fmri studies in the pharmaceutical industry: turning data into information paul m. matthews imaging,...

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

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

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

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

Introduction to the workshop

• Applications of functional MRI in drug development

• The peculiar nature of fMRI data

• Optimising the outcome measure

Potential applications of fMRI to drug development

• Patient stratification

• Pharmacodynamic response

• Proof of mechanism

• Early phase outcome study

• Surrogate marker of outcome

Stratification: a specific, functional “intermediate phenotype” for schizophrenia?

MacDonald et al., Am J Psychiatry, 2003

Pharmacodynamics of pain responses to remifentanil

Courtesy of Dr. R. Wise, I. Tracey (Oxford)

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

pHMRI as a tool for proof of mechanism in translational studies

Human metamphetamine responseVollm et al., 2005

Early phase outcome measure: providing a “reason to believe”

Right inferior frontal cortex

Basal ganglia

Anterior cingulate

Brain activation in the Stroop task

MS patients have reduced right prefrontal

activity in the Stroop task

MS patients recruit additional left prefrontal cortex during the

Stroop task

Early phase outcome measure: providing a “reason to believe”

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Drug Placebo

Act

ivat

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Rat

io

P-1

P-2

P-3

P-4

P-5

C-1

C-2

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C-4

Healthy controls

Patients

Abnormal brain activition in MS

transientlynormalises after

rivastigmine administration

MRI as a surrogate marker for disease activity in multiple sclerosis

Compston A, Coles A. Lancet 2002;359:1221–31

Rep

rin

ted

wit

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MRI as a surrogate marker for disease activity in multiple sclerosis

T2-weighted Gadoliunium enhanced

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

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)

fMRI reflects local field potential and local neuronal correlation of activity

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

“Resting state networks” directly reflect network-based activity in the brain

0.5% 3% 0.1% 50%

Mean BOLD signal change

Coefficient of variation

A new way forward? Network-based patient stratification

MMSERSN

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)

Acknowledgements

Steve Smith, Irene Tracey, Richard Wise, Christian Beckmann, Alison Perry, Sarah Cader, Jackie Palace, Peter Jezzard, Phil

Cowen, Angelo Bifone