The document introduces BioMAP systems, which use primary human cells in disease-relevant assays to model complex human biology. The systems include over 30 validated assays that can be used to generate biomarker response profiles for compounds. These profiles are stored in a reference database along with clinical outcome data. Specialized informatics tools can then be used to analyze profiles, predict clinical effects, and reveal mechanisms of action. The systems aim to bridge the gap between in vitro and in vivo testing.

1. Introduction to BioMAP® Systems
Bridging the Gap From In Vitro to In Vivo
1

2. BioMAP® Systems Model Complex Biology
2

3. BioMAP® Technology Platform
BioMAP Reference Predictive
Assay Systems Profile Database Informatics Tools
Human primary cells Biomarker responses to drugs Specialized informatics tools are
Disease-models are stored in the database used to predict clinical outcomes
30+ systems
Human Biology Integrated into a Robust, Scalable Platform
3

4. BioMAP® Systems
Human primary cell-based assays
Engineered to model complex human disease biology
 Physiologically relevant assay conditions
 Mixtures of stimulation factors, co-cultures of cells
 Complex culture conditions selected to achieve stable
signaling networks that reflect in vivo tissue states
 Clinically validated disease biomarkers
 Quantitative and reproducible
 Robust readouts (proteins, mediators); standardized
assays, QMP, SOPs
 Assay formats manage disease variations among donors
 Validated with known drugs
4

5. Current Validated BioMAP® Systems
Primary Human Cell Types Disease Relevance BioMAP*
Th1 and Th2 inflammation, allergy,
Endothelial cells (EC) asthma, dermatitis, angiogenesis, wound healing,
3C 4H
restenosis, atherosclerosis
Th1 inflammation, psoriasis, COPD
EC+lymphocyte+monocytes LPS SAg HPNo
fibrosis, monocyte and T cell responses
EC+Macrophages Macrophage responses, arthritis, COPD, fibrosis
Mphg BT
B cells + T cells Immune responses
HSM3C HTh2
EC+Smooth Muscle Cells Vascular inflammation, restenosis, atherosclerosis
EC+Th2 blasts Allergy, asthma HDF3CT
HDFT
Arthritis, asthma, dermatitis, fibrosis, psoriasis,
Fibroblasts
wound healing HDF3C HDFNo HDF3CGF
Myofibroblasts Fibrosis, COPD, wound healing
K3CT MyoF
Keratinocytes Psoriasis, dermatitis, wound healing
Keratinocytes+Fibroblasts Psoriasis, dermatitis, wound healing
KF3CT KFNo
Th1 and Th2 inflammation
Bronchial Epithelial Cells
Allergy, asthma, fibrosis, COPD
BE3C BE4T
Bronchial Epithelial Cells +Fibroblasts Asthma, allergy, fibrosis, COPD
Smooth Muscle Cells Vascular inflammation, asthma, COPD, fibrosis BF4T SM3C
5

6. BioMAP® Assay Development Pipeline
 Innate immunity cells
 Neutrophils, M1 and M2 macrophages
 Renal epithelial cells
 Astrocytes
 Hepatic cells
 Hepatocytes, sinusoidal endothelial cells (LSEC), stellate cells (HSC),
liver fibroblasts
 Skeletal muscle cells, adipocytes, foam cells
 Skeletal myoblasts and myotubes
 Adipocytes derived from adipose tissue derived mesenchymal stem
cells (ADMSC), mesenchymal stem cells (MSC), and preadipocytes
 Foam cells derived from monocytes
 Bone / joint cell types
 MSC and ADMSC-derived chondrocytes and osteoblasts, monocyte-
derived osteoclasts
 Intestinal cells
 Intestinal epithelial cells and intestinal myofibroblasts
6

7. Informatics and Data Analysis
 Optimized algorithms for profile matching and function similarity
clustering (network pharmacology, systems biology)
 Quantitative analysis for screening and lead optimization
 Potency and efficacy ranking, EC50 curves
7

8. BioMAP® Analysis of Prednisolone
BioMAP Systems
Log expression ratio (Drug/DMSO control)
99% significance
envelope
Control (no drug)
Dose
Response
Cytotoxicity Readouts
Readout Parameters (Biomarkers)
Each Drug Induces a Signature Profile
Profiles retain shape over multiple concentrations
8

9. BioMAP® Analysis of Prednisolone - Clinical Validation
SAA
PAI-1 PAI-1
MMP-1
IL-8
MCP-1 IL-8
PGE2 E-selectin
Collagen I & III
TNF-
MCP-1, IL-8, E-sel. decrease PGE2 decrease Collagen I, III decrease PAI-1, SAA increase
Leukocyte recruitment Pain, swelling Skin atrophy CV complications
Sartori et al., 1999
Many, e.g. Jilma et al., 2000 Sebaldt et al., 1990 Autio et al., 1994 Fyfe et al., 1997
BioMAP® Profiling Can Bridge the Gap from In Vitro to In Vivo
9

10. BioMAP® Analysis Reveals Mechanism of Action
Pairwise Correlation of BioMAP Reveals Functional Similarities
Protein Estrogen R
synthesis
Microtubule
PKC Activation Destabilizers
Transcription
PI-3K
JNK
NFkB
Pathway
mTOR Relationships
Hsp90
DNA
Calcineurin synthesis Retinoids
CDK
HMG-CoA
reductase
Ca++ Mitochondrial
Mobilization ET chain
p38 MAPK
Microtubule
Stabilizers
Mechanism of Action MEK
10
(On-Target)

11. BioMAP® Reference Database
BioMAP database contains profiles of >2700 agents
• Drugs – Clinical stage, approved, and failed
• Experimental Chemicals - Research tool compounds, environmental chemicals
• Biologics - Cytokines, factors, peptides, antibodies, soluble receptors
11

12. BioMAP® Applications
 Screening and lead optimization using primary cells
 Phenotypic screening and Indication Discovery
 Screening for second-generation drugs
 Biological annotation of compounds
 Target and compound validation in human cells
 Benchmarking to standard of care
 Safety assessment
 Translational biology
 Specialized assays, also with patient cells, patient classification
 Testing drug combinations
 Annotation for pharmacodynamic markers
12 12

13. Contacts
Ellen Berg, PhD
General Manager
BioSeek, LLC
eberg@bioseekinc.com
650-416-7621
Bridging the Gap From In Vitro to In Vivo
BioSeek, LLC
310 Utah, #100
South San Francisco, CA 94080