BIOCRATES Life Sciences AG
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1 BIOCRATES Life Sciences AG The Deep Phenotyping Company European Business Development Conference BIO-Deutschland, Dr. Wulf Fischer-Knuppertz CEO 1
2 The Company Targeted Metabolomics Founded 2002 in Innsbruck, Austria Spin-off University Innsbruck 2006: world s first metabolomics kit on market 2013: 1 CE-marked IVD, 5 research kits commericially available, Services Lab 50 Employees 2
3 Agenda 1. Deep Phenotyping 2. Technology Evolution of Metabolomics Research 3. Products & Services 4. Matching of Analytical Data and Knowledge 5. Standardization of Data Format 6. Areas of Application & Indications (Biomarker) 3
4 Deep Phenotyping Mass Spectrometry based Metabolic Analysis 4
5 Metabolic Phenotyping From single Biomarker to Metabolic Signature Diseases / Disorders Personalized Medicine Phenotype Metabolic endpoints Dynamics - Early diagnosis - Disease Staging - Drug response prediction - Treatment efficacy - Toxicology markers Metabolic Signatures Dis-regulations/ Pathways - Amino Acid - Fatty Acid - Lipids - Energy Metabolism 5
6 Deep Phenotyping Evolution of Metabolomics Research I II III IV Qualitative Untargeted Mx Profiling Semi-quantitative Targeted Mx Quantitative Targeted Mx Standardized data format Quality controlled IVD Companion Diagnostics Metabolite Inventory Pathway Identification Pathway Validation Disease Signatures Diagnostics number of samples number of metabolites 6
7 Broad Analytical Panel > 210 analytes in kits, > 630 analytes in service lab Metabolite Classes Metabolites Contract Research p150 Kit p180 Kit MetaDis Kit SteroIDQ Kit Stero17 Kit Acyl carnitines x x x x Amino acids x x x x Hexose 1 x x x x Sphingolipids 15 x x x x Glycerophospholipids x x x x Biogenic amines x x x Steroid hormones x x x Neurotransmitters 9 x Bile acids 17 x Eicosanoids 17 x Fatty acids 62 x Intermediates energy metabolism 15 x Oxysterols 16 x Phospholipids and ceramides 331 x Vitamins 12 x Fat-soluble vitamins 4 x Oxidative stress 6 x 7
8 Product & Services Product Portfolio AbsoluteIDQ p180 Kit Acylcarnitines Glycerophospho- and sphingolipids Hexose Amino acids (LC-MS/MS) Biogenic amines (LC-MS/MS) AbsoluteIDQ MetaDis Kit Metabolic Syndrome Diabetes Mellitus Type 2 Diabetic nephropathy/ckd 186 analytes 163 analytes SteroIDQ Kit (CE/IVD) 16 steroid hormones: 3 classes - Mineralcorticoids - Glucocorticoids - Sex steroids 16 hormones 8
9 Biocrates: Deep Phenotyping Fully Integrated Center of Competency Know-how in Metabolomics Sample Banking Assay Portfolio KIT Development Expertise Products on the Market Contract Research Biomarker/ Signatures Kit Disorders, Pathways Spearhead to recognize new customer demands Indication / metabolites relationship Translation into new Kits and IT-tools 9
10 Product & Services Analysis of run data and external data Integration of analytical results and external databases Integration of metabolite pathways and diseases Pubmed Molecules & Pathways Metabolites of AbsoluteIDQ p180 Kit can be found in approx. 200 pathways Database Molecules & Pathways 10
11 Standardization of Data Formats Multidimensional compilation of data for analysis different labs & MS/MS instruments interlaboratory comparison different instrument technologies Deep Phenotyping Quality tagged Concentration MetIDQ Database Quantified Metabolites Samples Outcome: Harmonized & Standardized data format in one combined data base different Omics technologies Metabolomics Proteomics Genomics data collection/ storage long time reliable for re-analysis e.g. need for comparability in drug development phases for regulatory submission 11
12 Areas of Application New insights in disease related metabolic disorders Diabetes/ Metabolism Floegel et. al. 2012: Early metabolic alterations are associated with T2D risk Kidney Disease Goek et al. 2012: Distinct metabolic phenotypes were reproducibly associated with egfr in 2 separate population studies Cancer Qiu et. al. 2013: Based on 3 metabolites, breast cancer patients could be differentiated from healthy controls with a sensitivity of 98.1 % and a specificity of 96.0 %. Pharmaceutical Research Suhre et. al. 2011: One advantage of our approach of determining metabolite ratios is that they provide a highly reproducible measure [of acute drug response] 12
13 Thank You for Your Attention! Contact: 13
14 Back-up 14
15 Areas of Application Indication: Diabetes/Metabolism Floegel et. al. 2012: Early metabolic alterations are associated with T2D risk Lehmann et. al. 2013: Metabolic patterns allow for a differentiation between metabolically benign and metabolically malign Non-alcoholic Fatty Liver Horakova et. al. 2012: A combined use of PUFA and Thiazolidinediones (TZDs) could improve efficacy of the therapy of obese and diabetic patients Differentiation of Metabolic Syndrome and Type 2 Diabetes from healthy controls by defining metabolic phenotypes Monitor early deregulations of metabolism such as markers of sub-clinical inflammation, oxidative stress, or insulin resistance, and influencing factors for those Predict and assess anti-diabetic drug efficacy, define metabolic phenotypes of drug response 15
16 Areas of Application Indication: CKD/ Kidney Toxicity Goek et al. 2012: Distinct metabolic phenotypes were reproducibly associated with egfr in 2 separate population studies Lundin et al. 2011: Kidney disease is associated with metabolic changes, involving Tryptophane metabolism and confirming the role of SDMA as a marker of kidney function. Monitor renal function Identify distinct metabolomic profiles in different stages of CKD Observe metabolic changes induced by nephrotoxicants Improve decision making for drug therapy (treatment strategy, [nephro]toxic drug effects, dose finding) 16
17 Areas of Application Indication: Cancer Qiu et. al. 2013: Based on 3 metabolites, breast cancer patients could be differentiated from healthy controls with a sensitivity of 98.1 % and a specificity of 96.0 %. Jaeger et. al. 2011: Metabolomic analysis elucidated several small molecules as markers for the response of breast cancer cells to resveratrol. Identification of novel biomarkers for cancer and cancer progression Better knowledge of common pathological pathways of cancer, cancer-related complications and major co-morbidities Finding determination of treatment success and individual susceptibility for adverse treatment effects 17
18 Areas of Application Pharmaceutical Research Suhre et. al. 2011: One advantage of our approach of determining metabolite ratios is that they provide a highly reproducible measure [of acute drug response] Kus et. al. 2011: Differences between Rosiglitazone and Pioglitazone became apparent. Horakova et. al. 2012: These beneficial metabolic effects support the idea that a combined use of PUFA and Thiazolidinediones (TZDs) could improve efficacy of the therapy of obese and diabetic patients Elucidation of on-target and off-target drug effects Use of a single analytical approach from early phase research to late phase clinical trials Definition of target sub-populations (metabolic phenotypes) likely to overproportionally benefit from a new drug 18
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