Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

The CZ region BIOMEDREG

505 views

Published on

EuroBioForum 2012 | 18 April 2012
Presentation by Marian Hajduch, Coordinator at BIOMEDREG

Published in: Travel, Health & Medicine
  • Be the first to comment

  • Be the first to like this

The CZ region BIOMEDREG

  1. 1. Introduction to Personalized Medicine in the CzechRepublic and BIOMEDREG Project as a New Research Platform for Molecular and Translational Medicine Marian Hajduch, MD, PhD Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc Czech Republic EuroBioForum 2012, Brussels
  2. 2. Palacký University in Olomouc• Established in 1573•The second oldest university after the Charles Universty in Prague•Olomouc Archibishop – center of Moravian religion and education – alumni or region associatedscientists: Johann Gregor Mendel, Sigmund Freund, Konrad Zirm, Otto Wichterle, Frantisek Santavy,Jiri Bartek•Currently 23.000 students, approx. 7% of Czech university students and 3000 employees OLOMOUC Johann Gregor Mendel Konrad Zirm
  3. 3. • Part I – Introduction to Personalized Medicine in the Czech Republic• Part II – BIOMEDREG Project as a New Research Platform for Molecular and Translational Medicine
  4. 4. Biomarker use Prognostic Predictive estimates the responseprovides information about to a specific treatment patient outcome, before the advance regardless of therapy of therapy Pharmacological estimates changes Surrogate after treatment substitutes associated a clinical endpoint with target hit by therapy
  5. 5. History of Personalized Medicine in the Czech Republic (Oncology)• Started in 2002 with introduction of trastuzumab (Herceptin) on theCzech market•Critical role of health insurance companies (request for centralizeddiagnostics of HER-2 gene)• 2002-2010 Reference Laboratory at Palacky University in Olomouc•2005- Systemic collection of clinical information on patients treatedwith biological therapies for evaluation of cost effectiveness (drugregistries)•2008- Introduction of six new laboratories of predictive medicine acrossthe country for predictive cancer biomarkers
  6. 6. Predictive Cancer Biomarkers – Where we are?Part of the clinical routine#• Her-2 in breast and gastric cancers (trastuzumab, lapatinib)• KRAS/BRAF mutations – colorectal cancers (cetuximab, panitumumab) Mutation present EG F Resistant to TK• EGFR1 mutations – NSCLC (gefitinib, erlotinib) Gefitini b GTP inhibitros Erlotini k- b Ras PI13• BRAF mutations – melanoma (vemurafenib)* Raf AKT Mek• ALK translocations – NSCLC (crizotinib)* MAPK#diagnostics is paid from the health insurance Cellular proliferation*not reimbursed yet and survival
  7. 7. Specialized Molecular Diagnostics of Cancers – HER-2 gene IHC:0 FISH: normal Her-2/neu CEP 17 IHC: 1+ to 2+ IHC: 3+ FISH: amplification Laboratory/Institute holds accreditation decision according to CSN ISO/IEC 17025/15189 to meet European diagnostic standards (www.cia.cz)
  8. 8. Immunohistochemistry discordances among RL a LLs >1 or >2 IHC grades Discordance 0-6 6-12 12-18 18-24 24-30 30-35 0-35 RL vs. LLs months months months months months months months (%) (%) (%) (%) (%) (%) (%) ≥ 2 IHC 14,08 19,51 12,59 19,33 31,52 36,99 21,33 ≥ 1 IHC 28,17 43,90 37,04 40,34 50,00 53,42 41,61
  9. 9. Survival analysis (TTP) of mBRC Her-2 Therapeutic response of metastatic Her-2 patients on trastuzumab based therapies. positive breast cancer patients to Comparison of patients examined versustrastuzumab based therapies. Comparison not examined in the Reference laboratoryof patients examined versus not examined (RL). in the Reference laboratory (RL). Median TTP of RL examined pts.: RL 64,6 (χ2 = 6,27, df = 1, p = 0,01) weeks Median TTP of RL not examined pts: 37,7 weeks Overall median CR+PR_SDí PD TTP: 48,41 weeks 100 % Percentage of patients not examined in RL 100% p=0.02 examined in RL 80 % all pts. 80% Percentage of patients CR+PR+SD 60% 60 % PD 40% 20% 40 % 0% 20 % RL yes RL no N = 42 N = 83 0% 0 20 40 60 80 100 120 140 160 180 200
  10. 10. Evaluation of HER-2 gene in breast cancer patients by FISH assay in Reference laboratory in Olomouc trastuzumab in local 900 BRC 800 785 726 742 700 679 610 600number of patients 500 400 350 300 trastuzumab 285 287 274 in metastatic 200 BRC 100 68 32 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 years
  11. 11. Major Comprehensive Cancer Centers and Comprehensive oncologyDiagnostic Laboratories – Self Learning System centers Hematooncology centers Predicitive medicine laboratories Ústí n. L. Masaryk Hospital Liberec in Usti nad Labem Regional Bioinformatics, biostatistics Hospital Liberec and drug registries Hradec Králové Prague University Hospital in University Hospital Hradec Kralove i Plzeň Motol University Hospital Na University Hospital Plzen Bulovce and General Forum of Oncologists University Hospital Biannual Therapeutic Standards Ostrava University Hospital Ostrava Jihlava Olomouc Regional Hospital Jihlava University Nový Jičín Hospital Olomouc Regional České Budějovice Hospital Brno Novy Jicin Regional Hospital Ceske Masaryk Memorial Cancer Budejovice Institute Brno University Hospital Brno Zlín and St. Annes University Regional Hospital Hospital Zlin Laboratories must hold accreditation decision according to CSN ISO/IEC 17025/15189 to meet European diagnostic standards and perform external quality control.
  12. 12. Sample size in the registries: overview (the system started with Herceptin in 2005)Breast Registry Renis – mRCC Registry Herceptin – adjuvant Sutent 1221 1852 therapy Nexavar 719 Herceptin – mBC 1120 Afinitor 204 Herceptin – combined 194 Torisel 47 Lapatinib 222 Avastin 40 Avastin 85 Registry Corect – Colorectal CancerNSCLC Registry Avastin 3731 Tarceva 2183 Erbitux 815 Alimta 819 Vectibix 183 Avastin 59 Iressa 31 TOTAL:Alimta - MPM 124 > 13 500 valid recordsTarceva – Pancreatic cancer 58
  13. 13. Accessible follow-up (in months) Follow-up (months) Min Median MaxRegistry Therapy Sample Median Min Max Herceptin – adjuvancy 1593 17,5 0,0 63,9 Her-adjuvance Herceptin - mBRC 1005 18,5 0,1 112,8 HER-mBCBreast Lapatinib 213 7,8 0,0 45,3 lapatinib Avastin 83 11,2 0,7 38,2 avastin Avastin 3612 11,9 0,0 70,4 Avastin-crcCorect Erbitux 787 9,0 0,0 68,3 erbitux Vectibix 168 6,7 0,0 29,5 vectibix Tarceva 2121 4,3 0,0 54,3 TarcevaTulung – Alimta 786 5,6 0,0 43,0 AlimtaNSCLC Avastin 56 7,4 0,2 18,5 Avastin Iressa 28 3,3 0,0 14,6 Iress 0 20 40 60 80 100 120 Follow-up (months)
  14. 14. Duration of applied target therapy as example of quantitative outcome (suitable for assessment of economic demands) Therapy duration (weeks) 10% percentile Median 90% percentileRegistry Therapy Sample Median 10% 90% Herceptin – adjuvancy1) 1132 50,9 30,0 54,6 Herceptin - adjuvance Herceptin – mBRC1) 727 45,6 11,0 124,1 Herceptin - mBCBreast Lapatinib 149 20,6 5,7 58,4 Lapatinib Avastin 55 25,0 6,0 55,0 Avastin - Prs Avastin 2610 26,0 7,8 66,4 Avastin - crcCorect Erbitux 612 19,1 2,1 52,1 erbitux Vectibix 119 16,9 4,0 46,0 vectibix Tarceva 1671 11,0 3,0 43,9 tarcevaTulung – Alimta 683 9,0 3,0 18,4 alimtaNSCLC Avastin 41 16,0 3,3 29,3 avastin Iressa 13 9,0 4,1 31,7 iressa 0 25 50 75 100 125 Therapy duration (weeks)
  15. 15. Herceptin (adj. therapy) – progression-free survival N*=1583 Survival time calculated since the therapy onset.1,00,8 PFS Median PFS Not reached (95% IS)0,6 % patients PFS (95% IC)0,4 1yr PFS 96,9 (96,0; 97,9) 2yr PFS 94,3 (92,9; 95,7)0,2 5yr PFS 93,4 (91,7; 95,1)0,0 0 12 24 36 48 60 72 84 96 Time (months)
  16. 16. Herceptin (mBRC) – progression-free survival N= 1005 Survival time calculated since the therapy onset.1,0 PFS0,8 Median PFS 14,5 months (95% IS) (12,8; 16,2)0,6 % patients PFS (95% IC)0,4 1yr PFS 56,5 (53,3; 59,8) 2yr PFS 27,4 (24,0; 30,8)0,2 5yr PFS 17,6 (13,9; 21,3)0,0 0 12 24 36 48 60 72 84 96 108 120 Time (months)
  17. 17. Uniqueness of the Czech National Cancer Registry• the Czech National Cancer Registry (CNCR) contains almost 1.8 mil. records on cancer patients since 1977• population-based data, covering 100% of the Czech population• double control of mortality data: records are independently verified against Death Records Database• mortality coding according to WHO nomenclature• all cancer diagnoses included
  18. 18. Predictive information system for cancer care:Step 2 = Predictive estimation of incidence and prevalence Breast cancer (C50) INCIDENCE Number of cases 2012 (90% confidence interval) Stage I 3,353 (3,126; 3,580) Stage II 2,212 (2,026; 2,399) Stage III 1,004 (884; 1,123) Stage IV 573 (498; 649) Unstaged 214 (157; 269) TOTAL 7,356 (6,691; 8,020) PREVALENCE Number of cases 2012 (90% confidence interval) Stage I 30,933 (30,644; 31,222) Stage II 28,131 (27,855; 28,407) Stage III 7,490 (7,348; 7,632) Stage IV 3,600 (3,501; 3,699) Unstaged 2,228 (2,150; 2,306) TOTAL 72,382 (71,498; 73,266)
  19. 19. Success of the breast cancer screening program: (c) increasing proportion of early-stage cancers there has been substantial increase in proportion of early-stage cancers during recent years 100% Organised breast Proportion of cases cancer screening 80% 60% 40% 20% 0% 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 2099 2000 2001 2002 2003 2004 2005 2006 2007 2008 09 19 Rok Stage IV * DCO, cases diagnosed by autopsy, early Stage III Unstaged deaths, therapy had not been started due to objective reasons Stage II incomplete records Stage I objective reasons* Source of data: Czech National Cancer Registry
  20. 20. Data collection, mining, analysisProf. Ladislav Dusek, Ph.D. Jan Mužík, Ph.D., senior data analystdirector Institute of Biostatistics and AnalysesInstitute of Biostatistics and Analyses Masaryk University, Brno, CzechMasaryk University, Brno, Czech Republic Republic
  21. 21. ConclusionsPersonalized medicine (oncology) in the Czech Republic was centralized intoComprehensive Cancer Centers and six „reference“ laboratories of predicitivemedicine.The Czech Society for Oncology developed and implemented the full set ofregistries monitoring segment of targeted anti-tumor therapy includingbiomarkers.The registries are able to collect representative multidimensional data whichcannot be obtained directly from the other sources.Combination with other information sources allows to assess accessibility of careand to predict incidence and prevalence of treated patients.Registries offer comprehensive outcomes suitable for cost-effectivenessanalyses: direct and indirect care, hospital stays, dosage of medication and timeof medication, etc.Registries offer reliable outcomes necessary for the evaluation of safety, efficacyand quality of the care: adverse events, therapeutic response, survival,biomarkers.
  22. 22. • Part I – Introduction to Personalized Medicine in the Czech Republic• Part II – BIOMEDREG Project as a New Research Platform for Molecular and Translational Medicine
  23. 23. Infrastructural project for chemical biology and translational medicine (BIOMEDREG) – concentrating, evaluating and developing the national chemical and biomarker knowledge Compound storage/library Clinical High throughput trials screening Preclinical studies Institute of Organic Chemistry and Biochemistry, ASCR Institute of Chemical Technologies PragueMedicinal chemistry Palacký University Olomouc Universtiy Hospital Olomouc Data collection for national & Biomarkers international databases Biobanking Therapeutic standards
  24. 24. Biomedicine for regional development and human resources BIOMEDREGProject Leader: Primary aim:Palacký Universty in Olomouci To establish the Institute ofPartners: OLOMOUC Molecular and TranslationalUniversity Hospital in Olomouc Medicine at PalackyInstitute of Organic Chemistry and Biochemistry AS University in OlomoucCRInstitute of Chemical Technologies in PragueAllocation:Approx. 40 M €EU Structural Funds -2nd Priority Axis OP VaVpIPhase of the Project:Realization phase started on April 1, 2010Information:www.biomedreg.eu, www.imtm.cz
  25. 25. Building of research infrastrucutres in the Czech Republic 1952-56 2010-2012Professor of Pathology R. Kodousek
  26. 26. 1956 2012(construction phase – 15 months, 4700 m2)
  27. 27. Core facilities• Genomics (HTS qPCR in 1536 format), Affymetrix platform, NGS, mass spectrometry (Sequenome)• Proteomics (2x MALDI-TOF/TOF, HPLC-MS, qTRAP, qTOF, orbitrap)• Metabolomics (GC-TOF, qTRAP, orbitrap)• Microscopy: AFM, Raman microscopy, IR microscopy, confocal spinning disc and laser scanning microscopy, superresolution, PALM, SIM, TIRF, transmission and raster EM)• HTS/HCA analysis (compound library+dispensing, 3-arm robotic system for screening of small molecules in BSL2+/BSL3 and/or hypoxic environment, readers: fluorescence, luminisence, radioactivity, absorbance, wide field confocal HCA, mass spectrometry based screening)• BSL3 laboratories• Small animal imaging centre: optical (fluorescence, luminiscence)., X-ray, PET/CPECT/CT, ultrasound• Radiochemistry, medicinal and combinatiorial chemistry• Biobank
  28. 28. Research programs1. Molecular basis of diseases and molecular targets2. Medicinal chemistry3. Chemical biology nad experimental therapeutics4. Biomarkers5. Pharmacology and toxicology6. Translational medicine
  29. 29. Selected outcomes of the project (since April 2010)Publications with IF total: 96, cummulative IF=440, average IF=4,8 (IF<3: 45, IF 3-5: 27; IF5-10: 14; IF>10: 6)Patents: 6 national, 6 international, 1 spin-off9 graduated PhD. students83 scientists/PhD. students
  30. 30. IMTM is the national node for EATRIS: Relationship to other ESFRI and interest in further collaborations•BBMRI – interface: tissue and bio-banks, expertise in human and animal (model) pathology, qualitystandards, policies, patient data banks, disease-specific data banks;• ECRIN – interface: transfer of projects that successfully passed clinical phase 0, I and IIa studies toprogress with late phase II and beyond; use of ECRIN where multi-centre studies are needed evenfor early phase clinical trials; exchange observations from the clinic back to scientists (reversetranslation), expertise in regulatory affairs, common training courses;• INFRAFRONTIER – interface: consultation in choosing the right animal model for pre-clinicalstudies, characterisation of novel and disease-specific (mouse) models; archiving of such; qualitystandards and regulatory standards (animal husbandry, animal studies, etc.), training courses;• INSTRUCT – interface: service in /access to specialty infrastructure components in structural BIOMEDREGbiology, e.g. in small molecule characterization, elaboration of a biological mechanism of action; EATRIS• EU-Openscreen – interface: collaborative use of technology and interdisciplinary expertiseCEITEC for OLOMOUCsmall molecule discovery and development, access to large compound libraries or INSTRUCT ICRCchemoinformatics, databases; ECRIN RECAMO• EuroBioImaging – interface: collaboration on nonstandard/sophisticated problems in BBMR BRNObiomolecular or biomedical imaging, training possibilities;• ELIXIR (bioinformatics and databases) – interface: exchange on IT management, standarddefinitions for data collection, storage, utilisation, and on a mid- to long-term basis,agreements on data hosting etc.
  31. 31. PERSONALIZED MEDICINE THE RIGHT THERAPY TO THE RIGHT PATIENT ON RIGHT TIME LEADING TO OPTIMIZATION OF RISK/BENEFIT RATIO FOR INDIVIDUAL PATIENTTranslational Medicine Personalized Medicine
  32. 32. THANK YOU FOR ATTENTIONmarian.hajduch@upol.czhajduchm@gmail.comwww.imtm.czwww.medchembio.cz

×