrogate or complement to the gold standard of tissue biopsy.  A liquid biopsy provides biomarker information that a physician needs to understand in order to choose the best therapy for a patient. 

Biocept is a San Diego, CA based company with cutting edge cancer diagnostics developed to capture and analyze circulating tumor cells (CTCs) as well as cell-free circulating tumor DNA (CtDNA).   The company has 18 patents issued on it’s proprietary technology that it uses to perform testing on patient samples through it’s CLIA and CAP accredited laboratory. 

The company has validated 13 assays and currently markets these tests worldwide. 

The talk will explain the company’s offerings in detail and also cover key points about the very large opportunity to help patients through liquid biopsy. 

Learning Objective 1:Reasons why physicians use liquid biopsy today and where the uses are trending for the future

Learning Objective 2:Biocept technology overview for both CTC and CTDNA capture and biomarker analysis

Learning Objective 3:Validation results for Biocept Target Selector Assays

Learning Objective 4: Partners for clinical validation along with publications, poster and abstract overview

Biobanks are a powerful resource in the advancement of precision medicine, and integrating large scale genomics data across Biobank cohorts offer opportunities to further enhance and expedite clinical translation research. In this presentation, we will discuss different genomics/transcriptomics technologies and platforms that could be implemented in a Biobank setting based on our experience and strategy at the Partners HealthCare Biobank. In addition, we will look at ways that wet bench and data analysis workflows can be integrated into existing Biobank and laboratory infrastructure. Finally, I will share strategies to provide researchers with accessibility and efficient use of genomics Biobank data implemented at our institution.

Learning Objective 1: Describe different genomics platforms and technologies that could be leveraged in DNA/plasma/serum Biobanks

Learning Objective 2: Explore strategies that allow easier integration of genomics data into existing infrastructure and that promote accessibility of data to researchers.

In this talk, I will use examples from my research using big data analytics to define ideals of precision medicine and digital health across a variety of diseases. Specifically, I will introduce the audience to my work in large-scale population-wide analysis with public and private data sources, and my work on using mobile technology and digital health to foster these two ideals and improve patient care.

Challenges in achieving comparability, reproducibility and accuracy in biological assays has driven a demand for improved confidence in measurements that support development of regenerative medicine therapies.  There have been extensive discussions about the inability to reproduce biological research findings and two surveys of industry stakeholders have found that product consistency and lack of standards may be the single greatest challenge facing the field of regenerative medicine [1,2].  There are many strategies for achieving measurement assurance, such as reference materials, inter-laboratory testing and standard test methods.  However, there are challenges in applying these strategies to complex biological measurements which will require critical thinking to unravel.  

Learning Objective 1: Understand the concept of measurement assurance.

Learning Objective 2: Learn key measurement definitions: measurand, uncertainty, reference material, inter-laboratory comparability study.

Learning Objective 3: Learn strategies to achieve measurement assurance.

Much has been made in the popular press about importance of our "genes" in everything from our weight, intelligence, and our risk of disease.  While there is a scientific basis for many of these claims, the truth is generally far more nuanced and the medical implications far less obvious than the headlines, or even the back page story details, tend to acknowledge.  This holds true for the genetics of drug response.  That is, how our genes impact how well we respond to a particular drug, or how likely we are to have an adverse outcome.  In this presentation, we will delve into some of the science underlying these claims and hopefully come away with a clearer idea of the role, revealed to date, that genetics plays and potential implications for medical care.

Learning Objective 1: Learn how we study the effect of genetics on drug response

Learning Objective 2: Understand the role that genetics has been shown to have on drug response

Learning Objective 3: Learn how genetic studies of drug response are expected to change

Gastrointestinal (GI) disorders are now widely recognized as a clinical symptom of autism spectrum disorder (ASD), and research into the microbiome-gut-brain axis is beginning to reveal the interconnectivity between GI pain and potential behavioral challenges. Emerging data on the gut microbiome in ASD has also suggested that altered host-microbe interactions may contribute to disease symptoms. Here, we will discuss the history of the relationship between the microbiome and ASD, including more recent publications that have identified distinct microbiome-neuroimmune signatures in ASD as well as demonstrated the potential efficacy of fecal microbiota transplantation. While in-depth studies of the gut microbiome in ASD that are underway will generate the critical mass of data needed as a comparison dataset, a case study will be presented to illustrate the benefit of longitudinal sampling of a single patient in parallel with collection of clinical metadata (behavioral, gastrointestinal, and dietary).

Learning Objective 1: Explain the potential role of the gut-brain axis in ASD

Learning Objective 2: Describe how changes in the microbiome correlate with changes in behavior

Learning Objective 3: Identify diagnostic and therapeutic potential of microbiome characterization and microbial manipulation

Launched in early 2015, the Precision Medicine Initiative (PMI) takes advantage of the progress made in genomic testing – progress largely driven by rapid advances in DNA sequencing technology - to accelerate the development of new treatments that are designed specifically to meet patients’ individual characteristics, including their genetic makeup. In support of the PMI, FDA has been adapting its regulatory authorities for genomic tests in ways that both encourage innovation and ensure that these tests provide accurate and useful results. While current regulatory approaches are appropriate for conventional diagnostics that measure a limited number of substances associated with a disease or condition, such as blood glucose or cholesterol levels, new next generation sequencing (NGS)-based tests can rapidly characterize an entire human genome and identify millions of genetic variations at a time. Thus these tests require an oversight that is adapted to their unique nature.  We will discuss the dynamic, flexible approach that FDA has proposed for oversight of NGS-based tests, which seeks to protect public health, while driving innovation.

Learning objective 1: Understand FDA’s proposed community developed standards-based approach to demonstrating a tests analytical validity.

Learning objective 2: Learn about FDA’s proposed approach to recognizing genetic databases.

Learning objective 3: Understand how FDA is supporting the development of bioinformatics approaches for NGS by the community

Abstract Coming Soon

The starting point for an interaction between a patient and a clinician is almost always a set of clinical facts (aka a phenotype). Phenotype-first medicine is the standard way in which the practice of medicine has traditionally proceeded. In fact, phenotype-first medicine has been the routine approach applied to genetics in medicine. For example, when a woman with a strong family history of breast or ovarian cancer is evaluated, and the potential use of DNA sequencing of the BRCA1 and BRCA2 genes is considered, it is the clinical fact that drives the decision of whether or not to obtain that genomic sequence information. GenomeFIRST™ Medicine (a subset of precision medicine) turns this process around by building systems that can be activated before "the problem" arises. This is care that is based on an individual's DNA sequence and it will be applied in some important settings without waiting for the emergence of a clinical phenotype. Our GenomeFIRST™ Medicine program takes a comprehensive approach to care that includes:

1. Genomic screening.
2. Interpretation of DNA sequence variants.
3. Communication of interpretations to patients and providers.
4. Support of patients and providers in the process of translating and clinically managing these results.

This 21^st Century medicine approach takes advantage of new DNA-sequencing technologies that are making DNA testing more accurate, less expensive and faster. We believe that this change will quickly lead us to a time when most of us will have our genome sequenced and available to inform our care.

GenomeFIRST™ Medicine is rooted in a learning healthcare system approach (as defined by the Institute of Medicine) that is focused on "...the collaborative healthcare choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety and value in healthcare."

Recent advances in DNA sequencing have now made it possible to characterize genomes, transcriptomes and even methylomes which is transforming both basic research and clinical practice. Whole genome sequencing (WGS) is a powerful tool to analyze molecular alterations that occur during the development of cancer, but there are a number of challenges to using WGS as a clinical tool. A practical alternative to WGS is the utilization of mate-pair next generation sequencing (MP-Seq) which can be done for a fraction of the cost of WGS. We have been using MP-Seq to characterize the different roles that human papillomavirus (HPV) plays in the development of different cancers. The cancer that we have been studying is oropharyngeal squamous cell carcinoma (OPSCC) as this cancer is increasingly caused by infection with HPV and there has been an epidemic increase in the incidence of this cancer. We utilized MP-Seq to analyze a group of HPV-positive OPSCCs. What we have found is that HPV is integrated into the genome of OPSCCs in only 30% of these cancers, which is quite distinct from what is observed in cervical cancer. In addition, we have found that the highly unstable common fragile sites and the large genes contained within these regions are hot-spots both for viral integrations and for other alterations in these cancers. Several large common fragile site genes are consistently altered in these cancers. MP-Seq can also determine genome-wide molecular alterations and these alterations can be utilized as cancer-specific markers for the detection of circulating tumor-free DNA from the blood of these patients. This could provide a powerful tool for the development of the liquid biopsy to monitor cancer-treatment of these patients. We will discuss how MP-Seq could thus become a powerful clinical tool for the characterization of genomic alterations in cancer and the development of the liquid biopsy.

Learning Objective 1: Understand how MP-Seq can provide important information about genomic alterations in cancer

Learning Objective 2: Learn about how HPV is involved in the development of different cancers

Learning Objective 3: Learn about how MP-Seq can be a powerful tool to aid in the development of the liquid biopsy