Q: Tell us about Data4Cure.

 

A: Data4Cure develops and provides its partners with an integrative platform that combines systems biology, machine learning and AI technologies to turn vast amounts of omics, phenotypic and clinical data (both public and proprietary) into a data-driven biomedical knowledge graph. The platform uses this information to build comprehensive maps of diseases to identify new drug targets and biomarkers, find new indications for existing drugs, and match drugs to patient subtypes. We are proud to work with some of the largest and most innovative pharmaceutical companies and leading research institutions who use our platform to gain new insights from their data and build their internal knowledge networks.

Q: What led you to found Data4Cure?

 

A: As a computer scientist and computational biologist, I am always interested in how we can combine and model different types of data together to better understand complex systems and make better decisions. Around 2013, I was working at UC San Diego, developing and publishing on new network and systems approaches which worked well for simple organisms such as yeast but weren’t yet as effective for human disease. I thought we can do better by bringing in a lot more diverse types of data and merging systems biology with some of the new machine learning and semantic learning technologies that were becoming available. That would require a new set of tools and a computational platform that would start to tie all of the pieces together. I thought the work could be more effective done through a company. So instead of looking to start my own academic lab, I left to start Data4Cure helped by our scientific co-founder Dr. Trey Ideker, key scientific advisors Drs. Lee Hood and Napoleone Ferrara, as well as early investors. We were very fortunate to be joined by extraordinary computational biologists and engineers and began working with pharmaceutical companies to apply some of the integrative systems biology machinery toward patient stratification and drug development. It gave us a good view into the problems people are facing both in terms of specific analytical challenges, as well as the bigger problem of growing knowledge from more and more data.

What we were able to develop over the last three to four years is an integrated system that not only applies many advanced analytical methods to the data but provides a technology platform to iteratively update knowledge based on new data and literature. The resulting information is stored in a dynamic data-driven knowledge graph that is unique to each organization. This technology became the basis for the Biomedical Intelligence Cloud — our SaaS offering for pharmaceutical R&D which we launched last year. We are continuously improving it by curating and feeding in new large datasets and building new applications to address a wider range of analytical problems.

Q: What are some of the key unique ideas behind the Biomedical Intelligence Cloud? What contextual knowledge do you bring in?

 

A: The key idea is convergence of evidence and information coming from multiple sources like multidimensional omics data, phenotypic data, molecular networks and pathways, literature, clinical trials, and other structured and non-structured data that may exist both within the organization and outside in the public domain. Typically information coming from each one of these sources is noisy, incomplete, and difficult to interpret. By putting the data together in context we are able to extract the most robust pieces of information and make better sense of it.

The Biomedical Intelligence Cloud uses a proprietary knowledge graph technology called CURIE to continuously aggregate various pieces of evidence, learn how they fit together and apply them toward interesting problems in the pharmaceutical and clinical R&D. We think of it also as convergence of systems biology and ML/AI because the technology leverages recent methods from machine learning and AI but is also heavily informed by the developments in systems biology and incorporates a lot of prior knowledge from the biomedical domain.

Q: What types of problems in pharmaceutical R&D do you help address and how does systems biology and ML help?

 

A: The platform has applications throughout the drug development pipeline from early target discovery and validation, to mechanism of action and efficacy studies, to patient selection and developing companion diagnostics. In each of these areas there is an opportunity for integrative systems-based modeling but there are also unique challenges. The platform helps address these individual areas using a set of dedicated applications.

For instance, to support target discovery and validation, users might start by building integrative molecular maps of diseases which integrate omics, phenotypic and literature information with molecular networks and pathways to identify the key system components with potential for therapeutic intervention. Precision medicine is all about precisely mapping disease subtypes and predicting how they might respond to therapy either as single agent or as combinations. This is where some of the other applications become useful. We have an application that performs a deep molecular subtyping of disease based on multidimensional omics data and specific disease pathways perturbed in each patient. Other applications couple machine learning algorithms with knowledge of molecular networks and pathways to predict sensitivity or resistance to drugs in specific patient subsets. We currently have over 10 applications available on the platform and are expanding with new ones in the next months.

Q: You will be speaking in the Immunotherapy Track as well as the AI showcase at PMWC 2018. What are the applications of the platform toward immune oncology? Can you give some use case examples of cancer biomarkers that the Biomedical Intelligence Cloud helped discover?

 

A: Immuno-oncology research and clinical trials is one the areas in which our platform has seen the most growth in 2017. We are particularly interested in understanding and predicting which patients across different histologies will respond to specific types of immunotherapy (e.g. PD1 or PD-L1 inhibitors) and which other patients may respond to combination therapies in which IO drugs might be combined with other therapies.

The power of the platform is that we can effectively combine multiple types of data, such as are often generated by the new IO clinical trials and apply a range of systems and ML approaches to make sense of these data. What is emerging is a view of the tumor-immune system interactions in which multiple factors such as cancer subtypes, immune infiltration, neoantigen load, checkpoint expression and tumor clonal evolution each may together determine response.

Our system can extract multidimensional information about disease biology coming from the analysis of large research cohorts and use it to boost signal and increase the ability to make accurate predictions for new clinical trial cohorts. In my talk I plan to discuss several case studies using recent trials in lung adenocarcinoma and melanoma.

We are very excited to contribute to the PMWC 2018 program. We’ve been part of the conference since the very beginning of Data4Cure. Every year the quality of the program and level of participants makes it a phenomenal event for anyone working in the field. The 2018 edition will be particularly interesting for anyone interested in immuno-oncology, and applications of machine learning and AI in medicine.

Interview with Daniel Chen from IGM Biosciences

Q: Checkpoint inhibitors, particularly with PD-L1/PD-1 targeting agents, have benefited a broad range of patients with cancer. How will we improve on this?

A: It’s true that PD-L1/PD-1 inhibitors have led to durable responses in a subset of patients, and survival benefit in many of the patients treated- either as monotherapy or combination.

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Call from PMWC 2019 Silicon Valley Program Committee – We Must Accelerate and Deliver on the Promise of Precision Medicine

Precision medicine advancements are real as demonstrated by the high volume of molecular, “precise” drugs on the market, which are based on extensive molecular and translational understanding of the specific drug targets.

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#AI Play in Patient Diagnosis? How Can We Prepare the Next Generation to Make Sense of Enormous Amounts of Health-related Data?

What role should artificial intelligence play in patient diagnosis? How can we best prepare the next generation to make sense of enormous amounts of health-related data? These were just a few of the questions explored at the 15th Precision Medicine World Conference held at Duke University September 24-25, 2018.

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Interview with Daniella Beller, Manager, Maccabi Research Institute Biobank

Q: What makes the Maccabi Research Institute biobank unique?

A: To explain the uniqueness of the Maccabi Biobank (named “Tipa” in Hebrew which means “drop” or “just a little”), first you must know a little about Maccabi.

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Why We Need Public-Private Partnerships (PPP) To Foster Drug Discovery

Investments in pharma R&D has substantially increased over the last decades. Yet there appears to be no clear correlation to the number of newly approved drugs. This fact is accompanied by ever-increasing healthcare costs, fueled by an aging population and the parallel rise in the chronic disease burden.

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Precision Medicine: A Decade of Improving the Standard of Care

In January, PMWC will host its 2019 Silicon Valley event, the largest Precision Medicine conference in the world with over 2,500 attendees gathering at the Santa Clara Convention Center. We are humbled and honored to have reached this stage of growth and are looking forward to continuing our work with key stakeholders and decision makers across the industry to ever strengthen this forum for exchange of critical and timely topics, to move the field of precision medicine forward and to improve the Standard of Care.

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Interview with David Hong from Karius

Q: What need is Karius addressing?

A: Physicians often have difficulty pinpointing the exact pathogen that is causing disease. Conventional diagnostics like blood cultures or PCR can have poor sensitivity due to pretreatment with antibiotics, the breadth of potential pathogens present, and the requirement for invasive procedures to access deep-seated infections.

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Interview with Charles Jaffe, MD, PhD from HL7

Q: What need is HL7 addressing?

A: For more than three decades, HL7 has provided the platform to enable global health data interoperability. This is more important than ever, as the cost of healthcare has increased exponentially, and the complexity of clinical evidence has grown to an almost unmanageable state.

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Interview with Eden Haverfield from Invitae

Q: What need is Invitae addressing?

A: Our mission is to bring comprehensive genetic information into mainstream medical practice to improve the quality of healthcare for billions of people. Invitae is uniquely positioned to answer some of life’s most serious and complex questions with the highest quality genetics and at an affordable price.

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Call by Ralph Snyderman (Duke U.) for Big Changes to Get to the Next Level of Precision Medicine

Beyond next-generation gene sequencing and developing diagnostic tools and targeted therapies, theoverall approach to clinical care has to be re-envisioned to fulfill the promise of precision medicine. Care must move from sporadic treatment of episodic disease (a reactive mode) to predicting disease and then acting to prevent and mitigate it (a proactive mode).

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Interview with William Hearl From Immunomic Therapeutics, Inc.

Q: What need is Immunomic Therapeutics, Inc. addressing?

A: Immunomic Therapeutics’ nucleic acid vaccines have the potential to utilize the body’s natural biochemistry to develop a broad immune response, including antibody production, cytokine release and critical immunological memory.

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Interview with Ralph Snyderman from Duke University

Q: What are some of the critical contributions that academic institutions and medical centers are making to implement and accelerate precision medicine?

A: Over the past decade, the field of precision medicine has created technologies enabling far more personalized and effective health care delivery. Many of the most dramatic advances have come in the field of oncology but targeting care to the needs of the individual is rapidly achieving broader applications.

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Interview with Catherine Reinis Lucey from UCSF

Q: What research are you or your lab focusing on and why, and what problem(s) are you trying to solve?

A: My work involves designing, implementing and studying innovations in medical education that allow our medical schools to fulfill our social contract to improve the health of our communities and reduce the suffering of our patients.

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Interview with Gunnar Carlsson from Ayasdi

Q: What need is Ayasdi addressing?

A: Ayasdi is pioneering the application of artificial intelligence to value-based care by targeting two of the most complex problems in healthcare: population risk stratification and clinical variation management.

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Interview with Nikole Kimes from Siolta Therapeutics

Q: What need is Siolta Therapeutics addressing?

A: Chronic diseases, including inflammatory diseases such as asthma, now represent the leading cause of mortality and morbidity worldwide.

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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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