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The basis for personalized predictive medicine
Tomorrow: 
Patient DNA is fully genotyped one time only 
A database is consulted in order to 
oDevelop a molecular diag...
Tomorrow: the Personal Genome Card is available. 
The database is consulted whenever necessary 
oGenetic susceptibility ...
Bridging the gap 
Need to decipher the genetic basis of common complex diseases and responses to treatment 
Today’s tech...
Drug Responses are Multigenic 
Pharmacokinetics Pharmacodynamics 
individual 
metabolism 
individual 
action 
Molecular su...
sporadic 
Combinations of many low-effect 
gene variants 
(eg: AD, Migraine, NID- Diabetes, Psoriasis) 
Most disease is th...
ABCDEFG 
ABCDEFG ABCDEFG 
ABCDEFG ABCDEFG 
ABCDEFG ABCDEFG ABCDEFG ABCDEFG 
Over Generations 
A combination of many subtle...
Finding low effect variants will require high density genotyping of large populations 
“…a density of SNPs of one every 10...
Multigenic Diseases: Gene Hunting 
Genome-wide / hypothesis-free approach 
Using very high density markers 
At least 30...
Technology Overview
SNPtyping with Manteia technology 
No SNP map needed 
Not SNP-specific 
“One” tube per patient 
Readily scalable 
Det...
Manteia Technology: PAS( Parallel Amplification and Sequencing ) 
Four basic steps 
1: Isolate genomic DNA from blood or c...
Patient 1 
Patient n 
Isolate 
Genomic DNA 
Cut DNA with 
Restriction Endonuclease Enzyme 
1 
2 
3 
4 
5 
1 
2 
3 
4 
5
Type IIs 
recognition site 
n 
Genomicfragment 
n 
Ligation 
Type IIs 
digest 
Short genomic 
fragment 
n 
Linker 1
Restriction site 
Type IIs 
recognition sites 
n 
Genomicfragment 
n 
Ligation 
n 
Type IIs 
digest 
Short genomic 
fragme...
n 
n 
Ligation 
Linearized 
Colony Template 
Linker 2 
5 
4 
3 
2 
1 
DNA fragment sizes 
normalized 
Each restriction end...
5 
4 
3 
2 
1 
Clone DNA fragments 
Into “DNA Colony Vectors” 
5 
4 
3 
2 
1 
DNA fragment sizes 
normalized 
n 
Variable ...
n 
Colony vectors 
Short primers 
n 
n 
Functionalization 
Chemically functionalized surface
PAS Array 
Density = f([template],[primer],t) 
ss DNA Colony Vector(107/cm2) 
ss Oligonucleotide 
Primers (4x104/μm2) 
Gla...
100 nm 
Arch formation 
DNA:DNA 
Hybrid 
DNA replication 
Add nucleotides + polymerase 
(25b complementarity)
Replicated 
Colony Vectors 
Attached 
terminus 
Free 
terminus 
Attached 
terminus 
2 
1 
1 
2 
Denaturation 
Attached 
te...
1-2 μm 
DNA 
Colonies 
(1000-2000 copies in each) 
1 
2 
100 μm
Sequencing primers 
Added to the array 
DNA:DNA 
Hybrids 
C 
A 
C 
T 
G 
C 
T 
G 
A 
Sequencing primer 
Anonymous 
Fragmen...
Cycle 3 
C 
A 
C 
T 
G 
C 
T 
G 
A 
G 
T 
0 
1 
2 
3 
4 
Signal 
A 
G 
T 
C 
C 
A 
C 
T 
G 
C 
T 
G 
A 
A 
0 
1 
2 
3 
4 
...
Manteia Sequencer Prototype
Signal intensity dataDNA colonies image processing 
Raw image 
10 mm 
Processed image 
10 mm
Expected sequence: GGCTGTATAGAutomated colony sequencing results
From Sequence Fragments to SNPS
Genetic variability in the human population: 
Between 2 individuals: 1 SNP every 1331 bp 
(SNP consortium, Nature 409,928)...
The same stretches of DNA are sequenced in each patient 
patient #1 
patient #47 
patient #125 
patient #571 
.... 
.... 
...
Mega-SNP data analysis: “genetic” approach 
Classical frequent SNP problem: 
-number SNP >> population 
-distance between ...
SNPtyping with Manteia technology 
No dependent on SNP maps 
Not SNP-specific 
“One” tube per patient 
Readily scalabl...
Business Model 
Identify Gene Variant Associations 
Alone or in partnerships 
Retain rights to these associations for a...
Collaborations with biopharmaceutical companies 
Clinical partnerships 
Clinical trials assessment & recruitment 
Drug...
Collaborations 
Clinical 
Studies 
Association Studies 
Gene Variants 
Disease 
Causation 
Progression 
Drug Targets 
Resp...
Personal Genome Card 
Internal Programs: 
Personal Treatment Guidelines 
In conjunction with Personal Genome Cards 
Pr...
Treatment Guidelines 
Single Disease Clinical Populations 
Association Studies 
Patterns ofGene Variants 
Manteia 
Technol...
Disease Selection 
Serious diseases 
High incidence 
Several treatments available 
Each treatments works for only a fr...
Personal Treatment Guidelines 
Market example: Breast Cancer 
200,000 new diagnoses each year in US; 300,000 in EU. 
$2...
Risk Profiles 
Association Studies 
Patterns ofGene Variants 
Manteia 
Technology 
Genotypes 
Personal 
Genotype 
Card 
Ri...
Disease Selection 
High incidence 
Prevention is possible 
Preventive treatment is available 
Early diagnosis leads to...
Personal Risk Profiles 
Market example: Colorectal cancer 
4,000,000 turn 50 each year in the US 
8,000,000 target popu...
Manteia non confidential-presentation 2003-09
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Manteia non confidential-presentation 2003-09

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A non confidential corporate presentation of "Manteia Predictive Médicine" as of September 2003. Présents DNA colony sequencing resutls, instrument, DNA preparation for genotyping.

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Manteia non confidential-presentation 2003-09

  1. 1. The basis for personalized predictive medicine
  2. 2. Tomorrow: Patient DNA is fully genotyped one time only A database is consulted in order to oDevelop a molecular diagnosis of specific disease oPredict responses to each of the available treatmentsDiagnosis and treatment Today’s medical practice is for the most part: Imprecise in diagnosis Selecting treatment by trial-and-error
  3. 3. Tomorrow: the Personal Genome Card is available. The database is consulted whenever necessary oGenetic susceptibility to specific diseases is assessed Preventive measures are taken in consultation with a family physician, including: oLife style changes oRoutine screenings for those at elevated risk, allowing for early diagnosis and better prognosis oPersonalized preventive treatment Today’s medical practice is for the most part reactive to diseasePrevention
  4. 4. Bridging the gap Need to decipher the genetic basis of common complex diseases and responses to treatment Today’s technologies are not up to the task: Too complex (e.g., procedures are SNP specific) Too expensive (> 0.1€per SNP)
  5. 5. Drug Responses are Multigenic Pharmacokinetics Pharmacodynamics individual metabolism individual action Molecular sub-types Drug Individual responses individual pathways Individual response to medicines is likely a consequence of many low-effect genetic variants
  6. 6. sporadic Combinations of many low-effect gene variants (eg: AD, Migraine, NID- Diabetes, Psoriasis) Most disease is the result of combinations of low- effect genetic variantsCommon Diseases are Multigenicfamilial Moderate-penetrance gene variants (eg: BRCA1,2) Single high- penetrance gene variants (eg: CF, Huntington Disease)
  7. 7. ABCDEFG ABCDEFG ABCDEFG ABCDEFG ABCDEFG ABCDEFG ABCDEFG ABCDEFG ABCDEFG Over Generations A combination of many subtle genetic variants may tip the balance in favor of disease ABCDEFG ABCDEFG Combinations of low-effect variants
  8. 8. Finding low effect variants will require high density genotyping of large populations “…a density of SNPs of one every 10,000 –30,000 bp can rapidly narrow the search for susceptibility genes*.” Roses. Nature, 405 (2000) pp862. (SVP, Genetics Research, GSK) “…roughly 500,000 SNPs will be required for whole-genome association studies in samples drawn from large outbred populations.” (pp139). “…efficient technologies are needed for genotyping hundreds of thousands of SNPs in thousands of individuals” (pp143). Kruglyak. Nature Genetics, 22 (1999).(Fred Hutchinson Cancer Research Center & HHMI) *100,000 –300,000 SNPs
  9. 9. Multigenic Diseases: Gene Hunting Genome-wide / hypothesis-free approach Using very high density markers At least 300,000 SNPs/genome Large numbers of subjects At least 2,000 per disease/treatment Totaling at least 600 million SNPs typed/disease Today cost/SNP = 10-20¢ Tractable when cost falls below 1¢/SNP
  10. 10. Technology Overview
  11. 11. SNPtyping with Manteia technology No SNP map needed Not SNP-specific “One” tube per patient Readily scalable Detection method: sequencing genome fragments Below 0.1¢ per SNP
  12. 12. Manteia Technology: PAS( Parallel Amplification and Sequencing ) Four basic steps 1: Isolate genomic DNA from blood or cheek-swab 2: Cut up the DNA and collect the fragments 3: Amplify all the fragments in parallel on a solid surface 4: Sequence all the fragments in parallel
  13. 13. Patient 1 Patient n Isolate Genomic DNA Cut DNA with Restriction Endonuclease Enzyme 1 2 3 4 5 1 2 3 4 5
  14. 14. Type IIs recognition site n Genomicfragment n Ligation Type IIs digest Short genomic fragment n Linker 1
  15. 15. Restriction site Type IIs recognition sites n Genomicfragment n Ligation n Type IIs digest Short genomic fragmentsPAS2
  16. 16. n n Ligation Linearized Colony Template Linker 2 5 4 3 2 1 DNA fragment sizes normalized Each restriction endonuclease=> ~1.5 million fragments
  17. 17. 5 4 3 2 1 Clone DNA fragments Into “DNA Colony Vectors” 5 4 3 2 1 DNA fragment sizes normalized n Variable region Constant region Constant region
  18. 18. n Colony vectors Short primers n n Functionalization Chemically functionalized surface
  19. 19. PAS Array Density = f([template],[primer],t) ss DNA Colony Vector(107/cm2) ss Oligonucleotide Primers (4x104/μm2) Glass surface 1 2 5’ endscovalently attached 3’ endsfree in solution
  20. 20. 100 nm Arch formation DNA:DNA Hybrid DNA replication Add nucleotides + polymerase (25b complementarity)
  21. 21. Replicated Colony Vectors Attached terminus Free terminus Attached terminus 2 1 1 2 Denaturation Attached terminus Attached terminus
  22. 22. 1-2 μm DNA Colonies (1000-2000 copies in each) 1 2 100 μm
  23. 23. Sequencing primers Added to the array DNA:DNA Hybrids C A C T G C T G A Sequencing primer Anonymous Fragment of genomic DNA (Variable region) Colony Vector (Constant region) Colony Vector (Constant region)
  24. 24. Cycle 3 C A C T G C T G A G T 0 1 2 3 4 Signal A G T C C A C T G C T G A A 0 1 2 3 4 Signal A G T C Cycle 1 Wash Add C A C T G C T G A Cycle 2 G 0 1 2 3 4 Signal A G T C
  25. 25. Manteia Sequencer Prototype
  26. 26. Signal intensity dataDNA colonies image processing Raw image 10 mm Processed image 10 mm
  27. 27. Expected sequence: GGCTGTATAGAutomated colony sequencing results
  28. 28. From Sequence Fragments to SNPS
  29. 29. Genetic variability in the human population: Between 2 individuals: 1 SNP every 1331 bp (SNP consortium, Nature 409,928) In the population (Krugliak, Nature Genetics 27,234 ): Frequency >= 10% : 1 SNP every 600bp Frequency >= 1% : 1 SNP every 290bp Frequency >= 0.1%: 1 SNP every 200 bp
  30. 30. The same stretches of DNA are sequenced in each patient patient #1 patient #47 patient #125 patient #571 .... .... Sequenced fragments acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt acgtaggtgcaggtcagt … tagcgtAtcgtaggtagat tagcgtAtcgtaggtagat tagcgtAtcgtaggtagat tagcgtAtcgtaggtagat tagcgtGtcgtaggtagat tagcgtAtcgtaggtagat tagcgtAtcgtaggtagat tagcgtAtcgtaggtagat tagcgtGtcgtaggtagat tagcgtAtcgtaggtagat … SNP Making SNP identification possible Each restriction endonuclease: => 1.5 million fragments => 25 million bases sequenced => 1% of the genome scanned => 100,000 SNPs scored
  31. 31. Mega-SNP data analysis: “genetic” approach Classical frequent SNP problem: -number SNP >> population -distance between SNP > linkage range -moderate population (50~300) => How to differentiate real linkage signal from false positives/negatives Manteia’s Mega-SNP approach: -distance between SNP < linkage range -moderately frequent SNPs -large population (1,000~10,000) =>SNP clusters of high statistical signifcance 1 Mbp Linkage Signal 1 Mbp Linkage Signal 2~4 LD range “running average”
  32. 32. SNPtyping with Manteia technology No dependent on SNP maps Not SNP-specific “One” tube per patient Readily scalable Detection method: sequencing genome fragments Tracktable biostatistics and bioinformatics Below 0.1¢ per SNP (Q1-2006)
  33. 33. Business Model Identify Gene Variant Associations Alone or in partnerships Retain rights to these associations for application to: Therapeutic response prediction Disease risk assessments License out rights for application to: Drug discovery Develop and market a Personal Genome Card in conjunction with access to a database of clinical and genetic associations.
  34. 34. Collaborations with biopharmaceutical companies Clinical partnerships Clinical trials assessment & recruitment Drug revival Development of marketed Companion Tests Discovery partnerships Target discovery in diseased populations Transcriptome analysisCollaborations
  35. 35. Collaborations Clinical Studies Association Studies Gene Variants Disease Causation Progression Drug Targets Response to Therapy Drug Discovery Predictive Tests Marketing Manteia Technology Individual Patterns
  36. 36. Personal Genome Card Internal Programs: Personal Treatment Guidelines In conjunction with Personal Genome Cards Predict patient responses to therapy Efficacy and side-effects Personal Risk Profiles In conjunction with Personal Genome Cards Predict lifetime risk of sporadic cases of common diseases. Permit appropriate interventions and monitoring for those at risk. Business Model
  37. 37. Treatment Guidelines Single Disease Clinical Populations Association Studies Patterns ofGene Variants Manteia Technology Therapy 1 Responders Non Responders Therapy 2 Responders Non Responders Therapy 3 Responders Non Responders Pharmacokinetics Pharmacodynamics Disease subgrouping Genotypes Personal Genotype Card Treatment Guideline PRODUCT
  38. 38. Disease Selection Serious diseases High incidence Several treatments available Each treatments works for only a fraction of patients Treatments are expensive Treatments have serious side effects Delaying effective treatments leads to poorer prognosis All frequent diseases where sub-optimal treatment has a high cost
  39. 39. Personal Treatment Guidelines Market example: Breast Cancer 200,000 new diagnoses each year in US; 300,000 in EU. $2,500 per comprehensive Treatment Guideline Potential US+EU market: $1.25B/year Maximal penetration @ 30% = $375MM/year Net income @ 20% = $75MM/year Personal Genome Card
  40. 40. Risk Profiles Association Studies Patterns ofGene Variants Manteia Technology Genotypes Personal Genotype Card Risk Profile PRODUCT Single Disease Clinical Populations Disease Subgroups Matched Populations
  41. 41. Disease Selection High incidence Prevention is possible Preventive treatment is available Early diagnosis leads to much better prognosis Where there is either no available screen Where screening is expensive or unpleasant
  42. 42. Personal Risk Profiles Market example: Colorectal cancer 4,000,000 turn 50 each year in the US 8,000,000 target population US+EU $500 Risk Profile for colorectal cancers Potential US+EU market: $4B per year Maximal penetration @ 10% = $400MM/year Net income @ 10% = $40MM/year Personal Genome Card

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