An InSilico driven in-vitro organotoxicity->hepatotoxicity

platform

Overview Ontomine-wet lab bridge

Why do we need our own platforms

Criteria for insilico>in-vitro->in-vivo platforms

Data Collection

Ontomine Analysis & Matrix Processing and Analysis

Annotation of result

Gene Expression Analysis

Final BioMarkers

Ontomine-wetlab bridge

Ontomine is pretty smart at predicting bioactivity and toxicity endpoints from 2d chemical structure. (e.g. Redoxis, Egyptian study)

Ontomine can link drug targets affected with particular biological or toxicity endpoints. This increases confidence in predictions.

Publication searches, patent searches and microarray analysis along with protein expression and structure information can help discover toxicity linked proteins.

Thus we can potentially discover predictive or diagnostic biomarkers of hepatotoxicity that need to be validated in the wet lab.

Validated biomarkers can be patented and a proprietary high throughout platform developed for drug discovery services.

•Differentiation from competition. So many CRO's with the same offerings!

• How long can we get business on labor cost alone or the “INDIA ADVANTAGE”?

•Scientific excellence. More high profile customers will turn to us if we have proprietary platforms that are comparable if not better and faster.

•Long term business potential. In this competitive sector, IP is the only way to survive in the long term

•Informatics or offering specific wet lab services cannot hope to have the impact that a combined offering can have.

•Informatics need not be a precursor to wet lab analysis. It can also serve as an engine for discovering interesting things e.g. biomarkers , lead identification tools.

•We all get an exciting scientific career and not a 9-5 job running assays.

The need to build platforms

Novel patentable Proteins / mRNA/ genes as biomarkers.High throughput formats. Choice of Multiple technologies.Lower costs was compared to other options in early discovery.Focus on high value end points e.g. hepatotoxicity, renal toxicity etc. that have been lead causes of drug withdrawalsDevelopment of (preferably) non-invasive hepatotoxicity diagnostic platformDiagnostic or predictive?

Criteria for Toxicicity platform

Selection of model compounds for hepatotoxic mechanism from reliable sources like toxicology journals/encyclopedia/webresources etc

Compounds with wide variety of end point pathologies like General hepatotoxicity, Cholestasis, Necrosis and others were used.

Drug-Toxicity Matrix Preparation (~50 compounds were considered)

Data Collection

Compound Cholestasis Hepatitis Inducer/enlarger NecrosisFlutamide -1 -1 -1 1 1 -1 -1 -1 -1Methyldopa -1 -1 -1 1 -1 -1 -1 -1 -1Dantrolene -1 -1 -1 1 -1 -1 -1 -1 -1Diflunisal -1 -1 -1 1 -1 -1 -1 -1 -1Perhexilene -1 -1 -1 1 -1 1 -1 1 -1

Genotoxic carcinogen

Non-genotoxic

Microvesicular steatosis

Macrovesicular steatosis

Steatosis General

03/23/09

Matrix Generation

Primary matrix with 788 Targets

Secondary matrix with 116 Targets

PROCESS-IMATRIX GENERATION

ONTOMINEPROCESSING

Ontomine Predicted

788 Targets

50-KnownHepato Toxins

Ontomine Analysis

03/23/09

Result Annotation

• Predicted biomarkers were annotated for biological relevance (NCBI-Gene DB), literataure mining (PubGene), secretory behaviour (Secretory Protein Database

[SPD]), tissue expression (Expasy, PIR), protein structure information (PDB)

03/23/09

Gene Expression Analysis• Toxicogenomics data was taken from

NCB-GEO (Accession :GSE13442)

• Experiment Title : “Blood gene expression of rats exposed to acetaminophen (hepatotoxic) or methyl parathion (neurotoxic)”

• Experiment Design : 38 samples were analyzed in this experiment. 15 rats were intraperitoneally administered acetaminophen (AP), 15 rats were intraperitoneally administered methyl parathion (MP), and 8 rats were intraperitoneally administered vegetable oil. At time intervals of 4, 12, and 24 hours following administration of acetaminophen or methyl parathion, 4 rats per chemical were sacrificed and blood was collected. At the 168-hour time interval, 3 rats per chemical were sacrificed and blood was collected. The control animals were sacrificed at the 24-hour time interval. Therefore, there were four rats in each of the 4-, 12-, and 24-hour time points for each chemical and four control rats for each chemical. Similarly, there were three rats in the 168-hour time interval for each chemical.

03/23/09

Gene Expression Analysis• QC analysis : Genes with S/N value >3 and flag

< 5000 in atleast 60% of samples were retained (ABI specification)

• Differential expressed genes were found by linear modeling (R package) with a cutoff BH corrected pValue of 0.01 (1216 DE genes)

• Rat gene symbols were translated to corresponding human gene symbol with the help of HomoloGene ids. (for result comparison)

03/23/09

GeneExpression

Analysis

1216 DE genes

Secretory,Toxico-

genomics

LiteratureSearch

for 115

Targets

TissueExpression

81 putative novel BM

34 BM with literature info

Final Results:* 11 novel biomarkers expressed in blood (5 are non-patented)

Gene Names DescriptionNCF1 Neutrophil cytosolic factor 1MCL1 Mcl-1BCL2A1 Bcl-XLEIF2B5 Catalytic epsilon subunit of the translation initiation factor eIF2BHSP90AB1 90-kda heat shock protein beta HSP90 beta

03/23/09

Gene Names DescriptionNCF1 Neutrophil cytosolic factor 1MCL1 Mcl-1BCL2A1 Bcl-XLEIF2B5 Catalytic epsilon subunit of the translation initiation factor eIF2BHSP90AB1 90-kda heat shock protein beta HSP90 betaCLK3 CDC-like kinase 3 isoform hclk3CDC42 Cell division cycle 42 (GTP binding protein, 25kDa)KLF5 Kruppel-like factor 5G6PD Glucose-6-phosphate dehydrogenase isoform aHIF1A Hypoxia-inducible factor 1, alpha subunit (basic helix-loop-helix transcription factor)NR4A1 Nuclear receptor subfamily 4, group A, member 1

Biomarkers list

03/23/09

Biomarkers Validation using Ontomine

• Validation set with known toxicity were taken (they were not part of Ontomine KB)

• Predicted toxicity by Ontomine: Hepatitis & Necrosis.

• Target proteins were compared with 11 Biomarkers identified by our analysis.– 10 out of 11 biomarkers were found :)

03/23/09

For here to ?

• Study CRO's offering toxicity platforms, costs, strategies

• Extend functionality to more organ toxicity end points

• More specific sub-categories in hepatotoxicity.

• Design in-vitro, vivo assays• Validation and patenting