fMRI Studies in the Pharmaceutical Industry: Turning Data into Information

1. fMRI Studies in the Pharmaceutical Industry: Turning Data into Information Paul M. Matthews Imaging, Genetics and Neurology Clinical Imaging Centre, Hammersmith Hospital GlaxoSmithKline Clinical Neurosciences, Imperial College, London FMRIB Centre, University of Oxford

2. 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

3. 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 aninternational network for molecular imaging • Hardware/IT needs are being addressed in high value partnership with Siemens

4. Experimental medicine Disease selection Gene function to target assoc’n PoC to commit to Phase III Target to Lead Lead to Candidate Pre- clinical FTIH to PoC File and launch Life cycle man’ment Phase III Target family selection Why is the pharmaceutical industry interested in fMRI? GENETICS/’OMICS BIOMARKERS IMAGING

5. Introduction to the workshop • Applications of functional MRI in drug development • The peculiar nature of fMRI data • Optimising the outcome measure

6. Potential applications of fMRI to drug development • Patient stratification • Pharmacodynamic response • Proof of mechanism • Early phase outcome study • Surrogate marker of outcome

7. Stratification: a specific, functional “intermediate phenotype” for schizophrenia? MacDonald et al., Am J Psychiatry, 2003

8. Pharmacodynamics of pain responses to remifentanil Courtesy of Dr. R. Wise, I. Tracey (Oxford)

9. pHMRI as a tool for proof of mechanism in translational studies Sagittal plane, x=1.4mm Sagittal plane, x=3.0mm SSctx Mctx thal PrL thal Sagittal plane, x=1.0mm PrL AcbSh VTA Rat metamphetamine response Schwarz et al. NeuroImage 34, 1627-1636 (2007)

10. pHMRI as a tool for proof of mechanism in translational studies Vollm et al., 2005 Human metamphetamine response

11. Early phase outcome measure: providing a “reason to believe” Brain activation in the Stroop task Anterior cingulate Right inferior frontal cortex Basal ganglia

12. MS patients have reduced right prefrontal activity in the Stroop task MS patients recruit additional left prefrontal cortex during the Stroop task

13. Early phase outcome measure: providing a “reason to believe” Abnormal brain activition in MS transientlynormalises after rivastigmine administration Patients Healthy controls

14. MRI as a surrogate marker for disease activity in multiple sclerosis Reprinted with permission from Elsevier Compston A, Coles A. Lancet 2002;359:1221–31

15. MRI as a surrogate marker for disease activity in multiple sclerosis T2-weighted Gadoliunium enhanced

16. 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

17. 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)

18. fMRI reflects local field potential and local neuronal correlation of activity

19. 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

20. “Resting state networks” directly reflect network-based activity in the brain Mean BOLD signal change Coefficient of variation 0.5% 3% 0.1% 50%

21. A new way forward? Network-based patient stratification RSN MMSE

22. 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)

23. Acknowledgements Steve Smith, Irene Tracey, Richard Wise, Christian Beckmann, Alison Perry, Sarah Cader, Jackie Palace, Peter Jezzard, Phil Cowen, Angelo Bifone