Dr. Laura Jelliffe-Pawlowski, PhD, is an Associate Professor of Epidemiology & Biostatistics in the UCSF School of Medicine and is the Director of Precision Health and Discovery with the UCSF California Preterm Birth Initiative. Dr. Jelliffe-Pawlowski and her team work to identify new tools, tests and technologies that can help identify pregnant women and babies at increased risk for preterm birth, complications of prematurity, and associated birth defects and developmental delays. She has a particular focus and interest in work that leverages molecular markers to help predict outcomes and identify in-roads for intervention. Read her full bio.

Interview with Laura Jelliffe-Pawlowski of UCSF

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: In my view, both are absolutely true – patient healthcare data aggregation allows for great breakthroughs and is also challenging from an ethical perspective in terms of privacy and patient choice. Combining information from health records for millions of people gives us insight into disease and disease processes in way that can allow us to predict and share, with some precision, what the disease trajectory might look like for an individual patient. At the same time, patients continue to express great concerns about data privacy. We need to be able to consider both issues simultaneously – our need for large numbers and the need to consider patient choice and control in the sharing of records.

Q: What are the biggest hurdles today in getting people to share their health data?

A: Historical, societal, and medical traditions are often not our friend when we are looking to have people share their health data – especially vulnerable populations who are often at the highest risk for the health outcomes we are studying – for example heart disease, diabetes, poor birth outcomes. A history of exploitation and implicitly and explicitly racist and classist treatment of certain individuals (e.g. Black, poor, and immigrant people) in medical and medical research settings means that many people don’t trust the medical profession and medical research professionals. Until this tradition is addressed in a multi-factorial way I am not sure it is reasonable to even have the expectation that these groups would willingly share their data.

Q: How can they be overcome? What is needed?

A: While we are making some headway in addressing historical traditions in medicine and medical research that have been both dismissive and exploitative (through training around issues like implicit bias) in my view we won’t really start to break down these barriers until we do two key things: 1) we must elevate and partner with other professionals across race/ethnicity and socioeconomic groupings in all clinical and research endeavors (whether focused specifically on disparities or more broadly on health). Only with inclusion of these individuals as partners and leaders can we begin to understand the full picture and bring whole populations into the fold in this journey) ; 2) we must include study participants – including those who share their medical records with us, as partners in our work (inclusion of community advisory boards in all planning processes is a good step along this road but it goes much further – commitment to sharing data with participants is another element of this, including patients and participants in leadership and decision making groups is another – asking participants and the affected populations what THEY think we should do and then DOING IT is another — paying participants for their time is another — the list goes on and on but is really nested in true partnering).

Q: What has worked? Can you provide some examples that demonstrate that patients and healthy people can successfully share their data where everyone benefits?

A: We have a prospective study underway that I think exemplifies good strategies for approaching research with vulnerable populations and how we might engage larger populations in investigations where data sharing is needed in order to advance discovery to interventions to improve health for those most in need and for everyone. The Supporting Our Ladies And Reducing Stress to Prevent Preterm Birth (SOLARS) study in Oakland, California, funded by the UCSF California Preterm Birth Initiative (UCSF PTBi-CA), is investigating the role of stress in the observed disparities in preterm birth (delivery before 37 completed weeks gestation) in Black and Latina women using a community-engaged, community-based approach for enrollment and follow-up with a focus on identifying low-income women. The study focuses initially on discovery with the ultimate goal of uncovering interventions and involves collection of survey data throughout pregnancy on stress, psychological well-being, and health as well as biospecimens and hospital record review and integration. When we had the idea for this study many other clinicians and researchers questioned whether vulnerable women would engage deeply in this work with us and contribute biospecimens across pregnancy but the community advisory board of the UCSF PTBi-CA felt strongly that because the study was led and staffed by women with lived experience and women of color and because it focused specifically on understanding the role of stress and birth outcomes specifically in Black and Latina women within their geography that women would want to participate and would even be excited to do. Our pilot that tested whether this was true was hugely successful – very vulnerable Black and Latina women engaged with the study, stayed in the study, and expressed enjoying participating. We are now working to enroll 500 women in the study and plan to go bigger – increasing the number of women and locations as the study progresses and as more funding is secured. I think this study continues to be successful because women see themselves in the study and the study teams and feel that they are contributing to the health of their communities – this seems to be absolutely key. They are our partners not our study subjects.

Q: We have a long way to go with clinical trials enrolling at 2-3% today and that number falling. What type and level of shift in culture, laws, collection methods, or other areas is going to be needed to accomplish widespread data sharing?

A: I think we may see some increase in enrollment into trials if we work to partner more with communities in the work we do. We likely need to shift our models of how and where we enroll participants starting with the communities that are affected most by whatever it is that is being researched. If it is an intervention or treatment focused on heart disease or cancer – talk to people with heart disease or about what they think – might recruitment in support groups be helpful, do they have connections to other groups in the community that might be supportive or might even allow recruitment in their offices? Shifting how and where we engage and again, partnering, is key in my view. We may have to actually begin to require some level of patient and community engagement in funding proposals and human subjects applications to push engagement and shift how research is done but it seems like true progress might require this and that such partnering would contribute to the generalizability of findings. Once partnering takes hold open sharing of information will likely feel less threatening because individuals are being included in decision making – that is what partnership is – shared engagement, shared benefits.

Q: How can participants be incentivized to share their health data and other data that researchers need to improve prevention and treatment and to develop new therapies and health practices?

A: I think we have to shift this idea of needing to “incentivize” people to share their data to one where we really focus on how we can partner with people to understand better why they may not want to share and also work to include all kinds of people with all kinds of backgrounds in how we approach sharing. I think we need to talk about why and with whom sharing might happen and be open to people having some choice in how this happens and with whom. Sometimes people are okay sharing some kinds of data and not other types or sharing for certain reasons and with certain groups. We also need to be super mindful of who is reaping the benefits of sharing and making sure that those benefits reach those who contributed data – this may be in the form of, for example, making sure we pay people for their time when contributing data or in making sure the gain more information about their own health. An all or none proposition to sharing may lead to our never having data that is truly representative of our populations.

Q: Will there always be certain communities or populations that will not participate in research because of history or privacy issues?

A: Yes, there may always be communities or populations that don’t want to share but we must not make assumptions about who these groups are. We need to engage people and groups as partners and be flexible around what sharing looks like.

Q: What role will personal technology play in scaling health data sharing and collection?

A: I think consideration of personal technology is key to think about broader sharing of data. Of course there is the “sharing” that happens without a person’s knowledge or approval (or via an approval that was buried deep in long, rarely read approval when you downloaded an application on your phone for example) and then there is the sharing that is transparent and truly agreed to. I think shifting from a burying agreements to share and truly transparent sharing can only help in the long-run because it suggests that a person is valued and that their privacy and choice is prioritized.

Q: What do you predict the landscape will look like in 10 years in terms of people sharing their health data? What are the determinants to making your vision a reality?

A: This is a tough one. What I will say is that I hope it looks more like, for example, the 23andMe model where individuals are asked if they want to contribute their genetic data to certain research projects as they arise and if they say yes – great, and if they say no that is okay too. I think this kind of choice-making leads to more “yes” answers because it is clear that people are valued and their wishes and opinions are prioritized. In my opinion greater flexibility in sharing helps at multiple levels – better results, better generalizability and greater trust in the reasons and questions behind what we are asking people to share and how they, their families, and their communities will benefit.

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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Call for Action: The Time is Now for Patient Data Interoperability

The use of new technologies can provide breakthrough benefits for both patients and providers. However, with increased sharing comes increased risks to the security and privacy of patient data. Currently data is being accumulated across many organizations and initiatives but is often either siloed or simply not accessible. Researchers suggest that patient education tactics can help quell security concerns during patient data sharing.

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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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Breaking News: CMS Takes Actions to Lower Prescription Drug and Other Healthcare Costs – Seema Verma Speaking @PMWC19

The cost of healthcare has been rising at an annual rate of 7% be it company-sponsored health insurance, public insurance such as Medicare and Medicaid, or private insurance. As such, healthcare was top of mind for many individuals this 2018. In the November midterm election many items related to healthcare such as Medicaid expansion, provider pay and indirect effects on the Affordable Care Act could be found on the ballot.

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Did You Catch All 6 of These Big Genomic Medicine Headlines in Recent Weeks?

Genomic sequencing, the driver of modern genomic medicine has come a long way in a short time, and its potential to continue driving innovations in precision medicine is enormous. PMWC 2019 Silicon Valley Jan. 20-23 in the Santa Clara Convention Center will focus on topics that are in the headlines and on everyone’s minds, in NGS and in precision medicine.

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Interview with Christopher Hopkins of Nemametrix

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: We should all be working towards integrating these technologies into routine patient care as quickly as possible, because genomic medicine has the capacity to make profound impacts now.

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Interview with Kristine Ashcraft of YouScript

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: It’s certainly hard to predict, but our goal is to see precision medicine tools in the hands of most providers in the next five years.

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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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