Given the disconnection between the large increase in knowledge regarding glutamatergic systems and the slow pace of therapeutic development, a major focus of the meeting was the identification of barriers to translation. There is clearly a need for both improved compounds and improved preclinical models. A major focus, however, was on the need for improved biomarkers to exploit targets that have already been identified. A unique challenge in neuropsychiatric research is the fact that we are unable to ascertain actual drug concentrations within brain tissue and so cannot know whether the dose is appropriate relative to the affinity of the target. Thus, biomarkers are required to verify both structural target engagement (that doses of drug administered during clinical trials effectively occupy their intended target) and functional target engagement (that compounds, after binding, have the anticipated effects at the molecular, synaptic, and network targets).
Structural target engagement
Most currently available medications were developed before modern neuroimaging techniques. Dose selection, therefore, has been based primarily on the maximum tolerated dose (MTD), in which the dose was increased until CNS side effects were observed and the efficacy was then determined at this maximal dose. Only subsequently have receptor occupancy biomarkers been developed, and occupancy of the D2 dopamine receptor demonstrated for antipsychotics (46
) and serotonin transporter occupancy shown for antidepressants (49
Whereas the MTD concept is arguably appropriate for some classes of compounds, this approach is inadequate for most glutamatergic targets. For example, many glutamate receptors become down-regulated at full occupancy, requiring partial activation for effective stimulation. In such cases, doses above a critical range may lead to a deceptive lack of efficacy. For some targets, such as mGluR5 (51
) or GlyT1 (glycine transporter 1) (52
), positron emission tomography (PET) ligands are available. Moreover, in a recent GlyT1 inhibitor trial, dosing designed to produce midrange occupancy on the basis of PET occupancy led to preliminary but encouraging evidence of beneficial effect (53
), consistent with animal findings (54
). In contrast, studies with this inhibitor at the MTD produced negative results, highlighting the importance of monitoring occupancy in glutamatergic trials.
For most of the glutamatergic targets, no validated PET ligands have been developed, and development of further ligands is complicated by high costs, the need for specialized chemistry expertise in fast synthesis (because PET isotopes are short-lived), and access to imaging resources. High costs may be difficult to justify for isolated single drug development program. However, once developed, such ligands would be useful to academic, government, and pharma users.
In response to this specific problem, a work group has been convened through the National Institutes of Health to generate specific proposals for consortia that would share resources across academia, government, and industry to foster ligand development while permitting pharma to maintain proprietary development candidates (see Models for collaborative drug development section). Such consortia may be critical to overcoming a practical, but key, barrier to translational medicine approaches for neuropharmaceutical development.
PET ligands may also be crucial for patient stratification. For example, in autism, it has been suggested that the autistic phenotype can result from either too little or too much synaptic protein synthesis (45
). If this is correct, then a treatment with a beneficial response for some might be deleterious for others, complicating treatment development. Thus, knowledge of pretreatment target density may be critical for patient selection and therapeutic design.
Functional target engagement
In addition to demonstrating structural target engagement, a critical step in drug development is demonstration that binding of a drug within the CNS produces the expected functional engagement of the target and the expected effect on network-level neural processing. As with structural target engagement, demonstration of functional target engagement is critical for selecting doses that produce engagement that can be related to behavioral changes in animal models and therapeutic effects in humans. Moreover, functional biomarkers may prove essential for identifying disease subpopulations for an informative trial with a specific class of drugs.
Several promising candidate biomarkers that can be implemented in both preclinical and clinical phases of drug development have been explored over recent years. In particular, electrophysiological measures in rodents, primates, and humans are sensitive to NMDAR antagonists such as ketamine or PCP. However, ideal parameters for use in preclinical and clinical development programs have not been established. A recurrent limitation at present is that academic development of biomarkers is difficult to accomplish because academic researchers frequently do not have access to high-affinity tool compounds to assist in biomarker development. Conversely, without biomarkers to guide compound development, it is difficult for industry to develop and prioritize new compounds. As with structural measures, development of biomarkers within a precompetitive space with compounds contributed by pharma would facilitate progress for all compounds while permitting companies to retain proprietary rights.
This class of biomarkers is based on well-characterized alterations in brain electrical activity during disease states and the relationship of these signals to underlying glutamatergic function. In academic research, such measures are used to evaluate pathophysiological mechanisms preclinically and some have been used to verify effects of NMDAR antagonists. The participants at the meeting discussed which of these have the sensitivity and specificity needed for hypothesis testing in drug development and could become standards for the field. Academic researchers have focused auditory responses when exploring glutamatergic function. To date, only brain electroencephalography measures have been subject to sufficient standardization to be applied, albeit narrowly, to the development of drugs (especially GABAergic) that inhibit brain activity.
MMN is an auditory event-related potential component elicited by deviant stimuli in an auditory “oddball” paradigm, in which a series of repetitive tones is interrupted infrequently by a physically distinct oddball stimulus. MMN measures functioning of the auditory sensory memory system (56
). Because MMN is elicited by unattended as well as attended stimuli, this paradigm can be used across clinical populations relatively free from confounds relating to motivation or task engagement. Furthermore, it is generated in the auditory cortex, a brain region that is relatively conserved across rodents, monkeys, and humans (57
Fig. 3 An example biomarker for glutamate-based drug development. (A) MMN is an event-related potential generated in primary auditory cortex. (B to D) Auditory-evoked field potentials (AEP), current source density (CSD), and multiunit activity (MUA) analyses (more ...)
Deficits in MMN generation are reliably observed in schizophrenia (58
) and are related to overall level of function (60
), but are not observed in other psychotic disorders or depression (61
). Abnormalities of MMN generation are reported in autism (62
) and Alzheimer’s disease (64
), although patterns of deficit differ from those of schizophrenia. Schizophrenia-like deficits in MMN generation are observed in monkeys (65
), humans (66
), and rodents (70
) after treatment with NMDAR antagonists. These results point to the possibility of using MMN-like responses in rodents as a tool to interrogate the NMDAR system (72
) and to evaluate compounds that increase or facilitate NMDAR function.
Auditory N100 (N1) is a somewhat simpler auditory response that reflects response to individual stimuli independent of deviance from previous stimuli. N1 declines exponentially in amplitude as stimulation interval decreases below 9 s, suggesting that its generation is also modulated by short-term sensory memory traces. Schizophrenia patients show deficits in N1 generation that can be reproduced in monkeys (73
) by acute NMDAR antagonist administration. In mice, N1 shows similar characteristics as in humans (74
), suggesting that it may serve as a simple tool for translational biomarker approaches. In autism, increases in N1 latency are observed both in patients and in mice prenatally exposed to valproic acid (76
Auditory 40-Hz steady-state response
Auditory function may also be probed with rapidly presented stimuli, which elicit steady-state (as opposed to transient) responses that can be analyzed as a function of spectral frequency over time. The auditory system shows a peak resonance at 40 Hz (that is, within the γ range), a response that is impaired in schizophrenic, bipolar, and autistic patients (77
), and is hypothesized to reflect impaired synchrony within local glutamate/GABA circuits in auditory cortex (79
). As with other passive auditory measures, the auditory 40-Hz steady-state response may be ideal for cross-species translation, although ideal frequencies for stimulation in animals remain unknown.
Brain function may also be assessed with functional brain measures such as functional magnetic resonance imaging (fMRI) that can be applied to a variety of tasks to probe specific activation patterns in neural circuits as well as during resting conditions to map functional networks. Several initiatives are under way to permit standardization of fMRI approaches across platforms (such as the Biomedical Informatics Research Network). An advantage of fMRI is that most cognitive tasks currently used to assess dysfunction in neuropsychiatric conditions can be adapted to fMRI conditions. In general, however, fMRI cannot be readily obtained in either awake rodents or primates, limiting their use for translational research from animals to humans. Nonetheless, for establishing drug effects on glutamate function in humans, fMRI may prove to have broader application than evoked auditory electrophysiological approaches because of its potential to explore the dynamic interactions across multiple brain regions during specific stimulation protocols and at rest.
The use of fMRI to assess resting functional connectivity is arguably the most promising new application of the blood oxygen level–dependent (BOLD) signal to identify brain functional networks and has already been shown to be highly reproducible between and within subjects (80
) and to be sensitive to disruption by diseases (81
). Its reproducibility as well as its sensitivity to neuropathology makes it a promising tool to serve as a translational biomarker in brain diseases. Resting-state fMRI (rsfMRI) has been investigated to date in Alzheimer’s disease (82
), schizophrenia (84
), depression (81
), and addiction (85
). In addition, rsfMRI measures can be obtained in primates and rodents (86
), facilitating its use for translational research. Other measures, such as diffusion tensor imaging (87
), may provide a structural correlate that could be applicable in human, primate, and rodent species (90
Imaging of biochemistry
Other imaging-based procedures may also be developed for assessment of effects of glutamatergic compounds. Magnetic resonance spectroscopy (MRS) can be used to measure N
-acetyl aspartate (NAA) levels, which reflect the integrity of glutamatergic neurons, as well as glutamate/glutamine turnover (91
). Abnormalities of these measures have been reported in schizophrenia (93
), as have glutamate/glutamine ratios in CSF (94
Finally, because binding of NMDAR channel blockers such as PCP or ketamine is use-dependent, radioligand-based approaches [PET and SPECT (single-photon emission computed tomography)] may also be used to image glutamatergic function. To date, use-dependent ligands such as CNS-1261 have been tested (91
), but the resolution of such agents is not yet sufficient for widespread translational use.
Models for collaborative drug development
Given the high cost of biomarker development, current collaborative models require that much or all of the work be conducted in the precompetitive space—with pharma and academia providing expertise; pharma providing compounds; and government, foundations, and pharma providing funding or in-kind contributions (). Technology developed in the precompetitive space would be available to all stakeholders, with companies maintaining proprietary rights only for specific development candidates.
Fig. 4 Schematic model of interactive drug development among academia, government, and pharma, designed to overcome barriers to translational drug development. In this model, biomarkers are developed in a precompetitive space, with pharma providing nonproprietary (more ...)
In the United States, small-scale support for ligand development is currently available through Small Business Innovation Research funding mechanisms. Such models, however, specifically limit collaborations to small entities that may or may not have sufficient resources or access to high-affinity ligands to successfully complete the task. Other examples of collaboration include the Alzheimer Disease Neuroimaging Initiative (ADNI) in which funding from the National Institute of Aging, industry, and advocacy groups has been combined to develop biomarkers of disease state and progression that can be applied to drug development.
The original 5-year ADNI effort has been expanded and extended to a second phase in which multiple brain imaging and blood and CSF measures are being refined and standardized for use in clinical trials that follow subjects with predementia. A similar consortium of government and foundations was recently developed for Parkinson’s disease [Parkinson’s Progression Markers Initiative (PPMI)] with a goal of achieving synergy with the Alzheimer’s effort because structural and functional imaging methodologies as well as proteomics and/or metabolomics of blood and CSF require the same performance characteristics to be useful in drug development independent of diagnosis.
An alternative model for collaboration is the European Innovative Medicines Initiative (IMI), which is a joint initiative between the European Union and pharma. Under this initiative, academic consortia compete for funding for research defined by a consortium of companies, with funding coming from pooled resources of government and industry. For instance, the challenges in drug development for schizophrenia and depression are being addressed under the project entitled “Novel Methods leading to New Medicines in Depression and Schizophrenia” (NEWMEDS), which contains 10 work packages covering system-based animal models and translational and patient stratification biomarkers.
In IMI, government and industry contribute equal funding, with the latter’s contribution coming mostly from“in-kind” support rather than funds committed to a central source. No such program is presently in place in the United States. In general, a 1:1 funding match between government/academia and industry would produce a program attractive enough to align industry while still providing sufficient value added to government to justify the added complexity that such collaborations necessarily entail.