Describes a proposed process combining in silico, in vitro, and in vivo analysis to improve drug development and testing

1. Robert Marcus
Menlo Park, California 94025
May 2006
Multiscale Modeling for Drug
Development and Testing
Wednesday, December 23, 15

2. Need
• Drug development cost to market is $1B per drug
• “Some believe that extensive use of in silico
technologies could reduce the overall cost of drug
development by as much as 50 percent” from (http://
www.fda.gov/oc/initiatives/criticalpath/whitepaper.html)
• Linking computational biology and pre-clinical lab
drug testing will reduce the cost of drug development
• ESD has the opportunity to develop a technical
approach for supporting drug development processes
to enable an expanded role in this area
Wednesday, December 23, 15

3. Multiscale Modeling Elements
• Layer Identification
• Interface Definition
– Within layers
– Across layers
• Cross-layer Transport Coupling
– Material
– Energy
– Information
• Model Characterization
• Mapping Models
Wednesday, December 23, 15

4. Context
Computational
Biology
Medical
Computational
Physiology
Pharmacokinetics
Compartment
Models
In silico
Drug
Discovery
Pre-Clinical
Testing
Clinical
Testing
In vitro
& in vivo
Genomics,
Proteomics
Analysis
Biosciences Patient
Testing
Complex
Mappings
Drug
process
phases
Molecules, Cells,
Pathways
Tissue, Organs,
Organisms
Humans, Groups
Scales
Wednesday, December 23, 15

5. Current Models in Biomedical Research
From recent talk at SRI by Prof. Tony Hunt of UCSF
Wednesday, December 23, 15

6. Multiscale Modeling Bridges the Gap
From recent talk at SRI by Prof. Tony Hunt of UCSF
Wednesday, December 23, 15

7. Multiscale Modeling Approach
Computational
Biology
(Models of Molecules,
Cells, Pathways)
Computational
Physiology
(Multiscale Models of
Molecules. Cells, Pathways,
Tissues, Organs, Organisms)
Biosciences
(Lab for Drugs,
Tissues, Organs,
Organisms)
Complex mappings
from pathway models
to drug effects make
predictions difficult Comparison of lab
measurements and
computational
prediction
Lower level models
used when
necessary
Wednesday, December 23, 15

8. Current Gov-Funded Efforts in
Multiscale Modeling in Biology
• Interagency Modeling and Analysis Group (IMAG)
for biomedical modeling formed April 2003
including NSF, NIH, DOE, NASA, and USDA
• IMAG’s Multiscale Modeling (MSM) initiative
focused on funding multiscale modeling in
biomedical, biological, and behavioral systems
• MSM’s goal is to develop new methodologies that
span multiple biological scales applicable to
biomedical, biological, and behavioral research
• Awards were made to 24 projects in early 2005
(http://www.nibib.nih.gov/nibib/File/Research/IMAG/MSM
%20PI%20Info%20for%20Web.pdf)
Wednesday, December 23, 15

9. Related Work
• Companies
– Entelos develops PhysioLab and Virtual Patient simulations.
– Admetis has in silico ADME-Tox tools that are complementary
to SRI Biosciences in vivo and in vitro ADME capabilities.
Research
– Prof. Tony Hunt UCSF has synthetic simulation of in vitro
metabolism.
– Several other projects developing multiscale modeling tools for
biology have been contacted about future presentation at SRI
ADME-Tox = Absorption, Distribution, Metabolization, and Excretion - Toxicity
Wednesday, December 23, 15

10. Context for External Organization Roles
Computational
Biology
Medical
Computational
Physiology
Pharmacokinetics
Compartment
Models
In silico
Drug
Discovery
Pre-Clinical
Testing
Clinical
Testing
In vitro
& in vivo
Genomics,
Proteomics
Analysis
Biosciences Patient
Testing
Drug
process
phases
Molecules, Cells,
Pathways
Tissue, Organs,
Organisms
Humans, Groups
Scales
Medical
Physiology
(Admetis)
Medical
Computational
(Entelos)
Computational
Physiology
(Prof. Tony Hunt)
Wednesday, December 23, 15

11. Possible Startup Project:
Drug Induced Liver Damage
(DILI)
Wednesday, December 23, 15

12. DILI Project Motivation
• Drug testing is extremely expensive (~ $1 billion)
and time-consuming
• Most new drug candidates are eliminated in pre-
clinical testing
• The most common reason for elimination is toxic
reaction with liver
• In silico filtering of candidates can save on the cost
of pre-clinical testing
• Computational analysis may be the only way to
predict multiple drug interactions
Wednesday, December 23, 15

13. DILI Project Roles
• Entelos – Physiolab empirical data based computer
models of drug effects on liver
• SRI Computational Biology – Working with Tony
Hunt provides causal models for drug effects
• SRI Biosciences – Lab results from measuring
metabolism and drug effects on livers
• Critical Path Institute – Manages consortium of drug
companies supporting DILI testing. (Predictive
Safety Consortium)
• Other groups – Provide additional lab and
computational capabilities as needed
Wednesday, December 23, 15

14. DILI Project Relationships
Computational
Biology +
Hunt
Drug Damage
To Liver
Computer
Testing
Entelos
COMPUTER
Clinical
Testing
LAB Biosciences
Lab data
Bottom-up
models
Top-down
Models
Pre-clinical
Testing
Critical Path Institute
Consortium
Supports
TBD
TBD
Data and
Models are
For Liver
Wednesday, December 23, 15

15. Multiscale Biological References
• Ramping up to Multiscale in Biomedical Modeling (http://
www.biomedicalcomputationreview.org/2/2/6.pdf)
• Computational Physiology and Physiome Project
(http://ep.physoc.org/cgi/content/full/89/1/1)
• Full Reactive Modeling of a Multi-Cellular Animal (Harel)
(http://www.wisdom.weizmann.ac.il/~dharel/papers/GrandChallenge.doc)
• Discrete Event Multi-level Models for Systems Biology
(Zeigler)
(http://ist-socrates.berkeley.edu/~seanhjk/quals/references/
Uhrmacher_DiscreteEventSystemsBio.pdf)
Wednesday, December 23, 15