Sebastian Kronmueller incubates startup businesses within Healthineers with a focus on novel molecular applications. His current incubation businesses include the Siemens Healthcare Laboratory in Berkeley, California and NEO New Oncology in Cologne, Germany. Previously he led the execution of strategic initiatives as Head of Special Projects for Siemens Healthineers, playing an instrumental role in shaping the strategy of Siemens Healthineers in preparation for the IPO planned in 2018. Before this role he led a project management team for companion diagnostics and software development and was responsible for the carve-out and divestment of the Healthineers Microbiology business. Read his full bio.

Interview with Sebastian Kronmueller of Siemens Healthineers

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: Human physicians will certainly not be replaced by machine learning or AI technologies. There is a lot of hype around the topic of applied machine learning technologies, but the reality of what the models can do is quite different from the popular imagination. AI tools are mainly great for automation of repetitive tasks, pattern recognition – especially in images, and targeted information retrieval from large multidimensional databases. So, they can support physicians for a particular diagnosis (as e.g. demonstrated for diabetic retinopathy) and help them automate parts of their daily live, maybe even become more efficient with the growing bureaucratic burden posed by EMR systems, but they will not replace them or other qualified healthcare personnel in the foreseeable future. Navigating the subtleties of disease and treatment will stay a human domain, but hopefully AI can support to make the lives of both the physician and the patient easier and opens up the possibility of spending more time on core tasks like the important patient-healer relationship.

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

A: I personally see the greatest value in use cases where we achieve either direct operational improvements or leverage AI to help diagnose disease better. A good operational use case is the use of AI in Siemens Healthineers new Atellica solution to automatically identify the type of sample tubes that have been loaded into the system. It takes a photo of the various sample tubes, uses a pre-trained AI system for identification of their dimensions and automatically configures the system to process them optimally. Great operational application.

Identifying diabetic retinopathy via a pre-trained machine vision system is a good example for a diagnostic application. Another impressive diagnostic application is to use ML to understand changes in the immune system due to cancer. At Siemens Healthineers we also have a variety of strong diagnostic applications, for example automated segmentation and quantification of medical imaging information and the use of machine learning for multi-marker based in-vitro diagnostics. And we currently are working on providing a “digital twin” to physicians which integrates all relevant patient data to aid in diagnosis and treatment. I will talk about this at the conference.

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

A: My hope is that AI will make physicians lives much easier in the near term. Prepopulating forms in EMR systems, helping with specific diagnoses and reducing the number of individual tasks needed to move a patient through clinical pathways will be great improvements. We will see these tools moving into clinical practice gradually in the next years. The other area in which already sees tremendous benefits is research. AI/ML systems can help with the complex task of patient stratification, identification of novel therapeutics and biomarkers and in general support our understanding of human health. The introduction of AI here is also a gradual process over the next years, not something that will happen overnight.

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

A: In my opinion, all really successful applications of AI/ML are based on real, functional mechanisms that are easier to grasp via the technology. An example from Healthineers is the virtual heart as part of the digital twin. It models the electrical pulses when the heart is beating – a real world, functional mechanism – and helps to understand irregularities. To successfully apply AI we need to improve our understanding of these functional mechanisms, and the way to do this properly is traditional scientific research. So one challenge to realize AI/ML in healthcare is finding the right research results where AI/ML can have a positive impact.

Another challenge is the fact that Healthcare systems already use many, many legacy IT systems which we are already struggling to manage and maintain. In a sense, AI/ML can be seen as an IT technology like relational databases – it enables new applications, but requires strong systems around it to be managed properly. So to make AI work, we have to find a way to upgrade these existing systems or to build appropriate interfaces. And cybersecurity, already a key topic in Healthcare, will become even more important to protect the vast amount of data we’ll be capturing to make AI effective.

Finally, I don’t think the current regulatory and reimbursement mechanisms are adequate to capture many of the most recent advancements. For example, having a computer vision enabled diagnosis is not an IVD and doesn’t have a reimbursement code, but de-facto can be as accurate and clinically relevant as a biomarker driven blood test. We need to make sure we differentiate clearly here between value-added applications and noise, but for the former we need to have clear processes in place how to achieve regulatory approval and adequate reimbursement from CMS.

Q: How close are we with successfully using AI for the purpose of mining big data?

A: I think that is another one of the misunderstandings about AI and “big data”. It is extremely hard to mine big data successfully and to distinguish between signal and noise. If a data set is big enough it is always possible to find many, many correlations which seem meaningful – but they are just noise, the functional mechanism I’ve mentioned before is missing and they cannot be meaningfully generalized. I don’t think AI/ML will change that. When it comes to understanding big data I believe in the strength of classical scientific methods to build understanding and enable interpretation.

Once this is available, e.g. by understanding inflammatory reactions in organs due to pathogens, it is possible to use AI/ML to screen large amounts of data, in this case images, to identify typical patterns. But the understanding comes first. At Healthineers we have gigantic data lakes – over 300 million curated clinical datasets – but we follow the logic of building understanding first, then applying AI to apply the insights to data and then moving towards clinical applications.

Q: What is your outlook or vision for use of AI/Machine Learning in healthcare?

A: I think it will help physicians, healthcare professionals and researchers to perform their job more efficiently, will help make technology supportive instead of distracting and improve diagnostic accuracy and treatment across the board. But it will be based on real insights which we’ve gained by traditional science, and the change will be gradual via many small improvements over time, not sudden and holistic. I think of it more as a technology like relational databases – huge impact for every single human being on the planet, but it happened over time and in parallel to many other technological advances like the internet. The same will be true for AI.

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

A: For me PMWC is always a great opportunity to learn from many brilliant people. So I’m looking forward to many good discussions and presentations! If you see me at the conference and would like to talk, please don’t hesitate to approach me.

Interview with Ilan Kirsch of Adaptive Biotechnologies

Q: The Nobel Prize in Medicine was awarded recently to James Allison and Tasuku Honjo 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: For decades cancer was viewed as solely a cell-autonomous condition.

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BMS buys Celgene | Lilly buys Loxo Oncology – Does this Signal a Return to Strong Deal-Making Activities in 2019?

Bristol-Myers Squibb’s blockbuster $74B deal to buy Celgene creates an oncology powerhouse amid industrywide excitement about the rapidly evolving science and explosive growth of the sector. The agreement could signal a return to deal-making for the pharmaceutical industry in the $133B global oncology therapeutics market.

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Interview with Gini Deshpande of NuMedii

Q: What need is NuMedii addressing?

A: NuMedii, has been pioneering the use of Big Data, artificial intelligence (AI) and systems biology since 2010 to accelerate the discovery of precision therapies to address high unmet medical needs. Artificial Intelligence approaches are a natural fit to harness Big Data as they provide a framework to ‘train’ computers to recognize patterns and sift through vast amounts of new and existing genomic

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Interview with Minnie Sarwal of UCSF

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: Completion of complete sequence data from the human genome project, and the advances in proteomic, microRNA and epigenetic assays added a layer of pathway biology to the understanding of human diseases.

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Interview with Shidong Jia of Predicine

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: We will see accelerated human genome profiling for clinical Dx in 2019 and the coming years as more biomarker-based cancer drugs are gaining approval.

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Interview with Iya Khalil of GNS Healthcare

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 think that there’s a lot of speculation and uncertainty around AI, but I don’t foresee a time when we won’t need physicians.

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Interview with Ilya Michael Rachman of Immix Biopharma Inc.

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.” Besides CAR T-cell therapy what do you think next generation immunotherapies will look like to successfully combat cancer?

A: The next generation of immunotherapies will build on the insights discovered by immunologists like James Allison and Tasuku Honjo and extend them to modify the body’s response to tumors.

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Join me to Kick off PMWC Silicon Valley in the Santa Clara Convention Center, Focusing on Every Element of Precision Medicine

My team worked in collaboration with Bill Dalton, Kim Blackwell, Atul Butte / India Hook Barnard, Nancy Davidson and Sharon Terry to create a program that touches every component of precision medicine while bringing together all of its key stakeholders. Leading participating institutions including Stanford Health Care, UCSF, Duke Health, Duke University, John Hopkins University, University of Michigan and more will share their learnings and experiences and their successes and challenges, as they make precision medicine the new standard of care for all.

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Interview with Dominic Eisinger of Myriad RBM

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.” Besides CAR T-cell therapy what do you think next generation immunotherapies will look like to successfully combat cancer?

A: Next generation immunotherapies include CAR-Ts, TCRs, cancer vaccines, ADCs, bi-specific antibodies, and checkpoint inhibitors.

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2018 Year in Review Milestones: Stakeholder Partnerships Carving Precision Medicine’s Future

2018 has clearly been a year when significant opportunities intersected with strong partnerships to yield advancements. In particular, the clinical advancements that were realized are a testimony to stakeholders working together to deliver on promises affecting major aspects of precision medicine. 2018 has clearly been a year when significant opportunities intersected with strong partnerships to yield advancements.

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Interview with Lisa Alderson of Genome Medical

Q: Tell us a little bit about Genome Medical. What market need is Genome Medical addressing and how?

A: Genome Medical is a telegenomics company that is bridging the gap between available, genetic expertise and the clinical application of genomics.

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Interview with Nasir Bhanpuri of Virta Health

Q: What need is Virta Health addressing?

A: Virta Health delivers an evidence-based treatment to safely and sustainably reverse type 2 diabetes without the use of medications or surgery. In the U.S. alone, type 2 diabetes and prediabetes affects 115 million people, and the economic burden is well-over $300 billion and growing.

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Interview with Jussi Paananen of Blueprint Genetics Inc.

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: Right now, we are looking at merely a fragment of clinical work that could be replaced by a machine.

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Our Healthcare System Clearly Needs a Revamp And It’s Happening!

Patients are demanding an exceptional healthcare experience; one that makes care more. At PMWC, we can sense a revolution in the healthcare system on the horizon with fee-for-service losing dominance and innovative technology playing a key role in healthcare delivery.

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Interview with Sebastian Kronmueller of Siemens Healthineers

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: Human physicians will certainly not be replaced by machine learning or AI technologies.

Read More
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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