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Medical imaging Seminar Session 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. 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 from
our knowledge and expertise, please contact us
at enquiries@spaceideashub.com
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. Space Research Centre
Department of Physics and Astronomy,
Michael Atiyah Building,
University of Leicester
Satellite Missions to Medical Imaging
GW Fraser
e-mail gwf.le.ac.uk
Tel 0116 252 3542 (direct line) or 3491 (PA)
Space IDEAS Hub Workshop , 24th January 2012.
5. The University of Leicester Space Research Centre
• 100 staff and postgraduate students
• 550 m2 Phase III of Michael Atiyah Building – opened January 2011
by the Minister for Science and Innovation
• Six current space projects and laboratory programme in detectors
and optics
Working 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)
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)
13. 2.Radial
1.Radial
Collimator in
Collimator in
Planetary
Nuclear Medicine
Science
5.Applications 3. Novel Additive
in Nuclear Manufacturing
Medicine ? Technology
4.Novel
Collimator
Designs and
Materials
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
18. 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
26. 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
27. Analysis of immunostaining
• How to discriminate:
- Membranous staining
- Cytoplasmic staining
- Nuclear staining
- Overlapping nuclei
- Background staining
36. 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
37. 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
39. 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
40. 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
41. 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 Archival
Medical Imaging – Leicester January 24th, 2012
42. 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 index
Medical Imaging – Leicester January 24th, 2012
43. So, what is inside the boxes which we use today?
Medical Imaging – Leicester January 24th, 2012
44. HCS is the convergence of technologies across disciplines
It has taken 10 years to evolve tools and workflow that provides a
meaningful 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 underestimated
Medical Imaging – Leicester January 24th, 2012
45. Workflow-Based Software Environment for Large-Scale
Biological Experiments
Karol Kozak et al….. 2010 15: 892 J Biomol Screen
Medical Imaging – Leicester January 24th, 2012
46. HCS is the convergence of technologies across disciplines
It has taken 10 years to evolve tools and workflow that provides a
meaningful 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 underestimated
Medical Imaging – Leicester January 24th, 2012
47. 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 processing
Medical Imaging – Leicester January 24th, 2012
48. 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
windows
Unique pharmacokinetic properties
Medical Imaging – Leicester January 24th, 2012
49. 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 assays
CHI’s 9th High Content Analysis Conference January 13th, 2012
50. 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
51. Drug stability Mathematical model
TOPOTECAN is unstable in aqueous media
‘low’ loading cell
undergoing rapid hydrolysis from active (L) to
Hc
inactive (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
52. 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 2
Plasma membrane efflux Ejection at target
53. 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, Madrid
Medical Imaging – Leicester January 24th, 2012
54. 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 probes
Reliable filtering of idiosyncratic hepato-toxicants
before animal testing or market release
ArrayScan
Cellomics
Medical Imaging – Leicester January 24th, 2012
Primary hepatocytes
57. 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
58. 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
59. 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
61. 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 formulation
F 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
62. 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 Screen
Medical Imaging – Leicester January 24th, 2012
63. Considering other assay formats – aim to improve relevance of cell model
Screens in whole organisms such as: Carolina Wahlby – Broad Institute
The roundworm Caenorhabditis elegans is an effective model system for biological processes
such as immunity, behavior, and metabolism.
Medical Imaging – Leicester January 24th, 2012 Screening for viability in a complex system
64. 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 culture
Medical Imaging – Leicester January 24th, 2012
65. 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
Pulp
Medical Imaging – Leicester January 24th, 2012
66. 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 processing
Medical Imaging – Leicester January 24th, 2012
67. Defining the pipeline for nephrotoxicity
Defining the models – imaging – interrogation - prediction
Medical Imaging – Leicester January 24th, 2012
68. 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
69. 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 proceedings
Medical Imaging – Leicester January 24th, 2012
70. HCS is the convergence of technologies across disciplines
It has taken 10 years to evolve tools and workflow that provides a
meaningful 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 translation
Medical Imaging – Leicester January 24th, 2012
71. Consortium for TAG and TRAK technologies:
Encoding of cell lineages across different model systems
Mario Negri
Monica Lupi
Swansea U and Cardiff U Paolo Ubezio
Huw Summers
Paul Rees
Rachel Errington Dr Anne Plant and
the Cell System
Paul Smith Science Group
Sally Chappell
Martyn Brown
James Tonkin
Nick White
Richard White
Dr Anne Carpenter and Dr Mark Bray and Dr Carolina Wahlaby
73. 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
74. Driving Innovation
Stratified Medicines
Innovation Platform
Alasdair Gaw
Lead Specialist Stratified Medicine
75. 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
76. Driving Innovation
New strategy launched 2011
http://www.innovateuk.org/
77. 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
78. 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
79. Driving Innovation
SMART: Previously Grant for R&D
Proof of Market Proof of Concept Prototype Development
This grant enables companies to A grant to explore the technical This funding is used by
assess commercial viability, feasibility and commercial companies to develop a
through: 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 years
Maximum grant – £25k Maximum grant – up to £100k Maximum grant – £250k
Funding 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
80. 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
81. 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.
82. 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
clinicians
Right Drug, Right Patient, Right Dose, Right Time
Optimal Benefit
83. 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
84. 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
85. Driving Innovation
Stratified 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
86. Driving Innovation
Stratified 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 investment
https://connect.innovateuk.org/web/stratified-medicines-innovation-platform/overview
87. 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
90. 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
91. 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
92. Driving Innovation Imaging in Respiratory studies
Use of HR-CT in COPD
Dirksen AJRCCM 1999
56 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
93. 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
94. Driving Innovation
Clinical Relevant Measures for animal models
Saline Challenge Challenge plus treatment
96. Thank you for your interest
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