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Michael J. Becich, MD PhD - becich@pitt Chairman, Department of Biomedical Informatics

Informatics and the Future of Pathology (and Medicine): Making a Case for The Need for Computational Pathologists. Michael J. Becich, MD PhD - becich@pitt.edu Chairman, Department of Biomedical Informatics http://www.dbmi.pitt.edu University of Pittsburgh School of Medicine.

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Michael J. Becich, MD PhD - becich@pitt Chairman, Department of Biomedical Informatics

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  1. Informatics and the Future of Pathology (and Medicine): Making a Case for The Need for Computational Pathologists Michael J. Becich, MD PhD - becich@pitt.edu Chairman, Department of Biomedical Informatics http://www.dbmi.pitt.edu University of Pittsburgh School of Medicine

  2. Disclosures by MJB • Corporate Support for API and APIII • 750K projected for 2013 [Cerner, Misys, GE, IBM, IMPAC, McKesson - Cisco, Verizon, CAP Today - Aperio, Apollo, Applied Imaging, De-ID Corp, GE Medical Systems/Triple G, Nikon, Omnyx, Olympus, SCC Soft, Sysmex, SNOMED, PSA, ThermoFisher, Zeiss, multiple others] • Startup/Public Companies (Royalties, Licensing or Stock - MJB): • Omnyx – Joint Venture with UPMC and GE (http://www.omnyx.com) – digital pathology • De-ID (http://www.de-idata.com/) licensing payments to DBMI and DBMI staff/faculty) – deidentification software for text medical records • Consultancy • Empire Genomics – Physician Advisory Board (paid) • NinePoint Medical – Technical Advisory Board (http://www.ninepointmedical.com/) – in vivo microscopy • Pathology Education Consortium (PEC) with Bruce Friedman (volunteer) • Cancer Center Consulting – MD Anderson, Moffitt Cancer Center, NFGC, UMDNJ, U CO, VCU (honorarium) • CTSA Consulting – Duke, MCW, Northwestern, U AK, UC Davis, U Chicago, UCLA, U KY, U NM, U MN, UC Davis, U WI/Marshfield, Wash U (honorarium) Slide 2

  3. Goals for today’s discussion • “Disruptive Technologies” and their Impact on the Practice of Pathology • CAP Transformations – wake up call • Redefining the populations we serve • Issues with AP and CP integration • The role of Pathology Informatics in Computational Pathology – call to action!!

  4. Goal • How will new technologies impact the future of pathology? • Key areas of evolution: • Molecular Path – Next Generation Sequencing • Imaging – Whole Slide Imaging • Personalized Medicine – Next Generation Warehousing of Data, Tissue/Blood and DNA • Medical Records and “Real” Decision Support • AP/CP Integration (Patient Oriented Reports)

  5. Objective • Today we will discuss trends in technology in Medicine and Pathology that will impact the way our profession is practiced in the next 5 to 10 years. • Focus will be on making the case for “Computational Pathologists” in Pathology Informatics Programs • Impact on Pathology’s Future • How to enable this transformation?

  6. Pathology Informatics is a Domain of Clinical Informatics

  7. Today’s Situation • AP and CP are not integrated • Molecular Diagnostics has no Laboratory Information system to support it • Imaging integration is in its infancy • Decision Support is Crude • Pathologists are playing a passive role in MMR, DS and Info Mgmt

  8. How Did We Get Here? • Pathology Reports have not changed in decades – this is a major problem • Original assumptions (pathologist as consultant to MDs) about the scope of our practice may no longer be valid • Pathology leadership is not Informatics savvy but progress is at hand. • Training Programs do not support the Informatics/Tech needs of trainees

  9. New Technologies and Their Impact • Whole Slide Imaging / Digital Pathology Workflow • WSI technology is maturing rapidly • GE, Phillips, Siemens all launching products • “Companion Diagnostics” are enabling deeper (and more complex) diagnostics • Next Generation Sequencing (NGS) • Massively parallel sequencing is here and 2nd generation machines (ABI, Illumina, etc…) are being replaced by 3rd generation technology (Ion Torrent, PacBio, etc…) • Implications are that an entire human genome can be done in a laboratory in about a month for about $10K • Goal with new technology is a few days and about $1K!!!

  10. Digital Can Improve Quality of Care in Pathology http://www.pathologyinformatics.org/Resources/ldip2103.jpg 1850 - Present H&E Lung Automated subcellular localization of RRM1 in 187 stage I NSC Lung Cancer patients, stratifies patients following surgical treatment. Today Automated IHC AQUATM Lung

  11. Advanced Diagnostics Enabled by Digital Pathology Ginty F, The relative distribution of membranous and cytoplasmic Met is a prognostic indicator in stage I and II colon cancer , Clinical Cancer Research, June 15 2008

  12. Circulating Tumor Cells Use of Imaging Tools Diagnostic innovation/invention are key to our future Clinical and Anatomic Pathology Convergence From Schwartz, CAP, 2009 Perspective on the Future of Pathology

  13. 360-sec 20x scan 60-sec 20x scan 20-second 40x multi-angle scan Imaging Multispectral imaging Rapid secondary consultations Subspecialist work flow triage Applications Computer-aided detection Computer-aided diagnosis 100 Terabytes Petabytes 100 Petabytes Enterprise image management Storage Pathology PACS 2017 2007 2012 Digital Pathology Timeline • This evolution will require development of sophistication in pathology departments in the areas of • Decision Support Tools • IntelligentArchiving • Image Processing and Analysis • Computer Assisted Vision for CAD • These are the domains of Computational Pathology!!! Modified from: From Schwartz, CAP, 2009 Emerging Developments and Your Future in Pathology * Source: Sg2 T3 Virtual Slide Imaging

  14. Industry recognizes the opportunity Are diagnostics the new wonder drug on Wall Street? From Schwartz, CAP, 2009 Perspective on the Future of Pathology

  15. WSI is key to the evolution of Surgical Pathology • Tumor diagnostics (which represents the majority of surgical pathology practice) are becoming increasingly important and complex • In our aging population patients survive with multiple cancer occurrences & die with their tumors not from them • Pathology itself is changing from primarily diagnostics to increasingly complex theranostics (personalized medicine) • Will require digital pathology/WSI for these advanced tools • Unlike clinical pathology (high degree of automation and quality control) anatomic pathology is not automated • Doesn’t easily render itself to standardization and quality control measures. • We need to begin the evolution of this important aspect of medicine as surg path case volume is expected to double in the next 5 years!!! Slide 16

  16. Personalized medicine and theranostics • Theranostics is applying the power of pathology to predict therapeutic response • Determining whether a treatment is working • Monitoring healthy people to detect early signs of disease • Producing safer drugs by predicting potential for adverse effects earlier • Targeting groups of people most likely to benefit from a drug, while keeping its use from those who may be harmed by it • Producing better medical products • Ready access to information • Decreasing health care costs Modified from: From Schwartz, CAP, 2009 Emerging Developments and Your Future in Pathology

  17. Next Gen Sequencing From Mark Boguski’s presentation at the IOM, July 19, 2011

  18. Next Gen Sequencing From Mark Boguski’s presentation at the IOM, July 19, 2011

  19. From Mark Boguski’s presentation at the IOM, July 19, 2011

  20. From Mark Boguski’s presentation at the IOM, July 19, 2011

  21. From Mark Boguski’s presentation at the IOM, July 19, 2011

  22. From Mark Boguski’s presentation at the IOM, July 19, 2011

  23. Modified from: From Schwartz, CAP, 2009 Emerging Developments and Your Future in Pathology As Medicine evolves from the treatment of illness to aggressive promotion of wellness – genomics/informatics will be key!!!! Computational Pathology will be the key enabler!!!

  24. Recommendation • Phase One • Focus on Building Training Opportunities • Residency, Fellowships, Pathology Informatics 201X • Launch first Computational Pathology Fellowships • Focus on Developmental Informatics Agenda • Secure Intramural and Extramural Funding • Take Leadership Role in New Technologies and CoSBBI • Phase Two • Use Technologies for Transforming Pathology • Report Integration, Data Warehousing, Next Generation Sequencing, Imaging, Decision Support

  25. Pathology Informatics 2014 (formerly APIII) 19th Annual Meeting May 9th-13th, Pittsburgh, PA 1996-1999 Anatomic Pathology, Imaging & Internet 2000-2003 Anatomic and Clinical Pathology 2004-2007 Oncology & Bioinformatics 2008-10 Imaging Informatics – Radiology and Pathology 2010-14 Merger of Lab InfoTech Summit and APIII to form “Pathology Informatics 201X” http://apiii.upmc.edu http://www.pathinformatics.pitt.edu

  26. Association for Pathology Informatics (API)http://www.pathologyinformatics.org “…to advance the field of pathology informatics as an academic and a clinical subspecialty of pathology…” Slide 28

  27. Computational Pathology Fellowships • Why this “new” fellowship is key! • Pathology Informatics is now established as a “division” or “subspecialty” in may practices • This is perceived as a service component to Pathology Practice – the Information Technology component • Academic Pathology Informatics is emerging • Struggles from the lack of defined research focus • PathoBioinformatics (coined by Friedman, 2007) is the domain of Computational Pathology • This is the true “Informatics” component of Path Info • These fellows will help build the research leaders!!!

  28. Recommendation • Phase Three • Partner with other Specialties • Oncology, Radiology and Biomedical Informatics • Evolve a Pathology Centric Information Plan • Pathology Emerges as Medicine’s Information Specialist • Leverage this position to create new opportunities • Molecular Pathology Enables Personalized Medicine • The Data, Tissue/Blood and DNA Trusted Source • Diagnostic Interventional Centers Fueled by Imaging Systems and Staffed by Pathology/Radiology

  29. Summary • Pathology is uniquely situated to evolve towards taking information technologies that emerge and integrate them into deeply into the practice of medicine • Aggressively recruit trainees in Computational Pathology and Pathology Informatics (my passion!!!) • Influence leadership in Pathology to grow the solutions in this space!!!

  30. Key Publications by Our Team – NOTE: Please e-mail me at becich@pitt.edu if you want PDFs • Park S, Parwani AV, Aller RD, Banach L, Becich MJ, Borkenfeld S, Carter AB, Friedman BA, Rojo MG, Georgiou A, Kayser G, Kayser K, Legg M, Naugler C, Sawai T, Weiner H, Winsten D, Pantanowitz L. The history of pathology informatics: A global perspective. J Pathol Inform. 2013 May 30;4:7. doi: 10.4103/2153-3539.112689. Print 2013. • Lee RE, McClintock DS, Balis UJ, Baron JM, Becich MJ, Beckwith BA, Brodsky VB, Carter AB, Dighe AS, Haghighi M, Hipp JD, Henricks WH, Kim JY, Klepseis VE, Kuo FC, Lane WJ, Levy BP, Onozato ML, Park SL, Sinard JH, Tuthill MJ, Gilbertson JR. Pathology informatics fellowship retreats: The use of interactive scenarios and case studies as pathology informatics teaching tools. J Pathol Inform. 2012;3:41. doi: 10.4103/2153-3539.103995. Epub 2012 Nov 28. • Gullapalli RR, Desai KV, Santana-Santos L, Kant JA, Becich MJ. Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics. J Pathol Inform. 2012;3:40. doi: 10.4103/2153-3539.103013. Epub 2012 Oct 31. • Gullapalli RR, Lyons-Weiler M, Petrosko P, Dhir R, Becich MJ, LaFramboise WA. Clinical integration of next-generation sequencing technology. Clin Lab Med. 2012 Dec;32(4):585-99. • Fine JL, Grzybicki DM, Silowash R, Ho J, Gilbertson JR, Anthony L, Wilson R, Parwani AV, Bastacky SI, Epstein JI, and Jukic DM. Evaluation of whole slide image immunohistochemistry interpretation in challenging prostate needle biopsies. Hum Pathol, 39(4):564-72. 2008. • Horbinski C, Fine JL, Medina-Flores R, Yagi Y, Wiley CA. Telepathology for Intraoperative Neuropathologic Consultationsat an Academic Medical Center: A 5-Year Report. J Neuropathol Exp Neurol, 66(8):750-9. 2007. • Raab SS, Grzybicki DM, Condel JL, Stewart WR, Turcsanyi BD, Mahood LK, Becich MJ. Effect of lean method implementation in the histopathology section of an anatomic pathology laboratory. J Clin Pathol. 2008 Nov;61(11):1193-9. Epub 2007 Aug 3. PMID: 17675533 • Gilbertson JR, Ho J, Anthony L, Jukic DM, Yagi Y, Parwani AV. Primary histologic diagnosis using automated whole slide imaging: a validation study. BMC Clin Pathol, 6:4. 2006. • Becich, M.J. Patel A.A. and Jukic D.M. A Diagnostic Virtual Microscope System for Whole Slide Robotic Imaging: The Value of Virtual Slides for the Practice of Pathology. Gu, J. and Ogilvie, R.W., Eds., Virtual Microscopy and Virtual Slides in Teaching, Diagnosis and Research, Taylor & Francis, Boca Raton, 2005;19; 297-312. • Becich, M.J. The role of the Pathologist as tissue refiner and data miner: The impact of functional genomics on the modern pathology laboratory and the critical roles of Pathology Informatics and Bioinformatics. Molec Diag. 2000;5(4):287-299. Slide 32

  31. End of Talk – e-mail me at becich@pitt.edu if you have questions/clarifications not covered in the discussion.NOTE: E-mail me if you want PDFs of articles or presentation. Thank you for the invitation to present to the CoSBBI UPCI Summer Academy.

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