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Navigating the FDA: Getting to Market – CVG Second Thursday, 3/14/13

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Paige Rasid
Paige Rasid

The document discusses how cancer biomarker discovery has evolved from focusing on single biomarkers identified through laboratory findings and requiring many years of development, to now interrogating entire cancer genomes through sequencing. This allows the identification of many markers from few samples. Structural mutations in cancer genomes are analyzed, finding higher-level organization to private mutations. A fusion gene indicator of genomic instability in breast cancer is identified in 30% of cases. Genomic organization shows chromosomes can generate "cancer gene cassettes" and the germline affects therapeutic outcome. Focus is shifting to systems oncogenomics and structural mutations in cancer.

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THANK YOU CVG SPONSORS B Round A Round Venture Capital Sponsors Professional Service Firms
Welcome Marketing at the Speed of Light Konstantine Drakonakis Director, New Haven LaunchCapital CTNEXT: New Haven Hub Derek Koch Usha Pillai
Three Minute Pitches Marcia Fournier Judson Brewer Lew Bender John Bala SterileWave Medical Corp.
Navigating the FDA: Getting to Market Marketing at the Speed of Light Introduction Paul Hughes Partner Wiggin and Dana LLP Keynote Edison T. Liu, M.D President & CEO The Jackson Laboratory
Navigating the FDA or What is on the horizon? March 15,2013 Edison Liu, M.D. edison.liu@jax.org
We discover precise genomic solutions for disease and empower the global biomedical community in our shared quest to improve human health. The Jackson Laboratory To discover precise genomic solutions for better medicine
Biomarker Discovery in Cancer Then: Single biomarker, spurred by a some laboratory findings, years of development before reaching clinic One marker  many samples Now: Interrogation of a cancer genome, in silico validation, identification of new therapeutic targets Many markers  few samples Oct 1997
HER2 and clinical trials Start of study CALGB 8869: 1989 Ann Thor Don Berry Publication of final paper: 1998 Soon Paik Mei He Lynn Dressler Craig Henderson Hyman Muss In vitro observation: ARAC – RAS interaction J Natl Cancer Inst. Koo, et al. Can Res 59:6057, 1999 90(18):1346-60 (1998) Patients with acute myeloid leukemia and RAS mutations benefit most from postremission treatment with high-dose cytarabine: a Cancer and Leukemia Group B study. Neubauer A, et al. J Clin Oncol. 26(28):4603-9, 2008. 9 years per marker, over 1,500 patients: There has got to be a better way
Biomarker Discovery in Cancer Then: Single biomarker, spurred by a some laboratory findings, years of development before reaching clinic One marker  many samples Now: Interrogation of a cancer genome, in silico validation, identification of new therapeutic targets Many markers  few samples Oct 1997
Sequenced Breast Cancers: focusing on  structural mutations PET library construction PET sequences mapping Analysis of Cancer & sequencing to reference genome  Specific Mutations 1Kb 10Kb PET mapping span Concordant PET  tag density Automated cancer  genome assembly: Concordant PETs 7 month analysis to 4 days Discordant PETs SOLiD
Structure variations Deletion Unpaired inversion (Inverted orientation)  Abnormal length Different strand Tandem Duplication Translocation Incorrect order  Different chromosome Fusion points  predict fusion genes
Structural Genomic Changes in Breast Cancer Genome Research 21(5):665-75 (2011)
Cancer rearrangements are most often private and unique: Irrelevant mutations or part of the “long tail” Inaki K, et al. Transcriptional consequences of genomic structural aberrations in breast cancer. Genome Res. 2011 May;21(5):676-87.
Gene ontology (GO) analysis of genes with break points in cancer genomes: There is a higher organization to the collection of single structural mutations Breast cancer Gastric cancer 1) Genes with break points RefGen Expecte Obser RefGen Expecte Obser Biological Process3) +/‐ P value +/‐ P value e d ved e d ved Cell adhesion‐mediated  386 20.88 51 + 2.22E‐06 Cell adhesion 592 31.61 73 + 2.62E‐09 signaling Cell adhesion‐ Cell adhesion 592 32.02 65 + 3.47E‐06 386 20.61 49 + 9.66E‐06 mediated signaling Neuronal activities 561 30.34 54 + 1.52E‐03 Signal transduction 3256 173.84 222 + 1.53E‐03 Biological process unclassified 5972 322.97 269 ‐ 3.04E‐03 Synaptic transmission 275 14.68 33 + 3.24E‐03 Electron transport 230 12.44 2 ‐ 1.05E‐02 Cell communication 1207 64.44 98 + 4.47E‐03 Other intracellular signaling cascade 212 11.47 27 + 1.12E‐02 Neuronal activities 561 29.95 51 + 6.94E‐03 Cell communication 1207 65.28 97 + 1.16E‐02 Biological process unclassified 5972 318.84 273 ‐ 2.36E‐02 Chemosensory perception 204 11.03 1 ‐ 2.67E‐02 Chemosensory perception 204 10.89 1 ‐ 3.04E‐02 Developmental processes 2065 111.68 144 + 2.97E‐02 Genes in recurrent high copy regions2) 2.35E‐ Chromatin packaging and  0.0024 Signal transduction  3256 151.33 100 ‐ 194 2.21 11 +  05 remodeling  9 Cell surface receptor mediated signal  2.05E‐ 1576 73.25 41 ‐ transduction  03 7.74E‐ Developmental processes  2066 96.02 65 ‐ 03 1.39E‐ G‐protein mediated signaling  793 36.86 16 ‐ 02
RPS6KB1‐TMEM49 fusion gene induced by tandem  replication is found in 30% of breast cancers.  5’ TMEM RPS6K (~100kb) 5’ TMEM RPS6K (~100kb) 5’ TMEM RPS6K TMEM RPS6K (~100kb) (~100kb) 5’ TMEM RP EM RPS6K RPS6KB1-TMEM49 fusion gene
Historical data Expression of RPS6KB1‐VMP1 fusion Our data is correlated with: ‐Poor prognosis ‐Expression of neighboring oncogenes  around the tandem duplication ‐Expression of oncogenes in ~3Mb adjacent  region ‐ Associated with gene amplification of locus  The fusion gene is always associated with amplification of this region
S6K‐TMEM Fusion Transcript is an indicator of genomic instability in an “oncogenic region”  of the genome harboring at least 2 oncogenic  components miRNA21 TMEM 49 S6Kinase
Indicator structural mutation:  S6K‐TMEM Fusion Transcript is an indicator of the amplification of an “oncogenic region” of the genome miRNA21 Oncogenic TMEM 49 S6Kinase bloc miRNA21 miRNA21 Tandem duplication S6 TMEM  TMEM 49 Kinase S6Kinase 49 Gene Amplification
Genomic Organization and Cancer: Higher order organization of mutations in cancer genomes Chromosome as an oncogenic organizer Chromosomal “origami” to generate cancer gene cassettes Effect of the germline on cancer therapeutic outcome Focus on Structural Mutations in Cancer Systems Oncogenomics
Chronic Myelogenous Leukemia (CML) Optimizing treatment for CML based on genetic  makeup of the patient KP Ng, Axel Hillmer,… Yijun Ruan. Ong Sin Tiong Nat Med. 2012 Mar 18;18(4):521‐8. Imatianib (Gleevec) – primary and effective treatment Clinical Challenge: Drug resistance • Acquired resistance – resistance after long term  treatment ‐ due to second ABL mutation • Primary resistance – resistance at the beginning of  treatment.  • In Asia, complete cytogenetic response rates are lower ‐ 50% vs. 74%.  Mechanism unknown   
Question: is there a reason why 25% of CML cases do not respond to imatinib? Approach: Compared the genomes of three CML cases with primary resistance to Imatinib with two CML cases sensitive to Imatinib therapy Results: 3/3 resistance cases had the same 2.9kb deletion in the BIM gene not seen in sensitive cases (0/2) Ng KP, Nat Med. 18(4):521-8 (2012)
BIM: • BIM is a gene that activates cell death (pro‐apoptotic).  • Activated BCR‐ABL1, suppresses BIM function thus  allowing leukemia cells to survive. When CML cells are  treated with Imatinib, BIM expression goes up  cell  death Death of Bcr-ABL: CML Intact BIM Leukemia cells Imatinib
How does it work?:    The 2.9kb BIM deletion polymorphism results  an abnormal transcript (E3) that a produces a truncated and inactive  BIM protein Normal Transcripts E3 Imatinib Death of Bcr-ABL: CML Intact BIM Leukemia cells Imatinib Deletion Polymorphism Bcr-ABL: CML BIM Primary E3 Drug Resistance
BIM deletion polymorphism: • This deletion polymorphism is 3‐5X more common in  CML cases resistant to imatinib that sensitive cases • This 2.9 kb 2 deletion of BIM is not a mutation, but is a  polymorphism present in normal genomes (a germline polymorphism): 12% in Asian individuals 0% in Africans  0% in Caucasians
We used this genomic intelligence to overcome this resistance: Imatinib Bcr-ABL: CML BIM 3 Primary Drug Resistance BH3 mimetics Imatinib Death of Bcr-ABL: CML BIM Leukemia cells Ng KP, Nat Med. 18(4):521-8 (2012)
This genomic experiment with 5 patients explains the lower response rate In North Asians to a life saving treatment in CML. Personalizing medicine in Asia Now: New ~50% cytogenetic response CML Patient in Asia Check for bcr-ABL YES rearrangement Check for 2.9kb deletion polymorphism in BIM YES NO Imatinib ? ? & BH3-mimetic Imatinib >75% cytogenetic 75% cytogenetic ? response response
Translation Initiative We will construct avatars of your cancer: So that we can discover the best drugs for  your cancer So that we can devise personalized and  private diagnostic for your cancer So that we understand the nature of your  cancer and explore the reasons for drug  resistance So that we may project how your cancer  might evolve
PDX of patient = Patient “Avatar” of Drug Response Drug 1 Questions Single tumor Drug 2 Addressed: from a patient What drugs will be effective for Drug 3 my tumor? How to combine these drugs? Drug 4
Predictive for Therapeutics Activity of afatinib, cetuximab and erlotinib in LG703
Cancer Avatar: General workflow Patient Tumor from Hartford Hospital JAX CT/BH JAX West Deep Sequencing PDX Model: Test Drugs predicted by genomics Genome Analysis: Extract the Source Code Future Treatments Immediate Personalized Treatment Plan Diagnostic
Radiologist of the Genome Radiologist Interprets complex data rendered through Is the consultants computational algorithms to doctors
What is the field looking for? • Tools and processes to enhance efficiency in the medical system • Life style enhancement: prolonging productive life and healthspan preventive therapeutics health monitoring performance enhancement mobility and independence • Personalization of information and medical care
Navigating the FDA March 15,2013 Edison Liu, M.D.
Navigating the FDA: Getting to Market Marketing at the Speed of Light Panelists Pamela Bunes CEO, President & Director EpiEP, Inc. Harry Penner Co-founder, Executive Chairman New Haven Pharmaceuticals Dr. Frank Sciavolino Co-founder, Board Member, Chief Scientific Officer & President Thetis Pharmaceuticals LLC
Navigating the FDA: Getting to Market March 2013 Crossroads Venture Group
Overview  Pre-Clinical Requirements  Shift in Approval Requirements  Clinical Trial Sizing  Diagnostics  505(b)2 36
 Premier Chemistry – Yale - Multiple Partners  Pfizer – Schering Plough – Merck – Am. Home  Anxiety / Alzheimers / Sleep / Obesity / Schiz.  FDA Pre-Clinical Requirements Increased 37
 Multiple Programs - Antibiotics  Nobel Laureate Science – Tom Steitz (Yale)  Premier Investors  FDA Changed Approval Criteria After Phase II 38
 In-Licensed Programs – Purdue + Yale  Premier Investor Base – Domain / Canaan / FMP  Epilepsy – Core Focus  Equivocal Trial Results – Too Small “n” 39
n  Diagnostic - CSF Detection  CI / Launch Capital / Management Financed  Ambitious Multi-antibody Strip Test  510k vs. PMA 40
 In-licensed Programs – Flamel + Yale  CI + Ironwood + Enhanced + Kuzari + EJ Funds  Lead Product – Anti-Platelet  505(b)2 – Multiple FDA Interactions  CMC + Approval Issues 41
Closing Points  Stay Abreast of All FDA Related Trends – Pre-clinical to Approval  Maintain Strong Contact to FDA – Except When It Might Be Judicious Not To  March to NDA - Process is Critical – The Longest Path to Approval Is a Short Cut 42
THANK YOU CVG SPONSORS B Round A Round Venture Capital Sponsors Professional Service Firms
CVG Upcoming Events Boardroom Series Second Thursday 7:30 AM – 9:00 AM 4:30 PM – 7:00 PM March 20 April 11 Investment by Strategics Electronic Health Records (EHR) Hartford A Look at the Industry and Its Future March 27 Hartford Employment and Immigration Issues Stamford May 9 April 3 Financial Services Stamford M&A: Legal Implications Stamford June 13 April 12 BioTech/Pharma M&A: Tax Considerations Hartford Glastonbury
CVG 2013 Calendar Offering 60 Events Attendance to all Second Thursday events is free for members.

More Related Content

Navigating the FDA: Getting to Market – CVG Second Thursday, 3/14/13

  • 1. THANK YOU CVG SPONSORS B Round A Round Venture Capital Sponsors Professional Service Firms
  • 2. Welcome Marketing at the Speed of Light Konstantine Drakonakis Director, New Haven LaunchCapital CTNEXT: New Haven Hub Derek Koch Usha Pillai
  • 3. Three Minute Pitches Marcia Fournier Judson Brewer Lew Bender John Bala SterileWave Medical Corp.
  • 4. Navigating the FDA: Getting to Market Marketing at the Speed of Light Introduction Paul Hughes Partner Wiggin and Dana LLP Keynote Edison T. Liu, M.D President & CEO The Jackson Laboratory
  • 5. Navigating the FDA or What is on the horizon? March 15,2013 Edison Liu, M.D. edison.liu@jax.org
  • 6. We discover precise genomic solutions for disease and empower the global biomedical community in our shared quest to improve human health. The Jackson Laboratory To discover precise genomic solutions for better medicine
  • 7. Biomarker Discovery in Cancer Then: Single biomarker, spurred by a some laboratory findings, years of development before reaching clinic One marker  many samples Now: Interrogation of a cancer genome, in silico validation, identification of new therapeutic targets Many markers  few samples Oct 1997
  • 8. HER2 and clinical trials Start of study CALGB 8869: 1989 Ann Thor Don Berry Publication of final paper: 1998 Soon Paik Mei He Lynn Dressler Craig Henderson Hyman Muss In vitro observation: ARAC – RAS interaction J Natl Cancer Inst. Koo, et al. Can Res 59:6057, 1999 90(18):1346-60 (1998) Patients with acute myeloid leukemia and RAS mutations benefit most from postremission treatment with high-dose cytarabine: a Cancer and Leukemia Group B study. Neubauer A, et al. J Clin Oncol. 26(28):4603-9, 2008. 9 years per marker, over 1,500 patients: There has got to be a better way
  • 9. Biomarker Discovery in Cancer Then: Single biomarker, spurred by a some laboratory findings, years of development before reaching clinic One marker  many samples Now: Interrogation of a cancer genome, in silico validation, identification of new therapeutic targets Many markers  few samples Oct 1997
  • 10. Sequenced Breast Cancers: focusing on  structural mutations PET library construction PET sequences mapping Analysis of Cancer & sequencing to reference genome  Specific Mutations 1Kb 10Kb PET mapping span Concordant PET  tag density Automated cancer  genome assembly: Concordant PETs 7 month analysis to 4 days Discordant PETs SOLiD
  • 11. Structure variations Deletion Unpaired inversion (Inverted orientation)  Abnormal length Different strand Tandem Duplication Translocation Incorrect order  Different chromosome Fusion points  predict fusion genes
  • 12. Structural Genomic Changes in Breast Cancer Genome Research 21(5):665-75 (2011)
  • 13. Cancer rearrangements are most often private and unique: Irrelevant mutations or part of the “long tail” Inaki K, et al. Transcriptional consequences of genomic structural aberrations in breast cancer. Genome Res. 2011 May;21(5):676-87.
  • 14. Gene ontology (GO) analysis of genes with break points in cancer genomes: There is a higher organization to the collection of single structural mutations Breast cancer Gastric cancer 1) Genes with break points RefGen Expecte Obser RefGen Expecte Obser Biological Process3) +/‐ P value +/‐ P value e d ved e d ved Cell adhesion‐mediated  386 20.88 51 + 2.22E‐06 Cell adhesion 592 31.61 73 + 2.62E‐09 signaling Cell adhesion‐ Cell adhesion 592 32.02 65 + 3.47E‐06 386 20.61 49 + 9.66E‐06 mediated signaling Neuronal activities 561 30.34 54 + 1.52E‐03 Signal transduction 3256 173.84 222 + 1.53E‐03 Biological process unclassified 5972 322.97 269 ‐ 3.04E‐03 Synaptic transmission 275 14.68 33 + 3.24E‐03 Electron transport 230 12.44 2 ‐ 1.05E‐02 Cell communication 1207 64.44 98 + 4.47E‐03 Other intracellular signaling cascade 212 11.47 27 + 1.12E‐02 Neuronal activities 561 29.95 51 + 6.94E‐03 Cell communication 1207 65.28 97 + 1.16E‐02 Biological process unclassified 5972 318.84 273 ‐ 2.36E‐02 Chemosensory perception 204 11.03 1 ‐ 2.67E‐02 Chemosensory perception 204 10.89 1 ‐ 3.04E‐02 Developmental processes 2065 111.68 144 + 2.97E‐02 Genes in recurrent high copy regions2) 2.35E‐ Chromatin packaging and  0.0024 Signal transduction  3256 151.33 100 ‐ 194 2.21 11 +  05 remodeling  9 Cell surface receptor mediated signal  2.05E‐ 1576 73.25 41 ‐ transduction  03 7.74E‐ Developmental processes  2066 96.02 65 ‐ 03 1.39E‐ G‐protein mediated signaling  793 36.86 16 ‐ 02
  • 15. RPS6KB1‐TMEM49 fusion gene induced by tandem  replication is found in 30% of breast cancers.  5’ TMEM RPS6K (~100kb) 5’ TMEM RPS6K (~100kb) 5’ TMEM RPS6K TMEM RPS6K (~100kb) (~100kb) 5’ TMEM RP EM RPS6K RPS6KB1-TMEM49 fusion gene
  • 16. Historical data Expression of RPS6KB1‐VMP1 fusion Our data is correlated with: ‐Poor prognosis ‐Expression of neighboring oncogenes  around the tandem duplication ‐Expression of oncogenes in ~3Mb adjacent  region ‐ Associated with gene amplification of locus  The fusion gene is always associated with amplification of this region
  • 18. Indicator structural mutation:  S6K‐TMEM Fusion Transcript is an indicator of the amplification of an “oncogenic region” of the genome miRNA21 Oncogenic TMEM 49 S6Kinase bloc miRNA21 miRNA21 Tandem duplication S6 TMEM  TMEM 49 Kinase S6Kinase 49 Gene Amplification
  • 19. Genomic Organization and Cancer: Higher order organization of mutations in cancer genomes Chromosome as an oncogenic organizer Chromosomal “origami” to generate cancer gene cassettes Effect of the germline on cancer therapeutic outcome Focus on Structural Mutations in Cancer Systems Oncogenomics
  • 20. Chronic Myelogenous Leukemia (CML) Optimizing treatment for CML based on genetic  makeup of the patient KP Ng, Axel Hillmer,… Yijun Ruan. Ong Sin Tiong Nat Med. 2012 Mar 18;18(4):521‐8. Imatianib (Gleevec) – primary and effective treatment Clinical Challenge: Drug resistance • Acquired resistance – resistance after long term  treatment ‐ due to second ABL mutation • Primary resistance – resistance at the beginning of  treatment.  • In Asia, complete cytogenetic response rates are lower ‐ 50% vs. 74%.  Mechanism unknown   
  • 21. Question: is there a reason why 25% of CML cases do not respond to imatinib? Approach: Compared the genomes of three CML cases with primary resistance to Imatinib with two CML cases sensitive to Imatinib therapy Results: 3/3 resistance cases had the same 2.9kb deletion in the BIM gene not seen in sensitive cases (0/2) Ng KP, Nat Med. 18(4):521-8 (2012)
  • 22. BIM: • BIM is a gene that activates cell death (pro‐apoptotic).  • Activated BCR‐ABL1, suppresses BIM function thus  allowing leukemia cells to survive. When CML cells are  treated with Imatinib, BIM expression goes up  cell  death Death of Bcr-ABL: CML Intact BIM Leukemia cells Imatinib
  • 23. How does it work?:    The 2.9kb BIM deletion polymorphism results  an abnormal transcript (E3) that a produces a truncated and inactive  BIM protein Normal Transcripts E3 Imatinib Death of Bcr-ABL: CML Intact BIM Leukemia cells Imatinib Deletion Polymorphism Bcr-ABL: CML BIM Primary E3 Drug Resistance
  • 24. BIM deletion polymorphism: • This deletion polymorphism is 3‐5X more common in  CML cases resistant to imatinib that sensitive cases • This 2.9 kb 2 deletion of BIM is not a mutation, but is a  polymorphism present in normal genomes (a germline polymorphism): 12% in Asian individuals 0% in Africans  0% in Caucasians
  • 25. We used this genomic intelligence to overcome this resistance: Imatinib Bcr-ABL: CML BIM 3 Primary Drug Resistance BH3 mimetics Imatinib Death of Bcr-ABL: CML BIM Leukemia cells Ng KP, Nat Med. 18(4):521-8 (2012)
  • 26. This genomic experiment with 5 patients explains the lower response rate In North Asians to a life saving treatment in CML. Personalizing medicine in Asia Now: New ~50% cytogenetic response CML Patient in Asia Check for bcr-ABL YES rearrangement Check for 2.9kb deletion polymorphism in BIM YES NO Imatinib ? ? & BH3-mimetic Imatinib >75% cytogenetic 75% cytogenetic ? response response
  • 27. Translation Initiative We will construct avatars of your cancer: So that we can discover the best drugs for  your cancer So that we can devise personalized and  private diagnostic for your cancer So that we understand the nature of your  cancer and explore the reasons for drug  resistance So that we may project how your cancer  might evolve
  • 28. PDX of patient = Patient “Avatar” of Drug Response Drug 1 Questions Single tumor Drug 2 Addressed: from a patient What drugs will be effective for Drug 3 my tumor? How to combine these drugs? Drug 4
  • 29. Predictive for Therapeutics Activity of afatinib, cetuximab and erlotinib in LG703
  • 30. Cancer Avatar: General workflow Patient Tumor from Hartford Hospital JAX CT/BH JAX West Deep Sequencing PDX Model: Test Drugs predicted by genomics Genome Analysis: Extract the Source Code Future Treatments Immediate Personalized Treatment Plan Diagnostic
  • 31. Radiologist of the Genome Radiologist Interprets complex data rendered through Is the consultants computational algorithms to doctors
  • 32. What is the field looking for? • Tools and processes to enhance efficiency in the medical system • Life style enhancement: prolonging productive life and healthspan preventive therapeutics health monitoring performance enhancement mobility and independence • Personalization of information and medical care
  • 33. Navigating the FDA March 15,2013 Edison Liu, M.D.
  • 34. Navigating the FDA: Getting to Market Marketing at the Speed of Light Panelists Pamela Bunes CEO, President & Director EpiEP, Inc. Harry Penner Co-founder, Executive Chairman New Haven Pharmaceuticals Dr. Frank Sciavolino Co-founder, Board Member, Chief Scientific Officer & President Thetis Pharmaceuticals LLC
  • 35. Navigating the FDA: Getting to Market March 2013 Crossroads Venture Group
  • 36. Overview  Pre-Clinical Requirements  Shift in Approval Requirements  Clinical Trial Sizing  Diagnostics  505(b)2 36
  • 37.  Premier Chemistry – Yale - Multiple Partners  Pfizer – Schering Plough – Merck – Am. Home  Anxiety / Alzheimers / Sleep / Obesity / Schiz.  FDA Pre-Clinical Requirements Increased 37
  • 38.  Multiple Programs - Antibiotics  Nobel Laureate Science – Tom Steitz (Yale)  Premier Investors  FDA Changed Approval Criteria After Phase II 38
  • 39.  In-Licensed Programs – Purdue + Yale  Premier Investor Base – Domain / Canaan / FMP  Epilepsy – Core Focus  Equivocal Trial Results – Too Small “n” 39
  • 40. n  Diagnostic - CSF Detection  CI / Launch Capital / Management Financed  Ambitious Multi-antibody Strip Test  510k vs. PMA 40
  • 41.  In-licensed Programs – Flamel + Yale  CI + Ironwood + Enhanced + Kuzari + EJ Funds  Lead Product – Anti-Platelet  505(b)2 – Multiple FDA Interactions  CMC + Approval Issues 41
  • 42. Closing Points  Stay Abreast of All FDA Related Trends – Pre-clinical to Approval  Maintain Strong Contact to FDA – Except When It Might Be Judicious Not To  March to NDA - Process is Critical – The Longest Path to Approval Is a Short Cut 42
  • 43. THANK YOU CVG SPONSORS B Round A Round Venture Capital Sponsors Professional Service Firms
  • 44. CVG Upcoming Events Boardroom Series Second Thursday 7:30 AM – 9:00 AM 4:30 PM – 7:00 PM March 20 April 11 Investment by Strategics Electronic Health Records (EHR) Hartford A Look at the Industry and Its Future March 27 Hartford Employment and Immigration Issues Stamford May 9 April 3 Financial Services Stamford M&A: Legal Implications Stamford June 13 April 12 BioTech/Pharma M&A: Tax Considerations Hartford Glastonbury
  • 45. CVG 2013 Calendar Offering 60 Events Attendance to all Second Thursday events is free for members.