Biomarkers of Pancreatic -cell Mass, Function, and Diabetes Treatment Selection

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1 Biomarkers of Pancreatic -cell Mass, Function, and Diabetes Treatment Selection Creative Partnerships in Biopharmaceutical Research CQDM / Montreal in vivo Meeting 8 June,

2 THE TEAM Marc Prentki Montreal Diabetes Research Center CRCHUM Remi Rabasa-Lhoret Montreal Diabetes Research Center IRCM Eustache Paramithiotis Caprion Proteomics Inc Pancreatic cell biology, Mechanisms of insulin secretion Cell & animal models Clinical practice Human physiology Phenotyping Biomarker discovery & validation Proteomics Translational Medicine Deep, complimentary expertise in our respective fields Prototype translational medicine collaboration Project would not have been possible without the CQDM initiative 2

3 DIABETES Progressive chronic disease Pathogenesis affected by physiology, genetics, environment Pancreatic -cells are central in pathogenesis Increasing incidence, particularly Type II diabetes Metabolically Healthy Normal weight Metabolically Healthy Overweight Insulin resistant Hyperinsulinemic Obese NGT IGT/IFG T2D Diet OHGAs OHGAs + Insulin Insulin sensitivity remains low Years Normal ß cell islets ß cell compensation ß cell dysfunction ß cell failure Prentki & Nolan, J Clin Invest

4 INDIRECT MEASUREMENTS OF -CELL STATUS Basal & stimulated glucose tolerance Blood C-peptide levels Glucose, insulin, pro-insulin levels Glycosylated hemoglobin (HbA1c) Currently available tests Imprecisely monitor physiological status of -cells Need biomarkers specific for -cell mass and function IMPACT Improve assessment of disease & treatments Better evaluate potential therapies & enable novel approaches Monitor pre-diabetics earlier & better 4

5 MULTIPLE TREATMENT OPTIONS FOR TYPE II DIABETES Success Success Success Success Life style failure + Met Failure Met and/ Met + Met and/or SU + Failure or SU+ Failure SU DPP-4i bedtime Ins Failure Safety /tolerability Safety : hypo Safety : tolerability Safety : hypo Success : Glycosylated HbA1c 7.0% or drops 1.5% Failure : Glycosylated HbA1c >7.0% or drops < 1.5% Success or Failure evaluated over 5 months Met: Metformin, SU: Sulfonyurea, DPP-4i : Incretin: Ins: Insulin Progressive -cell failure and other considerations drive treatment choice Distinct responder and non-responder groups; lacking effective segregation Improve matching of patients to effective medicines Patient stratification may drive targeted drug development Need biomarkers to aid treatment selection and monitor therapy 5

6 NOVEL BLOOD BIOMARKERS OF -CELL MASS & FUNCTION Target secreted proteins before release 30 Glucolipotoxicity G5.5 G20 P5.5 P20 Palmitate & glucose cause human islet cell death Use fresh human and animal model -cells, exposed or not to glucolipotoxic insult Use other relevant tissues Isolate secretory vesicles, identify differentially expressed and constitutive contents Define uniquely expressed & condition-specific -cell secretory proteins 6

7 PROMISING PRELIMINARY DATASET Biological process (#identified) Hormones/ cytokines (13) Proteolysis (16) Apoptosis (6) Exosome secretion (37) Examples of proteins identified Insulin, glucagon, somatostatin, neurosecretory protein, VGF MMP14, elastase 2A, pancreatic secretory trypsin inhibitor Clusterin, MIF, cathepsin B, endoplasmin, stress-70 protein Cofilin, moesin, Gi2, rab2, aspartate aminotransferase, stomatin Fresh human pancreatic -islets Rich dataset of relevant proteins identified 93 previously known signal sequence+ secreted proteins 85 novel signal sequence+ secreted proteins 37 signal sequence- secreted proteins Focusing on secretory vesicles substantially enhanced candidate discovery 7

8 -CELL MASS & FUNCTION BIOMARKERS PROJECT OUTLINE AIM 1 Biomarker discovery 1. Toxic or control treatment of isolated -cells 2. Secretory vesicle contents 3. Large scale proteomics AIM 2 Assay dev 4. Prioritize biomarker candidates; assemble panel 5. Reagent & multiplex MRM assay development AIM 3 Biomarker Validation 6. Validation in animal models 7. Validation in patient samples 8

9 EXAMPLES OF PREDICTIVE & PHARMACODYNAMIC BIOMARKER DISCOVERY Red: SOC Blue: Short term survival (<4 mo) Red: Longer term survival (>4 mo) Blue: SOC + Investigational Drug Pharmacodynamic markers Plasma comparisons 1 month posttreatment show effect of Investigational Drug in cancer Prognostic markers Baseline plasma comparisons can segregate g short and longer survivors 9

10 NOVEL BLOOD BIOMARKERS OF DIABETES TREATMENT SELECTION & MONITORING Discovery sample set Plasma from 40+ Type II diabetes patients before and soon after addition of glyburide to metformin therapy Follow for 5 months with standard tests to assess response Response predictive & pharmacodymanic biomarker discovery using collected samples Validation sample set Test plasma from independent metformin-glyburide patient set Additional populations Population/situation # [BCF] [BCM] Cross sectional Healthy normal glucose tolerant controls sex, age, and BMI matched with T1D or T2D patients 50 N N Obese (BMI>30 kg/m 2 ) new onset T2D 20 Lean (BMI<27 kg/m 2 ) new onset T2D 20 T2D under intensive insulin therapy 20 Prospective observational Baseline Follow-up Baseline Follow-up New onset T1D baseline and 18 months follow up 20 Pregnancy in NGT women 1 st vs 3 rd trimester 20 Pre vs post pancreatectomy 15 N N Short term intervention Healthy control o 6hr Somatostatin infusion 15 N N N The additional population samples will also be used for clinical evaluation of -cell mass & function biomarkers 10

11 TREATMENT SELECTION & MONITORING BIOMARKERS PROJECT OUTLINE AIM 1 Biomarker discovery 1. Discovery 2. Large scale samples & plasma clinical data proteomics AIM 2 Assay dev 3. Prioritize candidates; assemble panel 4. Multiplex MRM assay development AIM 3 Biomarker Validation 5. Validation in independent patient samples & controls 11

12 SUMMARY Aim to develop one or more panels of protein biomarkers able to effectively measure pancreatic -cell mass, -cell function, and predict likely response to specific therapies Such tests t are expected to have wide application in basic research, drug discovery, and clinical practice 12

13 CAPRION PROTEOMICS - INTRODUCTION Privately held company based in Montreal, Canada Leading proteomics technology (CellCarta ) and service provider: Biomarker discovery & validation Target discovery Dx discovery and development 35 employees (30 scientists) Founded in 2000 under Caprion Pharmaceuticals Inc. Spun-out into stand-alone service business and acquired by Great Point Partners, LLC in 2007 Established equity and strategic biomarker partnership with Covance in

14 PARTNERSHIP-DRIVEN BUSINESS MODEL Proteomics Services Caprion Proteomics Inc. In-vitro Diagnostics Biomarkers/Personalized Medicine Infectious disease Biomarker discovery - CellCarta Brucellosis Multiplexed MRM assays for rapid Tuberculosis biomarker validation 2others Drug Target discovery & validation Diabetes Oncology cell-surface targets for Oncology antibody therapy and Dx imaging Retained IP rights Infectious Disease vaccine and Discover, validate and antibiotic targets develop Dx products to Secreted protein targets/therapies human proof of concept Fee-for-service business model in Establish licensing partnership with pharma, biotechs and partnerships with Dx not-for-profit organizations Acheived operating profitability since 2006 companies for regulatory and commercial development 14

15 PARTNERSHIP-DRIVEN BUSINESS MODEL Caprion Proteomics Inc. Proteomics Services Biomarker discovery and validation In-vitro Diagnostics Infectious disease (NIAID) Diabetes (CQDM ) Drug Target discovery & validation Oncology Infectious diseases Oncology (TBD)

16 CAPRION IN-VITRO DIAGNOSTICS DEVELOPMENT STRATEGY Focus on initiatives that leverage and enhance Caprion existing core competencies CellCarta proteomics discovery in tissues (organelles) and plasma Multiplexed MRM assays for rapid biomarker validation Leverage expertise of academic and industrial partners that provide disease area knowledge and access to clinical i l biological i l samples Seek opportunities to secure significant non-dilutive funding to: engage g in longer term programs that can deliver validated/licensable product make it through valley of death with retained IP rights address fundamental but underfunded industry need for early-stage innovation in diagnostic biomarkers Integrate programs into a longer term strategy that diversifies Caprion from pure tech platform/service provider to a product company without need for significant venture capital Initiatives like CQDM are essential to Caprion success 16