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Obrecht M, Zurbruegg S, Accart N, Lambert C, Doelemeyer A, Ledermann B, Beckmann N. Magnetic resonance imaging and ultrasound elastography in the context of preclinical pharmacological research: significance for the 3R principles. Front Pharmacol 2023; 14:1177421. [PMID: 37448960 PMCID: PMC10337591 DOI: 10.3389/fphar.2023.1177421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023] Open
Abstract
The 3Rs principles-reduction, refinement, replacement-are at the core of preclinical research within drug discovery, which still relies to a great extent on the availability of models of disease in animals. Minimizing their distress, reducing their number as well as searching for means to replace them in experimental studies are constant objectives in this area. Due to its non-invasive character in vivo imaging supports these efforts by enabling repeated longitudinal assessments in each animal which serves as its own control, thereby enabling to reduce considerably the animal utilization in the experiments. The repetitive monitoring of pathology progression and the effects of therapy becomes feasible by assessment of quantitative biomarkers. Moreover, imaging has translational prospects by facilitating the comparison of studies performed in small rodents and humans. Also, learnings from the clinic may be potentially back-translated to preclinical settings and therefore contribute to refining animal investigations. By concentrating on activities around the application of magnetic resonance imaging (MRI) and ultrasound elastography to small rodent models of disease, we aim to illustrate how in vivo imaging contributes primarily to reduction and refinement in the context of pharmacological research.
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Affiliation(s)
- Michael Obrecht
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nathalie Accart
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Christian Lambert
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Arno Doelemeyer
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Birgit Ledermann
- 3Rs Leader, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nicolau Beckmann
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
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2
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Carmichael O. The Role of fMRI in Drug Development: An Update. ADVANCES IN NEUROBIOLOGY 2023; 30:299-333. [PMID: 36928856 DOI: 10.1007/978-3-031-21054-9_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Functional magnetic resonance imaging (fMRI) of the brain is a technology that holds great potential for increasing the efficiency of drug development for the central nervous system (CNS). In preclinical studies and both early- and late-phase human trials, fMRI has the potential to improve cross-species translation of drug effects, help to de-risk compounds early in development, and contribute to the portfolio of evidence for a compound's efficacy and mechanism of action. However, to date, the utilization of fMRI in the CNS drug development process has been limited. The purpose of this chapter is to explore this mismatch between potential and utilization. This chapter provides introductory material related to fMRI and drug development, describes what is required of fMRI measurements for them to be useful in a drug development setting, lists current capabilities of fMRI in this setting and challenges faced in its utilization, and ends with directions for future development of capabilities in this arena. This chapter is the 5-year update of material from a previously published workshop summary (Carmichael et al., Drug DiscovToday 23(2):333-348, 2018).
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Affiliation(s)
- Owen Carmichael
- Pennington Biomedical Research Center, Baton Rouge, LA, USA.
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3
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Comparison of test–retest reliability of BOLD and pCASL fMRI in a two-center study. BMC Med Imaging 2022; 22:62. [PMID: 35366813 PMCID: PMC8977011 DOI: 10.1186/s12880-022-00791-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/21/2022] [Indexed: 11/17/2022] Open
Abstract
Background The establishment of test–retest reliability and reproducibility (TRR) is an important part of validating any research tool, including functional magnetic resonance imaging (fMRI). The primary objective of this study is to investigate the reliability of pseudo-Continuous Arterial Spin Labeling (pCASL) and Blood Oxygen Level Dependent (BOLD) fMRI data acquired across two different scanners in a sample of healthy adults. While single site/single scanner studies have shown acceptable repeatability, TRR of both in a practical multisite study occurring in two facilities spread out across the country with weeks to months between scans is critically needed. Methods Ten subjects were imaged with similar 3 T MRI scanners at the University of Pittsburgh and Massachusetts General Hospital. Finger-tapping and Resting-state data were acquired for both techniques. Analysis of the resting state data for functional connectivity was performed with the Functional Connectivity Toolbox, while analysis of the finger tapping data was accomplished with FSL. pCASL Blood flow data was generated using AST Toolbox. Activated areas and networks were identified via pre-defined atlases and dual-regression techniques. Analysis for TRR was conducted by comparing pCASL and BOLD images in terms of Intraclass correlation coefficients, Dice Similarity Coefficients, and repeated measures ANOVA. Results Both BOLD and pCASL scans showed strong activation and correlation between the two locations for the finger tapping tasks. Functional connectivity analyses identified elements of the default mode network in all resting scans at both locations. Multivariate repeated measures ANOVA showed significant variability between subjects, but no significant variability for location. Global CBF was very similar between the two scanning locations, and repeated measures ANOVA showed no significant differences between the two scanning locations. Conclusions The results of this study show that when similar scanner hardware and software is coupled with identical data analysis protocols, consistent and reproducible functional brain images can be acquired across sites. The variability seen in the activation maps is greater for pCASL versus BOLD images, as expected, however groups maps are remarkably similar despite the low number of subjects. This demonstrates that multi-site fMRI studies of task-based and resting state brain activity is feasible.
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Sadraee A, Paulus M, Ekhtiari H. fMRI as an outcome measure in clinical trials: A systematic review in clinicaltrials.gov. Brain Behav 2021; 11:e02089. [PMID: 33662169 PMCID: PMC8119793 DOI: 10.1002/brb3.2089] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 12/29/2020] [Accepted: 01/02/2021] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION More than one-thousand trials with functional magnetic resonance imaging (fMRI) as an outcome measure were registered in clinicaltrials.gov at the time of writing this article. However, 93% of these registered trials are still not completed with published results and there is no picture available about methodological dimensions of these ongoing trials with fMRI as an outcome measure. METHODS We collected trials that use fMRI as an outcome measure in the ClinicalTrials.gov registry on 13 October 2018 and reviewed each trial's record entry. Eligible trials' characteristics were extracted and summarized. RESULTS In total, 1,386 clinical trials were identified that reported fMRI in their outcome measures with fMRI as the only primary outcome in 33% of them. 82% of fMRI trials were started after 2011. The most frequent intervention was drug (pharmacological intervention) (29%). 57% of trials had parallel assignment design and 20% were designed for cross-over assignment. For task-based fMRI, cognitive systems (46%) based on Research Domain Criteria (RDoC) was the most frequent domain of tasks. Less than one-third of trials (28%) registered at least one region of interest for their analysis. Food cue reactivity task, pain perception task, n-back task, and monetary incentive delay task were recruited in more than 25 registered trials. CONCLUSION The number of fMRI trials (fMRI as an outcome measure) with both task and rest protocols is growing rapidly. Our study suggests a growing need for harmonization and standardized checklists on both methods and analysis for preregistration of fMRI-based outcomes in clinical trials.
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Affiliation(s)
- Alaleh Sadraee
- Institute for Cognitive Science StudiesTehranIran
- Iranian National Center for Addiction StudiesTehran University of Medical SciencesTehranIran
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5
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Grimm O, Nägele M, Küpper-Tetzel L, de Greck M, Plichta M, Reif A. No effect of a dopaminergic modulation fMRI task by amisulpride and L-DOPA on reward anticipation in healthy volunteers. Psychopharmacology (Berl) 2021; 238:1333-1342. [PMID: 33140215 PMCID: PMC8062334 DOI: 10.1007/s00213-020-05693-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 10/23/2020] [Indexed: 01/02/2023]
Abstract
RATIONALE Dysregulation of dopaminergic neurotransmission, specifically altered reward processing assessed via the reward anticipation in the MID task, plays a central role in the etiopathogenesis of neuropsychiatric disorders. OBJECTIVES We hypothesized to find a difference in the activity level of the reward system (measured by the proxy reward anticipation) under drug administration versus placebo, in that amisulpride reduces, and L-DOPA enhances, its activity. METHODS We studied the influence of dopamine agonist L-DOPA and the antagonist amisulpride on the reward system using functional magnetic resonance imaging (fMRI) during a monetary incentive delay (MID) task in n = 45 healthy volunteers in a randomized, blinded, cross-over study. RESULTS The MID paradigm elicits strong activation in reward-dependent structures (such as ventral striatum, putamen, caudate, anterior insula) during reward anticipation. The placebo effect demonstrated the expected significant blood oxygen level-dependent activity in reward-dependent brain regions. Neither amisulpride nor L-DOPA led to significant changes in comparison with the placebo condition. This was true for whole-brain analysis as well as analysis of a pre-defined nucleus accumbens region-of-interest mask. CONCLUSION The present results cast doubt on the sensitivity of reward anticipation contrast in the MID task for assessing dopamine-specific changes in healthy volunteers by pharmaco-fMRI. While our task was not well-suited for detailed analysis of the outcome phase, we provide reasonable arguments that the lack of effect in the anticipation phase is not due to an inefficient task but points to unexpected behavior of the reward system during pharmacological challenge. Group differences of reward anticipation should therefore not be seen as simple representatives of dopaminergic states.
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Affiliation(s)
- Oliver Grimm
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany.
| | - Magdalena Nägele
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Lea Küpper-Tetzel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Moritz de Greck
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Michael Plichta
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
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6
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Borsook D, Upadhyay J, Hargreaves R, Wager T. Enhancing Choice and Outcomes for Therapeutic Trials in Chronic Pain: N-of-1 + Imaging (+ i). Trends Pharmacol Sci 2020; 41:85-98. [DOI: 10.1016/j.tips.2019.12.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/27/2019] [Accepted: 12/04/2019] [Indexed: 10/25/2022]
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7
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Carmichael O, Schwarz AJ, Chatham CH, Scott D, Turner JA, Upadhyay J, Coimbra A, Goodman JA, Baumgartner R, English BA, Apolzan JW, Shankapal P, Hawkins KR. The role of fMRI in drug development. Drug Discov Today 2018; 23:333-348. [PMID: 29154758 PMCID: PMC5931333 DOI: 10.1016/j.drudis.2017.11.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 10/19/2017] [Accepted: 11/13/2017] [Indexed: 12/17/2022]
Abstract
Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility.
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Affiliation(s)
- Owen Carmichael
- Pennington Biomedical Research Center, Baton Rouge, LA, USA.
| | | | - Christopher H Chatham
- Translational Medicine Neuroscience and Biomarkers, Roche Innovation Center, Basel, Switzerland
| | | | - Jessica A Turner
- Psychology Department & Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | | | | | | | - Richard Baumgartner
- Biostatistics and Research Decision Sciences (BARDS), Merck & Co., Inc., Kenilworth, NJ, USA
| | | | - John W Apolzan
- Pennington Biomedical Research Center, Baton Rouge, LA, USA
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8
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Khalili-Mahani N, Rombouts SARB, van Osch MJP, Duff EP, Carbonell F, Nickerson LD, Becerra L, Dahan A, Evans AC, Soucy JP, Wise R, Zijdenbos AP, van Gerven JM. Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry. Hum Brain Mapp 2017; 38:2276-2325. [PMID: 28145075 DOI: 10.1002/hbm.23516] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Revised: 11/21/2016] [Accepted: 01/04/2017] [Indexed: 12/11/2022] Open
Abstract
A decade of research and development in resting-state functional MRI (RSfMRI) has opened new translational and clinical research frontiers. This review aims to bridge between technical and clinical researchers who seek reliable neuroimaging biomarkers for studying drug interactions with the brain. About 85 pharma-RSfMRI studies using BOLD signal (75% of all) or arterial spin labeling (ASL) were surveyed to investigate the acute effects of psychoactive drugs. Experimental designs and objectives include drug fingerprinting dose-response evaluation, biomarker validation and calibration, and translational studies. Common biomarkers in these studies include functional connectivity, graph metrics, cerebral blood flow and the amplitude and spectrum of BOLD fluctuations. Overall, RSfMRI-derived biomarkers seem to be sensitive to spatiotemporal dynamics of drug interactions with the brain. However, drugs cause both central and peripheral effects, thus exacerbate difficulties related to biological confounds, structured noise from motion and physiological confounds, as well as modeling and inference testing. Currently, these issues are not well explored, and heterogeneities in experimental design, data acquisition and preprocessing make comparative or meta-analysis of existing reports impossible. A unifying collaborative framework for data-sharing and data-mining is thus necessary for investigating the commonalities and differences in biomarker sensitivity and specificity, and establishing guidelines. Multimodal datasets including sham-placebo or active control sessions and repeated measurements of various psychometric, physiological, metabolic and neuroimaging phenotypes are essential for pharmacokinetic/pharmacodynamic modeling and interpretation of the findings. We provide a list of basic minimum and advanced options that can be considered in design and analyses of future pharma-RSfMRI studies. Hum Brain Mapp 38:2276-2325, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Najmeh Khalili-Mahani
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Canada.,PERFORM Centre, Concordia University, Montreal, Canada
| | - Serge A R B Rombouts
- Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.,Institute of Psychology and Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | | | - Eugene P Duff
- Institute of Psychology and Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.,Oxford Centre for Functional MRI of the Brain, Oxford University, Oxford, United Kingdom
| | | | - Lisa D Nickerson
- McLean Hospital, Belmont, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Lino Becerra
- Center for Pain and the Brain, Harvard Medical School & Boston Children's Hospital, Boston, Massachusetts
| | - Albert Dahan
- Department of Anesthesiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Alan C Evans
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Canada.,McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Jean-Paul Soucy
- PERFORM Centre, Concordia University, Montreal, Canada.,McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Richard Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Alex P Zijdenbos
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Canada.,Biospective Inc, Montreal, Quebec, Canada
| | - Joop M van Gerven
- Centre for Human Drug Research, Leiden University Medical Centre, Leiden, The Netherlands
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9
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Doyle OM, Mehta MA, Brammer MJ. The role of machine learning in neuroimaging for drug discovery and development. Psychopharmacology (Berl) 2015; 232:4179-89. [PMID: 26014110 DOI: 10.1007/s00213-015-3968-0] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Accepted: 05/11/2015] [Indexed: 12/30/2022]
Abstract
Neuroimaging has been identified as a potentially powerful probe for the in vivo study of drug effects on the brain with utility across several phases of drug development spanning preclinical and clinical investigations. Specifically, neuroimaging can provide insight into drug penetration and distribution, target engagement, pharmacodynamics, mechanistic action and potential indicators of clinical efficacy. In this review, we focus on machine learning approaches for neuroimaging which enable us to make predictions at the individual level based on the distributed effects across the whole brain. Crucially, these approaches can be trained on data from one study and applied to an independent study and, unlike group-level statistics, can be readily use to assess the generalisability to unseen data. In this review, we present examples and suggestions for how machine learning could help answer fundamental questions spanning the drug discovery pipeline: (1) Who should I recruit for this study? (2) What should I measure and when should I measure it? (3) How does the pharmacological agent behave using an experimental medicine model?, and (4) How does a compound differ from and/or resemble existing compounds? Specifically, we present studies from the literature and we suggest areas for the focus of future development. Further refinement and tailoring of machine learning techniques may help realise their tremendous potential for drug discovery and drug validation.
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Affiliation(s)
- Orla M Doyle
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK.
| | - Mitul A Mehta
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | - Michael J Brammer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
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10
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Test–retest reliability of evoked heat stimulation BOLD fMRI. J Neurosci Methods 2015; 253:38-46. [DOI: 10.1016/j.jneumeth.2015.06.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 06/01/2015] [Accepted: 06/03/2015] [Indexed: 11/19/2022]
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11
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Hargreaves RJ, Hoppin J, Sevigny J, Patel S, Chiao P, Klimas M, Verma A. Optimizing Central Nervous System Drug Development Using Molecular Imaging. Clin Pharmacol Ther 2015; 98:47-60. [PMID: 25869938 DOI: 10.1002/cpt.132] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 04/07/2015] [Indexed: 12/12/2022]
Abstract
Advances in multimodality fusion imaging technologies promise to accelerate the understanding of the systems biology of disease and help in the development of new therapeutics. The use of molecular imaging biomarkers has been proven to shorten cycle times for central nervous system (CNS) drug development and thereby increase the efficiency and return on investment from research. Imaging biomarkers can be used to help select the molecules, doses, and patients most likely to test therapeutic hypotheses by stopping those that have little chance of success and accelerating those with potential to achieve beneficial clinical outcomes. CNS imaging biomarkers have the potential to drive new medical care practices for patients in the latent phases of progressive neurodegenerative disorders by enabling the detection, preventative treatment, and tracking of disease in a paradigm shift from today's approaches that have to see the overt symptoms of disease before treating it.
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Affiliation(s)
| | - J Hoppin
- inviCRO, LLC, Boston, Massachusetts, USA
| | - J Sevigny
- Biogen, Cambridge, Massachusetts, USA
| | - S Patel
- Biogen, Cambridge, Massachusetts, USA
| | - P Chiao
- Biogen, Cambridge, Massachusetts, USA
| | - M Klimas
- Merck Research Laboratories, West Point, Pennsylvania, USA
| | - A Verma
- Biogen, Cambridge, Massachusetts, USA
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12
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Borsook D, Hargreaves R, Bountra C, Porreca F. Lost but making progress--Where will new analgesic drugs come from? Sci Transl Med 2015; 6:249sr3. [PMID: 25122640 DOI: 10.1126/scitranslmed.3008320] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
There is a critical need for effective new pharmacotherapies for pain. The paucity of new drugs successfully reaching the clinic calls for a reassessment of current analgesic drug discovery approaches. Many points early in the discovery process present significant hurdles, making it critical to exploit advances in pain neurobiology to increase the probability of success. In this review, we highlight approaches that are being pursued vigorously by the pain community for drug discovery, including innovative preclinical pain models, insights from genetics, mechanistic phenotyping of pain patients, development of biomarkers, and emerging insights into chronic pain as a disorder of both the periphery and the brain. Collaborative efforts between pharmaceutical, academic, and public entities to advance research in these areas promise to de-risk potential targets, stimulate investment, and speed evaluation and development of better pain therapies.
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Affiliation(s)
- David Borsook
- Center for Pain and the Brain, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Richard Hargreaves
- Center for Pain and the Brain, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Chas Bountra
- Department of Clinical Medicine, University of Oxford, Oxford OX1 2JD, UK
| | - Frank Porreca
- Center for Pain and the Brain and Department of Pharmacology, University of Arizona, Tucson, AZ 85724, USA.
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13
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Seah S, Asad ABA, Baumgartner R, Feng D, Williams DS, Manigbas E, Beaver JD, Reese T, Henry B, Evelhoch JL, Chin CL. Investigation of cross-species translatability of pharmacological MRI in awake nonhuman primate - a buprenorphine challenge study. PLoS One 2014; 9:e110432. [PMID: 25337714 PMCID: PMC4206294 DOI: 10.1371/journal.pone.0110432] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2014] [Accepted: 09/22/2014] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Pharmacological MRI (phMRI) is a neuroimaging technique where drug-induced hemodynamic responses can represent a pharmacodynamic biomarker to delineate underlying biological consequences of drug actions. In most preclinical studies, animals are anesthetized during image acquisition to minimize movement. However, it has been demonstrated anesthesia could attenuate basal neuronal activity, which can confound interpretation of drug-induced brain activation patterns. Significant efforts have been made to establish awake imaging in rodents and nonhuman primates (NHP). Whilst various platforms have been developed for imaging awake NHP, comparison and validation of phMRI data as translational biomarkers across species remain to be explored. METHODOLOGY We have established an awake NHP imaging model that encompasses comprehensive acclimation procedures with a dedicated animal restrainer. Using a cerebral blood volume (CBV)-based phMRI approach, we have determined differential responses of brain activation elicited by the systemic administration of buprenorphine (0.03 mg/kg i.v.), a partial µ-opioid receptor agonist, in the same animal under awake and anesthetized conditions. Additionally, region-of-interest analyses were performed to determine regional drug-induced CBV time-course data and corresponding area-under-curve (AUC) values from brain areas with high density of µ-opioid receptors. PRINCIPAL FINDINGS In awake NHPs, group-level analyses revealed buprenorphine significantly activated brain regions including, thalamus, striatum, frontal and cingulate cortices (paired t-test, versus saline vehicle, p<0.05, n = 4). This observation is strikingly consistent with µ-opioid receptor distribution depicted by [6-O-[(11)C]methyl]buprenorphine ([(11)C]BPN) positron emission tomography imaging study in baboons. Furthermore, our findings are consistent with previous buprenorphine phMRI studies in humans and conscious rats which collectively demonstrate the cross-species translatability of awake imaging. Conversely, no significant change in activated brain regions was found in the same animals imaged under the anesthetized condition. CONCLUSIONS Our data highlight the utility and importance of awake NHP imaging as a translational imaging biomarker for drug research.
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Affiliation(s)
- Stephanie Seah
- Imaging, Merck & Co. Inc., West Point, Pennsylvania, United States of America
- Translational Medicine Research Centre, MSD, Singapore, Singapore
| | - Abu Bakar Ali Asad
- Imaging, Merck & Co. Inc., West Point, Pennsylvania, United States of America
- Translational Medicine Research Centre, MSD, Singapore, Singapore
| | - Richard Baumgartner
- Biostatistics and Research Decision Sciences, Merck & Co. Inc., Rahway, New Jersey, United States of America
| | - Dai Feng
- Biostatistics and Research Decision Sciences, Merck & Co. Inc., Rahway, New Jersey, United States of America
| | - Donald S. Williams
- Imaging, Merck & Co. Inc., West Point, Pennsylvania, United States of America
| | | | | | - Torsten Reese
- Translational Medicine Research Centre, MSD, Singapore, Singapore
| | - Brian Henry
- Translational Medicine Research Centre, MSD, Singapore, Singapore
| | - Jeffrey L. Evelhoch
- Imaging, Merck & Co. Inc., West Point, Pennsylvania, United States of America
| | - Chih-Liang Chin
- Imaging, Merck & Co. Inc., West Point, Pennsylvania, United States of America
- Translational Medicine Research Centre, MSD, Singapore, Singapore
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Modo M, Kolosnjaj-Tabi J, Nicholls F, Ling W, Wilhelm C, Debarge O, Gazeau F, Clement O. Considerations for the clinical use of contrast agents for cellular MRI in regenerative medicine. CONTRAST MEDIA & MOLECULAR IMAGING 2014; 8:439-55. [PMID: 24375900 DOI: 10.1002/cmmi.1547] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2013] [Revised: 04/21/2013] [Accepted: 05/09/2013] [Indexed: 12/24/2022]
Abstract
Advances in regenerative medicine are rapidly transforming healthcare. A cornerstone of regenerative medicine is the introduction of cells that were grown or manipulated in vitro. Key questions that arise after these cells are re-introduced are: whether these cells are localized in the appropriate site; whether cells survive; and whether these cells migrate. These questions predominantly relate to the safety of the therapeutic approach (i.e. tumorigenesis), but certain aspects can also influence the efficacy of the therapeutic approach (e.g. site of injection). The European Medicines Agency has indicated that suitable methods for stem cell tracking should be applied where these methods are available. We here discuss the European regulatory framework, as well as the scientific evidence, that should be considered to facilitate the potential clinical implementation of magnetic resonance imaging contrast media to track implanted/injected cells in human studies.
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Affiliation(s)
- Michel Modo
- University of Pittsburgh, Department of Radiology, McGowan Institute for Regenerative Medicine, Pittsburgh, PA, 15203, USA
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15
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English BA, Thomas K, Johnstone J, Bazih A, Gertsik L, Ereshefsky L. Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia. Biomark Med 2014; 8:29-49. [PMID: 24325223 DOI: 10.2217/bmm.13.135] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Schizophrenia is a severe mental disorder characterized by cognitive deficits, and positive and negative symptoms. The development of effective pharmacological compounds for the treatment of schizophrenia has proven challenging and costly, with many compounds failing during clinical trials. Many failures occur due to disease heterogeneity and lack of predictive preclinical models and biomarkers that readily translate to humans during early characterization of novel antipsychotic compounds. Traditional early-phase trials consist of single- or multiple-dose designs aimed at determining the safety and tolerability of an investigational compound in healthy volunteers. However, by incorporating a translational approach employing methodologies derived from preclinical studies, such as EEG measures and imaging, into the traditional Phase I program, critical information regarding a compound's dose-response effects on pharmacodynamic biomarkers can be acquired. Furthermore, combined with the use of patients with stable schizophrenia in early-phase clinical trials, significant 'de-risking' and more confident 'go/no-go' decisions are possible.
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Use of functional imaging across clinical phases in CNS drug development. Transl Psychiatry 2013; 3:e282. [PMID: 23860483 PMCID: PMC3731782 DOI: 10.1038/tp.2013.43] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Accepted: 03/15/2013] [Indexed: 12/20/2022] Open
Abstract
The use of novel brain biomarkers using nuclear magnetic resonance imaging holds potential of making central nervous system (CNS) drug development more efficient. By evaluating changes in brain function in the disease state or drug effects on brain function, the technology opens up the possibility of obtaining objective data on drug effects in the living awake brain. By providing objective data, imaging may improve the probability of success of identifying useful drugs to treat CNS diseases across all clinical phases (I-IV) of drug development. The evolution of functional imaging and the promise it holds to contribute to drug development will require the development of standards (including good imaging practice), but, if well integrated into drug development, functional imaging can define markers of CNS penetration, drug dosing and target engagement (even for drugs that are not amenable to positron emission tomography imaging) in phase I; differentiate objective measures of efficacy and side effects and responders vs non-responders in phase II, evaluate differences between placebo and drug in phase III trials and provide insights into disease modification in phase IV trials.
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Plichta MM, Schwarz AJ, Grimm O, Morgen K, Mier D, Haddad L, Gerdes ABM, Sauer C, Tost H, Esslinger C, Colman P, Wilson F, Kirsch P, Meyer-Lindenberg A. Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery. Neuroimage 2012; 60:1746-58. [PMID: 22330316 DOI: 10.1016/j.neuroimage.2012.01.129] [Citation(s) in RCA: 222] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Revised: 01/26/2012] [Accepted: 01/28/2012] [Indexed: 11/26/2022] Open
Abstract
Even more than in cognitive research applications, moving fMRI to the clinic and the drug development process requires the generation of stable and reliable signal changes. The performance characteristics of the fMRI paradigm constrain experimental power and may require different study designs (e.g., crossover vs. parallel groups), yet fMRI reliability characteristics can be strongly dependent on the nature of the fMRI task. The present study investigated both within-subject and group-level reliability of a combined three-task fMRI battery targeting three systems of wide applicability in clinical and cognitive neuroscience: an emotional (face matching), a motivational (monetary reward anticipation) and a cognitive (n-back working memory) task. A group of 25 young, healthy volunteers were scanned twice on a 3T MRI scanner with a mean test-retest interval of 14.6 days. FMRI reliability was quantified using the intraclass correlation coefficient (ICC) applied at three different levels ranging from a global to a localized and fine spatial scale: (1) reliability of group-level activation maps over the whole brain and within targeted regions of interest (ROIs); (2) within-subject reliability of ROI-mean amplitudes and (3) within-subject reliability of individual voxels in the target ROIs. Results showed robust evoked activation of all three tasks in their respective target regions (emotional task=amygdala; motivational task=ventral striatum; cognitive task=right dorsolateral prefrontal cortex and parietal cortices) with high effect sizes (ES) of ROI-mean summary values (ES=1.11-1.44 for the faces task, 0.96-1.43 for the reward task, 0.83-2.58 for the n-back task). Reliability of group level activation was excellent for all three tasks with ICCs of 0.89-0.98 at the whole brain level and 0.66-0.97 within target ROIs. Within-subject reliability of ROI-mean amplitudes across sessions was fair to good for the reward task (ICCs=0.56-0.62) and, dependent on the particular ROI, also fair-to-good for the n-back task (ICCs=0.44-0.57) but lower for the faces task (ICC=-0.02-0.16). In conclusion, all three tasks are well suited to between-subject designs, including imaging genetics. When specific recommendations are followed, the n-back and reward task are also suited for within-subject designs, including pharmaco-fMRI. The present study provides task-specific fMRI reliability performance measures that will inform the optimal use, powering and design of fMRI studies using comparable tasks.
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Affiliation(s)
- Michael M Plichta
- Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, University of Heidelberg/Medical Faculty Mannheim, Mannheim, Germany.
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Schwarz AJ, Becerra L, Upadhyay J, Anderson J, Baumgartner R, Coimbra A, Evelhoch J, Hargreaves R, Robertson B, Iyengar S, Tauscher J, Bleakman D, Borsook D. A procedural framework for good imaging practice in pharmacological fMRI studies applied to drug development #1: processes and requirements. Drug Discov Today 2011; 16:583-93. [PMID: 21635967 DOI: 10.1016/j.drudis.2011.05.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2010] [Revised: 04/19/2011] [Accepted: 05/11/2011] [Indexed: 11/30/2022]
Abstract
There is increasing interest in the application of quantitative magnetic resonance imaging (MRI) methods to drug development, but as yet little standardization or best practice guidelines for its use in this context. Pharmaceutical trials are subject to regulatory constraints and sponsor company processes, including site qualification and expectations around study oversight, blinding, quality assurance and quality control (QA/QC), analysis and reporting of results. In this article, we review the processes on the sponsor side and also the procedures involved in data acquisition at the imaging site. We then propose summary recommendations to help guide appropriate imaging site qualification, as part of a framework of 'good imaging practice' for functional (f)MRI studies applied to drug development.
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Affiliation(s)
- Adam J Schwarz
- Brain Imaging Center, McLean Hospital, 115 Mill St. Belmont, MA 02478, USA
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