fmri studies in the pharmaceutical industry: turning data into information paul m. matthews imaging,...
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fMRI Studies in the Pharmaceutical Industry: Turning Data into Information
Paul M. MatthewsImaging, Genetics and NeurologyClinical Imaging Centre, Hammersmith HospitalGlaxoSmithKline Clinical Neurosciences, Imperial College, LondonFMRIB Centre, University of Oxford
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The GSK Clinical Imaging Centre
• Established with joint planning and funding from GSK, Imperial College and the Medical Research Council
• A centre equipped with state-of-the-art imaging systems for PET/CT and MRI
• A centre with expertise in radiochemistry/biology, image analysis and modelling, imaging physics and clinical research applications
• A centre for collaborative research in key areas of interest (especially neurosciences and oncology)
• A centre to drive disease understanding and new therapeutics development
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GSK Clinical Imaging Centre: operations
• CIC began operations in a staged fashion from 2Q07
• Progressive increase to full capacity over 3 years (end 2Q10)
• Goals:– In-house image analysis and curation: adding value
– Asset-specific molecular imaging
– Development, evaluation and validation of novel PD measures
• The CIC effort is supported by strong academic partnerships, including an international network for molecular imaging
• Hardware/IT needs are being addressed in high value partnership with Siemens
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Life cycleman’ment
File andlaunch
Phase IIIPoC to
commit toPhase III
FTIH to
PoC
Pre-clinical
Lead toCandidate
Target toLead
Genefunctionto targetassoc’n
Diseaseselection
Target familyselection
Why is the pharmaceutical industry interested in fMRI?
Experimental medicine
GENETICS/’OMICS
BIOMARKERS
IMAGING
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Introduction to the workshop
• Applications of functional MRI in drug development
• The peculiar nature of fMRI data
• Optimising the outcome measure
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Potential applications of fMRI to drug development
• Patient stratification
• Pharmacodynamic response
• Proof of mechanism
• Early phase outcome study
• Surrogate marker of outcome
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Stratification: a specific, functional “intermediate phenotype” for schizophrenia?
MacDonald et al., Am J Psychiatry, 2003
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Pharmacodynamics of pain responses to remifentanil
Courtesy of Dr. R. Wise, I. Tracey (Oxford)
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Sagittal plane, x=1.0mm
Sagittal plane, x=1.4mm Sagittal plane, x=3.0mm
AcbSh
PrL
SSctx
VTA
PrL
Mctx
thal
thal
pHMRI as a tool for proof of mechanism in translational studies
Schwarz et al. NeuroImage 34, 1627-1636 (2007)
Rat metamphetamine response
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pHMRI as a tool for proof of mechanism in translational studies
Human metamphetamine responseVollm et al., 2005
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Early phase outcome measure: providing a “reason to believe”
Right inferior frontal cortex
Basal ganglia
Anterior cingulate
Brain activation in the Stroop task
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MS patients have reduced right prefrontal
activity in the Stroop task
MS patients recruit additional left prefrontal cortex during the
Stroop task
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Early phase outcome measure: providing a “reason to believe”
0
1
2
3
4
5
6
7
8
9
10
Drug Placebo
Act
ivat
ion
Rat
io
P-1
P-2
P-3
P-4
P-5
C-1
C-2
C-3
C-4
Healthy controls
Patients
Abnormal brain activition in MS
transientlynormalises after
rivastigmine administration
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MRI as a surrogate marker for disease activity in multiple sclerosis
Compston A, Coles A. Lancet 2002;359:1221–31
Rep
rin
ted
wit
h p
erm
issi
on
fro
m E
lsevie
r
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MRI as a surrogate marker for disease activity in multiple sclerosis
T2-weighted Gadoliunium enhanced
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The peculiar nature of fMRI data
• fMRI is an indirect measure of neuronal activity
• fMRI relies on small, voxel-associated signal changes– Changes are small relative to intrinsic contrast in image
• fMRI generates a statistical image– Outcome is probabilistic, not binary
• The brain works through networks, not individual regions
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fMRI is sensitive to changes in local blood oxygenation
With presynaptic neuronal activity, blood flow increases and the proportion of red blood cells carrying oxygen increases in the small blood vessels,
enhancing the MRI signal specifically in that region of brain
See Jezzard, Matthews, Smith, Functional Magnetic Resonance Imaging: an Introduction to Methods (OUP)
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fMRI reflects local field potential and local neuronal correlation of activity
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The peculiar nature of fMRI data
• fMRI is an indirect measure of neuronal activity
• fMRI relies on small, voxel-associated signal changes– Changes are small relative to intrinsic contrast in image
• fMRI generates a statistical image– Outcome is probabilistic, not binary
• The brain works through networks, not individual regions
![Page 20: FMRI Studies in the Pharmaceutical Industry: Turning Data into Information Paul M. Matthews Imaging, Genetics and Neurology Clinical Imaging Centre, Hammersmith](https://reader036.vdocuments.us/reader036/viewer/2022062716/56649dbb5503460f94aac0ee/html5/thumbnails/20.jpg)
“Resting state networks” directly reflect network-based activity in the brain
0.5% 3% 0.1% 50%
Mean BOLD signal change
Coefficient of variation
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A new way forward? Network-based patient stratification
MMSERSN
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Summary and outline of the day
• fMRI is based on indirect measures, subject to modulation by vasoactive factors (Jezzard)
• Signal changes are small- multiple subject, instrument and site factors contribute to variance (deCrespigny)
• Perfusion provides an alternative to BOLD, potentially less subject to non-specific time-dependent effects (Woolrich)
• Multiple metrics can be used as outcomes- specifying the question is critical (Smith)
• Multivariate methods are powerful for exploratory analyses and may offer a new primary outcomes measure (Beckman)
• Matching brains to provide summary measures and neuroanatomical contextualisation need as much thought as functional signal acquisition (Jenkinson)
• Promising work suggests there is a way forward, but the community must work together to ensure that we are taking it (Smith)
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Acknowledgements
Steve Smith, Irene Tracey, Richard Wise, Christian Beckmann, Alison Perry, Sarah Cader, Jackie Palace, Peter Jezzard, Phil
Cowen, Angelo Bifone