Sleep changes as translational pharmacodynamic biomarkers

Posted: 9 October 2009 | Magnus Ivarsson, Head of Physiological Biomarkers, Department of Experimental Biological Sciences, Pfizer | No comments yet

Pharmacodynamic biomarkers in drug discovery: Developing a new drug is an expensive and time-consuming business1-3. A substantial part of the overall cost of drug development is the investment in molecules that fails at some point during the development process and it is necessary to identify these compounds as early as possible. Several different approaches are being pursued across the pharmaceutical industry to reduce the high attrition rates. One of these approaches is to identify biomarkers that are predictive of safety or efficacy and can be used in early clinical trials to build confidence that the molecule is engaging the intended target and is therefore worth investing more resources on4.

Pharmacodynamic biomarkers in drug discovery: Developing a new drug is an expensive and time-consuming business1-3. A substantial part of the overall cost of drug development is the investment in molecules that fails at some point during the development process and it is necessary to identify these compounds as early as possible. Several different approaches are being pursued across the pharmaceutical industry to reduce the high attrition rates. One of these approaches is to identify biomarkers that are predictive of safety or efficacy and can be used in early clinical trials to build confidence that the molecule is engaging the intended target and is therefore worth investing more resources on4.

Pharmacodynamic biomarkers in drug discovery: Developing a new drug is an expensive and time-consuming business1-3. A substantial part of the overall cost of drug development is the investment in molecules that fails at some point during the development process and it is necessary to identify these compounds as early as possible. Several different approaches are being pursued across the pharmaceutical industry to reduce the high attrition rates. One of these approaches is to identify biomarkers that are predictive of safety or efficacy and can be used in early clinical trials to build confidence that the molecule is engaging the intended target and is therefore worth investing more resources on4.

The Biomarkers Definitions Working Group (2001)5 defined a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”. A biomarker used to study the physiological effects of the drug is termed ‘pharmacodynamic biomarker’ and can either be specific (e.g. PET binding, which is directly related to the particular target) or non-specific (e.g. fMRI or sleep changes that normally cannot be directly linked to target)6. Electrophysiological measurements like sleep and electroencephalography (EEG) changes are relatively easy, non-invasive, inexpensive and replicable within subjects7,8. Positive results in normal subjects provide evidence of a central nervous system effect and, as mentioned above, can be used as pharmacodynamic biomarkers. Doses for early clinical trials are mainly based on these types of pharmacodynamic data from pre-clinical experiments, which makes it critically important to understand the translatability of these pharmacodynamic measurements from pre-clinical species to humans. The rest of this article will focus on our current understanding of sleep and its use as a non-specific translatable pharmacodynamic biomarker in the drug discovery process.


Sleep is a highly regulated, recurring state of quiescence with minimal processing of sensory information with nearly complete lack of motor activity. However, in spite of a substantial amount of efforts, it is still not clear what the purpose and function of sleep actually is. In the last decade, our understanding of the regulation of sleep-wake control and the underlying neural circuitry has increased dramatically. In short, the regulation of sleep-wakefulness involves reciprocal interactions between two opposing processes – one that promotes wakefulness and one that promotes sleep. Wakefulness and cortical arousal have been shown to be mediated by several ascending pathways originating from specific cell groups in the brainstem and together these pathways make up the ‘ascending reticular activating system’. The cell groups include most major neurotransmitters e.g. cholinergic, serotonergic, noradrenergic, dopaminergic, and histaminergic neurons. The ascending pathways consists of two major divisions and the first part project to the thalamus and is critical for transmitting information to the cerebral cortex. The second part bypasses thalamus and projects to the hypothalamus and the basal forebrain and then on to the cerebral cortex. These projections from the different cell groups fire in a specific pattern to promote arousal or wakefulness. Another recently discovered neurotransmitter system that plays an important role in the control of wakefulness is the orexinergic system, which originates exclusively from neurons located in the lateral hypothalamus. The orexinergic neurons projects to the brainstem and the reticular activating system and are mainly firing during wakefulness, thus positively reinforcing arousal. In contrast to the diverse wake promoting system, the main contributor to the control of sleep is located in the ventro-lateral preoptic (VLPO) nuclei of the hypothalamus. The GABAergic neurons in the VLPO inhibit the different branches of the ascending arousal system and thereby promotes sleep. However the VLPO also receives inhibitory afferents from the major monoaminergic and histaminergic systems and this mutual inhibition contributes to the generation of stable sleep and wake states9-11. We have a good understanding of how sleep is regulated, but before any sleep changes are used as a translational pharmacodynamic biomarker we need to address the similarities or differences between human and rodent sleep.

Human and rodent sleep

In order to compare human and rodent sleep we need to look into what signals you record and how you analyse sleep in the different species. The electroencephalogram was first introduced by the German psychiatrist Hans Berger in the 1920s. In humans the EEG signal is normally acquired with a number of scalp electrodes, and the resulting signal represents the summated inhibitory and excitatory postsynaptic potentials in the neurons in the underlying cortex. The number of scalp electrodes varies depending on utility, but to measure sleep changes a minimum of two electrodes is recommended. The physiology of sleep is normally characterised with a range of different electrophysiological measurements (EEG, electromyogram- EMG, electrooculogram – EOG) and when the assessment is performed under standardised conditions and analysis criteria it is referred to as polysomnography. This type of sleep analysis has been fully incorporated as an efficacy endpoint in the development of new sleep promoting agents12. The principles for analysing sleep is similar in rodents, with the main difference being that the EEG signals are normally collected directly from the cortical surface instead of with scalp electrodes. However the analysis of rodent sleep has not been standardised and there are as many analysis systems as there are groups studying sleep in rodents. This is an issue for addressing translatability and there is a need for an automatic sleep analysis system that can deal with both human and rodent data based on similar algorithms.

Normal adults sleep in consolidated periods of time at specific times of the day. However, a complicating factor is that sleep is not a unitary state but is further subdivided into rapid eye movement (REM) and non-REM (NREM) sleep. In humans, the NREM sleep is then further divided into additional three stages (stages 1-3), which roughly corresponds to increasing depth of sleep. In a typical sleep episode these sleep states alternate and each NREM-REM cycle lasts approximately one and a half hours and is referred to as the ultradian cycle. Humans usually have between six to nine ultradian cycles per sleep period. Rodents do not have a consolidated sleep pattern like humans, but instead display an active period (dark phase) and a resting period (light phase) with a preference for wakefulness and sleep, respectively. However, the individual sleep episodes of rodent sleep show a similar ultradian pattern to human sleep, but the cycling through NREM and REM stages has a much shorter duration. Rodents have approximately the same number of ultradian cycles per hour as humans have per night13-16. There are a number of other similarities including further subdivisions of the NREM sleep in rodents, presence of sleep spindles, but due to the shorter ultradian cycles in rodents the separation into further stages becomes more difficult.

Humans show more consolidated periods of NREM sleep early on during the sleep period with increasing amount of REM sleep later on in the resting period, similar to the distribution of sleep states that can be recorded during a rats resting phase. It is also well known that sleep alters with age and that the sleep pattern is markedly different in elderly compared to young individuals. Age-related changes affect all stages of human sleep and, typically, aged individuals report increased sleep onset latency, frequent awakenings, impaired sleep stability and an overall less stable sleep pattern. Rodents have also been shown to have less continuous sleep with increasing age and more fragmented sleep. Pandi-Perumal and colleagues (2002)17 have published a comprehensive review of age related changes in sleep and circadian rhythms in both animals and humans.

In conclusion, even though the overall sleep pattern in the nocturnal rodent is different from the human sleep pattern the underlying sleep architecture, distribution of sleep states and age-related changes are very similar. The next key issue to address is whether pharmacologically active compounds cause the same changes in rodent sleep as they do in human.

Drug induced changes in human and rat sleep

A substantial number of pharmacologically active compounds have been shown to have an effect on both human and rodent sleep. A change in the sleep or wake pattern are caused by drugs that interfere with the different neuronal cell populations involved in the regulation of sleep as outlined above. These compounds can be classified broadly into three major groups based on their effect on sleep a) sleep promotors; b) stimulants or wake promotors or c) REM suppressors. To give a comprehensive summary of all of the compounds is outside the scope of this review and the focus will be on a few examples from each category.

Sleep promotors – the largest class of drugs that promotes sleep interacts with the GABAergic system and includes the benzodiazepines, barbiturates and volatile anaesthetics. At low doses, these compounds are interacting directly with the ascending arousal system by potentiating the inhibitory effects of GABA on these systems. Gaboxadol is a more recent compound that interacts slightly differently with the GABAergic system. Gaboxadol binds to different subtypes of the GABA-A receptor (alpha-4 and delta) and has been shown to increase the amount of deep sleep and stabilise the sleep episodes18-20. In rodents, the same sleep enhancing effect of Gaboxadol has been shown, with a significant increase in the duration of NREM sleep episodes21. The first generation of antihistamines cross the blood-brain barrier and have been shown to cause sedation in humans, specifically a reduction in sleep onset latency22-25. The antihistamines have a direct blocking effect of the arousing properties of the central histaminergic system. Similar reductions in sleep onset latency are also a characteristic effect of antihistamines in rodents26.

Stimulants – The number of drugs that impair sleep is far higher than the drugs that promote sleep. Drugs that stimulate the central nervous system directly, normally prolong sleep-onset latency and cause more frequent awakenings and reductions in sleep depth. Several of the wake-promoting drugs act on the dopaminergic system by blocking dopamine reuptake (e.g. amphetamines, methylphenidate). An alternative stimulant is modafinil, which also binds to the dopamine uptake carrier site and interferes with noradrenaline uptake27,28. Modafinil has been shown to potently increase waking and increase the sleep onset latency in rodents29,30. Human sleep studies with modafinil show very similar changes in sleep pattern as those described with rodents28,31,32.

Antidepressants – Nearly all antidepressants of different categories (e.g. tricyclic antidepressants, monoamine oxidaase inhibitors and selective serotonin reuptake inhibitors) have been shown to cause an increased REM onset latency and a suppression of REM sleep in healthy volunteers33,34. In rodents, the same REM suppressant profile caused by antidepressants has been shown repeatedly13,35,36. However it is important to distinguish between a suppression of REM sleep as a marker of drug effect and as an indication of antidepressant effect.

As far as we know, drugs that cause a change in human sleep have been shown to cause a similar change in the sleep pattern/architecture in rats in spite of technological differences. The last issue to address in this article is whether there are translatable models of sleep disturbances.

Translatable models of sleep disturbances

A number of different tests have been developed in humans to assess the sedative or stimulant effects of drugs (Multiple Sleep Latency Test37; Maintenance of Wakefulness Test38). A number of models of sleep disruption have also been reported in the literature, but the studies have not been designed with a direct comparison between the rodent model and a clinical situation in mind39-41. Paterson and colleagues (2007)42 specifically addressed the translatability issue by developing a caffeine-induced model of insomnia in rats and healthy volunteers. The sleep-onset insomnia induced by caffeine administration was reversed with two sleep promoting compounds, zolpidem and trazodone, which work through the GABAergic and serotonergic system, respectively. Caffeine was shown to increase the sleep onset latency in both rats and humans and the effect was attenuated by both zolpidem and trazodone. This is a promising translatable model of insomnia with which to test novel sleep promoting compounds with different mechanisms of action and shows that both humans and rats respond very similarly in this model of sleep disturbance.


In summary, human and rodent sleep is structurally very similar and most of our knowledge of sleep regulation originates from rodent experiments. Due to the nature of translatable research there will always be differences in recording and analysis techniques, but we need to continue with the effort of minimising the impact of these limitations. In spite of the methodological differences it is clear that drugs from different drug classes interact with the sleep regulating centres in both humans and rodents in a similar way, both under normal conditions and in models of insomnia. Therefore drug induced sleep changes in rodents should play a key role as non-specific translatable pharmacodynamic biomarkers in the drug discovery process.


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