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Archive for the ‘Artificial Intelligence in Medicine – Applications in Therapeutics’ Category


LIVE Day Two – World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 9, 2019

 

www.worldmedicalinnovation.org

 

The Forum will focus on patient interactions across care settings, and the role technology and data can play in advancing knowledge discovery and care delivery. The agenda can be found here.

https://worldmedicalinnovation.org/agenda/

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

represented by Founder & Director, Aviva Lev-Ari, PhD, RN will cover this event in REAL TIME using Social Media

@pharma_BI

@AVIVA1950

@PHSInnovation

#WMIF19 

Tuesday, April 9, 2019

7:00 am – 8:00 am
7:00 am – 5:00 pm
7:40 am – 7:50 am
Bayer Ballroom

Opening Remarks

  • Chief Innovation Officer, PHS; President, Partners HealthCare International
7:50 am – 8:40 am
Bayer Ballroom

Implementing AI in Cancer Care

With AI-enabled care strategies and digital technologies, clinicians and patients are embracing new approaches to improve the lives of cancer patients through enhanced diagnosis and treatment. These include AI-guided tools for more precise methods of predicting risk, more effective screening strategies, patient data driven insights  and more personalized treatments. Panelists will engage on how these and other innovations are enabling a new era of cancer care.

  • Chief, Breast Imaging Division, MGH; Professor of Radiology, HMS
  • FDA
  • President and Co-Founder, LunaDNA
  • Patients contribute personal data get share in the company
  • democratization by AI use
  • unrepresented population in research
  • education on technology
  • Retrospective and longitudinal studies
  • Bid Trust engaging responsively
  • Delta Electronics Professor, Electrical Engineering and Computer Science Department, MIT
  • developper of AI based applications @MGH Cancer Center
  • Training AI on 3% of population vs randomized that has its bias of patient selection
  • no standards of publishing AI in medicine
  • AI to help women
  • Integration of systems to help patients
  • Director, Cancer Genome Analysis, Broad Institute; Professor, Pathology, HMS
  • AI for early detection
  • big data analysis – noise vs point of signals
  • drug resistance using genomics
  • AI – regulate the type information reviewed by doctors
  • data acquisition and monitoring along the life of the product not only till FDA approve it
  • Reporting adverse events
  • Data cost of sequencing is dropping, biomarkers,
  • regulatory needed to adopt AI and reimbursement starts at academic center followed by the entire country
  • CEO, insitro
  • AI for drug discovery
  • epigenetic effect on lesions
  • Physician are over promised on Genomics, asking them to use complex data from multiple source need be curated before it gets to Physicians
  • Reversed clinical trial vs randomized 30 years follow up
  • Data is anonymized used in research contributors get back own diagnosis genomics understanding

 

8:40 am – 9:30 am
Bayer Ballroom

Imagining Medicine in the Year 2054

In 1984 Isaac Asimov was asked to predict what life in 2019 would be like. Using the same aperture, we as what will constitute health care 35 years from now? Current trends suggest that there will be significant gains in immunotherapy, gene therapy, and breakthrough treatments for neurologic, cardiovascular and oncologic diseases. Panelists will draw on their visionary perspective and will reflect on what to expect and why.

Moderator: Keith Flaherty, MD
  • Director, Clinical Research, Cancer Center, MGH; Professor of Medicine, HMS
  • CEO, Flagship Pioneering
  • Vice Chair for Scientific Innovation, Department of Medicine, BH; Associate Professor of Medicine, HMS
  • Director, Cellular Immunotherapy Program, Cancer Center, MGH; Assistant Professor, Medicine, HMS
  • Vice-Chair, Neurology, Director, Genetics and Aging Research Unit, MGH; Joseph P. and Rose F. Kennedy Professor of Neurology, HMS
9:30 am – 9:50 am
9:50 am – 10:15 am
Bayer Ballroom

1:1 Fireside Chat: Ash Carter, U.S. Secretary of Defense (2015 – 2017)

Moderator: Gregg Meyer, MD
  • Chief Clinical Officer, PHS; Professor of Medicine, HMS; 2019 Forum Co-Chair
  • U.S. Secretary of Defense (2015–2017)
10:15 am – 10:40 am
Bayer Ballroom

1:1 Fireside Chat: Honorable Alex Azar II, Secretary of Health and Human Services

Moderator: Gregg Meyer, MD
  • Chief Clinical Officer, PHS; Professor of Medicine, HMS; 2019 Forum Co-Chair
  • 24th Secretary of Health and Human Services
  • quality cate means outcomes
  • Pricing Transparency by HMOs and Hospitals
  • Plan D – instant electronic to Drug Pricing information
  • Medicare moves away from Procedure based payment
  • Data on services, drugs and procedures in a Patient-centered system
  • Big data, pricing information, CMS
  • AI inspector General – Claims – AI – do get yield
  • AI in procurement
  • AI for services to Medicare – prescription Tools for advising Patients on best drug to use based on medcial information
  • Patient HC information is owned by Pations and is portable
  • Blue Data 2.0 – access record by patients @CMS
10:40 am – 11:30 am
Bayer Ballroom

CEO Roundtable

Chief executives share perspectives on the impact of AI on their respective companies and industry segments. Panelists will discuss their views of AI, how AI figures into their organizations’ current product and investment strategies, and how they are measuring return on existing AI investments. The panel will also address opportunities and challenges surrounding AI, ranging from workforce needs to managing bias in AI development.

Moderator: Anne Klibanski, MD
  • Interim President and CEO, Chief Academic Officer, PHS; Laurie Carrol Guthart Professor of Medicine, HMS; 2019 Forum Co-Chair
  • Partnerships between companies like : GE, Phillips, Siemens
  • CEO, Philips
  • efficiencies and outcomes
  • adaptive intelligence to be integrated AI 1.8Billion Euro invested 600 scientists
  • collaboration with Dana Farber
  • Design thinking – work with clinicians to get insights on experience with technologies
  • system change for delivery of care
  • Open API – federated data architecture EMR companies will also need to adapt
  • Phillips builds centers in Pittsburgh, Cambridge, Amsterdam, Paris
  • EVP, Head, Pharmaceuticals Research and Development, Bayer AG
  • AI – R&D efficiency
  • Disruptive approaches optimization of synthesis of chemical reactions productivity and selection of molecules
  • In house data science expertise vs image pattern recognition of HTN collaboration with Merck
  • Collaboration with MIT on clinical Trials
  • changing provides vs longitudinal care
  • Access to talent – Data scientists Amazon is a competitor on talent for AI SKILLS DOMAIN EXPRET TOPIC
  • R&D AT BAYER – DATA SCIENCE IN each division
  • CEO, Siemens Healthineers
  • 400 research collaborations
  • “analog” way innovations generations
  • CEO, GE Healthcare
  • HC – Clinical command center in Hospitals collaboration with Partners
  • Investment is in platforms vs applications – Edison platform tool kits – Radiologist will develop their own on top of PLATFORMS from GE
  • Clinicians productivity will change with AI
  • Data scientist new identity – bigger developers of systems
11:30 am – 11:35 am
Bayer Ballroom
11:35 am – 11:45 am
11:45 am – 1:00 pm

Discovery Cafe Sessions

Lunch with Experts: Intensive sessions addressing cutting-edge artificial intelligence topics.

Provider Back Office of the Future

The application of AI-based technologies to the business side of health care — including functions such as billing, payment, and insurance claims management — could lead to significant improvements in health care operations and efficiency, with billions of dollars in savings each year. Panelists will discuss emerging tools and technologies as well as the opportunities and pitfalls of using AI to innovate and automate back office functions.

Moderator: Peter Markell, EVP, Administration and Finance, CFO and Treasurer, PHS

Inge Harrison, CNO/VP of Strategic Advisory Services, Verge Health

Kent Ivanoff, CEO, VisitPay

Mary Beth Remorenko, VP, Revenue Cycle Operations, PHS

Brian Robertson, CEO, VisiQuate

 

Chief Digital Strategy Officer Roundtable

With the advent of AI-enabled technologies, this session brings together leading chief digital health officers. The discussion will address tradeoffs in sequencing technology across academic medical centers; what technologies are being prioritized; and consumer expectations.

Moderator: Alistair Erskine, MD, Chief Digital Health Officer, PHS

Michael Anderes, Chief Innovation and Digital Health Officer, Froedtert Health; President, Inception Health

Adam Landman, MD, VP and CIO, BH; Associate Professor of Emergency Medicine, HMS

Aimee Quirk, CEO, innovationOchsner

Richard Zane, MD, Chief Innovation Officer, UCHealth; Professor and Chair,Department of Emergency Medicine, University of Colorado School of Medicine

 

Innovation Fellows: A New Model of Collaboration

The Innovation Fellows Program provides experiential career development opportunities for future leaders in health care. It facilitates personnel exchanges between Harvard Medical School staff from Partners’ hospitals and participating biopharmaceutical, device, venture capital, digital health, payor and consulting firms. Fellows and Hosts learn from each other as they collaborate on projects ranging from clinical development to digital health and artificial intelligence. Learn how this new model of collaboration can deliver value and lead to broader relationships between industry and academia.

Moderator: Seema Basu, PhD, Market Sector Leader, Innovation, PHS

Nathalie Agar, PhD, Research Scientist, Neurosurgery, BH; Associate Professor, Neurosurgery, Radiology, HMS

Paul Anderson, MD, PhD, Chief Academic Officer, BH; SVP, Research, BH; K. Frank Austen Professor of Medicine, HMS

Laurie Braun, MD, Partners Innovation Fellow, MGH and Boston Pharmaceuticals; Instructor in Pediatrics, HMS

David Chiang, MD, PhD, Research Fellow, BH; Innovation Fellow, Boston Scientific

David Feygin, PhD, Chief Digital Health Officer, Boston Scientific

Peter Ho, MD, PhD, CMO, Boston Pharmaceuticals

Harry Orf, PhD, SVP, Research, MGH; Principal Associate, HMS

 

Last Mile: Fully Implementing AI in Healthcare

This session will focus on how radiology and pathology specialties are currently applying AI in the clinic. Where will it be built out first? What are the barriers and how will these challenges be overcome?

Moderator: Keith Dreyer, DO, PhD, Chief Data Science Officer, PHS; Vice Chairman, Radiology, MGH; Associate Professor, Radiology, HMS

Katherine Andriole, PhD, Director of Research Strategy and Operations, MGH & BWH CCDS; Associate Professor, Radiology, HMS

Samuel Aronson, Executive Director, IT, Personalized Medicine, PHS

Peter Durlach, SVP, Healthcare Strategy & New Business Development, Nuance

Seth Hain, VP of R&D, Epic

Jonathan Teich, MD, PhD, Chief Medical Information Officer, InterSystems; Emergency Medicine, BH

 

Reimagining Disease Management

The management of disease has become vastly more challenging, both for patients and providers. AI-based technologies promise to improve and streamline patient care through a variety of approaches. This session will feature a discussion of these new tools and how they can enhance patient engagement and optimize care management.

Moderator: Sree Chaguturu, MD, Chief Population Health Officer, PHS; Assistant Professor, Medicine, HMS

Murray Brozinsky, Chief Strategy Officer, Conversa

Jean Drouin, MD, CEO, Clarify Health Solutions

Julian Harris, MD, President, CareAllies

Erika Pabo, MD, Chief Health Officer, Humana Edge; Associate Faculty, Ariadne Labs; Associate Physician, BH; Instructor, HMS

 

Standards and Regulation: The Emerging AI Framework

As the health care industry faces an explosion of AI-based tools, the FDA’s approach to these technologies is evolving. This session will focus on the agency’s approach to AI-based products, how to calculate the risk profile of these new technologies, and the challenges of securing adequate data rights.

Moderator: Brent Henry, Member, Mintz Levin

Bethany Hills, Member/ Chair, FDA Practice, Mintz Levin

Michelle McMurry-Heath, MD, PhD, VP, Global Regulatory Affairs and International Clinical Evidence, Johnson & Johnson Medical Devices

Bakul Patel, Associate Director, Digital Health, FDA

Michael Spadafore, Managing Director, Sandbox Industries

 

From Startup to Impact (Provider Solutions)

This session will introduce you to five leading startup companies who will each share their respective impact in delivery provider solutions in ten-minute pitches.

Moderator: Meredith Fisher, PhD, Partner, Partners Innovation Fund, PHS

Moderator: James Stanford, Managing Director, Fitzroy Health

William Grambley, COO, AllazoHealth

Gal Salomon, CEO, CLEW

Siddarth Satish, CEO, Gauss Surgical

Pelu Tran, CEO, Ferrum Health

Ed Zecchini, CIO, Remedy Partners

1:00 pm – 1:10 pm
1:10 pm – 2:00 pm
Bayer Ballroom

China: AI Enabled Healthcare Leadership

China’s health care system faces major challenges — and its population is aging more rapidly than nearly every other country. To help address these problems, the Chinese health technology sector is strongly embracing AI. What are the most exciting applications? What lessons does China’s early forays into AI-enabled patient care hold for other health care systems?

Moderator: James Bradner, MD
  • President, Novartis Institutes for BioMedical Research
  • Chief Innovation Officer, GE Healthcare
  • Analytics allowing higher throughput in China in Rural areas
  • Sepsis – detection is too late
  • data exhaust for facial recognition – anticipatory diagnosis
  • oncology tumor algorithm
  • CEO, Infervision
  • Medical imaging – four years to mature nodule detection
  • AI – no resale of data
  • Chairman and Co-Founder, Yidu Cloud
  • Medical records
  • Data privacy is personal consent if identification Passport level:
  • Doctor looking on Medical record need consent
  • Administration – clearance for access
  • Managing Partner, Qiming Venture Partners
  • AI HC companies execution to build companies
  • Valuation of all AI not only HC, dropped 30%
  • Real Doctor – 14 licensing for Internet medicine 90,000 patients a day are seen
  • Consumer EMR – Alibaba invested in
  • Investment in CRISPR
  • Invest in drug discovery in China
  • In China 150 programs of drug development of PD-1
  • Government  – 90% of patients go to Public Hospital which guard the data
  • Challenges AI in China — US – China Trade issue
  • CEO, Real Doctor Corporation Limited
  • Medical imaging 12 disease found from pictures build models to other 100 hospitals
  • small nodules detection
  • China-FDA no regulation established yet Learn from US FDA
2:00 pm – 2:30 pm
Bayer Ballroom

1:1 Fireside Chat: Mark Benjamin, CEO, Nuance

Moderator: Peter Slavin, MD
  • President, MGH; Professor, Health Care Policy, HMS
  • CEO, Nuance Communications
  • System produce NOTES from conversation, clinical language, notes read interactively by looking at other chart – LIVE EXAM more that an invoicing tool
  • patient case management made efficient
  • Documentation and Clinical notes embedded into the EHR enhance intelligence at Point-of-Care

 

2:30 pm – 3:00 pm
3:00 pm – 3:50 pm
Bayer Ballroom

Getting to the AI Investment Decision

The billions invested worldwide in AI-based health care technologies underscore the enthusiasm of global investors. But where are the greatest opportunities and what is the timeline to meaningful impact? In this panel, venture, private equity investors, and buy side analysts will discuss investment priorities, timelines, and key areas of interest

  • Partner, Partners Innovation Fund, PHS
  • When is the time right and when there is only a promise
  • VP, Venture and Managing Partner, Partners Innovation Fund, PHS
  • Looks like therapeutics but it is AI
  • Managing Director, Bain Capital Life Sciences
  • companies leveraging competencies
  •  Capital put to work what is it coming to do – specific value creation
  • Is the problem HC or an Academic Medical Center, i.e., MGH problem to solve
  • If no one at PHS willing to pay — let’s think again
  • Managing Partner, Polaris Partners
  • Data in Pharma companies are ready for AI application
  • algorithms and analytics
  • Value proposition
  • Language processing & ML – recognize patterns in consistant datasets – improve decision made in patient care
  • SVP, Strategy, Commercialization and Innovation, Amgen
  • Real data using AI for speeding drug discovery commercial application
  • predictive models for second MI with partner
  • Pilot study vs scaling up
  • Managing Director, Healthcare Group, Goldman Sachs
  • As AI algorithm mature, labor intensity curbed by AI
  • IPO
  • consolidation of big pharma
  • Partner, Google Ventures – started in 2008/9; Instructor in Medicine, BH
  • data quality needed for AI to avoid bias
  • Pharma is interested in Drugs not in Targets
  • Translator between technology and healthcare
  • Teach computer the rules to go then beating its creator unanticipated modes
  • IT is different in various industries more than West Coast vs East Coast
3:50 pm – 4:20 pm
Bayer Ballroom

1:1 Fireside Chat: Robert Bradway, CEO, Amgen

  • Partner, Atlas Venture
  • CEO, Amgen
  • DeCode Genetics acquired by Amgen
  • AI is in the beginning Rapata and Evenity (romosozumab) risk of fractures – review large images archives
  • Migraine only digital health  – this is not a big area for Amgen
  • Transparency
  • Encouraged to role back the Rebate Program the sickest pay to high – policy changes
  • Part 4
  • Rapata – lower LDL reduce risk for stroke MI 600Billion fighting Heart disease – price lowered 60% patients are directed to the more expensive product
  • Investment in Biosimilars and biologics made available free resources
  • risk is Washington, generics may become the rule for biologics
  • no favor innovating products vs Biosimilars
  • ObamaCare create 12 years of data exclusivity for biologics
  • 90% of prescription is generic products
  • cost of CVD in 2019 is a fraction of the cost 15 years ago
  • CURE – is used for Cancer at what price HEP C – is a cure very expansive
  • Meaning of innovations create frameworks for saving live
4:20 pm – 5:10 pm
Bayer Ballroom

Consumer Healthcare and New Models of Care Delivery

Al is powering a revolution in consumer health care, giving patients a deeper role in monitoring their own health and spawning new models of care delivery. Many health care organizations are increasingly focused on creating a digital “front door” for patients – a single gateway to mobile apps and other online services. Panelists will also discuss the role of remote monitoring and virtual care programs as well as the role of Al in care redesign and workflow.

Moderator: Diana Nole
  • CEO, Wolters Kluwer Health
  • President, Global Strategy Group, Samsung; Founder, CareVisor
  • Real time sensing to deliver realtime care plan: Human Avatar
  • AI is hidden
  • communication varies by generations phone vs SMS
  • VP and Global CTO, Sales, Dell EMC
  • IOT – scale
  • social media – peer pressure
  • President, Health Platforms, Verily Life Sciences
  • AI applied in diet management with images of snacks
  • Co-production of Health 50s-60s concept Co-Production health by patients give patients information and they will co-produce their healthier life style
  • VP and Chief Health Officer, IBM Corporation
  • AI continues to improve – actionable insights
  • AI augmented humanity
  • In China a Team of oncologist meet with entire families to discuss plan of care Cancer patients for GrandMa,
  • SVP, Head of Innovation and Health Equity, Microsoft Healthcare
  • AI – sequence T cells
5:15 pm – 5:25 pm
Bayer Ballroom

BioBank Award Announcement

  • Third place MGH – Computational Pathology
  • First Prize – $12,000 UPittsburg – Dept Biomedical Informatics – principal components
  • First Prize – IBM Center for Computational Health – supervised algorithm
5:30 pm – 6:30 pm

 

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LIVE Day One – World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 8, 2019

 

www.worldmedicalinnovation.org

 

The Forum will focus on patient interactions across care settings, and the role technology and data can play in advancing knowledge discovery and care delivery. The agenda can be found here.

https://worldmedicalinnovation.org/agenda/

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

represented by Founder & Director, Aviva Lev-Ari, PhD, RN will cover this event in REAL TIME using Social Media

@pharma_BI

@AVIVA1950

@PHSInnovation

#WMIF19 

@evanKristel 

Monday, April 8, 2019

7:00 am – 8:00 am
7:00 am – 5:00 pm
8:00 am – 9:40 am
Bayer Ballroom

First Look: Round 1

Nine rapid fire presentations on the applications of AI in Clinical Care

To view speakers and topics, click here.

Henry Chueh, MD

Director, MGH Lab of Computer Science, MGH; Assistant Professor, Medicine, HMS

Dxplain: Expanding diagnostic horizons

 

Synho Do, MD

Director, Laboratory of Medical Imaging and Computation (LMIC), MGH; Assistant Professor, HMS

Leveraging a Deep-Learning Algorithm for the Detection of Acute Intracranial Hemorrhage

 

Laura Germine, PhD

Director, Laboratory for Brain and Cognitive Health Technology, McLean; Assistant Professor, Psychiatry, HMS

The Next Generation of Cognitive and Behavioral Assessment

 

Satrajit Ghosh, PhD

Research Associate, MEE; Principal Research Scientist, MIT; Assistant Professor, Otolaryngology, HMS

Assistive Intelligent Technologies for Brain Health

 

Chris Sidey-Gibbons, PhD

Co-Director, PROVE Center, BH; Member of Faculty, HMS

Three Computational Techniques and One Tool to Bring the Patient Voice into Care

 

Xudong Huang, PhD

Co-Director, Neurochemistry Laboratory; MGH; Associate Professor, Psychiatry, HMS

Leveraging Artificial Intelligence for Brain Drug Discovery

 

Tina Kapur, PhD

Executive Director, Image-Guided Therapy, BH; Assistant Professor, Radiology, HMS

Using AI to Better Visualize Needles in Ultrasound-Guided Liver Biopsies

 

Bharti Khurana, MD

Director, Emergency Musculoskeletal Radiology, BH; Assistant Professor, HMS

 

 

Vesela Kovacheva, MD, PhD

Attending Anesthesiologist, BH; Instructor, Anesthesiology, HMS

Harnessing the Power of Machine Learning to Automate Drug Infusions in the OR and ICU

Constance Lehman, MD, PhD

Chief, Breast Imaging Division, MGH; Professor of Radiology, HMS

AI-Based Care Delivery: A New Paradigm for Curing Cancer

 

Lisa Nickerson, PhD

Director, Applied Neuroimaging Statistics Lab, McLean; Assistant Professor, HMS

Using Digital Phenotyping and Machine Learning to Forecast, Detect, and Prevent Drug Overdose Deaths

 

Federico Parisi, PhD

Research Fellow, Wyss Institute for Biologically Inspired Engineering, SRN

Mobile Health Technologies for Monitoring Motor Fluctuations in Patients with Parkinson’s Disease

 

Stuart Pomerantz, MD

Director, Neuro-CT, Neuroradiology, MGH; Instructor, HMS

AI-Powered Diagnostic Reporting for Spinal MRI of Degenerative Disease

 

Sandro Santagata, MD, PhD

Assistant Professor, Pathology, BH, HMS

 

Joseph Schwab, MD

Chief, Orthopaedic Spine Surgery, MGH; Associate Professor, HMS

Artificial Intelligence for Diagnosis and Management in Spine Surgery

 

Hiroyuki Yoshida, PhD

Director, 3D Imaging Research, MGH; Associate Professor, Radiology, HMS

 

Nazlee Zebardast, MD

Instructor, Ophthalmology, MEE, HMS

 

Li Zhou, MD, PhD

Associate Professor/Lead Investigator, BH; Associate Professor, HMS

 

Machine Learning and NLP to Track Disease Progression and Predict Health Outcomes

Moderator: Giles Boland, MD
  • Chair, Department of Radiology, BH; Philip H. Cook Professor of Radiology, HMS
Moderator: Trung Do
  • VP, Business Development, Innovation, PHS

Henry Chueh, MD

  • wrong diagnosis, leading malpractice claims
  • 1 out of 6 new diagnosis are wrong
  • help clinicians to make 1st diagnosis and every time correct — what need be considered
  • fever, rash, arthrisis (painful swallen joint) – no correct diagnosis
  • Adult Still disease – symptoms trigger condition –
  • DXplain Knowledge base + algorithms curated over 25 yr
  • >1 Million relationships
  • probabilistic inference algorithms
  • Amazon Web Services – micro services on Amazon Web
  • UI widgets for Web apps – mobile prototype
  • 20million hits per month
  • DXplain consumer, clinician, hospitals, payer, malpractice insurer

 

Synho Do, PhD

  • AI and DL for Stroke Patient management detection of acute intracranial haemorrhage from small dat sets
  • 1 of every 10 death is a Stroke caused, 5.8 million people die of Stroke Stroke is a medical emergency, CT Scan
  • Spotting brain bleeding after
  • Deep Learning algorithms – explainable AI  – human mimiking algorithm developed @MGH
  • Explainable AI – Multi-window mixing & multi-slice mixing is in PACS @MGH
  • commercial opportunity: Near stroke detection
  • @MGH Stroke with AI algorithms Patent IP @PartnerInnovation seeking funding for Stroke management

Laura Germine, PhD

  • Next generation of behavior assessment
  • in Psychiatry – neuropsychiatry
  • Problem of measurement of innovation with validity needed – Tools to measure and have outcomes
  • Unreasonable effectiveness of Good Data : Math achievement – visual-spatial attention
  • Looking for partners

Satrajit Ghosh, PhD

  • Mental health 1 in 4 adults 18% of adolescence 13% of children
  • first treatment effective only in 25% of cases
  • Brain structure and Function – using MR – observed behaviors – using Voice, speaking is a very complex activity
  • Talk intent emotions – window into the mind
  • Speech

Xudong Huang, PhD

  • Brain Drug Discovery – leveraging AI
  • Major depressive DIsorder ( MDD) – 16 million in US 210 Billion a year treatment burden
  • Alzheimer’s DIsease  – 5.8 million AS in US – $290 in 2019 a year treatment burden
  • Potential druggable for MDD and AD
  • Tryptophan-Kynurenina pathway
  • Secreted Protein Acidic and Cysteine rich
  • AI-Powered Drug Discovery Platform – AtomNet
  • Preclinical drug discovery and development
  • Screened 10MIllion compounds – 48 inhibitors for tryptophan-catabolizing enzymes in
  • Tryptophan-Kynurenina pathway

Tina Kapur, PhD

  • AI to visualize needles in UltraSound-guided (US) liver biopsy – safer to patient and easier for the physicina
  • mass in liver suspected to be from a metastasis in the pancreas
  • AI to enable the MD to see the needle completely independent of the US technician
  • Benefits if available to all performers of liver biopsy
  • Patients: Benefit from location of tissue biopsy sampling
  • prostate needle in MRI
  • Button labelled Needle, MD turn on/of button
  • navigation systems not in use
  • 95% proceedures done free hand
  • 1 Million US guided liver biopsy/yr, growing @4%
  • manufacturing of US equipment to be interested to embed

Bharti Khurana, MD

  • Home is the most dangerous place for women killing of women hit by husband. ages 25 to 38 – fracture of bone IPV – Intimate Partner Violence – 1 in 4 women and 1 in 9 men IPV is preventable under reporting
  • Tybanny of the Urgent
  • clinical decision support to predict risk probability automate alerts 95% 50% 15% – Probability of IPV – insivible to visible
  • empower healthcare providers
  • reduce ER volume will reduce cost

Vesela Kovacheva, MD, PhD

  • Titrating drug infusions – Personalized for patient safety reduce med error
  • Titrating drug infusions – automation system from anestesia – function automonically
  • local anestatic for Cesearian section – BP drog when spinal administration of anestatic agent
  • calculate every minure – 20 minutes are critical from drug infusion
  • decision to administer vasopressors is taken evey minute on the bP
  • Rural areas one anestosiolog suverviser three OR at the same time
  • 1.25 million C-section
  • 75% develop low BP
  • complications in babies decreased BP – tachepnis in neonatal – NICU 100Million $ per year.
  • develop same algorithms for propofol in sedetion and insulin in ICU
  • other surgeries – knee, hip, spinal

Constance Lehman, Md, PhD

  • Breast Cancer Out of 2 Billion women 2million will be diagnosed with breast cancer
  • screening will prevent development
  • current tools of mamography – no single interpretation and shortage
  • memograph vs Future risk of BC development
  • Deep Learning model; Training model consequitive memograms Risk model developed – AI technology on memograpm 0.71 when other factors added
  • DIverse races – RAce blind AI model
  • AI model of diagnosis in one year after the memogram taken
  • breast density – imager certified, 6% are dense, 85% and every number in between
  • Expertise: MGH, MIT, Prior failure of CAD
  • Patents for commercialization beyond MGH

Lisa Nickerson, PhD

  • 70,000 drug overdose, 50,000 opioids related
  • Death from prescription opioids is on the increase after 2013 – fentanyl – causing overdose
  • prescription opioids overdose Prevention strategies:
  • Targeted Naloxone distribution
  • Medication assisted treatment
  • Fentanyl screening in Tox tests
  • 911 good Samaritan laws
  • Syringe services programs

Federico Parisi, PhD

  • Mobile Health Applications – Monitoring motor fluctuation in Parkinson’s Disease (PD)
  • 7 – 10Million WOrldwide, 1 Million in the US,
  • dopamine-producing neuron
  • main medication in early stage – Levodopa
  • Need an objective and continuous monitoring toool for tacking the symptoms’ dynamics
  • mHealth for monitoring PD – mimiking clinical evaluations mail limitations: Deendency on standardized motor tasks in sufficient time resolution in symptoms severity during ADLs

Stuart Pomerantz, MD

  • DeepSPINE – Challenges of Lumbar Spine Imaging: Lumbar stenosis MR interpretation Suboptimal radiology
  • DeepSPINE – end-to-end processing pipeline for clinical deployment
  • AI-Powered Diagnosis & Reporting Solutions
  • DeepSPINE: Slice Angle Optimization
  • Predict disease severity/interpretation time
  • Route of optimal staffing
  • DeepSpine Data Layer Multi-Format Reporting: Traditional Text vs Tabular Image-Enhanced
  • Portfolio of applicationsWho benefits from MRI
  • Avoid unneccesary imaging – Clinical Decision-aking
  • Better predict who needs surgery

Sandro Santagata, MD, PhD

  • Tissue imaging quant pathology
  • DL for Mass spectrometry – full spectral resolution
  • interoperative paradigm – patient, biopsy, frozen tissue Tissue cyclic immunoflorescence hi Dimensional pathology
  • Human Tumor Atlas Network (HTAN) – phenotype cancers

Joseph Schwab, MD

  • Orthopedic Spin surgery – 1/2 million lumber fusion surgery, 5% complications $1.8 Billion
  • Data science in Spine today – algorithms based on 35,000 patients cases annotated
  • ML algorithm which Pations will need opioids after fusion
  • Predicted Probability – cost-benefit ration – Benefit to patient
  • Cervical stenosis C5-C6 – patient list of current medication – Prediction of a patient probability to need opioids after spinal surgery
  • Spinal metastasis – Survival prediction – is surgery needed if survival is few months?
  • Complications of hip replacement Perspective: Provider or Insurer
  • SORG-AI.com

Chris Sidey-Gibbons, PhD

  • Patient-reported data
  • identification of treatment satisfaction with care, quality of life, mental health,
  • ONE Questionnaire – filled by Patient – used by psychiatry since 1950
  • Clinical meaning, ML, Computer Adaptive Diagnosis (CAT algorithm) , NLP, response burden
  • ML – improve clinical meaning of Patient reported data, train algorithm – likely outcomes
  • Reconstructive surgery following mastectomy – survey of women
  • Plastic surgery Report – to improve CAT algorithm
  • imPROVE
  • InSpire

Hiroyuki Yoshida, PhD

  • Colon screening 150,000 new cases in the US, 55,000 death, 14B spent in the US
  • CT colonography (CTC)  & Colonoscopy
  • @MGH Laxative-free CT colonography: Oral oral contrast  followed by GI CT Scanning
  • GAN – generative adversarial networks: AI virtual bowel cleansing + AI small polyp detection
  • algorithms remove fecal material
  • Sensitivity: AI-latex-free – 96% sensitivity vs. CTC 46% and Laxative 67%

Nazlee Zebardast, MD

  • Deep learning for glaucoma detection – prevent
  • optic nerve disease, irriversible blindness
  • 76 Million 11 Million bilateral blind
  • +50% glacauma not diagnosed in the US – delay progression by screening
  • No reliable out reach programs – USPSTF recommended against screening
  • Deep learning used for Glaucoma detection _ Larger inter-reader interpretation variation
  • Improve reference standard
  • genetic risk of glaucoma
  • intaocular pressure – modifiable factor
  • Diabetic or non diabetic retinopathy
  • Age, gender, smokin SBP, refractive error
  • What the machine pays attention
  • high IOP and high genetic risk
  • commercialize DL based screening tool for glaucoma – 140 Million in the US
  • The market: 120 million age 30 to 40
  • Cost saving S5.8 Billion

Li, Zhou, MD, PhD

  • Palliative care ML and improve value of care
  • end of life care for Dementias: Latent topic modeling and trend analysis using clinical notes
  • reduce anxiety and depression patient more likely to have wishes known
  • Who are the patients that will benefit the most from palliative care
  • determine the right time for this intervention
  • free-text EHR data
  • Physical function status: Nutrition, feeding, swallowing
  • Commercialization – MTERMS Lab – pharmacovigilance, speech recognition, information extraction and decoding data mining

 

9:40 am – 9:55 am
9:55 am – 11:35 am
Bayer Ballroom

First Look: Round 2

Nine rapid fire presentations on the applications of AI in Clinical Care

To view speakers and topics, click here.

11:30 am – 11:45 am
11:45 am – 1:00 pm

Discovery Café Sessions

Lunch with Experts: Intensive sessions addressing cutting-edge artificial intelligence topics.

Applying AI to Save Lives During the Opioid Crisis

The U.S. is in the throes of a devastating epidemic of opioid addiction and overdose — some 130 people die nationally every day from opioids, says the National Institute on Drug Abuse. With a total economic cost of more than $78 billion a year, AI is being harnessed to develop new tools that can help alleviate this national crisis. This session will discuss AI-based strategies that academic and industry teams are leveraging to help clinical and public health officials better predict, identify, and treat opioid addiction, and also data privacy concerns.

Moderator: Thomas Sequist, MD, Chief Quality & Safety Officer, PHS

Bob Burgin, CEO, Amplifire Healthcare Alliance

Carm Huntress, CEO, RxRevu Inc

Sarah Wakeman, MD, Medical Director, Substance Use Disorder Initiative, MGH; Assistant Professor, Medicine, HMS

Scott Weiner, MD, Director, Brigham Comprehensive Opioid Response and Education (B-CORE) Program, BH; Assistant Professor, HMS

 

Community Hospitals: Key Component in Healthcare Transformation

Community hospitals are the largest sources of patient care in the U.S. As such, they represent a frontier in the transformation of health care. How are these organizations using AI and digital technologies to drive transformation? What are the distinctions from academic medical centers? This session will address these and other topics that impact community hospitals.

Moderator: Michael Jaff, DO, President, NWH, PHS, Professor of Medicine, HMS

Fabien Beckers, PhD, CEO, Arterys

Joanna Geisinger, CEO, TORq Interface

John Miller, MD, Director, Retinal Imaging, MEE; Assistant Professor, Ophthalmology, HMS

Lee Schwamm, MD, Director, Center for TeleHealth and Exec Vice Chair, Neurology, MGH; Professor, Neurology, HMS

Tal Wenderow, CEO, Beyond Verbal

 

Digital Management of Diabetes

Across the spectrum of patient care, the management of diabetes has been flooded with new technology and treatment options for both type 1 and type 2 diabetes – there is a range of new devices and software, including automatic insulin infusion systems, glucose sensors, AI-based algorithms and decision support tools, with an artificial pancreas on the horizon. This session will focus on these areas and clinical use cases that highlight the value of AI.

Moderator: Deborah Wexler, MD, Clinical Director, Diabetes Center, MGH; Associate Professor, HMS

Marie McDonnell, MD, Section Chief and Director, Diabetes Program, BH; Lecturer, HMS

Michael Meissner, PhD, CTO and VP, MED, Sanofi

Joshua Riff, MD, CEO, Onduo

Marie Schiller, VP, Connected Care and Insulins Product Development and Site Head, Cambridge Innovation Center, Eli Lilly

 

AI and Its Impact on the Future of Emergency Care

There are over 136 million Emergency Department visits annually in the U.S. providing 24/7 unscheduled treatment for problems from minor illness to life threatening traumatic injuries.  Emergency department care teams provide high quality, safe care in an efficient fashion.  In this session, we consider the future of AI in emergency care from the initial decision to seek emergency care, to diagnostic processes within the ED and final disposition decision..  From chat bots for patient triage, telehealth for patient visits to machine learning outcome prediction, we will consider how these novel technologies will impact emergency care delivery.

Moderator: Adam Landman, MD, VP and CIO, BH; Associate Professor of Emergency Medicine, HMS

Peter Chai, MD, Assistant Professor, Emergency Medicine, BH, HMS

Emily Hayden, MD, Attending Physician, Emergency Medicine, MGH; Instructor, Surgery, HMS

Kohei Hasegawa, MD, Attending Physician, Emergency Medicine, MGH; Associate Professor, Emergency Medicine, HMS

Sean Kelly, MD, CMO, Imprivata; Assistant Professor, Emergency Medicine, HMS

Bijoy Sagar, VP, Chief Digital Technology Officer, Stryker

 

Mental Health, Smartphone Apps and the Promise of AI

Patients can face significant barriers when it comes to accessing high-quality, evidence-based treatment for mental illness. AI-enabled technologies, including smartphone-based tools, that may help close this treatment gap for patients worldwide. This session will focus on efforts to develop smartphone apps and other tools, including those designed to help predict patients’ moods and provide cognitive behavioral therapy.

Moderator: Sabine Wilhelm, PhD, Chief of Psychology; Director, OCD and Related Disorders Program, MGH; Professor, Psychology, HMS

Jennifer Gentile, PsyD, SVP, US Clinical Operations, Ieso Digital Health

Thomas McCoy, MD, Director of Research, Center for Quantitative Health, MGH; Assistant Professor, Psychiatry and Medicine, HMS

Christopher Molaro, CEO, Neuroflow

David Silbersweig, MD, Chairman, Department of Psychiatry, BH; Stanley Cobb Professor of Psychiatry, HMS

Jeremy Sohn, VP, Global Head of Digital Business Development and Licensing , Novartis

 

From Startup to Impact (Pharma and Diagnostics)

This session will introduce you to five leading start-up companies who will each share their respective impact in the pharmaceutical and diagnostic realms in 10-minute pitches.

Moderator: James Brink, MD, Radiologist-in-Chief, MGH; Juan M. Taveras Professor of Radiology, HMS

Moderator: James Nicholls, Managing Director, Fitzroy Health

Sarah Beeby, EVP, GM Lifesciences, Clinithink

Charles Cadieu, PhD, CEO, Bay Labs

JB Michel, PhD, SVP Data Science & GM USA, BenevolentAI

Art Papier, MD, CEO, VisualDx

Alex Zhavoronkov, PhD, CEO, Insilico Medicine, Inc

1:00 pm – 1:15 pm
1:15 pm – 1:30 pm
Bayer Ballroom

Opening Remarks

  • Interim President and CEO, Chief Academic Officer, PHS; Laurie Carrol Guthart Professor of Medicine, HMS; 2019 Forum Co-Chair
1:30 pm – 2:00 pm
Bayer Ballroom

AI Strategy: AI from the Top

As the potential of AI comes into clearer view, many academic medical centers are taking notice and crafting institutional strategies for incorporating AI into clinical practice. But where are the most meaningful opportunities? What are the biggest challenges? And, importantly, will patient care be noticeably different — better, more available, and/or less costly?

  • Board Member, PHS; President Emerita and Professor of Neuroscience, MIT
  • Cross institutional cooperation is advocated
  • AI – what it will deliver in 2 years
  • what is the role of the Top management
  • how we mwasure how we do
  • Ethics and bias  in AI vs non-AI World
  • Chief Data Science Officer, PHS; Vice Chairman, Radiology, MGH; Associate Professor, Radiology, HMS
  • scaling Machine learning focused areas high accuracy, training ground truth, today the humans establish it in the future with AI ground truth will be created by AI
  • how to handle and move the intelligence and discoveries across units
  • Chief Digital Health Officer, PHS
  • Digitization of documentation – recording the session, Nauance – AI does the borden of communication translation
  • Easy button comparison of f patients wwith same ocndition what was the treatment
  • Chief Clinical Officer, PHS; Professor of Medicine, HMS; 2019 Forum Co-Chair
  • Future 5-10 years EHR is dehumanizing at present but with AI EHR will humanize again the relations of Physician and Patients

 

2:00 pm – 2:30 pm
Bayer Ballroom

1:1 Fireside Chat: Jensen Huang, CEO, NVIDIA

Introduction by: Cathy Minehan
  • Managing Director, Arlington Advisory Partners; Chairman, Board of Trustees, MGH
  • Chief Data Science Officer, PHS; Vice Chairman, Radiology, MGH; Associate Professor, Radiology, HMS
  • CEO, NVIDIA, established in 1993 graphics, Genomics analysis
  • storage data validation and
  • AI is reinventing computer graphics taught a NN to produce animation by virtual reality in robotics
  • in next three year: Crypo-currency was not foreseen
  • Data Science ingesting data , processing doing analytics
  • RAPIDS – open source data centers clouds and the edge working together
  • AI needs to be at the edge computing to be create at the edge not in the Cloud
  • self driving cars computation odne at the edge
  • Redundence and diversity – approach is diverse
  • In Radiology – democratization of AI announced today with NVIDIA & Partners
  • Driver intervene, Radiologist will intervene
  • Concept of “Beta” – Cloud application is in Beta
  • SW: data driven algorithm written by AI and know to learn amazing results
  • Conditions for NVIDIA to succeed: Speed, SW defined, pipeline flow data curated validated
  • expertise in the company
  • In 5 years: breakthrough NLP – summarize what was said
  • Curations done by AI
  • One shot learning – AI contextual aware Knowing who goes where, when and what acronyms are
  • AI: is software – yes SW that writes SW AI is automation of Automation

 

2:30 pm – 2:45 pm
Bayer Ballroom

Remarks: The Honorable Charlie Baker

Introduction by: Scott Sperling
  • Co-President, Thomas H. Lee Partners; Chairman of the Board of Directors, PHS
  • Governor of the Commonwealth of Massachusetts
  • AI to assist practitioners in their decisions
  • Information explotions to clinician
  • medical infrastructure needs AI
  • Healthcare is held to a higher standard, people believe in Practitioners – Healthcare is held in very high esteem

 

2:45 pm – 3:35 pm
Bayer Ballroom

Real World Evidence and Trial Optimization in the AI Era

AI is a tool for conducting faster, more efficient clinical trials. Panelists will discuss how AI-enabled methods can further adaptive trial capabilities, trial design and trial management.

Moderator: Thomas Lynch, MD
  • EVP and CSO, R&D, Bristol-Myers Squibb
  • why sharing data is so hard?
  • IBM Watson – PDF can be read by Watson and come out with a Diagnosis
  • Deputy Commissioner, FDA
  • AI assists in recruitment
  • Modernization of clinical trial is acknowledged
  • Data standards for EHR oncology context
  • EVP MA&PV and Bayer CMO, Bayer AG
  • control arms in rare diseases
  • diagnostics in hypertension
  • drug safety – #AI works
  • Chief Architect, Microsoft Healthcare
  • sharing data semantic interoperability is available
  • No clinical data model
  • Which symptoms actual were experienced?
  • Blockchain
  • CEO, My Own Med Inc.
  • Wearable Pharma is adding this dimens
  • Executive Director, Clinical Trials Office, PHS; Associate Professor of Medicine, HMS
  • computation, pattern recognitions to make CT more efficient
  • competitive model among sponsors hinders data sharing
3:35 pm – 4:25 pm
Bayer Ballroom

AI Driven Value-Based Care

As providers embrace value-based approaches, the demands of clinical data collection, assessment, and information-sharing loom large. In this data-driven environment, clinicians must sift through ever-growing pools of information that can exceed the limits of human capability. An assortment of AI-based solutions is now emerging that may offer some relief. Panelists will discuss how these approaches are helping to support better, more personalized care, and the challenges faced by clinicians and managers for effective adoption.

Moderator: Timothy Ferris, MD
  • CEO, MGPO; Professor of Medicine, HMS
  • CEO, American Heart Association
  • guideline on HTN, 1/2 million wake up with HTN a day after guidelines were enacted
  • AI will not be able to replace a clinician encouraging a patient
  • AI to free time of HC professional
  • EVP, President, Network Solutions, Change Healthcare
  • 1 trillion $ is wasted Healthcare is not consumer friendly #AI has opportunities to innovate home-based solutions
  • consumer focus technologies hand held devices
  • Levers
  • CEO, NHS England
  • AI can free time for health professionals
  • diagnostics
  • productivity in Healthcare has impact of the entire econommy US – 3 trillions size of HC sector
  • 2 1/2 million literature new to clinician evry year – AI will assist
  • Clinician explainability is very important
  • AI to benefit Healthcare for all
4:25 pm – 5:15 pm
Bayer Ballroom

Cardiovascular Care: Reinvented Through AI

Cardiovascular diseases remain the leading cause of death worldwide and an expense, making this area ripe for AI-enabled innovations. Teams are pursuing a range of AI-based tools in cardiovascular medicine: including AI-powered drug discovery and diagnostics to automated cardiac image analyses and AI-guided care delivery pathways. Panelists will discuss where AI is having a sizeable impact. The discussion will also include the perspectives of a patient who benefited from AI-enabled cardiovascular care.

  • Vice Chair for Scientific Innovation, Department of Medicine, BH; Associate Professor of Medicine, HMS
  • SVP, Global Head of Digital and Analytics, Sanofi
  • COTY in Copenhagen – AI augment capability of EMTs dispatcher is prompted with questions to decide if this call is Heart arrest caving few minutes for EMT response
  • Patient
  • Independent Recording Engineer Burke Recording
  • President, Bayer Pharma Americas Region, Bayer
  • In-silicon modeling is AI based and shorten cycle of drug discovery
  • Bridge clinical care and with clinical trials
  • Challenge island of dat are disconnected,
  • Chief Cardiovascular Imaging, MGH; Professor, Radiology, HMS

 

  • To see a neurologist you need to have an MRI done already
  • Chest CT, Abdominal CT Chest X-ray — done
  • CVD CT report five pages long, prognostics — AI will tell MD what medication to suggest
  • clinical care more standardized
  • AI in clinical trial is a big premise
  • No more trials if perpatient the cost id more than $5,000
  • AI is a tool to enable lower cost clinical trials
  • imaging data sharing in what ever form
  • ML and AI at all Radiology conferences
  • QA criteria – what is quality data, to inform care
  • EVP/GM, Healthcare and Life Sciences, Persistent Systems
  • How to use AI clinical work flow goal – to be sw driven AI is a component
  • large systems sw automation data and platform dat acapture is very importnat
5:15 pm – 5:45 pm
Bayer Ballroom

1:1 Fireside Chat: Seema Verma, Administrator, Centers for Medicare & Medicaid Services

Moderator: Sree Chaguturu, MD
  • Chief Population Health Officer, PHS; Assistant Professor, Medicine, HMS
  • Administrator, Centers for Medicare and Medicaid Services
  • 2020 20% of all expenses spent will be on Healthcare in the US
  • Gov’t was a barrier to innovations
  • initiative of cutting regulations
  • innovation – how we pay providers for value produced vs regulation that stay in the way
  • gov’t slow to respond: FDA approval and CMS access to treatment and reimbursement
  • Analysis of drug a patient takes, CMS – quality, medical record given to patient across all providers they use and be able to give to a new provides all historical data
  • Data privacy and security
  • Innovators in Colorado – health care cost need be lowered in a major way
5:45 pm – 6:45 pm

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The Regulatory challenge in adopting AI

Author and Curator: Dror Nir, PhD

In the last couple of years we are witnessing a surge of AI applications in healthcare. It is clear now, that AI and its wide range of health-applications are about to revolutionize diseases’ pathways and the way the variety of stakeholders in this market interact.

Not surprisingly, the developing surge has waken the regulatory watchdogs who are now debating ways to manage the introduction of such applications to healthcare. Attributing measures to known regulatory checkboxes like safety, and efficacy is proving to be a complex exercise. How to align claims made by manufacturers, use cases, users’ expectations and public expectations is unclear. A recent demonstration of that is the so called “failure” of AI in social-network applications like FaceBook and Twitter in handling harmful materials.

‘Advancing AI in the NHS’ – is a report covering the challenges and opportunities of AI in the NHS. It is a modest contribution to the debate in such a timely and fast-moving field!  I bring here the report’s preface and executive summary hoping that whoever is interested in reading the whole 50 pages of it will follow this link: f53ce9_e4e9c4de7f3c446fb1a089615492ba8c

Screenshot 2019-04-07 at 17.18.18

 

Acknowledgements

We and Polygeia as a whole are grateful to Dr Dror Nir, Director, RadBee, whose insights

were valuable throughout the research, conceptualisation, and writing phases of this work; and to Dr Giorgio Quer, Senior Research Scientist, Scripps Research Institute; Dr Matt Willis, Oxford Internet Institute, University of Oxford; Professor Eric T. Meyer, Oxford Internet Institute, University of Oxford; Alexander Hitchcock, Senior Researcher, Reform; Windi Hari, Vice President Clinical, Quality & Regulatory, HeartFlow; Jon Holmes, co-founder and Chief Technology Officer, Vivosight; and Claudia Hartman, School of Anthropology & Museum Ethnography, University of Oxford for their advice and support.

Author affiliations

Lev Tankelevitch, University of Oxford

Alice Ahn, University of Oxford

Rachel Paterson, University of Oxford

Matthew Reid, University of Oxford

Emily Hilbourne, University of Oxford

Bryan Adriaanse, University of Oxford

Giorgio Quer, Scripps Research Institute

Dror Nir, RadBee

Parth Patel, University of Cambridge

All affiliations are at the time of writing.

Polygeia

Polygeia is an independent, non-party, and non-profit think-tank focusing on health and its intersection with technology, politics, and economics. Our aim is to produce high-quality research on global health issues and policies. With branches in Oxford, Cambridge, London and New York, our work has led to policy reports, peer-reviewed publications, and presentations at the House of Commons and the European Parliament. http://www.polygeia.com @Polygeia © Polygeia 2018. All rights reserved.

Foreword

Almost every day, as MP for Cambridge, I am told of new innovations and developments that show that we are on the cusp of a technological revolution across the sectors. This technology is capable of revolutionising the way we work; incredible innovations which could increase our accuracy, productivity and efficiency and improve our capacity for creativity and innovation.

But huge change, particularly through adoption of new technology, can be difficult to  communicate to the public, and if we do not make sure that we explain carefully the real benefits of such technologies we easily risk a backlash. Despite good intentions, the care.data programme failed to win public trust, with widespread worries that the appropriate safeguards weren’t in place, and a failure to properly explain potential benefits to patients. It is vital that the checks and balances we put in place are robust enough to sooth public anxiety, and prevent problems which could lead to steps back, rather than forwards.

Previous attempts to introduce digital innovation into the NHS also teach us that cross-disciplinary and cross-sector collaboration is essential. Realising this technological revolution in healthcare will require industry, academia and the NHS to work together and share their expertise to ensure that technical innovations are developed and adopted in ways that prioritise patient health, rather than innovation for its own sake. Alongside this, we must make sure that the NHS workforce whose practice will be altered by AI are on side. Consultation and education are key, and this report details well the skills that will be vital to NHS adoption of AI. Technology is only as good as those who use it, and for this, we must listen to the medical and healthcare professionals who will rightly know best the concerns both of patients and their colleagues. The new Centre for Data Ethics and Innovation, the ICO and the National Data Guardian will be key in working alongside the NHS to create both a regulatory framework and the communications which win society’s trust. With this, and with real leadership from the sector and from politicians, focused on the rights and concerns of individuals, AI can be advanced in the NHS to help keep us all healthy.

Daniel Zeichner

MP for Cambridge

Chair, All-Party Parliamentary Group on Data Analytics

 

Executive summary

Artificial intelligence (AI) has the potential to transform how the NHS delivers care. From enabling patients to self-care and manage long-term conditions, to advancing triage, diagnostics, treatment, research, and resource management, AI can improve patient outcomes and increase efficiency. Achieving this potential, however, requires addressing a number of ethical, social, legal, and technical challenges. This report describes these challenges within the context of healthcare and offers directions forward.

Data governance

AI-assisted healthcare will demand better collection and sharing of health data between NHS, industry and academic stakeholders. This requires a data governance system that ensures ethical management of health data and enables its use for the improvement of healthcare delivery. Data sharing must be supported by patients. The recently launched NHS data opt-out programme is an important starting point, and will require monitoring to ensure that it has the transparency and clarity to avoid exploiting the public’s lack of awareness and understanding. Data sharing must also be streamlined and mutually beneficial. Current NHS data sharing practices are disjointed and difficult to negotiate from both industry and NHS perspectives. This issue is complicated by the increasing integration of ’traditional’ health data with that from commercial apps and wearables. Finding approaches to valuate data, and considering how patients, the NHS and its partners can benefit from data sharing is key to developing a data sharing framework. Finally, data sharing should be underpinned by digital infrastructure that enables cybersecurity and accountability.

Digital infrastructure

Developing and deploying AI-assisted healthcare requires high quantity and quality digital data. This demands effective digitisation of the NHS, especially within secondary care, involving not only the transformation of paper-based records into digital data, but also improvement of quality assurance practices and increased data linkage. Beyond data digitisation, broader IT infrastructure also needs upgrading, including the use of innovations such as wearable technology and interoperability between NHS sectors and institutions. This would not only increase data availability for AI development, but also provide patients with seamless healthcare delivery, putting the NHS at the vanguard of healthcare innovation.

Standards

The recent advances in AI and the surrounding hype has meant that the development of AI-assisted healthcare remains haphazard across the industry, with quality being difficult to determine or varying widely. Without adequate product validation, including in

real-world settings, there is a risk of unexpected or unintended performance, such as sociodemographic biases or errors arising from inappropriate human-AI interaction. There is a need to develop standardised ways to probe training data, to agree upon clinically-relevant performance benchmarks, and to design approaches to enable and evaluate algorithm interpretability for productive human-AI interaction. In all of these areas, standardised does not necessarily mean one-size-fits-all. These issues require addressing the specifics of AI within a healthcare context, with consideration of users’ expertise, their environment, and products’ intended use. This calls for a fundamentally interdisciplinary approach, including experts in AI, medicine, ethics, cognitive science, usability design, and ethnography.

Regulations

Despite the recognition of AI-assisted healthcare products as medical devices, current regulatory efforts by the UK Medicines and Healthcare Products Regulatory Agency and the European Commission have yet to be accompanied by detailed guidelines which address questions concerning AI product classification, validation, and monitoring. This is compounded by the uncertainty surrounding Brexit and the UK’s future relationship with the European Medicines Agency. The absence of regulatory clarity risks compromising patient safety and stalling the development of AI-assisted healthcare. Close working partnerships involving regulators, industry members, healthcare institutions, and independent AI-related bodies (for example, as part of regulatory sandboxes) will be needed to enable innovation while ensuring patient safety.

The workforce

AI will be a tool for the healthcare workforce. Harnessing its utility to improve care requires an expanded workforce with the digital skills necessary for both developing AI capability and for working productively with the technology as it becomes commonplace.

Developing capability for AI will involve finding ways to increase the number of clinician-informaticians who can lead the development, procurement and adoption of AI technology while ensuring that innovation remains tied to the human aspect of healthcare delivery. More broadly, healthcare professionals will need to complement their socio-emotional and cognitive skills with training to appropriately interpret information provided by AI products and communicate it effectively to co-workers and patients.

Although much effort has gone into predicting how many jobs will be affected by AI-driven automation, understanding the impact on the healthcare workforce will require examining how jobs will change, not simply how many will change.

Legal liability

AI-assisted healthcare has implications for the legal liability framework: who should be held responsible in the case of a medical error involving AI? Addressing the question of liability will involve understanding how healthcare professionals’ duty of care will be impacted by use of the technology. This is tied to the lack of training standards for healthcare professionals to safely and effectively work with AI, and to the challenges of algorithm interpretability, with ”black-box” systems forcing healthcare professionals to blindly trust or distrust their output. More broadly, it will be important to examine the legal liability of healthcare professionals, NHS trusts and industry partners, raising questions

Recommendations

  1. The NHS, the Centre for Data Ethics and Innovation, and industry and academic partners should conduct a review to understand the obstacles that the NHS and external organisations face around data sharing. They should also develop health data valuation protocols which consider the perspectives of patients, the NHS, commercial organisations, and academia. This work should inform the development of a data sharing framework.
  2. The National Data Guardian and the Department of Health should monitor the NHS data opt-out programme and its approach to transparency and communication, evaluating how the public understands commercial and non-commercial data use and the handling of data at different levels of anonymisation.
  3. The NHS, patient advocacy groups, and commercial organisations should expand public engagement strategies around data governance, including discussions about the value of health data for improving healthcare; public and private sector interactions in the development of AI-assisted healthcare; and the NHS’s strategies around data anonymisation, accountability, and commercial partnerships. Findings from this work should inform the development of a data sharing framework.
  4. The NHS Digital Security Operations Centre should ensure that all NHS organisations comply with cybersecurity standards, including having up-to-date technology.
  5. NHS Digital, the Centre for Data Ethics and Innovation, and the Alan Turing Institute should develop technological approaches to data privacy, auditing, and accountability that could be implemented in the NHS. This should include learning from Global Digital Exemplar trusts in the UK and from international examples such as Estonia.
  6. The NHS should continue to increase the quantity, quality, and diversity of digital health data across trusts. It should consider targeted projects, in partnership with professional medical bodies, that quality-assure and curate datasets for more deployment-ready AI technology. It should also continue to develop its broader IT infrastructure, focusing on interoperability between sectors, institutions, and technologies, and including the end users as central stakeholders.
  7. The Alan Turing Institute, the Ada Lovelace Institute, and academic and industry partners in medicine and AI should develop ethical frameworks and technological approaches for the validation of training data in the healthcare sector, including methods to minimise performance biases and validate continuously-learning algorithms.
  8. The Alan Turing Institute, the Ada Lovelace Institute, and academic and industry partners in medicine and AI should develop standardised approaches for evaluating product performance in the healthcare sector, with consideration for existing human performance standards and products’ intended use.
  9. The Alan Turing Institute, the Ada Lovelace Institute, and academic and industry partners in medicine and AI should develop methods of enabling and evaluating algorithm interpretability in the healthcare sector. This work should involve experts in AI, medicine, ethics, usability design, cognitive science, and ethnography, among others.
  10. Developers of AI products and NHS Commissioners should ensure that usability design remains a top priority in their respective development and procurement of AI-assisted healthcare products.
  11. The Medicines and Healthcare Products Regulatory Agency should establish a digital health unit with expertise in AI and digital products that will work together with manufacturers, healthcare bodies, notified bodies, AI-related organisations, and international forums to advance clear regulatory approaches and guidelines around AI product classification, validation, and monitoring. This should address issues including training data and biases, performance evaluation, algorithm interpretability, and usability.
  12. The Medicines and Healthcare Products Regulatory Agency, the Centre for Data Ethics and Innovation, and industry partners should evaluate regulatory approaches, such as regulatory sandboxing, that can foster innovation in AI-assisted healthcare, ensure patient safety, and inform on-going regulatory development.
  13. The NHS should expand innovation acceleration programmes that bridge healthcare and industry partners, with a focus on increasing validation of AI products in real-world contexts and informing the development of a regulatory framework.
  14. The Medicines and Healthcare Products Regulatory Agency and other Government bodies should arrange a post-Brexit agreement ensuring that UK regulations of medical devices, including AI-assisted healthcare, are aligned as closely as possible to the European framework and that the UK can continue to help shape Europe-wide regulations around this technology.
  15. The General Medical Council, the Medical Royal Colleges, Health Education England, and AI-related bodies should partner with industry and academia on comprehensive examinations of the healthcare sector to assess which, when, and how jobs will be impacted by AI, including analyses of the current strengths, limitations, and workflows of healthcare professionals and broader NHS staff. They should also examine how AI-driven workforce changes will impact patient outcomes.
  16. The Federation of Informatics Professionals and the Faculty of Clinical Informatics should continue to lead and expand standards for health informatics competencies, integrating the relevant aspects of AI into their training, accreditation, and professional development programmes for clinician-informaticians and related professions.
  17. Health Education England should expand training programmes to advance digital and AI-related skills among healthcare professionals. Competency standards for working with AI should be identified for each role and established in accordance with professional registration bodies such as the General Medical Council. Training programmes should ensure that ”un-automatable” socio-emotional and cognitive skills remain an important focus.
  18. The NHS Digital Academy should expand recruitment and training efforts to increase the number of Chief Clinical Information Officers across the NHS, and ensure that the latest AI ethics, standards, and innovations are embedded in their training programme.
  19. Legal experts, ethicists, AI-related bodies, professional medical bodies, and industry should review the implications of AI-assisted healthcare for legal liability. This includes understanding how healthcare professionals’ duty of care will be affected, the role of workforce training and product validation standards, and the potential role of NHS Indemnity and no-fault compensation systems.
  20. AI-related bodies such as the Ada Lovelace Institute, patient advocacy groups and other healthcare stakeholders should lead a public engagement and dialogue strategy to understand the public’s views on liability for AI-assisted healthcare.

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Digital Therapeutics: A Threat or Opportunity to Pharmaceuticals


Digital Therapeutics: A Threat or Opportunity to Pharmaceuticals

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Digital Therapeutics (DTx) have been defined by the Digital Therapeutics Alliance (DTA) as “delivering evidence based therapeutic interventions to patients, that are driven by software to prevent, manage or treat a medical disorder or disease”. They might come in the form of a smart phone or computer tablet app, or some form of a cloud-based service connected to a wearable device. DTx tend to fall into three groups. Firstly, developers and mental health researchers have built digital solutions which typically provide a form of software delivered Cognitive-Behaviour Therapies (CBT) that help patients change behaviours and develop coping strategies around their condition. Secondly there are the group of Digital Therapeutics which target lifestyle issues, such as diet, exercise and stress, that are associated with chronic conditions, and work by offering personalized support for goal setting and target achievement. Lastly, DTx can be designed to work in combination with existing medication or treatments, helping patients manage their therapies and focus on ensuring the therapy delivers the best outcomes possible.

 

Pharmaceutical companies are clearly trying to understand what DTx will mean for them. They want to analyze whether it will be a threat or opportunity to their business. For a long time, they have been providing additional support services to patients who take relatively expensive drugs for chronic conditions. A nurse-led service might provide visits and telephone support to diabetics for example who self-inject insulin therapies. But DTx will help broaden the scope of support services because they can be delivered cost-effectively, and importantly have the ability to capture real-world evidence on patient outcomes. They will no-longer be reserved for the most expensive drugs or therapies but could apply to a whole range of common treatments to boost their efficacy. Faced with the arrival of Digital Therapeutics either replacing drugs, or playing an important role alongside therapies, pharmaceutical firms have three options. They can either ignore DTx and focus on developing drug therapies as they have done; they can partner with a growing number of DTx companies to develop software and services complimenting their drugs; or they can start to build their own Digital Therapeutics to work with their products.

 

Digital Therapeutics will have knock-on effects in health industries, which may be as great as the introduction of therapeutic apps and services themselves. Together with connected health monitoring devices, DTx will offer a near constant stream of data about an individuals’ behavior, real world context around factors affecting their treatment in their everyday lives and emotional and physiological data such as blood pressure and blood sugar levels. Analysis of the resulting data will help create support services tailored to each patient. But who stores and analyses this data is an important question. Strong data governance will be paramount to maintaining trust, and the highly regulated pharmaceutical industry may not be best-placed to handle individual patient data. Meanwhile, the health sector (payers and healthcare providers) is becoming more focused on patient outcomes, and payment for value not volume. The future will say whether pharmaceutical firms enhance the effectiveness of drugs with DTx, or in some cases replace drugs with DTx.

 

Digital Therapeutics have the potential to change what the pharmaceutical industry sells: rather than a drug it will sell a package of drugs and digital services. But they will also alter who the industry sells to. Pharmaceutical firms have traditionally marketed drugs to doctors, pharmacists and other health professionals, based on the efficacy of a specific product. Soon it could be paid on the outcome of a bundle of digital therapies, medicines and services with a closer connection to both providers and patients. Apart from a notable few, most pharmaceutical firms have taken a cautious approach towards Digital Therapeutics. Now, it is to be observed that how the pharmaceutical companies use DTx to their benefit as well as for the benefit of the general population.

 

References:

 

https://eloqua.eyeforpharma.com/LP=23674?utm_campaign=EFP%2007MAR19%20EFP%20Database&utm_medium=email&utm_source=Eloqua&elqTrackId=73e21ae550de49ccabbf65fce72faea0&elq=818d76a54d894491b031fa8d1cc8d05c&elqaid=43259&elqat=1&elqCampaignId=24564

 

https://www.s3connectedhealth.com/resources/white-papers/digital-therapeutics-pharmas-threat-or-opportunity/

 

http://www.pharmatimes.com/web_exclusives/digital_therapeutics_will_transform_pharma_and_healthcare_industries_in_2019._heres_how._1273671

 

https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/exploring-the-potential-of-digital-therapeutics

 

https://player.fm/series/digital-health-today-2404448/s9-081-scaling-digital-therapeutics-the-opportunities-and-challenges

 

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THE 3RD STAT4ONC ANNUAL SYMPOSIUM APRIL 25-27, 2019, HILTON, HARTFORD, CONNECTICUT, 315 Trumbull St, Hartford, CT 06103

Reporter: Stephen J. Williams, Ph.D.

SYMPOSIUM OBJECTIVES

The three-day symposium aims to bring oncologists and statisticians together to share new research, discuss novel ideas, ask questions and provide solutions for cancer clinical trials. In the era of big data, precision medicine, and genomics and immune-based oncology, it is crucial to provide a platform for interdisciplinary dialogues among clinical and quantitative scientists. The Stat4Onc Annual Symposium serves as a venue for oncologists and statisticians to communicate their views on trial design and conduct, drug development, and translations to patient care. To be discussed includes big data and genomics for oncology clinical trials, novel dose-finding designs, drug combinations, immune oncology clinical trials, and umbrella/basket oncology trials. An important aspect of Stat4Onc is the participation of researchers across academia, industry, and regulatory agency.

Meeting Agenda will be announced coming soon. For Updated Agenda and Program Speakers please CLICK HERE

The registration of the symposium is via NESS Society PayPal. Click here to register.

Other  2019 Conference Announcement Posts on this Open Access Journal Include:

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  • World Medical Innovation Forum, Partners Innovations, ARTIFICIAL INTELLIGENCE | APRIL 8–10, 2019 | Westin, BOSTON

https://worldmedicalinnovation.org/agenda/

Aviva Lev-Ari, PhD, RN Founder, LPBI Group

will cover this event in Real Time

@AVIVA1950

@pharma_BI

 

 

Monday, April 8, 2019

7:00 am – 8:00 am
7:00 am – 5:00 pm
8:00 am – 9:40 am
Bayer Ballroom

First Look

Nine rapid fire presentations on the applications of AI in Clinical Care

Moderator: Giles Boland, MD
  • Chair, Department of Radiology, BWH; Philip H. Cook Professor of Radiology, HMS
Moderator: Trung Do
  • VP, Business Development, Innovation, PHS
9:40 am – 9:55 am
9:55 am – 11:35 am
Bayer Ballroom

First Look

Nine rapid fire presentations on the applications of AI in Clinical Care

11:45 am – 1:00 pm

Discovery Café Sessions

Lunch with Top Leading Experts: Intensive sessions addressing cutting-edge artificial intelligence topics.

Applying AI to Save Lives During the Opioid Crisis

The U.S. is in the throes of a devastating epidemic of opioid addiction and overdose — some 130 people die in this country every day from opioids, says the National Institute on Drug Abuse. With a total economic cost of more than $78 billion a year, academic and industry organizations are harnessing AI to develop new tools that can help alleviate this national crisis. This session will discuss some of the AI-based strategies that academic and industry teams are leveraging to help clinical and public health officials better predict, identify, and treat opioid addiction, as well as some of the concerns around data privacy.

Moderator: Thomas Sequist, MD, Chief Quality & Safety Officer, PHS

Bob Burgin, CEO, Amplifire Healthcare Alliance

Carm Huntress, CEO, RxRevu Inc

Sarah Wakeman, MD, Medical Director, Substance Use Disorder Initiative, MGH; Assistant Professor, Medicine, HMS

Scott Weiner, MD, Director, Brigham Comprehensive Opioid Response and Education (B-CORE) Program, BWH; Assistant Professor, HMS

 

Community Hospitals: Key Component in Healthcare Transformation

Community hospitals are the largest sources of patient care in the U.S. As such, they represent a critical frontier in the transformation of health care. How are these organizations using AI and digital technologies to drive transformation? What are the key distinctions from academic medical centers? This session will address these and other critical topics that impact community hospitals and their essential, though often overlooked, role in health care.

Moderator: Michael Jaff, DO, President, NWH, PHS, Professor of Medicine, HMS

Fabien Beckers, PhD, CEO, Arterys

Joanna Geisinger, CEO, TORq Interface

Lee Schwamm, MD, Director, Center for TeleHealth and Exec Vice Chair, Neurology, MGH; Professor, Neurology, HMS

Tal Wenderow, CEO, Beyond Verbal

 

Digital Management of Diabetes

Across the full spectrum of patient care, the management of diabetes has been flooded with new technology and treatment options for both type 1 and type 2 diabetes – there is a range of new devices and software, including automatic insulin infusion systems, glucose sensors, AI-based algorithms and decision support tools, with artificial pancreas on the horizon. This session will focus on these areas as well as clinical use cases that highlight the value of AI.

Moderator: Deborah Wexler, MD, Clinical Director, Diabetes Center, MGH; Associate Professor, HMS

Marie McDonnell, MD, Section Chief and Director, Diabetes Program, BWH; Lecturer, HMS

Joshua Riff, MD, CEO, Onduo

 

Emergency Medicine

 

Mental Health and the Promise of AI

Moderator: Sabine Wilhelm, PhD, Chief of Psychology; Director, OCD and Related Disorders Program, MGH; Professor, Psychology, HMS

Thomas McCoy, MD, Director of Research, Center for Quantitative Health, MGH; Assistant Professor, Psychiatry & Medicine, HMS

Christopher Molaro, CEO, Neuroflow

David Silbersweig, MD, Chairman, Department of Psychiatry, BWH; Stanley Cobb Professor of Psychiatry, HMS

 

From Startup to Impact (Pharma and Diagnostics)

With all the hype surrounding AI, this session will focus on what really matters. Impact! Who is really moving the needle in life sciences today? This session will introduce you to five leading companies who will share their client stories over lunch.

Moderator: James Brink, MD, Radiologist-in-Chief, MGH; Juan M. Taveras Professor of Radiology, HMS

1:00 pm – 1:15 pm
1:15 pm – 1:45 pm
Bayer Ballroom
1:45 pm – 2:35 pm
Bayer Ballroom

AMC AI Strategy: AI from the Top

  • Board Member, PHS; President Emerita and Professor of Neuroscience, MIT
  • Chief Data Science Officer, PHS; Vice Chairman, Radiology, MGH; Associate Professor, Radiology, HMS
  • Chief Academic Officer, PHS; Laurie Carrol Guthart Professor of Medicine, Academic Dean for Partners, HMS; 2019 Forum Co-Chair
  • Chief Clinical Officer, PHS; Professor of Medicine, HMS; 2019 Forum Co-Chair
2:35 pm – 3:25 pm
Bayer Ballroom

RWE and Trial Optimization in the AI Era

Moderator: Thomas Lynch, MD
  • EVP and CSO, R&D, Bristol-Myers Squibb
  • CMO, CSO, SVP Oncology, Flatiron Health
  • EVP MA&PV and Bayer CMO, Bayer AG
  • Chief Architect, Microsoft Healthcare
  • CEO, My Own Med Inc.
  • Executive Director, Clinical Trials Office, PHS; Associate Professor of Medicine, HMS
3:25 pm – 4:15 pm
Bayer Ballroom

AI Driven Value-Based Care

Moderator: Timothy Ferris, MD
  • CEO, MGPO; Professor of Medicine, HMS
  • CEO, American Heart Association
  • EVP, President, Network Solutions Change Healthcare
  • Vice Chairman, Investment Banking and Managing Director Lazard Freres
  • CEO, NHS England
4:15 pm – 5:05 pm
Bayer Ballroom

Cardiovascular Care: Reinvented Through AI

  • Vice Chair for Scientific Innovation, Department of Medicine, BWH; Associate Professor of Medicine, HMS
  • President, Bayer Pharma Americas Region, Bayer
  • Director, Cardiac Imaging MR PET CT Program, MGH; Professor, Medicine, HMS
5:15 pm – 6:15 pm

Tuesday, April 9, 2019

7:00 am – 8:00 am
7:00 am – 5:00 pm
7:50 am – 8:00 am
Bayer Ballroom

Opening Remarks

  • Chief Innovation Officer, PHS; President, Partners HealthCare International
8:00 am – 8:50 am
Bayer Ballroom

Implementing AI in Cancer Care

  • Associate Surgeon, BWH; Richard E. Wilson Professor of Surgery in the Field of Surgical Oncology, HMS
  • Chief, Breast Imaging Division, MGH; Professor of Radiology, HMS
  • President and Co-Founder, LunaDNA
  • Delta Electronics Professor, Electrical Engineering and Computer Science Department, MIT
  • Director, Cancer Genome Analysis, Broad Institute; Professor of Pathology, HMS
  • CEO, insitro
8:50 am – 9:40 am
Bayer Ballroom

Imagining Medicine in the Year 2054

In 1984 Isaac Asimov was asked to predict what life in 2019 would be like. Using the same aperture, we as what will health care look like 35 years from now? What capabilities will clinicians have that they now struggle with? And what will be the biggest challenges? Current trends suggest that we will see some significant gains in the areas of cancer immunotherapy, gene therapy for devastating rare diseases, and treatments for common neuropsychiatric conditions, including schizophrenia and depression. Panelists will draw on their visionary perspective and will reflect on what to expect and why.

Moderator: Keith Flaherty, MD
  • Director, Clinical Research, MGH; Professor of Medicine, HMS
  • Vice Chair for Scientific Innovation, Department of Medicine, BWH; Associate Professor of Medicine, HMS
  • Director, Cellular Immunotherapy Program, MGH; Assistant Professor, Medicine, HMS
  • Vice-Chair, Neurology, Director, Genetics and Aging Research Unit, MGH; Joseph P. and Rose F. Kennedy Professor of Neurology, HMS
  • CEO, Biogen
9:40 am – 10:10 am
10:10 am – 10:40 am
Bayer Ballroom
10:40 am – 11:30 am
Bayer Ballroom

CEO Roundtable

Moderator: Anne Klibanski, MD
  • Chief Academic Officer, PHS; Laurie Carrol Guthart Professor of Medicine, Academic Dean for Partners, HMS; 2019 Forum Co-Chair
  • EVP and Chief Commercial Officer, Bristol-Myers Squibb
  • CEO, Philips
  • EVP, Head, Pharmaceuticals Research & Development, Bayer AG
  • CEO, Siemens Healthineers
  • CEO, GE Healthcare
11:45 am – 1:00 pm

Discovery Cafe Sessions

Lunch with Top Leading Experts: Intensive sessions addressing cutting-edge artificial intelligence topics.

Back Office of the Provider Future

Moderator: Peter Markell, EVP, Administration and Finance, CFO and Treasurer, PHS

Kent Ivanoff, CEO, VisitPay

Connie Moser, Chief Operating Officer, Verge Health

 

Chief Digital Strategy Officer Roundtable

With the advent of healthcare AI-enabled technologies, this session brings together several chief digital health officers from a range of organizations. The discussion will address key tradeoffs in sequencing technology across academic medical centers; what technologies are being prioritized; and how consumer expectations are impacting the future delivery model of healthcare.

Moderator: Alistair Erskine, MD, Chief Digital Health Officer, PHS

Michael Anderes, Chief Innovation and Digital Health Officer, Froedtert Health; President, Inception Health

Adam Landman, MD, VP and CIO, Brigham Health; Associate Professor of Emergency Medicine, HMS

Aimee Quirk, CEO, innovationOchsner

Richard Zane, MD, Chief Innovation Officer, UCHealth; Professor and Chair,Department of Emergency Medicine, University of Colorado School of Medicine

 

Innovation Fellows: A New Model of Collaboration

The Innovation Fellows Program provides short-term, experiential career development opportunities for future leaders in health care focused on accelerating collaborative innovation between science and industry. It facilitates personnel exchanges between Harvard Medical School staff from Partners’ hospitals and participating biopharmaceutical, device, venture capital, digital health, payor and consulting firms. A successful example of open innovation, Fellows and Hosts learn from each other as they collaborate on projects ranging from clinical development to digital health & artificial intelligence to new care delivery models and industry disruption. Come listen to the experience and insights of our panelists, including Fellows, Industry Partners and hospital leadership, and learn how this new model of collaboration can deliver value and lead to broader relationships between industry and academia.

 

Last Mile: Fully Implementing AI in Healthcare

Moderator: Keith Dreyer, DO, PhD, Chief Data Science Officer, PHS; Vice Chairman, Radiology, MGH; Associate Professor, Radiology, HMS

Katherine Andriole, PhD, Director of Research Strategy and Operations, MGH & BWH CCDS; Associate Professor, Radiology, HMS

Samuel Aronson, Executive Director, IT, Personalized Medicine, PHS

Seth Hain, VP of R&D, Epic

Jonathan Teich, MD, PhD, Chief Medical Information Officer, InterSystems; Emergency Medicine, BWH

 

Reimagining Disease Management

Moderator: Sree Chaguturu, MD, Chief Population Health Officer, PHS; Assistant Professor, Medicine, HMS

Murray Brozinsky, Chief Strategy Officer, Conversa

Jean Drouin, MD, CEO, Clarify Health Solutions

Sandhya Rao, MD, Senior Medical Director, Population Health, PHS; Assistant Professor, Medicine, HMS

 

Standards and Regulation: The Emerging AI Framework

 

From Startup to Impact (Provider Solutions)

With all the hype surrounding AI, this session will focus on what really matters. Impact! Who is really moving the needle for healthcare providers today? This session will introduce you to five leading companies who will share their client stories over lunch.

Moderator: Meredith Fisher, PhD, Partner, Partners Innovation Fund, PHS

 

1:00 pm – 1:10 pm
1:10 pm – 2:00 pm
Bayer Ballroom

China: AI Enabled Healthcare Leadership

Moderator: James Bradner, MD
  • President, Novartis Institutes for Biomedical Research
  • CEO, Infervision
  • Managing Partner, Qiming Venture Partners
2:00 pm – 2:30 pm
Bayer Ballroom

1:1 Fireside Chat: Mark Benjamin, CEO, Nuance

Moderator: Peter Slavin, MD
  • President, MGH; Professor, Health Care Policy, HMS
  • CEO, Nuance Communications
2:30 pm – 3:00 pm
3:00 pm – 3:50 pm
Bayer Ballroom

Getting to the AI Investment Decision

  • VP, Venture & Managing Partner, Partners Innovation Fund, PHS
  • Managing Director, Bain Capital Life Sciences
  • Managing Partner, Polaris Partners
  • SVP, Strategy, Commercialization & Innovation, Amgen
  • Managing Director, Healthcare Group, Goldman Sachs
  • Partner, Google Ventures
3:50 pm – 4:20 pm
Bayer Ballroom
4:20 pm – 5:10 pm
Bayer Ballroom

Consumer Healthcare and New Models of Care Delivery

Moderator: Diana Nole
  • CEO, Wolters Kluwer Health
  • President, Global Strategy Group, Samsung; Founder, CareVisor
  • VP and Global CTO, Sales, Dell EMC
  • President, Health Platforms, Verily Life Sciences
  • VP and Chief Health Officer, IBM Corporation
  • SVP, Head of Innovation and Health Equity Microsoft Healthcare
5:15 pm – 6:15 pm

Wednesday, April 10, 2019

7:00 am – 12:00 pm
7:30 am – 9:30 am
Bayer Ballroom

Innovation Discovery Grant Awardee Presentations

Twelve clinical AI teams culled through the Innovation Discovery Grant program present their work illustrating how AI can be used to improve patient health and healthcare delivery. This session is designed for investors, entrepreneurs, investigators, and others who are interested in commercializing AI opportunities that are currently in development with support from the Innovation Office.

Moderator: David Louis, MD
  • Pathologist-in-Chief, MGH; Benjamin Castleman Professor of Pathology, HMS
9:30 am – 10:00 am
10:00 am – 10:30 am
Bayer Ballroom

1:1 Fireside Chat: Stefan Oelrich, Member of the Board of Management; President, Pharmaceutical, Bayer AG

Moderator: Betsy Nabel, MD
  • President, Brigham Health; Professor of Medicine, HMS
  • Member of the Board of Management, Bayer AG; President, Pharmaceutical, Bayer AG
10:30 am – 11:00 am
Bayer Ballroom

1:1 Fireside Chat: Deepak Chopra, MD, Founder, The Chopra Foundation

Moderator: Rudolph Tanzi, PhD
  • Vice-Chair, Neurology, Director, Genetics and Aging Research Unit, MGH; Joseph P. and Rose F. Kennedy Professor of Neurology, HMS
  • Founder, The Chopra Foundation
11:00 am – 11:50 am
Bayer Ballroom

Using AI to Predict and Monitor Human Performance and Neurological Disease

  • Chief of Neurology, Co-Director, Neurological Clinical Research Institute, MGH; Julieanne Dorn Professor of Neurology, HMS
  • Chief Scientist, Dolby Laboratories
  • Global Therapeutic Head, Neuroscience Janssen Research & Development
  • EVP and CMO, Biogen
  • CEO, Kitman Labs
11:50 am – 12:50 pm
Bayer Ballroom

Disruptive Dozen: 12 Technologies that will reinvent AI in the Next 12 Months

The culture of innovation throughout Partners HealthCare naturally fosters robust discussions about new “disruptive” technologies and which ones will have the biggest impact on health care. The Disruptive Dozen was created to identify and rank the technologies that Partners faculty feel will break through over the next decade to significantly improve health care. This year, the Disruptive Dozen focuses on relevant advances and opportunities in artificial intelligence (AI).

Moderator: Jeffrey Golden, MD
  • Chair, Department of Pathology, BWH; Ramzi S. Cotran Professor of Pathology, HMS
  • Associate Chief, Infection Control Unit, MGH; Assistant Professor, Medicine, HMS
1:00 pm – 1:10 pm
Bayer Ballroom

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Artificial Intelligence in Health Care and in Medicine: Diagnosis & Therapeutics

Reporter: Aviva Lev-Ari, PhD, RN

 

News You Need to Know Today

Monday, January 21, 2019

Top Stories

Mayo Clinic researchers use AI, EKG test to detect heart condition

AI applied to an electrocardiogram (EKG) test reliably detected asymptomatic left ventricular dysfunction (ALVD)—a precursor to heart failure—and predicted which patients were most at risk of developing the condition in the future, according to a Mayo Clinic study.

Radiologists at Belgian hospital adopt Aidoc neuro tool into workflows

The radiology department at the Antwerp University Hospital in Belgium has incorporated an Aidoc tool that uses AI to help radiologists make faster diagnoses from CT scans, the university announced Wednesday, Jan. 16.

AI algorithm outperforms doctors at finding cervical cancer

AI may be better at spotting cervical cancer and precancer after a study found a deep-learning algorithm was more accurate at recognizing the disease than human doctors.

Machine learning detects, treats UTIs earlier

Scientists at the University of Surrey in Guildford, England, developed a tool that uses machine learning to identify and treat urinary tract infections at early stages in dementia patients, according to a study published in PLOS One.

Featured Articles

GE Healthcare, Vanderbilt to develop AI-powered apps for immunotherapy cancer treatments

GE Healthcare and the Vanderbilt University Medical Center (VUMC) have partnered to develop diagnostic tools and AI-powered applications to create safer and more precise immunotherapy treatments for cancer patients.

AI-powered app can screen for anemia with fingernail picture

An Atlanta research team has developed a smartphone app that can screen for anemia just by taking a picture of a person’s fingernails—paving the way for a new, noninvasive method to detect and diagnose the condition.

UPCOMING

[Video Presentation] Architecting AI: Rethinking Medical Imaging & Defining the Strategy

Jan 30, 2019 | 2PM ET We asked the questions you want to: Why is imaging ripe for AI? How will improvements in image processing and reconstruction, quality control and work list prioritization improve the practice of radiology? Register today.

SOURCE

From: AI in Healthcare <news@mail.clinical-innovation.com>

Reply-To: AI in Healthcare <news@mail.clinical-innovation.com>

Date: Monday, January 21, 2019 at 7:30 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: Diagnostics | January 2019

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