Transcript The California Institute for Telecommunications and

Report on Cal-(IT)2
UCSD School of Medicine Research Council
October 15, 2002
Dr. Larry Smarr
Director, California Institute for Telecommunications and
Information Technologies
Professor, Dept. of Computer Science and Engineering
Jacobs School of Engineering, UCSD
DeGeM:
An Integrated Knowledge Environment
Molecular Medicine
Wireless Health
Care Delivery
Deliver tools to enable
personalized medicine
Create the Living Laboratory
for Health Care Professional
Systems Biology
Knowledge and Data
Engineering Lab
Enabling querying,
analysis, and creative
exploration of large,
integrated data sets
Building the Biomedical Grid
Knowledge
Discovery
Statistics
Analysis
Telescience &
Telemedicine
Integrated
Information
Integrating data and models
across scales
Biosystems Informatics
Develop new informatics strategies
to discover meaning of biological
and biomedical data and processes
The Biomedical Informatics Research Network
BIRN Test-beds:
Multiscale Mouse Models of Disease, Human Brain Morphometrics, and
FIRST BIRN (10 site project for fMRI’s of Schizophrenics)
FIRST BIRN: Functional Imaging Research in
Schizophrenia Testbed
• Clinical Specific Aims
– Is Frontal and Temporal Lobe Dysfunction the Cause of
Schizophrenia?
– How can Treatment Reverse this Dysfunction?
• Technological Specific Aims
– Integration of 4D Data from Multiple Sites - Acquired with
Different Non-Invasive Imaging Devices
– Integration of Information Obtained with Different Brain
Activation Tasks
NSF Experimental Network Research Project
The “OptIPuter”
• Driven by Large Neuroscience and Earth Science Data
– NIH Biomedical Informatics Research Network
– NSF EarthScope (UCSD SIO)
• Removing Bandwidth as a Constraint
– Links Computing, Storage, Visualization and Networking
– Software and Systems Integration Research Agenda
• NSF Large Information Technology Research Proposal
– UCSD and UIC Lead Campuses
– USC, UCI, SDSU, NW Partnering Campuses
– Industrial Partners: IBM, Telcordia/SAIC, CENIC
• PI—Larry Smarr; Funded at $13.5M Over Five Years
– Start Date October 1, 2002
www.calit2.net/news/2002/9-25-optiputer.html
Providing a 21st Century
Internet Grid Infrastructure
Wireless Sensor Nets, Personal Communicators
Routers
Tightly Coupled Optically-Connected OptIPuter Core
Routers
Loosely Coupled Peer-to-Peer Computing & Storage
The OptIPuter Project is Allowing UCSD
to Develop a Futuristic Optical Networking Fabric
Phase I, Fall 02
Phase II, Jan. 03
Phase III, Dec 04
SDSC
Cal-(IT)2
Engineeing
Arts
Medicine
Physical
Sciences
Sixth
College
SIO
½
Mile
Preuss
School
Developing Training in
New Biomedical Technologies
• Creating a Comprehensive, Campus Wide Training Program
– Focus on Bioinformatics
– UC Irvine Institute For Genomics And Bioinformatics
– Awarded A $4.3 Million, Multiyear NIH Training Grant
• To Consolidate Current UCI Bioinformatics Training Programs
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Department of Information & Computer Science (ICS),
the College of Medicine,
the School of Physical Sciences,
the School of Biological Sciences
the Institute for Genomics and Bioinformatics
20 UCI Faculty Members
Current and Potential Markets for
Remote Patient Monitoring
• Wellness
– Fitness Monitoring
– Obesity Epidemic
• Ambulatory Hospital Patients
• Cardiac Out Patients
• Elder Care
– Global Population of People Over 65, Will
Increase 88% by 2025
• Clinical Trials
– New Drug Discovery
• Emergency Response
– Natural Disasters
– Homeland Security
Exercise Was the First
Wireless Monitoring Application
Research and Development Required
for Remote Patient Monitoring
• Systems Integration of Sensing, Computing, Data,
Communication
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Wireless Communications
Sensor Platform
Sensors
Data Systems
Monitoring Station Software
• Simultaneously With Work On:
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Legal Issues
Privacy and Security
Patient Safety Liability
Reimbursement Regulations
Conceptual Framework for
a Personal Medical Assistant
Heart
Rate
BP
Temp
Blood
Glucose
Sensors
-Sensor Data
-Control Data
-Local-area
networking
Personal Medical Assistant
- Multi-Network Gateway
Medical
- Processor:
Monitoring
-Sensor Data Analysis,
Station
-Monitoring,
-Event Analysis
-Coding
-Communicates With
-Data Shaping
Monitoring Station
-Control Data
Source: Sujit Dey. UCSD ECE
Medical Monitoring Service
Adaptive Data Collection
Image/Video/Bio-Sensors
Event-triggered
Data Filtering/
Aggregation
Medical
Monitoring
Center
Source: Sujit Dey.
UCSD ECE
Content/Data
Shaping
- Multiple Physicians
- Client Data Interpretation
- Physician Identification/Location
- Set-up Of End-End Connection
Between Patient Sensor Network
& Physician
- Heterogeneous Appliances
- Multiple Networks/Conditions
- Patient Data & Reference Data
From Monitoring Center
Secure, reliable, private, preferential communication
over a heterogeneous network
Adding Wireless Sensors to Systems-on-Chip
Will Create Brilliant Sensors
Applications
Critical New Role of
Power Aware Systems
Sensors Embedded
Software
Processors
Memory
Protocol
Processors
DSP
Source: Sujit Dey, UCSD ECE
Radio
Internet
The Navy’s Mobile Integrated Diagnostic and
Data Analysis System (MIDDAS)
Principal Investigator: Lawrence Hermansen
Requirement: The Casualty Care and Mgmt
Transition Summary (MED 217 – ORD/MNS)
sponsored by N93/USMC requires the development
of non-invasive methods for forward casualty
diagnosis and treatment.
Approach: Develop, test, and evaluate a Mobile
Integrated Diagnosis and Data Analysis System
(MIDDAS) for improved combat casualty care.
Description:
MIDDAS has three major components – Data Acquisition
Glove (DAG), Patient Sensor Unit (PSU), and Medical
Operations Monitor (MOM). The DAG is used to obtain
vital signs during initial triage. The PSU stays with patient
and continuously transmits vital sign data to the MOM
where the data are stored and monitored.
Status:
Project is in second year of development. This year will
focus on hardware and software improvements as well as
testing and evaluation in mock battlefield environments.
Schedule
1. Developed a prototype MIDDAS
demonstrator system
2. Improve hardware and software.
Test and evaluate in mock
battlefield environments
3. Refine overall system, include
wireless and prepare for Transition
Source: PI Lawrence Hermansen, NHRC, San Diego
Sponsor: Office of Naval Research
FY01
FY02
FY03
MIDDAS Requirements Issues
• Fundamental Issue:
– Enhanced Battlefield Trauma Management
• Derive Non-invasive Methods for Forward Casualty
Diagnosis and Treatment
• Utilization of Commercial-Off-The-Shelf (COTS)
Products with New Technologies
• Provide Rapid Triage of Multiple Patients
• Continuous and Simultaneous Monitoring of Multiple
Patients
• Users: Navy And Marine Corps Health Care Providers
Source: PI Lawrence Hermansen, NHRC, San Diego
Sponsor: Office of Naval Research
MIDDAS Has Three Major Components
• Data Acquisition Glove (DAG) That Contains Sensors
For Body Temperature, Blood Pressure,
Electrocardiogram, Oxygen Saturation And Heart Rate
– Used To Obtain Vital Signs During Initial Triage
• Patient Sensor Unit (PSU), Continuously Monitors
Heart Rate, Heart Rate Variability, Blood Pressure,
Temperature, Ecg, Respiration Rate, sPO2 (Oxygen
Saturation) Rate, And CO2 (End-Tidal) Levels
– The PSU Stays With Patient And Continuously
Transmits Vital Sign Data To The MOM
• Medical Operations Monitor (MOM) Located At Field
Hospital Stores Data And Allows For
Telecommunication
– The Data Are Stored And Monitored
Source: PI Lawrence Hermansen, NHRC, San Diego
Sponsor: Office of Naval Research
The Data Acquisition Glove (DAG)
is Used
byAcquisition
the Health
Care
Provider
Data
Glove
(DAG)
Sensors:
•Heart Rate
•Oxygen Saturation
•Body Temperature
•Electrocardiogram
•Blood Pressure
Source: PI Lawrence Hermansen, NHRC, San Diego
Sponsor: Office of Naval Research
MIDDAS Medical Operations Monitor (MOM)
Located At Field Hospital Displays Information
Karl Van Orden
Commander
647-90-4444
Field Hospital
Fair
Source: PI Lawrence Hermansen, NHRC, San Diego
Sponsor: Office of Naval Research
Clinical Trials Market Background
• Prescription Drug Expenditures - $125B 2001
• R&D $50B – 2001e - $40B/$10B Pharma/Bio
– Pre-Clinical Studies - $10B
– Clinical Studies - $20B
– $3.5B - Patient Monitoring
• Number of Compounds in Clinical Studies - >3500
• Avg. # of Studies per New Molecular Entity (NME) – 68
• Avg. # of Patients used in All Studies per NME - 4200
• Legg Mason – Feb. 2001 Presentation
• Parexel Pharmaceutical R&D Statistical Sourcebook 2001
Source: Darrel Drinan. CEO PhiloMetron
PhiloMetron
Confidential
Costs and Duration Estimates
Per New Molecular Entity
2.5
3
1
1.5
2
2.5
Duration
(Yrs)
1.5
Clinical Development
Basic Research
FDA filing/
approval &
launch
preparation
Preclinical
Development
Discovery
Phase 1
Discovery
target
4%
Lead
candidate
15%
Phase 2
Phase 3
NDA
filed
IND
10%
15%
22%
31%
NDA
approval
3%
Cost
(% of total)
PhiloMetron Market Focus
(78% of Total Expenditures)
•McKinsey & Co., Lehman Brothers, PhRMA, FDA.
Source: Darrel Drinan.
CEO PhiloMetron
PhiloMetron
Confidential
Wireless Clinical Trial
In-Vivo Drug Monitoring
• Accelerates Drug Development Time
• Basic Physiological Monitoring
• Detects ADME - Toxicity Events – “Fail Fast”
• Remote Data Analysis for Pharmacokinetics
PhiloMetron
Confidential
Source: Darrel Drinan. CEO PhiloMetron
Advantages of Continuous Monitoring
Measurement Methodology
• Current - Single point manual measurements
Time
T1
T2
T3
T4
T5
Measurement Points
T6
T7
• PhiloMetron System (continuous monitoring) Statistically
Valid
Sample
Time
Source: Darrel Drinan.
CEO PhiloMetron
Time and
Cost Savings
PhiloMetron
Confidential
Non-Invasive Platform - Smart Band-Aid®
Can Also Link to Invasive Sensors
Antenna
Transdermal Patch
“Smart Band-Aid®”
CPU/Comm Chip
Battery
Skin
Sensors:
- Physical
- Chemical
- Biological
• Patent Pending
Source: PhiloMetron