There is robust evidence supporting strong association with CYP450 (Phase 1) enzymes and influence on drug levels (affecting response & side effects in many cases) with many psychotropic antidepressants and antipsychotics. Genetic implementation strategies for Phase-1 enzymes increasingly being adopted globally and genetic tests might become available specifically to predict specific side effects.

Advances in DNA sequencing, based upon massively parallel sequencing, has resulted in dramatic advances in DNA sequence output in the past few years. It is now possible to generate terrabases of accurate DNA sequence with a single run on several DNA sequencing platforms. This has then made it possible to characterize alterations that occur during cancer development. Genomic alterations can be characterized by targeted sequencing of genes that are frequently altered during cancer development, by sequencing of the entire exome, transcriptome sequencing, and even by whole genome sequencing. Each of these has their own inherent strengths and weaknesses. I will describe why I believe that the best strategy moving forward for the management of cancer patients is whole genome sequencing (WGS). This can currently be done reliably and inexpensively on two completing platforms. The first is the Illumina sequencing platform and the second is from BGI. WGS is a comprehensive technology that can detect all the alterations in a cancer genome and I will describe how and why this may prove to be the best approach for the management of cancer patients.

The introduction of targeted therapies into the clinical management of lung adenocarcinoma has had a massive impact on patient care. Multiple driver mutations are now druggable and treatments differ depending on the mutational pattern of each patient with advanced lung adenocarcinoma. Consequently, mutational analysis is critical for treatment decisions in clinical routine practice. While several techniques have been developed and introduced into clinical care over the past few years, next-generation sequencing (NGS) has evolved to become the new standard in molecular diagnostics for most institutions. Thus, the development of targeted sequencing panels, which only cover specific and relevant mutations, make NGS affordable and suitable for high-throughput processing. There is no consensus system for individual sample tracking and the storage of meta information which is therefore required to be set up in each diagnostic laboratory individually. Additionally, setting up a NGS workflow requires well-trained personal, complex workflows and the need for specialized bioinformatics to analyze and interpret the results. Two different sequencing techniques were established initially for NGS in clinics, the Ion Personal Genome Machine (PGM) and Illumina sequencing. While both systems are based on fundamentally different sequencing principles, their purpose for clinical mutation analysis is quite similar. However, both systems require each diagnostic laboratory to develop their own workflow, leading to a plethora of “homebrew” solutions as different devices for sample preparation can be integrated in the respective workflows

QIAGEN developed a novel sequencing system, the GeneReader, specifically designed for the needs of routine molecular diagnostics. In contrast to the existing solutions, the GeneReader system provides a complete workflow from sample preparation to data analysis. This reduced hands-on time during sample preparation, increased sample traceability and reproducibility address many of the issues of “homebrew” NGS solutions. Bioinformatic analysis is well integrated into the workflow and automated to strongly improve the quality and efficacy. The GeneReader can easily be installed and integrated into a routine pathology laboratory. Only limited training of the technical personnel is necessary. The high traceability is a strong advantage for daily routine sequencing and maybe very helpful for easily getting an accreditation according to the ISO 15189 norm. 

Here we will present the main characteristics of the GeneReader NGS system and the potential for using this system in daily practice. We demonstrate the suitability of the GeneReader NGS system in routine in a clinical and molecular pathology laboratory setting.

Finding effective treatments for cancer is fundamentally  a high-dimensional probabilistic planning, search, and optimization problem, characterized by  thousands of molecular subtypes,  tens of thousands of plausible drug regimens, and a dearth of high quality data on clinical responses.  These explosive combinatorics and the lack of data are overwhelming traditional approaches to clinical development, including the latest Bayesian adaptive trial designs and big data analytics.  However, this is precisely the kind of knowledge-based  planning and search problem that AI is uniquely designed to solve.  Many organizations are developing relevant AI-based applications, from decision support and treatment planning to treatment validation and real time response monitoring.  We will review these developments and describe a bold industry-wide initiative to integrate them for the immediate benefit of all cancer patients and their physicians, while radically improving the efficiency of clinical research and drug development. 

Crohn’s disease and ulcerative colitis also known as inflammatory bowel diseases or IBD, are characterized by chronic, recurrent inflammation of the gastrointestinal tract, which results from the interplay between genetic predisposition, altered immune response, intestinal microbial dysbiosis and environmental factors. The course of the disease is variable, with some patients having much more aggressive disease than others. Half of the patients will develop severe complications like strictures, fistulas and abscesses, which require surgery. In addition, some patients experience frequent relapses while others achieve prolonged remission without any additional therapy. Such variability in prognosis represents the difference between an excellent long-term outcome or progressive disability. Therefore, the main challenge in managing IBD is the early detection, ideally at diagnosis, of patients with potentially severe disease course and variability in treatment outcomes. Thus, if precision medicine is to be applied in IBD, it will require the stratification of patients with a high risk of relapse and complications, and better characterization of patients who may respond preferentially to specific therapies. In this presentation I will highlight current advances towards the integration of clinical and molecular phenotypes for early prediction of complicated disease course at diagnosis and response to biological therapy. I will also highlight the current efforts of the Crohn’s and Colitis Foundation to build the largest biorepository and research exchange platform called IBD Plexus, which aims to integrate longitudinal clinical data and patient reported outcomes from than 40,000 patients along with genetic and multi-omics profiles from 7,000 IBD patients, and how this platform will accelerate the path towards precision medicine in IBD.

Rare disease affects 30 million people in the United States, with nearly 50% of cases affecting children. Because nearly 80% of rare diseases are genetic, advancements in genomic testing are key to pinpointing an accurate diagnosis. The Rady Children’s Institute for Genomic Medicine has engineered a Whole Genome Sequencing process to rapidly decode, analyze and interpret the root causes of rare genetic disorders in newborns and children in intensive care in a matter of days. RCIGM president and CEO Stephen Kingsmore, MD, DSc, discusses how his team is working to equip clinicians with this critical information to facilitate medical decision making. 

Regulation of precision medicine is rapidly evolving.  The pre-existing regulatory framework did not contemplate many of the products and technologies which are becoming available with precision medicine.   FDA and other federal agencies have responded by attempting to develop a “flexible and adaptive” approach to regulation which simultaneously encourages innovation while still assuring that new precision medicine drugs and medical devices are safe and effective.
 
FDA has issued a series of non-binding “Guidance Documents” addressing different topics in precision medicine.   While non-binding, these guidance documents explain the Agency’s current thinking on specific issues and should be viewed as recommendations.

FDA in 2017 issued a Guidance Document relating to the use of “Real World Evidence” (RWE) to support regulatory decisions involving medical devices.   RWE represents a potentially faster, less expensive and more useful alternative to traditional randomized clinical trials (RCT’s) for generating data to support regulatory approvals of drugs and devices.  RWE consists of clinical evidence of a product's usage, benefits and risks obtained from an analysis of real-world data sources, such as patient EHR’s, insurance claims data and disease or device registries.  In 2017, FDA approved a new indication for a medical device based entirely on RWE.   

FDA has recently issued Guidance Documents and draft guidances covering many other aspects of precision medicine, including NGS–based tests, genetics variant databases and companion diagnostics.  Additionally, FDA and CMS have developed a parallel review process for devices aimed at allowing developers to concurrently obtain both marketing approval and eligibility for Medicare coverage. 

Many of FDA regulatory guidances have issued within the last 12 months.  It is likely that regulation of precision medicine will continue its evolution for the foreseeable future.

Recent advancements in the precision medicine field have presented a great promise to provide innovative solutions to pharmaceutical and healthcare industry to help transform medicine. By finding integrated solutions to analyze digital health as well as omics data presents a quick and more accurate method of diagnosing and treating diseases. This talk will focus on highlighting recent advancements in the field of precision medicine. Briefly, the importance of big data analytics to make complex biology simpler will be discussed. Of importance, an overview of recent advances in AI field and how we can exploit it to re-shape drug discovery and precision medicine fields will be discussed. Furthermore, how the medical professionals and health care systems are working towards adapting to this changing landscape to bring these breakthrough advances to clinical practice will be highlighted.

The therapeutic applications of medical cannabis and cannabinoid drugs is controversial, however the number of medical conditions in which cannabinoids and cannabis have shown promise as therapeutic treatments is expanding. The occurrence of side effects from cannabinoids is still a concern, especially with the wide variability in drug levels and response that has been observed. This is compounded by possible interactions with prescription drugs. Application of pharmacogenomics (PGx) and knowledge of drug-drug interactions could help patients and doctors navigate the complexities of combining prescription drugs and cannabis compounds. Genetic variants in several drug metabolizing enzymes may impact response to cannabinoids, including CYP3A4, CYP2C9, and CYP2C19. Furthermore, drug interactions caused by cannabinoids may also be mediated by drug metabolizing enzymes (e.g. CYP2C9, CYP2D6, CYP2B6, CYP1A1) and possibly drug transporters such as ABCB1. Understanding how commonly prescribed drugs and cannabinoids interact could help reduce risks associated with polydrug regimens. This presentation will discuss PGx testing for cannabis and potential impacts on commonly prescribed pharmaceuticals.

When the human genome was sequenced almost 15 years ago, it was a milestone for the understanding of an individual’s genome.  However to fully understand a disease, millions of individuals will need to be sequenced. As more patients samples are sequenced around the world, we are on the verge of understanding the genetic basis of disease.  QIAGEN is now a leader in aggregating the world’s knowledge of genetic diseases.  We have been manually curating genetic evidence for the past 20 years and have partnered with clinical testing labs throughout the world to bring knowledge of variants across all human genes (>23,000).  With the experience of having interpreted over 750,000 human samples, QIAGEN’s knowledgebase is the most comprehensive genetic knowledgebase in the world. This deep knowledge is able to quickly supply clinical evidence for rapid interpretation of NGS data as well as reduce the number of variants of unknown significance in NGS interpretation.

With prospective clinical sequencing of tumors emerging as a mainstay in cancer care, there is an urgent need for clinical support tools that aid clinicians in their decision making. To this end, we are developing tools for the visualization and interpretation of genomic variants in the context of clinical annotation. 

To this end, we have developed OncoKB, a precision oncology knowledge base that annotates the effects and treatment implications of somatic mutations in cancer. OncoKB annotations are available for research use via oncokb.org, and the database is used to annotate the sequencing reports of of tumor samples from patients at Memorial Sloan Kettering Cancer Center. 

We are also co-developers of the cBioPortal for Cancer Genomics. The cBioPortal is an open source software tool that provides intuitive visualization and analysis of cancer genomics data, allowing cross-cohort analyses but also the viewing and interpretation of individual tumor samples. The public site at cbioportal.org provides access to published sequencing data from more than 25,000 tumor samples, and private instances of cBioPortal are installed at multiple academic research centers, in hospitals, and pharmaceutical companies. Annotations from OncoKB as well as other sources, such as COSMIC, CIViC, and cancerhotspots.org, are integrated into cBioPortal to facilitate the interpretation of variants in cancer cohorts and individual patient samples.

This presentation will summarize the challenges of precision oncology and cancer genomics research and will present how OncoKB and the cBioPortal for Cancer Genomics can be used to overcome some of these challenges.

Precision medicine based on molecular profiling is moving from the realm of clinical utility studies towards standard of care. There remain, however, significant technological and implementation challenges that need to be addressed to ensure the widespread access to high complexity tests. These challenges include the provision of high quality, scalable assays that can be offered in clinically meaningful timeframes and at a cost that does not limit adoption. In addition, the computational and analytical environments must exist to host, compute, and deliver the increasingly large data sets created for each patient. There needs to be agreement on best practices and specifications for performance of secondary analysis tools (variant callers) across all classes of clinically meaningful variant categories. And, there needs to be education and training of a large network of variant review scientists, clinical geneticists, and molecular pathologists on variant interpretation and classification. This presentation will contemplate these challenges, highlight areas where progress has been made, and where more has yet to be done. 

Precision medicine and next-generation sequencing – Two terms characterized by a highly dynamic nature, strong innovations and a bright future. Both merged together will exert a decisive influence on academia, industry and the clinical environment. However, both are still facing several challenges and to do’s, which will need to be addressed in order to receive a standard status in the healthcare sector. Beginning with general problems like physicians awareness, novel clinical study designs as well as refunding policies and regulatory issues, the NGS upstream pipeline exhibits additional pitfalls such as quality of FFPE samples, missing standards and restrictive guidelines as well as biomarker validation and certification concerns. The data landscape represents an adjunct construction site, covering questions about the implementation of quality assured data, possible benchmarks, SOP’s, minimum requirements for quality metrics and final data storage considerations. The presentation will shine a light on those obstacles and will provide suggestions on how to possibly overcome them in order to pave the way for reliable, traceable and reproducible results within a standardized environment.