Presentation on theme: "Multiplexing IHC in a regulated environment"— Presentation transcript:
1 Multiplexing IHC in a regulated environment Flagship Biosciences LLCMultiplexing IHC in a regulated environment
2 Digital Pathology in the News CAP 2010‘Digital pathology continues to generate industry buzz….’‘there are over a dozen FDA 510(k) clearances for digital analysis of immunohistochemistry procedures, the waiting game continues for how the agency wants to regulate digitalization of hematoxylin and eosin (H&E) slides using whole slide imaging (WSI) systems’‘once these regulatory barriers are negotiated, digital pathology will move ahead at breakneck speed’
3 New Technologies for Health Care Star Trek technologiesVISORHyposprayTricorderThe holy grail of medicineDigital RadiologyDigital PathologyAre new technologies outpacing regulatory guidance?Who are the guiding decision-makers?In 2005, a team of medical researchers at Stanford University used a combination of microchip implants behind mice retinas and goggles equipped with LED readouts and a small camera to partially restore sight enough so that the mice could distinguish sets of black and white patterns.
4 Regulatory Needs in Digital Pathology? Use of whole slide images in an electronic environment – from acquisition to storageSystems qualifications (IQ/OQ/PQ validation)Quantitative image analysis on whole slide and TMA imagesAccessioning, viewing, scoring by pathologists, and adjudicationPeer reviews and digital archiving
5 Regulatory & Compliance Digital Pathology inDrug DevelopmentClinicalNovel regulatory problems?PreclinicalDiscovery5
6 Regulatory GuidanceRegulatory requirements for digital pathology present a complex series of processes in the drug development processDigital imagesStorageAnnotationsImage analysisorCFR - Code of Federal Regulations Title 21 (Food and Drugs)PART 11 Electronic Records; Electronic SignaturesPART 58 Good Laboratory Practice for Nonclinical laboratory Studies501(K) Premarket NotificationIn Vitro Diagnostic Multivariate Index Assays (21 CFR 809.3)CLIA - Clinical Laboratory Improvement Amendments
7 Digital Pathology and IA Discovery IHC investigations in potential new target organsResearchers seeking to validate hypothesisVerification and replication of literature claimsTissues from commercial tissue banks have unknown demographics, outcomes, unknown pre-analytical variables, etcXenograft modelingIn vivo pathobiology studiesEarly efficacy studies
8 Digital Pathology and IA Preclinical Toxicology studiesSafetyEfficacyPharmacokineticSpecial studiesPeer reviewVeterinary toxicological pathologistsNorth America, Japan, Europe (England, Germany, France, Switzerland)Few overseas - especially in emerging biotech areas such as India and ChinaVIPERMost pre-clinical studies must adhere to Good Laboratory Practices (GLP) in ICH Guidelines to be acceptable for submission to regulatory agencies.Pre-clinical studies involve in vitro and in vivo experiments Such tests assist pharmaceutical companies to decide whether a drug candidate has scientific merit for further development as an investigational new drug.
9 Digital Pathology and IA Clinical Clinical trialsInclusion criteriaRetrospective analysisCompanion DXSelection of biomarkersKit developmentPathology scoringTreatment regimens for personalized medicineHER2, ER, PR – breast cancerEGFR – lung cancer (NSCLC)Multiplexing multiple biomarkers (IHC-based)
10 Multiplexing Multiple Markers on One Slide is Difficult Quantum Dots …ready for the clinic…next yearTough problemDual-stained IHC slidesGreat research tool, double-staining is generally not high quality enough to run in diagnostic settingsProblems with cross-reactivity between chromogens, avoid DABUS Labs TriView for prostate and breast – for color aid for pathologist, not quantitationBreast: CK 5/6 (cytoplasmic brown) and p63 (nuclear/brown) stain myoepithelial cells, while CK8/18 labels the cytoplasm (cytoplasmic/red) of ductal or lobular epithelium.Dual or triple stained immunofluorescent (IF) slidesExpensive, no anatomical tissue contextIF not used extensively in the clinic
12 FDA Protein Expression Clearances Date510(k) Number Tissue Stain Reagent ApplicationScanScope XT System (Aperio)2009/08 K Breast Her2/neu Dako Tunable Image Analysis - System2008/10 K Breast PR Dako Reading on Monitor - System2008/08 K Breast ER/PR Dako Image Analysis - System2007/12 K Breast Her2/neu Dako Reading on Monitor - System2007/10 K Breast Her2/neu Dako Image Analysis - SystemPATHIAM (Bioimagene)2009/02 K Breast Her2/neu Dako Image Analysis - System2007/02 K Breast Her2/neu Dako Image Analysis - SWVIAS (Tripath)2006/09 K Breast P53 Ventana Image Analysis - System2006/04 K Breast Ki-67 Ventana Image Analysis - System2005/08 K Breast Her2/neu Ventana Image Analysis - System2005/05 K Breast ER/PR Ventana Image Analysis - SystemARIOL (Applied Imaging)2004/03 K Breast ER/PR Dako Image Analysis - System2004/01 K Breast Her2/neu Dako Image Analysis - SystemACIS (Clarient/Chroma Vision)2004/02 K Breast ER/PR Dako Image Analysis - System2003/12 K Breast Her2/neu Dako Image Analysis - SystemQCA (Cell Analysis)2003/12 K Breast ER Dako Image Analysis - SW
14 FACTS* Feature Analysis on Consecutive Tissue Sections A multiplexing biomarker approach for analysis*Patent Pending
15 Automating quantitative IHC ROI analysis in tissue is a HARD problem… What works on a few samples doesn’t translate to real-world samples, especially in clinical trials where the ability to control sample acquisition, handling, fixation, IHC, and scanning is limitedIHC histologies simply do not have enough biology information to allow the computer to quickly build a reproducible, reliable systemTissue variability is difficulton any computer softwareWhere is my ROI?
16 Common IA Needs Neurology Toxicology Diabetes Oncology Easy Robust Neurofibrillary tangles & tauAmyloid plaqueSpleen red/white pulpLiver toxicologiesToxicologyBiomarkers in kidney glomeruliDiabetesBeta cell mass in isletsBeta cell mass in islets with stereologyOncologyXenografttumor / normal / necrosisTumor bank samplestumor / normal / necrosisClinical trials samplestumor / normal / necrosisEasyRobustDifficultImpossible
18 GOAL: Minimal disruption to histology lab processes ConsecutivetissuesectioningGOAL: Minimal disruption to histology lab processesCareful sectioning to get excellent consecutive tissue ribbonsControl pre-analytical factors*All slides for biomarkers must be taken in same session
22 Consecutivetissuesectioning2. Automatedfeaturerecognition3. Imageand ROIregistrationGOAL: Successfully register image with <3% error rate on ROI transfers between consecutive sectionsImage registration approaches from radiologyMulti-modal, semi-automatic approachRequires first rotating, translating, and sizing two whole slide imagesSecondary step involves transferred ROI alignment (rotating, translating, sizing approach to near boundaries)
23 Consecutivetissuesectioning2. Automatedfeaturerecognition3. Imageand ROIregistration4. QC andpathologistreviewGOAL: Increase analysis accuracy while improving pathologist productivityTechnician review and exclusion of poorly identified featuresFeatures missing in adjacent sections (e.g. end-cut glomeruli or islets)Non-specific staining impacting feature recognitionPoorly matched featuresPathologist review and sign-out
24 Validation ApproachH&E stained slides were cut in 4 um sections. One section was used as the reference section. FACTS was run across consecutive sections and error analyses were calculatedFalse negative areaFalse positive areaTo estimate error per feature (as in this glomeruli example), we first must map the transferred region as well as find the “correct” region. The “correct” region can either be drawn manually, or using automated feature recognition, depending on the application.The differences between the two regions (XORed area) is then divided by the mapped region to give the percent error per feature
29 Xenografts – Specific Area Selection Total error = 1.0%False negative = 0.4%False positive = 0.6%Average feature diameter = 490 um
30 Oncology Clinical Trials - NSCLC Consecutive sections from NSCLC patients were cut and stained for an epithelial marker as well as a biomarker of interest.Automated feature recognition run on the epithelial stainNormal bronchioles excluded manuallyEpithelial stain delineates tumorStaining of epithelial surface linings and normal alveolar tissue excluded programmatically
31 Oncology Clinical Trials - NCSLC Automated feature extraction followed by vectorization to generate regions of interest - eliminates ‘non-alike’ tissue regions
32 Oncology Clinical Trials - NCSLC Image alignment followed by ROI alignmentROI transfer with human annotated areas for error calculationsROI alignmentImage alignment on deconvolved hemotoxylin channelsTotal error = 3.2%False negative = 1.7%False positive = 1.5%Average feature diameter = 315 um
33 Validation Summary Feature Average size False positive False negative Total errorLiver bile ducts56 µm0.6%4.1%4.7%Kidney glomeruli61 µm0.9%4.9%5.8%Fibrous capsule in implants62 µm1.3%1.4%2.7%Pancreas islets135 µm1.0%3.8%4.8%Xenografts (H&E to CD31 stains)490 µm0.4%NSCLC samples315 µm1.5%1.7%3.2%Spleen periarteriolar lymphoid tissue520 µm0.3%0.7%
34 What is the limit on multiplexing? 9 consecutive 4 µm sections from xenograft tumorH&E stainingFACTS false positive and false negative rates
35 What is the limit on multiplexing? Tissue SectionFalse Negative %False Positive %Total error %+184.108.40.206+220.127.116.11+20.62.4+11.40.7Reference section-11.9-22.23.3-33.95.7-43.65.5
38 Advantages of FACTSMultiple IHC biomarkers can be developed into one IVDMIAMore reliable approach for highly variable samples seen in real world situationsCost-effective and fits well into current GLP and CLIA practiceNo novel double/triple stains or biomarker development requiredFull audit trail of glass slidesFollows a precedent path with standard brightfield IHC IA digital imaging 510k approval process
39 Regulatory Alignment of FACTS Trackable, reproducible image transfer and registrationSimilar process as precedent FDA clearancesRequires no novel histology processesReview and pathologist sign out is the sameValidation through FDA regulations and CLIA compliance
40 Ongoing Flagship Projects with FACTS Preclinical ToxicologyLiver – bile ductsKidney: glomeruli dysfunctionPancreas: islets, alpha/beta cell massSpleen: red / white pulp, EMHDiscovery & ClinicalMultiple IHC measurements in xenograftsIVDMIA development in lung samplesStroma / Cancer in ER/PR/HER2TMA multiplexing in discovery and retrospective clinical trialsPrognosDx epigenetic markers (5 histone markers)
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