Dr. Ahmed’s lab at UConn Health is focused on doing research and development of intelligent big data analytics platforms to improve the quality and transition of healthcare for investigating heterogeneous clinical data to obtain actionable care gap-based information about patients for early detection and prevention of constitutional disorders and cancer, and developing efficient communication across healthcare units and scientific labs. Dr. Ahmed proposes PROMIS-Med; an advanced academic solution with effective, integrative and analytic access to clinical. Read his full bio.

Interview with Zeeshan Ahmed of UConn Health

Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future?

A: I personally believe that this question is little unfair, why we need to think that will machines replace physicians? Instead, we should think that how machines can play a vital role in improving the practice transformation by helping physicians. So far technology has been very effective and helpful, and looking at its progress, we can predict its bright future in natural and medical sciences.

Q: What are your thoughts?

A: Intelligent, innovative, smart and robust big data platforms are necessary to improve the quality and transition of healthcare by analyzing heterogeneous healthcare and OMICS data. To effectively meet the goals of healthcare data analytics, significant efforts are required from the experts in multidisciplinary sciences, located within one or multiple organizational units. One of the major unsolved challenges is to establish an efficient and secure workflow that can connect all internal and external organizational units, people, and systems to streamline transparent and reproducible data flow, quality inspection, integration, management, analysis, visualization, reporting, and sharing. AI and Data science can play a vital role in confluence of these modules, which will create space for a new era of open data and discovery in public healthcare.

Q: Can you provide some use cases that have already successfully demonstrate the value of AI/Machine Learning in healthcare?

A: There are many in-house, external academic, industrial and collaborative examples demonstrating potential benefits and strengths of AI and Data Science in healthcare. Talking about the institution, I am associated with; UConn Health is actively working at various subjects, which includes development of intelligent healthcare data analytic systems to combine clinical and genetic data from patients with information from scientific research, and apply AI techniques to identify patients at risks. UConn Health has also recently developed remote patient monitoring iPhone app to help patients suffering with heart failure, which in particular requires daily monitoring of many health parameters to enable management success and avoid decompensation and hospitalizations.

Highlighting worldwide efforts e.g., researchers at the University of Pennsylvania Health System have developed a machine learning tool that helps predict patients at highest risk for developing severe sepsis; Harvard and UPenn researchers are using AI to predict mortality for cancer patients; Microsoft and Cleveland Clinic collaborated and used Cortana to identify potential at-risk patients under ICU care; UCLA researchers presented Virtual Interventional Radiologist (VIR) to automatically communicate with referring clinicians; researchers at the University of Cambridge have developed an AI ‘robot scientist’ called Eve, which is designed to make the process of drug discovery faster and more economical; Arthritis Virtual Assistant developed by IBM to learn through interactions with patients and advice concerning medicines, diet, and exercise; and many other bioinformatics tools have been developed for the management and analysis of data leading to chronic medical conditions.

Q: What areas in healthcare will benefit the most from AI/Machine Learning applications and when will that be?

A: Healthcare data includes information about patient life style, medical history, visits to the practice, lab tests, imaging tests, diagnoses, medications, surgical procedures, consulted providers, claims, and OMICS profiles. Theoretically, almost every aspect of healthcare could benefit from Machine learning and Data Science applications e.g., intelligently analyzing healthcare data to predict and identify infection patterns to highlight patients at risk; mining biomedical images to predict cancer and many other serious diseases; developing decision support systems to improve clinical decision making process; implementing smart devices for monitoring, communicating, and helping patients; managing big data quality, analytic and integrity issues; and additionally, contributing in regeneration of artificial tissues and organs etc.

Q: What are some of the challenges to realize AI/Machine learning in healthcare?

A: Some of the neediest areas for AI include implementation of predictive analytics in clinical decision support systems and precision medicine; quick and comprehensive recognition of shifts and patterns in medical imaging data; efficient analysis of Echocardiography scans to detect patterns of heartbeats and diagnose coronary heart disease; and AI robots to efficiently carry out specific tasks in keyhole surgeries etc.

Q: What are the products and/or services UConn Health offers/develops in the AI/Machine Learning sector? What makes UConn Health unique?

A: UConn Health is a vibrant, integrated academic medical center that is entering an era of unprecedented growth in all three areas of its mission: academics, research, and clinical care.
It will be very broad and at large scaled to talk about UConn Health in detail, instead, I would like to draw focus on my lab at the Department of Genetics and Genome Sciences.

Ahmed lab is involved in the research and development of various bioinformatics, healthcare and genomics projects implementing Data Science and AI. However, its major focus is Precision Medicine and recently, we have proposed an innovatively designed big data platform i.e. Precise & Reproducible OMICS-Data Management and Integrative System for Precision Medicine (PROMIS-Med); an advanced academic solution with effective, integrative and analytic access to clinical, epidemiological, metabolomics, proteomics and genomics data of huge volume, velocity, variety, and veracity, and with the potential to advance the field of medicine with best strategies to diagnose and treat patients, and developing better understanding of biology. Aims include the development of one of the world’s largest precision medicine platforms to help patients, providers, practices and scientists.

Q: What are the short-term challenges that Ahmed Lab, at UConn Health and its peers are facing?

A: Doing research is all about finding and addressing challenges, now whether those are scientific, medical, methodological, computational, economical, data or resource oriented. Short-term challenges at my lab includes the allocation of resources for the efficient management, analysis and sharing of healthcare and OMICS data, and its increasing volume. Furthermore, we are actively looking forward to excellent in-house and worldwide collaborations, and funding opportunities.

Q: What is your role at UConn Health and what excites you about your work?

A: I am associated as an Assistant Professor and Assistant Director Bioinformatics: Medical Dean’s Precision Medicine Program at the Department of Genetics and Genome Sciences, School of Medicine, University of Connecticut Health Center (UConn Health), Farmington, CT, USA. I am playing different roles at UConn Health, which include: teaching and mentoring residents, fellows, staff and students; leading different clinical operational and research oriented projects; participating in direct and collaborative grant writing and publications; implementing HIPAA compliant healthcare data analytics platforms; planning development aspects required for Health IT systems including translation engine, data abstraction tools, data warehouse, data marts, analytic tools and healthcare data transport systems, as appropriate for the projects.

I feel excited in establishing my lab at UConn Health with focus on doing research and development of intelligent big data analytics platforms to improve the quality and transition of healthcare for investigating heterogeneous clinical data to obtain actionable care gap-based information about patients for early detection and prevention of constitutional disorders and cancer, and developing efficient communication across healthcare units and scientific labs. Playing my roles and establishing my lab, here, I would like to mention and sincerely acknowledge the strong support and guidance of Prof. Dr. Bruce Liang; Dean UConn School of Medicine, UConn Health. I am grateful to my department’s chair, Prof. Dr. Brenton Graveley, collaborators: Prof. Dr. Anthony Vella and Prof Dr. Melinda Sanders at UConn Health, Dr. Saman Zeeshan at The Jackson Laboratory, and Prof. Dr. Thomas Dandekar at the University of Wuerzburg, Germany.

Q: Is there anything else you would like to share with the PMWC audience?

A: Over a decade ago, earlier joining the fields of bioinformatics and healthcare data analytics, during one of my interviews for first job, I was asked a question that “why you decided to join the field of Computer Science?”, and I answered “because it’s in all fields of life, and I will enjoy working with increasing interests”. I feel proud for being part of it and glad to see the progress of AI and Data Science, when serving the field of medicine for benefiting humanity and saving lives.

Interview with Joe Zhang of Burning Rock Dx

Q: Genomic medicine is entering more hospitals and bringing with it non-invasive technology that can be used to better target and treat diseases. What are some key milestones that contributed to this trend?

A: The milestones in my mind include the first FDA clearance of Next Gen Sequencing instrument, MiSeqDx in 2013, this opened a new door for clinical utilization of parallel gene alteration detection in clinical setting.

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Interview with Kara Davis of Stanford

Q: The Nobel Price in Medicine was awarded recently to James Allison and Tasuku for their work on unleashing the body’s immune system to attack cancer, a breakthrough that has led to an entirely new class of drugs and brought lasting remissions to many patients who had run out of options. The Nobel committee hailed their accomplishments as establishing “an entirely new principle for cancer therapy.” What is your first-hand experience the impact that those new drugs had on patients?

A: These immune checkpoint inhibitors have been an incredible demonstration of the ability of the immune system to control and in some cases.

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Interview with Shannon J. McCall of Duke University

Q: Genomic medicine is entering more hospitals and bringing with it non-invasive technology that can be used to better target and treat diseases. What are some key milestones that contributed to this trend?

A: After several years of the promise of precision medicine and abundant clinical trial work, the recent FDA approval of solid-tumor-agnostic therapies dependent on molecular biomarkers has catapulted genomic/precision medicine into the standard-of-care for late stage cancer.

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Interview with Tao Chen of Paragon Genomics, Inc.

Q: Once sequencing has been validated as a clinical solution via trusted workflows, and coinciding with the technological developments driving costs lower, we can expect accelerated human genome profiling for clinical Dx. How soon, do you think, will we see accelerated growth and what can we expect?

A: For whole genome sequencing to be a reliable clinical tool, it will largely depend on the cost of sequencing the genome and our ability to interpret the data.

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Interview with Andrew Magis of Arivale

Q: Once sequencing has been validated as a clinical solution via trusted workflows, and coinciding with the technological developments driving costs lower, we can expect accelerated human genome profiling. How soon, do you think, will we see what kind of accelerated growth?

A: I think the acceleration has already begun. Large sequencing projects such as NHLBI Trans-omics for Precision Medicine (TOPMed) and NIH All of Us are sequencing 150,000 and 1 million individuals, respectively.

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Interview with Emily Leproust of Twist Bioscience

Q: NGS is enhancing patient care through improved diagnostic sensitivity and more precise therapeutic targeting. Prominent examples include cystic fibrosis and cancer. What other clinical areas NGS will most likely to change the standard-of-care in the near future?

A: Preventative medicine – using genetic data to identify traits that have the potential to cause harm in the future.

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Interview with Michael Phelps of UCLA

Q: You invented the PET scanner that changed the lives of millions of patients with cancer, brain and heart diseases. What are the potential benefits to patients of combining PET with radio-ablation technologies?

A: PET provides imaging assays of the biology of disease in many diseases today.

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Interview with Daniela Ushizima of Lawrence Berkeley National Lab

Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future? What are your thoughts?

A: I really hope that human physicians will not be replaced by machines in the foreseeable future.

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Interview with Amy Compton-Phillips of Providence St. Joseph Health

Q: Genomic medicine is entering more hospitals and bringing with it non-invasive technology that can be used to better target and treat diseases. What are some key milestones that contributed to this trend? What technological advancements are driving this change?

A: Genomic medicine is poised to move quickly from the research realm into integration with healthcare delivery, but there is always a time lapse between technology advances and what we do with those advances.

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Interview with James Taylor of Precision NanoSystems

Q: There are various new, emerging technologies that bring us closer towards a cure for life-threatening disorders such as cancer, HIV, or Huntington’s disease. Prominent examples include the popular gene editing tool CRISPR or new and improved cell and gene therapies. By when can we expect these new technologies being part of routine clinical care?

A: Patients are already receiving treatment using novel gene and cell therapies.

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Interview with Julie Eggington of Center for Genomic Interpretation

Q: Together with Robert Burton you founded the Center for Genomic Interpretation (CGI), a non-profit organization. Can you tell us more about CGI and the mission behind it?

A: CGI’s mission is to drive quality in clinical genetics and genomics. CGI works primarily with laboratories, health insurance payers, clinicians, and patients/consumers.

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Interview with Deven McGraw of Ciitizen

Q: Patient healthcare data aggregation and analysis is seen as both the panacea for tremendous breakthroughs in precision medicine and as one of its biggest challenges. Are both true and how so?

A:Yes, both are true. Achieving breakthroughs in precision medicine will require a lot of data – and yet it is often difficult for researchers to amass all of the data needed to advance precision medicine discoveries.

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Johns Hopkins
University Of Michigan

The Precision Medicine World Conference (PMWC), in its 16th installment, will take place in the Santa Clara Convention Center (Silicon Valley) on January 20-23, 2019. The program will traverse innovative technologies, thriving initiatives, and clinical case studies that enable the translation of precision medicine into direct improvements in health care. Conference attendees will have an opportunity to learn first-hand about the latest developments and advancements in precision medicine and cutting-edge new strategies and solutions that are changing how patients are treated.

Agenda highlights:

  • Five tracks will showcase sessions on the latest advancements in precision medicine which include, but are not limited to:
    • AI & Data Science Showcase
    • Clinical & Research Tools Showcase
    • Clinical Dx Showcase
    • Creating Clinical Value with Liquid Biopsy ctDNA, etc.
    • Digital Health/Health and Wellness
    • Digital Phenotyping
    • Diversity in Precision Medicine
    • Drug Development (PPPs)
    • Early Days of Life Sequencing
    • Emerging Technologies in PM
    • Emerging Therapeutic Showcase
    • FDA Efforts to Accelerate PM
    • Gene Editing
    • Genomic Profiling Showcase
    • Immunotherapy Sessions & Showcase
    • Implementation into Health Care Delivery
    • Large Scale Bio-data Resources to Support Drug Development (PPPs)
    • Microbial Profiling Showcase
    • Microbiome
    • Neoantigens
    • Next-Gen. Workforce of PM
    • Non-Clinical Services Showcase
    • Pharmacogenomics
    • Point-of Care Dx Platform
    • Precision Public Health
    • Rare Disease Diagnosis
    • Resilience
    • Robust Clinical Decision Support Tools
    • Wellness and Aging Showcase

Agenda highlights:

    • Five tracks will showcase sessions on the latest advancements in precision medicine which include, but are not limited to:
      • AI & Data Science Showcase
      • Clinical & Research Tools Showcase
      • Clinical Dx Showcase
      • Creating Clinical Value with Liquid Biopsy ctDNA, etc.
      • Digital Health/Health and Wellness
      • Digital Phenotyping
      • Diversity in Precision Medicine
      • Drug Development (PPPs)
      • Early Days of Life Sequencing
      • Emerging Technologies in PM
      • Emerging Therapeutic Showcase
      • FDA Efforts to Accelerate PM
      • Gene Editing / CRISPR
      • Genomic Profiling Showcase
      • Immunotherapy Sessions & Showcase
      • Implementation into Health Care Delivery
      • Large Scale Bio-data Resources to Support Drug Development (PPPs)
      • Microbial Profiling Showcase
      • Microbiome
      • Neoantigens
      • Next-Gen. Workforce of PM
      • Non-Clinical Services Showcase
      • Pharmacogenomics
      • Point-of Care Dx Platform
      • Precision Public Health
      • Rare Disease Diagnosis
      • Resilience
      • Robust Clinical Decision Support Tools
      • Wellness and Aging Showcase
  • Luminary and Pioneer Awards, honoring individuals who contributed, and continue to contribute, to the field of Precision Medicine
  • 2000+ multidisciplinary attendees, from across the entire spectrum of healthcare, representing different types of companies, technologies, and medical centers with leadership roles in precision medicine
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