Medical imaging Seminar Session 1

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Medical imaging Seminar Session 1

  1. 1. Medical Imaging – Opportunities for Business 24.01.12 Henry Wellcome Building University of Leicester A Space IDEAS Hub Event In association with:
  2. 2. About Space IDEAS Hub• A knowledge exchange project from the Space Research Centre of the University of Leicester• Feed expertise developed from space missions into commercial benefit for UK industry.• Delivering Innovative Design, Engineering, Analysis and Support (IDEAS) to your business.• Part financed by the European Regional Development Fund• UK companies can access and benefit from our technology and experience.If your organisation would like to benefit fromour knowledge and expertise, please contact usat enquiries@spaceideashub.com
  3. 3. Session 1 – What are we trying to image? 09:50 Space Missions to Medical Imaging Prof George Fraser 10:05 Image Analysis in Pathology Prof Mohammad Ilyas 10:25 Tools for Predictive Drug Screening A Joined up academic and Industry approach Dr Rachel Errington 10:45 Stratified Medicine in the UK Maximising the impact of UK Healthcare industries in a future wherw the Right Drug is given to the Right Patient at the Right Time for the Best Result Dr Alasdair Gaw
  4. 4. Space Research CentreDepartment of Physics and Astronomy,Michael Atiyah Building,University of LeicesterSatellite Missions to Medical ImagingGW Frasere-mail gwf.le.ac.ukTel 0116 252 3542 (direct line) or 3491 (PA) Space IDEAS Hub Workshop , 24th January 2012.
  5. 5. The University of Leicester Space Research Centre• 100 staff and postgraduate students• 550 m2 Phase III of Michael Atiyah Building – opened January 2011by the Minister for Science and Innovation• Six current space projects and laboratory programme in detectorsand opticsWorking at the Life Sciences Interface• BioImaging Unit (1998)• Spin-off companies – GTL, Bioastral and Spectral-ID• Business-facing units -G-STEP (2008) and Space IDEAS Hub (2010)• Working in areas as diverse as : Gamma ray Imaging (Lees) Ultrafast Imaging (Lapington) Hyperspectral Imaging, Diagnostics Development Unit (Sims)
  6. 6. Technology Push: from Astronomy to Biology ~mm ~light year
  7. 7.  : Chemistry · Medical diagnostics / therapeutics (diagnostic development /mass spectrometry) o Detectors o Diagnosis of disease in real time Drug design and Target synthesis o Parallel syntheses and screening o Biosynthetic engineering o Cancer chemistry· Protein mechanism o Protein structure, dynamics and mechanism o Protein design and dynamics of protein-protein interactions Spectroscopy and dynamics, Tools and technologies o Biological spectroscopy o Live cell imaging o Single molecule microscopy Computer Science Computer Science and Molecular Biology Computational Modelling o State based systems and stochastic models o Bioinformatics Algorithms Data Mining and Data Analysis o Reverse engineering o Bio-data and Genotype data o Observing Patterns Medical Diagnostics o software development for non-invasive medical diagnostics (links to Physics, Chemistry, and Engineering) Human Computer Interaction and Ageing Artificial Intelligence Engineering · Statistics and Artificial Intelligence (links for Computer Science/ Maths) o Reverse engineering based on real life monitoring Diagnostics o Signal processing and ‘real time’ processing, may require modelling o ex. automatic nervous system monitoring, and heart fluorination · Signal Processing o Including brain and cardiovascular signalling (links to Computer Science) Technology Development / devices for data acquisition Geology · Geology/Biology links through palaeobiology group · Geology, Environment, and Health o Ground contamination Impact of geo-hazards on human health Mathematics · Mathematical biology (links to Computer Science) o Mathematical ecology o Dynamics of evolution (links to Geography) o Data mining / bioinformatics (including microarrays/medical databases/physiological data) o Dynamics – modelling of biological systems (system level studies)o Brain modelling and neuroscience § Modelling of protein systems and biochemical pathways and mechanisms Physics and Astronomy · Medical Diagnostics and Treatment o Cancer therapy, nano-particle hyperthermia treatment, toxicity of heavy metal particles in human cells · Medical imaging and detectors · Diagnostic Development Unit · Tools and Technology Development o Medical imaging, spectrometry, particles and x-ray imaging The College of Science and Engineering Theme Leader Prof Emma Raven (Chemistry)
  8. 8. The BepiColombo Mercury Imaging X-ray Spectrometer (MIXS)
  9. 9. 9/2/2011 6
  10. 10. Collimator Design (1968)
  11. 11. The Hour-Glass Collimator
  12. 12. Additive Manufacture of Titanium Collimators D = 0.5 mm L = 25 mm Area = 40 x 40 sq.mm
  13. 13. 2.Radial 1.Radial Collimator in Collimator in Planetary Nuclear Medicine Science5.Applications 3. Novel Additive in Nuclear Manufacturing Medicine ? Technology 4.Novel Collimator Designs and Materials
  14. 14. Session 1 – What are we trying to image? 09:50 Space Missions to Medical Imaging Prof George Fraser 10:05 Image Analysis in Pathology Prof Mohammad Ilyas 10:25 Tools for Predictive Drug Screening A Joined up academic and Industry approach Dr Rachel Errington 10:45 Stratified Medicine in the UK Maximising the impact of UK Healthcare industries in a future wherw the Right Drug is given to the Right Patient at the Right Time for the Best Result Dr Alasdair Gaw
  15. 15. Image analysis challenges in Pathology Mohammad Ilyas
  16. 16. What does a Pathologist do? LOOK!
  17. 17. Challenges• Improving telepathology• Image analysis in diagnostic pathology:- Discrimination of normal from abnormal- Refining or creating new diagnostic criteria- Feature extraction (tumour grading, vascular invasion etc)- Automated analysis of special stains & immunostaining
  18. 18. Previous biopsy site in adenoma
  19. 19. Feature extraction – tumour grading
  20. 20. Challenges• Image analysis in tissue based research:- Automated analysis of large numbers of cases- Application to in-vitro assays- Integrated data analysis- Utilisation of newer imaging modalities
  21. 21. Analysis of immunostaining• How to discriminate:- Membranous staining- Cytoplasmic staining- Nuclear staining- Overlapping nuclei- Background staining
  22. 22. Other modalities• FT-IR• Raman spectroscopy• NMR
  23. 23. ?use in cancergenetics?use in featureextraction
  24. 24. Fundamental problems• Technological advances only recent but no standards yet for data format• Language – computer scientists don’t understand clinicians and vice versa• Computers don’t seem to recognize objects/patterns• Need interaction between image analysis experts and clinicians
  25. 25. Session 1 – What are we trying to image? 09:50 Space Missions to Medical Imaging Prof George Fraser 10:05 Image Analysis in Pathology Prof Mohammad Ilyas 10:25 Tools for Predictive Drug Screening A Joined up academic and Industry approach Dr Rachel Errington 10:45 Stratified Medicine in the UK Maximising the impact of UK Healthcare industries in a future wherw the Right Drug is given to the Right Patient at the Right Time for the Best Result Dr Alasdair Gaw
  26. 26. High‐content screening approaches in drug  development: Opportunities and challenges a joined‐up industry academic approach Rachel Errington
  27. 27. Medical Imaging for drug screening – Bridging the gaps in pre-clinical screening Bullen, Andrew. 2008. “Microscopic imaging techniques for drug discovery.”  Nat Rev Drug Discov 7 (1) (January): 54‐67. doi:10.1038/nrd2446.Medical Imaging – Leicester January 24th, 2012
  28. 28. What is high-content screening ? Where are we with HCS ten years on …… HCS was originally introduced by Lansing Taylor, Giuliano, and colleagues in their landmark article in JBS in 1997. Director University of Pittsburgh Drug Discovery Institute and Professor of Computational & Systems Biology From: Biomedical Microdevices 2:2, 99±109, 1999 Critical bottlenecks in the `drug development pipeline can potentially lead to too few well- qualified and too many poorly qualified lead compounds being tested in animal models. The critical constriction at Lead Optimization is getting worse as the speed of HTS increases. Speed alone is insufficient to identify optimal lead compounds emerging at the end of the early discovery pipeline prior to evaluation in expensive animal models. Higher biological content information on the effect of the compounds on cellular targets and cellular processes is required.Medical Imaging – Leicester January 24th, 2012
  29. 29. Our Solution for Automated Cell Analysis:Large-Scale Biology with HCS Automated Plate Delivery Auto-focus, Expose & Acquire Automated Image Analysis Analysis of Results Instantaneous Data Display Automatic Data ArchivalMedical Imaging – Leicester January 24th, 2012
  30. 30. HCS: Multi-parametric within and among channels Blue: Nuclei •Nuclear area •Nuclear diameter Red: Peroxisomes •Nuclear fragmentation •Peroxisome proliferation •Nuclear condensation •Peroxisome kinesis •Cell Number •Peroxisome localization HCS provides multiple read- outs from a single Green: Tubulin fluorescence channel •Cell morphology •Microtubule disruption •Microtubule bundling •Mitosis •Cell size Yellow: Phospho-histone H3 •Transcriptionally active DNA •Mitotic indexMedical Imaging – Leicester January 24th, 2012
  31. 31. So, what is inside the boxes which we use today?Medical Imaging – Leicester January 24th, 2012
  32. 32. HCS is the convergence of technologies across disciplinesIt has taken 10 years to evolve tools and workflow that provides ameaningful contribution to the vision posed by the HCS pioneers Journal of Biomolecular Screening 15(7); 2010 HCS is an interdisciplinary pursuit a fact that was originally underestimatedMedical Imaging – Leicester January 24th, 2012
  33. 33. Workflow-Based Software Environment for Large-Scale Biological Experiments Karol Kozak et al….. 2010 15: 892 J Biomol ScreenMedical Imaging – Leicester January 24th, 2012
  34. 34. HCS is the convergence of technologies across disciplinesIt has taken 10 years to evolve tools and workflow that provides ameaningful contribution to the vision posed by the HCS pioneers Journal of Biomolecular Screening 15(7); 2010 HCS is an interdisciplinary pursuit a fact that was originally underestimatedMedical Imaging – Leicester January 24th, 2012
  35. 35. Simple requirement for reliably finding nuclear location, shape, masking and DNA content HCS CHALLENGE – assay complexity Spatial - Nucleus vs cytoplasm Spatial - Membrane vs cytoplasm Model - Adherent cells Model - Suspension cell line Reporters – rare; cell cycle event Reporters – Fast; stress event Bioinformatics – data processingMedical Imaging – Leicester January 24th, 2012
  36. 36. Anthraquinones our bespoke far-red probes N 1.0x10 -6 OH O HN 0.8 9mA 7mA -6 5mA 0.8x10 3mA intensity 0.6 -6 Intensity (Arb.) 0.6x10 NH O OH Absorbance N 0.4 -6 0.4x10 DRAQ5 -6 0.2 0.2x10 0 640 645 650 655 660 0 200 300 400 500 600 700 800 900 Wavelength (nm) Wavelength (nm) Wavelength (nm) Absorption matches red emitters 20 Live cell penetrating 15 10 5 0 600 650 700 750 800 Spectral properties bound to chromatin DNA targeting providing the specification for the detection windowsUnique pharmacokinetic propertiesMedical Imaging – Leicester January 24th, 2012
  37. 37. Anthraquinone technology .. DRAQ5™, CyTRAK Orange™ & DRAQ7™ • simplifying assay development • reducing screening times • robust and informative assays - DNA content - nucl:cyto segmentations • early in vitro toxicity indications - via morphometrics • viability / in vitro toxicity assaysCHI’s 9th High Content Analysis Conference January 13th, 2012
  38. 38. Molecular modelling to predict drug functionality A B Ligands interacting with the minor groove Low energy complexes with DNA predicts that compound B should provide a better quenching agent than compound A Target identification of drugs number of photons  m ns time
  39. 39. Drug stability Mathematical modelTOPOTECAN is unstable in aqueous media ‘low’ loading cellundergoing rapid hydrolysis from active (L) to Hcinactive (H). Cells act as biosensors for active drug kdh2 kmi kcc2 Hm He koc2 kdl2 Ln fluorescence intensity kmo ke2 100 TPTL A 10 C 80 TPTH active drug kcm kcm kbBF(t)2 Lc kom kom 60 ki2 inactive drug ‘high’ loading cell 40 kmi Hc 20 B at pH 7.4 kdh1 Lm Le 00 0 0 time (mins) 120 kmo L H koc1 kcc1 0 2 4 6 8 10 kdl1 increasing pH ki1 Ln concentration TPT (µM) Ln ke1 medium Lc kbBF(t)1 Predicting dynamics of active drug in cellular compartments 0 lactone Topotecan in the Topotecan in the Topotecan in the hydroxy-acid 15 medium 15 cytoplasm 15 nucleus 10 10 10 5 5 5 0 0 0 0 1200 2400 3600 0 1200 2400 3600 0 1200 2400 3600 time time time Neil D. Evans et al, Mathematical Biosciences 189 (2004) 185-217
  40. 40. In silico predictions Determining the impact of resistance on drug delivery 20 16 12 AUC (Mh) 8 4 0 1.14 9 1.1 4.67 4 E- 28 4 .5 03 46 8.00 7E 65 8 .0 -0 3 kdl (s-1) 11.43 0 x10 kdh E -3(s-1) 84 1 .1 -0 3 102 4E -0 2Plasma membrane efflux Ejection at target
  41. 41. Cell imaging – HCS in drug discovery BD Pathway 855 •TOX: Total cell numbers as a measure of toxicity in addition to object/compartment location Rosado et al, 2008 pathway-specific inhibition assay with CFP, YFP and DRAQ5 readouts on BD Pathway 855 Simonen et al, 2008 Cyto:PM xloc inhibition assay with GFP and DRAQ5 on GE IN Cell 3000 Ba/F3 Image courtesy of Dr Wolgang Link CNIO, MadridMedical Imaging – Leicester January 24th, 2012
  42. 42. Cell imaging – HCS in drug discovery •TOX / DRUG SAFETY: IC50-linked information – Xu et al, 2008 •DRAQ5 - Cell count, Nuclear morphology •DRAQ5 - lipophilic accumulation in p’lipid vesicles (giving peri-nuclear spots) •combined with MMP-, ROS- and GSH-sensitive probesReliable filtering of idiosyncratic hepato-toxicantsbefore animal testing or market release ArrayScan CellomicsMedical Imaging – Leicester January 24th, 2012 Primary hepatocytes
  43. 43. CyTRAK Orange™ - segments .. 100.0Relative fluorescence intensity 100.0 Relative fluorescence intensity 80.0 80.0 60.0 60.0 40.0 40.0 20.0 20.0 0.0 0.0 400 500 600 700 800 900 300 400 500 600 700 800 Excitation wavelength (nm) Emission wavelength (nm) FITC CyTRAK Orange APC FITC CyTRAK Orange Cy7 •Labels live or fixed cells •Exλmax/Emλmax 510/610nm •Co-excited with GFP/FITC •Detection separated from GFP/FITC •Compatible with epifluorescence microscopesMedical Imaging – Leicester January 24th, 2012
  44. 44. CyTRAK Orange™ - flexible .. CA200773 CA200767 CyTRAK Orange Composite (BYFL) (BY630) 10M CyTRAK Orange (red) + 100nM CA200773 (green) 10M CyTRAK Orange (green) + 100nM CA200767 (red)Medical Imaging – Leicester January 24th, 2012
  45. 45. Tracking the dynamics of early cell death responses to DNA damaging agents - a systems approach Early events - Mitochondrial membrane potential DRAQ7™Medical Imaging – Leicester January 24th, 2012
  46. 46. HCS CHALLENGE – assay complexity  Spatial - Nucleus vs cytoplasm  Spatial - Membrane vs cytoplasm  Model - Stem cell / primary cells  Model - Organotypic  Reporters – rare; cell cycle event  Reporters – Fast; stress event  Bioinformatics – data processing
  47. 47. Presenting the model system to the optical path - Principal considerations and configurations  mounting medium  coverslips / microscope slides No. 0 – 0.085 to 0.13 mm thick No. 1 – 0.13 to 0.16 mm thick  chambers for perfusion, heating and CO2 No. 1.5 – 0.16 to 0.19 mm thick  Attention to optical quality  Attention to the assay logistics Single cell (suspension) to adherent cells to tissue slices
  48. 48. Optical plates ‐ coverglass bottom plates Perfusion chamber for 37oC CO2 incubators organotypic brain slices
  49. 49. Solid-phase environments • controlling cell and tissue tethering • probe delivery environments Gel viscosity 2600-3000 Pa s Thermoreversible gel-forming property Apparent viscosity Sol-Gel transition temperature (19.5-21.5 °C) 6.0E+06 controlled by uptake in PBS uptake in CyGel formulationF lu o r e s c e n c e in t e n s it y o f in d iv id u a l liv e c e ll n u c le i 5.0E+06 4.0E+06 Rapid gelation ( a r b . u n it s ) occurs 3.0E+06 within 5 sec at 2.0E+06 the transition t t 1.0E+06 0.0E+00 Sol viscosity up to 750 Pa s 00:00 00:14 00:28 00:43 00:57 01:12 01:26 Exposure period to DRAQ5 (h:min) Temperature (°C)Medical Imaging – Leicester January 24th, 2012
  50. 50. HCS imaging of 3D spheroids The vast majority of studies to identify cancer- associated genes and therapeutic targets use adherent cells grown in 2 dimensions on a plastic substrate, the multi-cellular composition of these 3D tumor spheroids presents both challenges and opportunities for their imaging and characterization. Figure shows a SUM149-GFP tumor spheroid stained with 5 μM of MitoSOX Red and the nuclear stain DRAQ5™, demonstrating the utility of this approach to imaging live unfixed tumor spheroids to analyze such parameters as the production of superoxide anion using the MitoSOX Red indicator by cells within the 3D tumor spheroid. Robertson 2010 15: 820 J Biomol ScreenMedical Imaging – Leicester January 24th, 2012
  51. 51. Considering other assay formats – aim to improve relevance of cell modelScreens in whole organisms such as: Carolina Wahlby – Broad InstituteThe roundworm Caenorhabditis elegans is an effective model system for biological processessuch as immunity, behavior, and metabolism.Medical Imaging – Leicester January 24th, 2012 Screening for viability in a complex system
  52. 52. Cell therapeutics Ex Vivo Modelling of Dental Pulp Progenitor Cell Behaviour Pulp digested in Single cell suspension grown Pulp extracted collagenase on fibronectin coated plates, from human dispase adherent cells selected teeth 2mm Mandible sliced on bone saw Mandible removed Surface to be Overnight culture of injected ‘marked’ by mandible slices: 1,000/1μl PKH-28 labelled Dental the addition of a blue Pulp Progenitor Cells injected agarose bead in mandible Slices Using a 35g micro-needle (135μm OD, 55μm ID) and maintained in cultureMedical Imaging – Leicester January 24th, 2012
  53. 53. CyGEL: provides an optical mountant compatible with viable tissue Injected mandible slices placed into Cover slip applied to assembly, mounting assembly and mounted in allowing presentation of a relatively CYGEL flat, level surface Sham Injected PKH 26 Reflected Light Dentine PulpMedical Imaging – Leicester January 24th, 2012
  54. 54. Providing connectivity of meta data in the entire imaging pipeline for toxicity assays Defining the models – imaging – interrogation - prediction Pipeline PN Species PN PN PN PN Establishing  Incorporating  Toxicology cell analysis Data mining  and  Tissue primary model quality assurance prediction HCS CHALLENGE – assay complexity  Spatial - Nucleus vs cytoplasm  Spatial - Membrane vs cytoplasm  Model - Stem cell / primary cells  Model - Organotypic  Reporters – rare; cell cycle event  Reporters – Fast; stress event  Bioinformatics – data processingMedical Imaging – Leicester January 24th, 2012
  55. 55. Defining the pipeline for nephrotoxicity Defining the models – imaging – interrogation - predictionMedical Imaging – Leicester January 24th, 2012
  56. 56. ProtocolNavigator – navigating through provenance trails Lee, J. A. et al., MIFlowCyt: the minimum information about a Flow Cytometry Experiment. Cytometry A 73 (10), 926 (2008).Medical Imaging – Leicester January 24th, 2012
  57. 57. Standardizing the Performance – an academic and industry pursuit Pipeline PN Species PN TissuePN Establishing primary  Incorporating  PN PN Toxicology cell analysis Data mining  and  model quality assurance prediction Score Score Score Score Score • Temporal scale • Trajectory + Data • Materials Best Practice Performance • Standards • Cost Michael Petrovich, American Society for Quality Control 52 Congress proceedingsMedical Imaging – Leicester January 24th, 2012
  58. 58. HCS is the convergence of technologies across disciplinesIt has taken 10 years to evolve tools and workflow that provides ameaningful contribution to the vision posed by the HCS pioneers Journal of Biomolecular Screening 15(7); 2010 HCS is an interdisciplinary pursuit with continued opportunities for discovery and translationMedical Imaging – Leicester January 24th, 2012
  59. 59. Consortium for TAG and TRAK technologies:Encoding of cell lineages across different model systems Mario Negri Monica LupiSwansea U and Cardiff U Paolo UbezioHuw SummersPaul ReesRachel Errington Dr Anne Plant and the Cell SystemPaul Smith Science GroupSally ChappellMartyn BrownJames TonkinNick WhiteRichard White Dr Anne Carpenter and Dr Mark Bray and Dr Carolina Wahlaby
  60. 60. … for extended content and betterinterpretation in your HCS assaysAcknowledgements:Prof Paul Smith & Dr Rachel Errington School of Medicine, CardiffProf Laurence Patterson & Dr Klaus Pors Inst of Cancer Ther., BradfordProf Fredika Robertson MD Anderson Cancer CentreDr Lyle Armstrong & Mr Ian Dimmick NE Stem Cell Inst, NewcastleDr Robert Martin Max Delbrück Center for Molec Med, BerlinDr Stefan Jaeger Evotec Pharma AG, HamburgDr Wolfgang Link CNIO, MadridMr Derek Davies CRUK London Laboratories, LondonDr Karen Hogg Dept of Biology, University of YorkMr Joe Trask Hamner Insts., Research Triangle ParkDrs Paul Wylie & Wayne Bowen TTP Labtech, MelbournDr Gareth Griffiths Imagen Biotech, ManchesterDr Tim Self Cell Jam I. Collagraph © Kirsten Edward Inst for Cell Signalling, Nottingham erringtonrj@cf.ac.uk
  61. 61. Session 1 – What are we trying to image? 09:50 Space Missions to Medical Imaging Prof George Fraser 10:05 Image Analysis in Pathology Prof Mohammad Ilyas 10:25 Tools for Predictive Drug Screening A Joined up academic and Industry approach Dr Rachel Errington 10:45 Stratified Medicine in the UK Maximising the impact of UK Healthcare industries in a future wherw the Right Drug is given to the Right Patient at the Right Time for the Best Result Dr Alasdair Gaw
  62. 62. Driving Innovation Stratified Medicines Innovation Platform Alasdair Gaw Lead Specialist Stratified Medicine
  63. 63. Driving Innovation Our aim is to address current business needs • Business investment is too low and too late • Technical and financial risks need to be mitigated • The time for financial return is too long for many players • Innovation disrupts value chains and business models • New partnerships are required to build new supply chains • Investment and innovation is required at multiple points • Longer term trends not visible to all players • Impact and opportunities from emerging technologies & policies • Innovation infrastructure complex and inefficient • Fragmented and difficult to navigate • Sub-national picture changing and less money available overall
  64. 64. Driving Innovation New strategy launched 2011 http://www.innovateuk.org/
  65. 65. Driving Innovation Focus on five areas • Accelerating the journey between concept and commercialisation – Understand the business journey and accelerate it – Provide a coherent package of support – matched to needs – Specific SME package – but recognise role of larger companies – Promote knowledge exchange • Connecting the innovation landscape • Turning government action into business opportunity • Investing in priority areas based on potential – High Value Manufacturing, Off-Shore Renewable Energy, Regenerative Medicine • Continuously improving our capability
  66. 66. Driving Innovation http://www.innovateuk.org/ COMPETITIONS _CONNECT SBRI Technology Strategy Share knowledge through Develop innovative Board funding KTNs and other networks products to meet competitions government needs CATAPULTS KTP SMART A network of world-leading Partner with academics to (Grant for R&D) technology and innovation develop new business Innovation funding for SMEs centres capability
  67. 67. Driving Innovation SMART: Previously Grant for R&DProof of Market Proof of Concept Prototype DevelopmentThis grant enables companies to A grant to explore the technical This funding is used byassess commercial viability, feasibility and commercial companies to develop athrough: potential of a new technology, technologically innovative• market research market testing product or process: product, service or industrial and competitor analysis • initial feasibility studies process:• intellectual property position • basic prototyping • small demonstrators• initial planning to take the project • Specialist testing and/or • intellectual property protection to commercialisation, including demonstration to provide basic • trials and testing, including clinical assessing costs, timescales and proof of technical feasibility • market testing funding requirements. • intellectual property protection • marketing strategies • investigation of production and • identifying routes to market assembly options. • product design work It also includes pre-clinical research • phase 0 pre-clinical studies for studies for healthcare technologies medicines. and medicines, including target identification and validation.Duration – up to 9 months Duration – up to 18 months Duration – up to 2 yearsMaximum grant – £25k Maximum grant – up to £100k Maximum grant – £250kFunding proportion – up to 60% Funding proportion – up to 60% of Funding proportion – up to 35%of total project costs total project costs of total project costs for medium enterprises; up to 45% for small and micro enterprises
  68. 68. Driving Innovation SMART: Grant for R&D – how it works • Applications welcome from any technology or sector area • Always open to applications – Open process – but run as a competition – All applications must meet Quality Threshold – Batched assessment - 6 competitions per year • Funds – Spread over the year – Balanced between different grant types • Open to UK based SMEs and pre-start-ups with fewer than 250 employees • Also be themed competitions in specific technology areas
  69. 69. Driving Innovation Levels of Funding: Collaborative R&D Type of Project Research Category Reference Code Funding level as a % of eligible project costs Business to Business Basic Research BASB2B 50% Collaborative Applied Research APPB2B 50% Research* Experimental EXPB2B 25% Development Science to Basic Research BASS2B 75% Business** Applied Research APPS2B 50% Collaborative Experimental EXPS2B 25% Research Development Claims up to Industrial 50% Industrial (SME)* 60% Academic 100% (of 80% Full Economic Cost (FEC)) Collaborative Research projects (at least two partners per consortium). Projects must be industrially led, academics only as a collaboration partner. Any one participant can bear a maximum of 70% of the eligible costs. The remaining 30% may be split between several participants. Each participant in the project must draw down at least 10% of their total eligible costs as grant.
  70. 70. Driving Innovation What is Stratified medicine • A therapy with – a companion diagnostic test – a clearly identified group of patients – an understanding of the disease at the molecular level – ready access to both tests and drugs by cliniciansRight Drug, Right Patient, Right Dose, Right Time Optimal Benefit
  71. 71. Driving Innovation Stratified Medicine Innovation Platform• Accelerate Development and Uptake of Stratified Medicine for Clinical Diagnosis and Treatment to: – Improve Patient Outcomes – Provide Cost Benefit to the NHS and The Healthcare Industry – Deliver wider UK economic benefit• Key Partners – Department of Health, Scottish Government Health Directorate – NICE, Medical Research Council, Technology Strategy Board – Arthritis Research UK, Cancer Research UK• Consultation and Advice – MHRA, NIHR• The combined 5 year Investment by Programme Partners in the area of Stratified Medicine amounts to £200 Million Putting UK healthcare at the heart of a revolution in the diagnosis and treatment of disease
  72. 72. Driving Innovation Vision• The UK should be the best place to develop, and adopt, Stratified Medicine• An increased collaborative culture throughout the sector – Shared Resources, Systems for effective data collection, sharing, governance & Use • NHS, business, academia, regulators and NICE• Improved Research – All NHS patients can choose to be involved in research • Use of patient information and records to inform the next generation of therapies• New Drug Diagnostic Combinations – Quicker and less expensive to get them Licensed• A smooth reimbursement process for stratified therapies and diagnostics• An Intellectual Property (IP) framework that encourages Innovation• The UK health system should have established stratified care pathways – Evidence provided of improvement in Patient Outcomes using Stratified Medicine
  73. 73. Driving InnovationStratified Medicine:Technology Roadmap• To deliver the UK vision• Build a community of people who will help• Take a strategic view of investment options – Identify the barriers – Programme activity to overcome them – Align investments in support of the programme activities• Early Signals – A clear UK vision agreed by around 100 people – Good consensus around the key issues – Identifying and bringing together the organisations required to support the delivery of the vision https://ktn.innovateuk.org/web/stratified-medicines-innovation-platform
  74. 74. Driving InnovationStratified Medicine Technology RoadMap Key Themes 1. Incentivising adoption 2. Increasing awareness 3. Patient recruitment – consents and ethics 4. Clinical trials 5. Data – collection, management and use 6. Regulation and standards 7. Intellectual property 8. Bio-banks and biomarkers 9. Increasing the impact of R&D investmenthttps://connect.innovateuk.org/web/stratified-medicines-innovation-platform/overview
  75. 75. Driving Innovation Contact details • Dr Graham Bell (graham.bell@tsb.gov.uk) • Dr Alasdair Gaw (alasdair.gaw@tsb.gov.uk) • https://connect.innovateuk.org/web/stratified- medicines-innovation-platform/overview
  76. 76. PCA cytokine normDriving Innovation The Future of Biomarkers: Where does imaging fit in?
  77. 77. Driving Innovation BioImaging: Surrogate Marker Inflammation / Injury Environment / Genetics Enzyme activity Cartilage/bone remodelling Signs and symptoms Joint space narrowing
  78. 78. Driving Innovation Computed Tomography (CT) and COPD Phenotyping • Potential exists for Stratified Medicine based on CT staging of predominant emphysema vs. predominant airways disease • Quantitative CT is an objective tool for determining presence and severity of emphysema, airway wall thickening and air trapping • Existing quantitative measures are not sophisticated enough to capture all information in the images available to the trained observer, including pattern of emphysema (centrilobular, panlobular, etc.), presence of centrilobular nodules, airway wall irregularity, bronchiectasis, etc. • Ongoing precompetitive work to develop a broad consensus on visual CT scoring criteria to separate distinct subtypes with the ultimate goal to facilitate the use of subphenotypes for startified medicine COPD CT workshop 2-5 Feb 2010 sponsored by National Heart, Lung and Blood Institute, COPD Foundation, Fleischner Society, COPDGene Project, AstraZeneca, CSL, GlaxoSmithKline, Novartis, Talecris, VIDA
  79. 79. Driving Innovation CT Can Identify Three Distinct Components of COPD Emphysema % lung less than -950 Hounsfield units (HU) on inspiratory CT Air trapping % lung less than -856 HU on expiratory CT Airway wall thickening % wall area / total bronchial area (segmental bronchi) Hypothesis: These quantitative CT parameters identify important subphenotypes of COPD
  80. 80. Driving Innovation Imaging in Respiratory studies Use of HR-CT in COPD Dirksen AJRCCM 199956 α1-antitrypsin deficient patients on α1-antitrypsin augmentation therapy vs placebo• No sign. effect on lung function• Annual loss of lung tissue: active 1.5 g/L, placebo 2.6 g/L (p=0.07)• CT was twice as sensitive as FEV1 for monitoring the progression of emphysema 19
  81. 81. Driving Innovation Magnetic Resonance Imaging (MRI) for Phenotyping• No ionizing radiation with MRI• MRI with hyperpolarized gas (3He or 129Xe) can be used to characterize emphysema and airway predominant phenotypes in COPD – Multiple endpoints, e.g. ventilation maps, air trapping, alveolar dimensions and gas transport – Hyperpolarized 3He not feasible for PHC due to limited availability and high cost. 129Xe may be an option. – MRI with hyperpolarized gas may be considered for patient stratification in specific studies• Novel MRI techniques emerging that do not rely on hyperpolarized gases – Oxygen enhanced MRI can generate maps of regional lung function. AZ sponsored projects 3He MRI for phenotyping in COPD. A-D: Emphysema ongoing. predominant (brighter red colors represent large alveolar air – MRI with 19F gas may generate similar data as spaces). E-H: Airway predominant (major ventilation hyperpolarized gas techniques. AZ should monitor defects visualized in the gray scale images) the development of this technology. Mathew, et al, EJR, 2009
  82. 82. Driving Innovation Clinical Relevant Measures for animal models Saline Challenge Challenge plus treatment
  83. 83. Driving Innovation Imaging in Translational Medicine
  84. 84. Thank you for your interest If your organisation would like to benefit fromour knowledge and expertise, please contact us. Space IDEAS Hub W: www.spaceideashub.com E: enquiries@spaceideashub.com T: 0116 229 7700 Follow us on:

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