LIVE Day Three – World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 10, 2019 | Leaders in Pharmaceutical Business Intelligence (LPBI) Group

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LIVE Day Three – World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 10, 2019

April 10, 2019 by 2012pharmaceutical

LIVE Day Three – World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 10, 2019

Reporter: Aviva Lev-Ari, PhD, RN

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

3.1.2 LIVE Day Three – World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 10, 2019, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

Wednesday, April 10, 2019

7:00 am

Innovation Discovery Grant Awardee Presentations

Eleven clinical teams selected to receive highly competitive Innovation Discovery Grants present their work illustrating how AI can be used to improve patient health and health care 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.

To view speakers and topics, click here.

Where AI Meets Clinical Care

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.

Peter Dunn, MD

Vice President, Perioperative Services and Healthcare System Engineering, MGH; Assistant Professor, Anesthesia, HMS

Using Deep Learning to Optimize Hospital Capacity Management

collaboration with @MIT @MGH
deploy mobile app across all Partners institutions

Kevin Elias, MD

Director, Gynecologic Oncology Research Laboratory, BH; Assistant Professor, HMS

Screening for Cancer Using Serum miRNA Neural Networks

cancer screening fragmented process – tests not efficient No screening for many common cancer type
Cervical, Breast, Colon, Ovarian Uterus Cancer
Serum miRNA multiple cancer types

Alexandra Golby, MD

Director, Image-Guided Neurosurgery, BH; Professor, Neurosurgery and Radiology, HMS

Using Machine Learning to Optimize Optical Image Guidance for Brain Tumor Surgery

optical visualization in Neurosurgery – to improve Brain Cancer surgery Tumor removal complete resection could cause neurological deficits
BWH original research on Neuronavigations, intraops MRI
New Tool Real Time: Color code tumors using light diagnostics with machine learning
GUIDING Brain surgery, applicable for Breast Cancer
iP filling prototype creation, testing, pre-clinical testing, clinical protocol established academic-industrial partnerships
AI based – World 1st guided neurosurgery

Jayashree Kalpathy-Cramer, PhD

Director, QTIM Lab, MGH; Associate Professor, Radiology, HMS

DeepROP: Point-of-Care System for Diagnosis of Plus Disease in Retinopathy of Prematurity

Prematurity 1250 gr <31 weeks f gestation
ROP – Retinopathy of prematurity (ROP)
Images annotated Plus/not plus – algorithm for rating images “normal” or “plus”
DeepROP Applicationsinto Camera for data acquisition, iPhone

Jochen Lennerz, MD, PhD

Associate Director, Center for Integrated Diagnostics, MGH; Assistant Professor, HMS

Predicting Unnecessary Surgeries in High-Risk Breast Lesions

10% reduction of high risk lesion equivalent to $1.4Billion in cost savings
Funding for Production line

Bruno Madore, PhD

Associate Professor, Radiology, BH, HMS

Sensor Technology for Enhanced Medical Imaging

ML Ultrasound – Organ configuration Motion (OCM) sensor
Hybrid MRI-ultrasound acquisitions
Long term vision – collaboration with Duke for a wireless device

Jinsong Ouyang, PhD

Physicist, MGH; Associate Professor, HMS

Training a Neural Network to Detect Lesions

Approach – train a NN using artificially inserted lesions

APPLICATIONS:

Build unlimitted number of training sets using small 15-50 human data sets generated
bone lession detection using SPECT
cardiac detect myocardial perfusion SPECT
Tumor detection PET
Volume detection/locatization of artificial Spinal Lesions (L1-L5)

David Papke, MD, PhD

Resident, Surgical Pathology, BH; Clinical Fellow, HMS

Augmented Digital Microscopy for Diagnosis of Endometrial Neoplasia

See tweet

Martin Teicher, MD, PhD

Director, Developmental Biopsychiatry Research Program, McLean; Associate Professor, Psychiatry, HMS

Poly-Exposure Risk Scores for Psychiatric Disorders

MACE Scale – psychopathology development – collinearity
Identifying sensitivity period predictors of major depression
predicting risk in adolescence – dataset with high collinearity
Onset of depression age 10-15
50% assessment exposure to adversity – based on neuroimaging
Analytics and AI longitudinal studies

Christian Webb, PhD

Director, Treatment and Etiology of Depression, Youth Lab, McLean; Assistant Professor, Psychiatry, HMS

Leveraging Machine Learning to Match Depressed Patients to the Optimal Treatment

4-8 wks of treatment till psychotropic drugs work
Data driven approaches: ML can match better patients to antidepressant treatments (Zoloft vs Placebo responder /non responder)?
Large number of variables prediction, prognosis calculator, good vs poor outcome
Better on Zoloft vs Placebo

Brandon Westover, MD, PhD

Executive Director, Clinical Data Animation Center, MGH; Associate Professor, Neurology, HMS

seizure, prediction of next attack
EEG readings – accurate diagnosis on epilepsy
50 million World wide
automated epilepsy detection
@MGH – 1,063 EEGs 88,000 spikes 7 experts scored – not all agreed
How well can experts identify spikes?
Super spike detector is better than Experts – False positive 60% 87% Sensitivity vs 10% and 87% by AI

Moderator: David Louis, MD

Pathologist-in-Chief, MGH; Benjamin Castleman Professor of Pathology, HMS

Moderator: Clare Tempany, MD

Vice-Chair, Radiology Research, BH; Ferenc Jolesz MD Professor of Radiology, HMS

9:30 am – 10:00 am

Morning Break

10:00 am – 10:30 am
Bayer Ballroom

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

Introduction by: John Fish

CEO, Suffolk; Chairman of Board Trustees, Brigham Health

Moderator: Betsy Nabel, MD

President, Brigham Health; Professor of Medicine, HMS

Stefan Oelrich

Member of the Board of Management, Bayer AG; President, Pharmaceutical, Bayer AG

Chief Digital Officers

Leaders at the top needs to understand AI
Millennials needs to fill Baby boomer retiring
Boston – funding Research by NIH by private investment technology transfer to commercialization
Career advice: Academia is the first step for credibility move to Big Pharma, create own company
America economic strength built on innovation in Healthcare to invest
Leadership at Bayer: “Culture eat strategy for Breakfast”
AI overcoming barriers – AI improving what we know Medical imaging human vs machine – AI is the new norm – platforms Imaging AI device to detect Hypertension more accurately development of Bayer and Merck – Bayer leader in Radiology
Clinical research End point to reach compare
Future billion end point which therapeutic pathway is best for which patient
Incentives for risky strategy
Motivation to collaborate in Boston: Cardiology with broad Institute
BWH data and algorithms to increase knowledge
Pricing medicine around the World
US system in-transparent – patients do not understand Price of meds Rebates to Payers
Medical Part B – no pass to Rebates price tied to value
As industry – innovations in Pharma reduce healthcare costs Germany 15% of HealthCare on Drugs, generics, “Patented medicine 4%” of all Best in Europe
beak silos
In US training physicians to lead innovations

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
IMAGING of Brains of Women in Meditation – enlongate telemeres
inflammation decrease – Sleep health interactions exsercise learning new things diet
flashing from brain wastes – amaloydosis AD – 35 genes variance leading to disease

Deepak Chopra, MD

Founder, The Chopra Foundation – Body-Mind Connection
AI – re-invest our bodies Telemeres, transferdomics,
Nutrition, sleep, excercise, BP, HR, sympathetic vs non sympatheric nervous system breathing pattern, – microbiome subjective experience with Vitals emotional well being
emersive augmented
longer Telemerese – anti aging correlation
biomarkers vs states of energy
wisdom best knowledge for self awareness – highest intelligence – NOT artificial
Thoughts on being aware

11:00 am – 11:50 am
Bayer Ballroom

Using AI to Predict and Monitor Human Performance and Neurological Disease

In the quest for effective treatments aimed at devastating neurological diseases like Alzheimer’s and ALS, there is a critical need for robust methods to predict and monitor disease progression. AI-based approaches offer promise in this important area. Panelists will discuss efforts to map movement-related disorders and use machine learning to predict the path of disease with imaging and biomarkers.

Moderator: Merit Cudkowicz, MD

Chief of Neurology, Co-Director, Neurological Clinical Research Institute, MGH; Julieanne Dorn Professor of Neurology, HMS

Poppy Crum, PhD,

Chief Scientist, Dolby Laboratories Stanford & Adobe – measuring experience
convergence of skills
internal wellness measured in the ear, motions
Stimulate Vagal nerve through the ear for depression treatment
Legislation in CA contribution to spaces

Husseini Manji, MD

Global Therapeutic Head, Neuroscience Janssen Research & Development
Disease starts earlier Biogen contributions in the field
measurement surrogate indicators for outcome given interventions
Autism-spectrum not one disease
AI will enhance the human competence for measurement
UK based efforts to share dat and launch programs for Dementia
Conditions of Brain & Mind – declining cognitive
Democratization of discovery
AI benefit iterative process in changing and improving Algorithms — FDA approved algorithm needs several versions in the future
Complexity of CNS Polygenic gene scores
Dynamics of AI

Alfred Sandrock, MD, PhD

EVP and CMO, Biogen
MS – follow patients, patient reporting in 10 centers , vision cognitions –
Obtain measurement even on normal people for early detection – FDA introduced Stage 1,2,3 Biomarker based
Newborn Kit of screening teat early helps
Home monitoring at Home for onset of AD

Dr. Isaac Galatzer-Levy – NYU & AiCure

All CNS diseases are heterogeneous
ML requires collaboration
AiCure – Medication adherence monitoring from Voice of patients
Sampling populations – cell phone
Re-investigate studies that have failed with new AI tools

11:50 am – 12:50 pm
Bayer Ballroom

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

The Disruptive Dozen identifies and ranks the AI technologies that Partners faculty feel will break through over the next year to significantly improve health care.