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European Pharmaceutical Contractor

Counting Sheep


There is a growing demand for pharmaceuticals for sleep-related disorders, as well as a need for a greater understanding of how drugs may affect sleep. Biomarkers, EEG and spectral analysis are among the qualitative tools in use or development for measuring sleep impact in clinical trials.

Sleep is something that many of us take for granted. For most of us, the process of initiating and maintaining sleep is an effortless and unconscious neurological process that is controlled without a thought. However, with age, disease, medication and as a primary (idiopathic) problem, sleep-related issues will present in most of us at some point in our lives. At this point, initiation, maintenance and control of sleep become an effort and a struggle.

Research into the cause of sleep problems continues, with new techniques, tools and biomarkers being developed to quantify and diagnose sleep-related disorders. However, there is need to further investigate the impact of sleep and sleep problems as a disease, as well as a need to investigate the impact of disease, drugs and lifestyle on sleep. Although the techniques and clinical trial methodology are advancing, we are sadly seeing a stagnation in the development of drugs to treat insomnia. Fortunately, new tools and biomarkers are being developed and validated that assist in the assessment of sleep.

There is no doubt that the recent trends in regulatory approvals of all drugs are moving towards a greater focus on safety. Data suggest that there is a decrease in the number of new chemical entities being granted licences. This is partly due to an increased level of scrutiny being levelled by the regulators, and partly because there is a paucity of compounds with promise being developed.

Although a slight improvement in the number of regulatory license approvals was seen in 2011, from a sleep perspective it was disappointing to see that the development of almorexant (an Actelion/ GSK partnership, potentially worth $2 billion per annum in revenue) was ceased.

The Need for Better Drugs for Sleep Disorders

For both the patient and the physician, currently available insomnia drugs are disappointing. Their use is typified by initial and short-lived resolution of symptoms, but frequent side effects and ultimately tolerance and addiction mar the long term use of benzodiazepines in particular. Many of the compounds have been around for a long time. There is certainly a need for more effective, safer compounds to treat sleep-related problems.

Sleep disorders like insomnia, obstructive sleep apnoea and restless leg syndrome are major issues. There are many other disorders and chronic conditions in which sleep and an alteration in sleep hygiene and function play a major role. For example, in Parkinson’s disease (PD) we know that disordered sleep plays a major role in the quality-of-life of the patient, but it is also an early sign of impending issues. At least one in six people above the age of 80 in the UK have some form of dementia, and the prevalence of drugs which have now increased functionality, as well as the use of techniques like deep brain stimulation mean that patients who are living for a lot longer are unfortunately still living with symptoms such as insomnia and poor quality sleep.

Most of us sleep for at least a third of our lives. Alter this ratio, and we begin to deteriorate psychologically and physically – very rapidly. Although the effects are temporary, and easily restored, reduce sleep chronically and several systems begin to demonstrate deterioration. Heart disease, metabolic syndrome and diabetes are amongst some of the problems that are becoming increasingly prevalent. If we corrected sleep issues, partial and sometimes complete resolution or prevention of other problems may be possible. This underscores the need to develop new drugs and devices to combat the problem.

Many diseases, particularly neurological diseases, often present with sleep problems as a primary symptom. Sleep problems may be present as an early and solitary symptom, often ignored as a separate issue.

It is estimated that sleep issues, and in particular insomnia, will affect at least 50 per cent of the population at some point. Chronic insomnia affects between five and 10 per cent of the population. Currently the drug therapy for sleep-related issues is largely anchored around either benzodiazepines and a group of nonbenzodiazepine drugs otherwise known as Z-drugs. Other compounds are under investigation, notably a group melatonin receptor agonists. Although a few other compounds and targets have made their way into the latter stages of clinical development, they have not yet made their way into common use due to lack of efficacy and safety issues.

The new and old drugs also have to contend and compete with an increased use of cognitive and behavioural therapy, driven by increased expertise, evidence and experience with these methods, but also in part driven by the lack of efficacy of the drugs in many cases.

Measuring Sleepiness

Methods for measuring the efficacy of drugs that induce or reduce sleep have developed significantly over the last 10 years. In addition to the improvement in subjective assessments and the creation and validation of disease-specific tests, several other novel tools are gaining traction and further use in clinical research.

For those striving to develop perfect methods of measuring/quantifying sleep (or indeed any clinical condition), the perfect surrogate marker (or biomarker) is a measure that is totally objective, inconspicuous to the subject and the tester, exquisitely sensitive, and absolutely specific – that is, an area under the receiver operating characteristics (AUC ROC) curve of 1. By these criteria, physiological measures that are based on brain activity such as electroencephalography (EEG), fMRI, or near-infrared spectroscopy would appear to hold the most promise of ever approaching perfection.

However, from a practical, real-life perspective, the value and usefulness of a ‘sleepiness’ measure is not the tool or biomarker’s ability to sensitively reflect the brain’s level of sleepiness, but the impact that the sleepiness has on the individual’s current and near-term ability to safely and efficiently perform normal or personally relevant tasks. An ideal sleepiness measure is one that is unobtrusively embedded in the relevant activity or task, and distinguishes sleeprelated functional decline from other performance declines.

In the world of sleep and neurological research, these types of qualitative tools are numerous. From pain scores to complex quality-of-life assessments and qualitative analyses, we are inundated with tools and scores. Data derived from these tools are perhaps open to the same degree of misinterpretation as physiological biomarkers. That said, if used in conjunction with each other the AUC ROC could approach 1 in the right circumstances.

Electroencephalograms

The role of EEG, and in particular the focus on focal abnormalities, has evolved over the last 75 years. It is now uncommon to use focal EEG for the identification and diagnosis of superficial cerebral mass lesions, unless the CT is broken. It used to be common practice to use the EEG of a comatose patient to lateralise lesions and pathology. If there was a decreased amplitude over one cerebral hemisphere, a subdural haematoma was strongly suspected. Today, with the availability and routine use of detailed imaging techniques such as CT and MRI, the EEG no longer plays this role, although it still has a central place in the diagnosis and management of patients with seizures, epilepsy and altered mental status, and of course it plays an important role in the diagnosis and research of sleep disorders.

The electroencephalogram is recorded by placing electrodes on the scalp. It is a complex electrical signal resulting from postsynaptic potentials of cortical pyramidal cells. The EEG is an indispensable and useful tool that is in essence indicative of brain state (for example waking, sleep, seizure) with specific state dependent features. During sleep, the EEG is recorded for periods of up to eight to 10 hours. For research and diagnostic purposes, sleep EEG is still scored and inspected manually, crucial aspects of the signal might not be recognised by visual inspection, and aggregated or holistic analysis is not objectively possible. Additional quantitative and mathematical analyses permit and uncover more detailed investigation of the sleep EEG.

Berger and Dietsch performed the first fast fourier transformation (FFT) of short EEG segments in 1932, their calculation took weeks to complete. Dietsch enlarged EEG curves and then manually measured the data points and calculated the harmonic elements using mathematical tables. Some brain waves, such as alpha activity (encompassing frequencies between eight and 12 Hz) in the resting EEG during relaxed wakefulness and sleep spindles in the non-REM sleep EEG are rhythmic.

Spectral analysis, which decomposes a signal into its constituent frequency components, is an important method to investigate brain activity. Sleep is typified by the phasic movement through stages that are typified by alterations in EEG activity. Through the mathematical transformation of the raw EEG signal, spectral analysis has transformed sleep research.

The result of spectral analysis is the production of power spectra that are easily analysed and graphically represented. Importantly, the use of spectral analysis often produces very subtle differences when used in clinical trials that compare different drugs. Further, the use of spectral analysis is being trialed as a tool for crossspecies validation of sleep signals. This methodology could also be used (once the validation work has been done) to assess the impact of other compounds on neurological function and sleep as assessed by EEG spectral analysis.

Potential Biomarkers

Although it is accepted that the shortand long-term reduction of sleep can lead to several symptoms – collectively known as sleep debt – what is less clear, is whether sleep debt is something that can be measured and quantified to a sufficient level of validation that can be used in clinical research. Salivary amylase has been shown to correlate with sleep debt, and shows promise for developing a biomarker of sleep.

Salivary analysis is increasingly being explored. Not only is the recent literature and interest in amylase as a biomarker of sleep debt exciting to the science, we are also increasingly using saliva in the analysis of drugs and hormones. The presence or absence of cortisol in the saliva, and the timing of excessively high levels in relation to sleep and wakefulness has proved particularly useful in the evaluation of stress and it’s relationship with sleep. Several other compounds are also assessed in the evaluation of sleep in clinical trials, most notably melatonin.

Drug development and clinical research increasingly utilise protein biomarkers in the hope that they will provide insight or short cuts to diagnoses – perhaps one could even suggest that they would become short cuts or heuristics to the longer term challenges that face clinical trials. There is much debate about this, and indeed the challenge that faces the use of any surrogate in clinical trials. There is an inevitable consequence to the use of these markers – oversimplification. Biomarkers, surrogates and all tools that predispose to clinical heuristics need be used with caution and an awareness of the temptation to use the data that they yield outside of context and expert analysis.

The Role of Genetics

As already pointed out, there are no simple ways to assess the degree of sleep loss in individuals. There is large variation in the degree of response to sleep loss. Some individuals are resistant to the effects of sleep deprivation, while others are considerably affected psychologically and physiologically. In sleep deprivation studies carried out on twins, it has been concluded that the behavioural response to sleep loss has high heritability.

Genetic and epigenetic studies are currently being conducted and reported which suggest that drug developers, and those involved with developing tools and interventions that affect sleep, will have to embrace pharmacogenomic biomarkers in clinical development. Naturally the incorporation of genetic assessment into trials brings with it certain complexities, not only in the metrology and validation, but there are ethical issues too. Fortunately, significant progress is being made in this regard, and the inclusion of genetic assessment and the response to sleep therapy is increasingly utilised in sleep research. What remains unclear is what happens when concomitant disease and drug regimes are evaluated with sleep – for example when unravelling the impact and relationships between Parkinson’s disease and sleep.

Current opinion is that information and oxidative stress play a crucial role in the pathophysiology of obstructive sleep apnoea. While it is not the case that airway inflammation is the only factor, it is certainly one of the central processes in sleep apnoea. Quantifying and monitoring this information is not currently part of the current management of the disease. In addition, the use of Redfern analysis as a biomarker of other disorders affected by sleep and alterations in the chronobiology are also being developed as from a research perspective the analysis of breath during sleep remains fairly simple to do. Quantifying and understanding the sensitivity and specificity of the produced compounds and volatile mediators, for example nitric oxide and carbon monoxide, remain an issue.

Conclusion

Sleep is often considered secondary to other conditions such as malnutrition and cancer. Unfortunately, not only do these conditions and their treatment (surgery and so on) alter sleep, but drugs that are totally unrelated to sleep also interfere with sleep patterns. Quantifying the exact nature of these effects is not only becoming increasingly important in the delineation of the safety parameters of drugs, but is also gaining significance in allowing companies to distinguish their compounds from other me-too compounds. For example, efavirenz effects sleep and its competitor nevirapine does not.

As with other areas of clinical development, the necessity to speed development and reduce costs has meant that innovative methods are sought to solve these problems. Parallel developments that also address these issues as a secondary effect to the original intention of improving techniques, have meant that they have been slow to gain traction amongst regulators. Novel statistical methods such as adaptive design are a good example of where this has occurred.

Academic and commercial sleep research centres are expanding the range of physiological, electrophysiological and other techniques used in the development of new and existing drugs in clinical trials. These newer techniques can be used to unpack the subtle safety issues and impact some drugs intentionally, or unintentionally, have on sleep.

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Hubert Bland is an experienced clinician and pharmaceutical physician. He has acted as medical expert for the discovery of a number of new chemical entities, developed several new indications for existing compounds and worked on several hundred clinical trials. He is currently Chief Medical Officer at the University of Surrey’s Clinical Research Centre, which specialises in early phase studies across a range of indications. He is an Educational Supervisor for the Royal College of Pharmaceutical Medicine, and sits on local and regional ethics and grant review panels. Email: h.bland@surrey.ac.uk
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