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

Wireless Health Care Delivery Molecular Medicine

Deliver tools to enable personalized medicine Create the Living Laboratory for Health Care Professional

Integrated Information Knowledge and Data Engineering Lab Systems Biology

Integrating data and models across scales

Enabling querying, analysis, and creative exploration of large, integrated data sets Telescience & Telemedicine

Building the Biomedical Grid

Knowledge Discovery 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)

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FIRST BIRN: Functional Imaging Research in Schizophrenia Testbed

Clinical Specific Aims

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Is Frontal and Temporal Lobe Dysfunction the Cause of Schizophrenia?

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How can Treatment Reverse this Dysfunction?

Technological Specific Aims

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Integration of 4D Data from Multiple Sites - Acquired with Different Non-Invasive Imaging Devices

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Integration of Information Obtained with Different Brain Activation Tasks

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NSF Experimental Network Research Project The “OptIPuter”

Driven by Large Neuroscience and Earth Science Data

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NIH Biomedical Informatics Research Network NSF EarthScope (UCSD SIO) Removing Bandwidth as a Constraint

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Links Computing, Storage, Visualization and Networking Software and Systems Integration Research Agenda NSF Large Information Technology Research Proposal

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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

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Start Date October 1, 2002 www.calit2.net/news/2002/9-25-optiputer.html

Providing a 21

st

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 Arts Medicine Physical Sciences Cal-(IT) 2 Engineeing Sixth College Preuss School SIO ½ Mile

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Developing Training in New Biomedical Technologies

Creating a Comprehensive, Campus Wide Training Program

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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

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Current and Potential Markets for Remote Patient Monitoring

Wellness

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Fitness Monitoring Obesity Epidemic Ambulatory Hospital Patients Cardiac Out Patients Elder Care

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Global Population of People Over 65, Will Increase 88% by 2025 Clinical Trials

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New Drug Discovery Emergency Response

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Natural Disasters Homeland Security

Exercise Was the First Wireless Monitoring Application

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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

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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

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Multi-Network Gateway - Processor: -Sensor Data Analysis, -Monitoring, -Coding -Communicates With Monitoring Station

Medical Monitoring Station

-Event Analysis -Data Shaping -Control Data

Source: Sujit Dey. UCSD ECE

Medical Monitoring Service

Adaptive Data Collection Image/Video/Bio-Sensors Event-triggered Data Filtering/ Aggregation

Source: Sujit Dey. UCSD ECE Medical Monitoring Center

Content/Data Shaping

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Client Data Interpretation

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Physician Identification/Location

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Set-up Of End-End Connection Between Patient Sensor Network & Physician

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Multiple Physicians

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Heterogeneous Appliances

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Multiple Networks/Conditions

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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

Critical New Role of Power Aware Systems

Applications

Sensors Embedded Software Protocol Processors Radio Processors Memory DSP

Internet Source: Sujit Dey, UCSD ECE

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

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Fundamental Issue:

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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

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Data Acquisition Glove (DAG) That Contains Sensors For Body Temperature, Blood Pressure, Electrocardiogram, Oxygen Saturation And Heart Rate

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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, sPO 2 (Oxygen Saturation) Rate, And CO 2

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(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

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The Data Are Stored And Monitored Source: PI Lawrence Hermansen, NHRC, San Diego Sponsor: Office of Naval Research

The Data Acquisition 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 Commander 647-90-4444 Source: PI Lawrence Hermansen, NHRC, San Diego Sponsor: Office of Naval Research

Clinical Trials Market Background

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Prescription Drug Expenditures - $125B 2001 R&D $50B – 2001e - $40B/$10B Pharma/Bio

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Pre-Clinical Studies - $10B Clinical Studies - $20B

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$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 Basic Research Discovery 1 1.5

2 2.5

Clinical Development Preclinical Development Phase 1 Phase 2 Phase 3 1.5

FDA filing/ approval & launch preparation Duration (Yrs) 4% Discovery target 15% Lead candidate 10% IND 15% 22% 31% NDA filed 3% NDA approval Cost (% of total) PhiloMetron Market Focus (78% of Total Expenditures)

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McKinsey & Co., Lehman Brothers, PhRMA, FDA. Source: Darrel Drinan. CEO PhiloMetron PhiloMetron Confidential

Wireless Clinical Trial In-Vivo Drug Monitoring

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Accelerates Drug Development Time

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Basic Physiological Monitoring

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Detects ADME - Toxicity Events – “Fail Fast”

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Remote Data Analysis for Pharmacokinetics PhiloMetron Confidential Source: Darrel Drinan. CEO PhiloMetron

Advantages of Continuous Monitoring Measurement Methodology

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Current - Single point manual measurements

T1 T2 Time T3 T4 Measurement Points T5 T6 T7 •

PhiloMetron System (continuous monitoring)

Statistically Valid Sample

Source: Darrel Drinan. CEO PhiloMetron

Time 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

• Patent Pending Sensors: - Physical - Chemical - Biological Source: PhiloMetron