Can Functional Magnetic Resonance Imaging Improve Success Rates in CNS Drug Discovery?

Abstract

INTRODUCTION: The bar for developing new treatments for CNS disease is getting progressively higher and fewer novel mechanisms are being discovered, validated and developed. The high costs of drug discovery necessitate early decisions to ensure the best molecules and hypotheses are tested in expensive late stage clinical trials. The discovery of brain imaging biomarkers that can bridge preclinical to clinical CNS drug discovery and provide a 'language of translation' affords the opportunity to improve the objectivity of decision-making. AREAS COVERED: This review discusses the benefits, challenges and potential issues of using a science based biomarker strategy to change the paradigm of CNS drug development and increase success rates in the discovery of new medicines. The authors have summarized PubMed and Google Scholar based publication searches to identify recent advances in functional, structural and chemical brain imaging and have discussed how these techniques may be useful in defining CNS disease state and drug effects during drug development. EXPERT OPINION: The use of novel brain imaging biomarkers holds the bold promise of making neuroscience drug discovery smarter by increasing the objectivity of decision making thereby improving the probability of success of identifying useful drugs to treat CNS diseases. Functional imaging holds the promise to: (1) define pharmacodynamic markers as an index of target engagement (2) improve translational medicine paradigms to predict efficacy; (3) evaluate CNS efficacy and safety based on brain activation; (4) determine brain activity drug dose-response relationships and (5) provide an objective evaluation of symptom response and disease modification.

Figure 1. fMRI in CNS Drug Discovery

The figure shows fMRI at the hub of research that has contributed to 4 major domains that can be integrated or interrelated (arrows) in Drug Discovery: (1) CNS Neurobiology: fMRI has contributed to understanding of CNS Pathways in humans and animals taking into account new and exciting information relating to genetics (functional genomics) brain function. (2) Applied Biology and Pharmacology: Exciting developments in using drugs in exploring neural system responses placebo. (3) Disease Process: In the domain of human Surrogate Models for disease, Disease Plasticity, Co-morbid Disease (e.g., depression or anxiety), novel insights are being reported using fMRI to evaluate these processes. (4) New Pharmacotherapies: Large investments have recently been made in academia and industry to use fMRI in Drug Discovery looking at functional effects of drugs on neural systems (see [9]). These developments will hopefully lead to the ability to evaluate drugs in early phase of development, new uses for current drugs, and perhaps contribute to a significant problem as it relates to Animal-Human Translation, where many drugs that do well preclinically, fail in the clinic. (Adapted from [161], with permission from Springer Science+Business Media).

Figure 2. Drug Discovery Flow

The drug discovery process and the potential points at which fMRI could be applied to help development.(Adapted from (Borsook et al., 2006 [9]) with permission from Nature Publishing Group).

Figure 3. Functional, Structural and Chemical Approaches to Measures of Brain Function

The figure shows the different approaches. Examples of data obtained for functional imaging method for BOLD fMRI, resting state networks (RSN) and pharmacological MRI (phMRI) are shown in the first three panels on the left. Morphological or anatomical methods that measure changes in gray matter (voxel-based methods or VBM) include measure of sub-cortical or cortical (cortical thickness) gray matter changes. Measure of chemical changes using magnetic resonance spectroscopy (MRS) in neural and glial systems in the brain is shown in the right panel for changes derived from specific region of interest.

Figure 4. Examples of Applications of Functional Imaging Approaches

A: Opioid Agonist-Antagonist phMRI Activation. The top portion of the figure shows increased (red) or decreased (blue) activation patterns in the brain following morphine 4 mg/70 kg (adapted from [52] with permission of Wolters Kluwers Health) vs. naloxone 4 mg (adapted from [53] with permission of the American Physiological Society). An example of actual significant activation is shown in the coronal sections below with increased activation for morphine and decreased in naloxone in the orvitofrontal gyrus. Schematic BOLD responses are noted next to each figure. Figures derived from original data sets. B: Differentiating Analgesic Drugs with fMRI. The figure shows 3 components to the effects of various analgesics (imipramine (50 mg), gabapentin (600 mg), clonazepam (0.5 mg), ketorolac (10 mg) and rofecoxib (25 mg), and vs. placebo) to a thermal stimulus (stressor) (Adapted from [61], with permission of John Wiley and Sons): Subjective Ratings – Subjective rating of pain (VAS 0–10 where 0 is no pain and 10 is the maximal pain they could imagine) shown in the graph cannot differentiate between drugs following noxious heat. The data is presented as mean rating ± SEM. fMRI Response – Sample axial slices depicting activation maps for two drugs (imipramine and clonazepam) and placebo. Note that there is an overall decrease in activation for imipramine vs. placebo and an overall increase in activation for clonazepam vs. placebo. Quantitative Ratings - Voxel count for 5 drugs vs. placebo for whole brain (WHB) activation. Note that for imipramine and gabapentin more voxels are activated in drug vs. placebo while for clonazepam, rofecoxib and ketorolac more voxels are activated in the drug vs. placebo. Topiramate has an intermediate or mixed effect. C: Opioid phMRI and PET studies. The figure shows phMRI maps (z > 2.3) following infusion of morphine (4 mg/70 kg) in healthy adult male subjects [52]. Note the commonality of activations for morphine [52]and [11C] carfentanil[64]. Key: 1 – anterior cingulate; 2 – caudate nucleus; 3 – frontal cortex; 4 – putamen; and 5 – thalamus for phMRI morphine [52] vs. carfentanil [64]. Dotted white lines indicate limits of brain acquisition for scans. This is adapted from [52] with permission of Wolters Kluwer Health and from [64] with permission of Nature Publishing Group. D: Translational Measures across Species. The figure shows the thermal response of rats and humans to a 46°C stimulus applied to the dorsum of the foot. Note that the activation patterns in the regions of interest (primary somatosensory cortex (SI), thalamus (Th), insula (I), anterior cingulate cortex (aCG) and amygdala (A)) is similar to that shown for specific regions known to be involved in pain. Note the signal sign (i.e., increase or decrease in BOLD signal) is similar in both species. Furthermore, two peaks are noted in the thalamus (insert) in both species. This provides some evidence for at least partial equivalence of response in across species. (From [61], with permission from John Wiley and Sons).

Figure 5. Biomarker Development

Left Panel: The panel shows the classic drug development pipeline flow from initial discovery in the laboratory to the drug use in the clinic. Some of these processes are detailed in Figure 2. Middle Panel: The panel shows CNS Biomarker Evolution from initial identification of the potential biomarker through processes that include exploration, demonstration, classification and it sues in the clinic before becoming a diagnostic in general medical and research use. Note that as progress toward a diagnostic use becomes more defined increasing levels of evidence for the biomarker are required (see Text and see [101]) Right Panel: The figure shows biomarker process (lifecycle) from initial definition to adoption. An initial observation suggesting a Potential CNS Biomarker may be observed in a small study that then needs to be evaluated in a larger Clinical Trial that contributes to Validation. Validation, demonstrating specificity and sensitivity of the biomarker assay is followed by Qualification (with demonstration of robust reproducibility) of the biomarker and then the required Regulatory Adoption. Once adopted, the process of Continued Evaluation of the biomarker defines its continued status (Continued Evaluation) that includes potential refinements as technologies and larger clinical datasets become available.