Drug Discovery Today � Volume 19, Number 3 �March 2014 EDITORIAL

editorial

Alan M. Palmer

The utility ofbiomarkers in CNSdrug development

A biomarker can be defined as a biological variable that has a

statistically significant relationship with parameters of disease

states or the activity of a drug or drug candidate. Biomarkers are

fast becoming an essential part of clinical development, largely

because they: (i) offer the prospect of more homogenous patient

populations in clinical trials through patient selection and strati-

fication; (ii) permit assessment of target engagement; (iii) allow the

consequences of target engagement to be measured; and (iv)

provide markers of disease modification. In the absence of a

statistically significant relationship with such measures, a biolo-

gical variable should not have the status of ‘biomarker’ but should,

instead, be referred to as ‘biomarker candidate’. Because biomar-

kers can increase the statistical power of clinical trials and predict

drug efficacy more quickly than conventional clinical endpoints,

they hold the potential to substantially accelerate product devel-

opment and increase confidence of demonstrating therapeutic

efficacy in Phase III trials. Since CNS drugs take 35% longer to

complete clinical trials and gain regulatory approval compared to

other new prescription medicines [1], CNS is the therapeutic area

that stands to benefit most from the effective application of

biomarkers in the clinical development process.

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For most disorders, biomarker measurements derive from the

determination of a biological variable in blood samples, but,

because of the existence of the blood–CNS barrier, this is not true

for CNS disorders. The blood–CNS barrier (BCNSB) comprises the

blood–brain barrier, the blood–spinal cord barrier and the blood–

CSF barrier. Together they separate the bloodstream and the CNS

and, thus, largely undermine the use of blood biomarkers for CNS

disorders [2]. Examples of the utility of biomarkers in the devel-

opment of CNS drug candidates are described below.

i. Patient selection and stratification

CNS disorders have traditionally been classified on the basis of

the clinico-pathological phenotype and a priori consensus

criteria. However, this approach may, weaken the power to

detect therapeutic efficacy in Phase II/III studies, since a

particular disease phenotype may result from different

pathophysiological mechanisms.

A CNS disorder where biomarkers play a critical role in patient

selection and stratification is multiple sclerosis (MS). Relap-

sing-remitting MS (RRMS) is the most common form of this

disease. It eventually converts to secondary progressive MS

(SPMS), which has a remission-free progression. The course of

another form of the disease, primary progressive MS (PPMS), is

entirely devoid of remissions. The immunomodulatory drugs

approved to treat MS are only efficacious in the treatment of

RRMS, so it is important to exclude people with SPMS and

PPMS from such studies. Magnetic resonance imaging (MRI) is

essential to this process, particularly when used in combina-

tion with contrast agents, such as gadolinium, which permits

new MS plaques (areas of demyelination) to be quantified.

MRI also plays a key role in the identification of prodromal

MS, termed clinically isolated syndrome (CIS). First-line

therapies (interferon-b drugs and glatirimer acetate) delay

the conversion from CIS to clinically definite MS, which

makes CIS an attractive target for disease-modifying medi-

cines [3].

An example of selecting patients most likely to respond to

pharmacotherapy is seen with the use of perfusion (PWI) and

diffusion-weighted MRI (DWI) in clinical trials of stroke. A

mismatch of PWI and DWI lesion volumes indicates those

patients most likely to respond to treatment with thrombo-

lytic or neuroprotective drugs [4]. Patient stratification on this

2013.11.016 www.drugdiscoverytoday.com 201

EDITORIAL Drug Discovery Today �Volume 19, Number 3 �March 2014

Edito

rial

basis markedly improves the statistical power of stroke studies

assessing the therapeutic efficacy of drug candidates. Another

example is the use of positron emission tomography (PET)

amyloid-b (Ab) imaging to distinguish between Alzheimer’s

disease (AD), which is characterised by Ab deposition, and

fronto-temporal dementia, which is not associated with Ab

deposition [5]. Patient stratification can also improve the

safety profile of a drug or drug candidate. An example is seen

in the treatment of stroke with intravenous recombinant

tissue plasminogen activator. Such treatment increases the

risk of intracranial haemorrhage (ICH) and this risk is

substantially diminished by the use of MRI or computerised

tomography to exclude patients with symptomatic ICH [6].

An increasingly powerful approach to improve patient

homogeneity in clinical trials is the selection of patients on

the basis of their genotype. For example, various mutations in

the amyloid protein precursor and presenilin genes cause

early onset autosomal AD, which forms the cornerstone of the

amyloid hypothesis of AD. A critical prediction of this

hypothesis is that drugs that reduce Ab concentrations in

the brains of people with AD will slow the progression of AD.

However, despite a large number of drug candidates, no such

disease-modifying medicine has yet emerged [7]. Because of

this, and in an attempt to improve the chances of clinical

success, a study is now underway with people with inherited

mutations that cause early-onset AD; this study is under the

aegis of the Dominantly Inherited Alzheimer Network.

ii. Target engagement

The direct measurement of the engagement of a CNS drug

candidate with its molecular target is an essential step in CNS

medicines research. PET and single-photon emission com-

puted tomography (SPECT) are non-invasive imaging tech-

niques that can provide valuable target engagement

information (particularly for receptors), provided a suitable

radioligand is available. Although SPECT has certain advan-

tages (such as the long half-lives of the radionuclides used), its

use is constrained by poor spatial and temporal resolution,

along with limited labelling possibilities. PET provides a

superior method for conducting drug occupancy studies. It

uses ligands containing short-lived positron emitting isotopes

(15O, 11C, 18F, 76Br), that necessitate a local cyclotron, to

determine receptor occupancy of a variety of different ligands

[8]. The extent of target engagement also provides important

information regarding both therapeutic efficacy and side-

effect liability. For instance, in the imaging of striatal

dopamine D2 receptors in patients with schizophrenia using

[11C]raclopride PET, ascending doses of up to 80% receptor

occupancy were progressively more effective in relieving

delusions and hallucinations, whereas doses above an 80%

occupancy were not associated with therapeutic benefit, only

an increase in extrapyramidal side effects [9]. Biochemical

measurements in CSF can also be used to establish target

engagement. For example, changes in CSF concentrations of

Ab following administration of drug candidates that act to

reduce Ab concentration in the brains of AD patients [10].

iii. Pharmacodynamics

Several techniques can be used to indirectly measure the effect

of CNS drugs or drug candidates on the intact brain in both

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healthy volunteers and patients. These include pharmacolo-

gic electroencephalography (phEEG) and pharmacologic MRI

(phMRI). EEG uses scalp electrodes to measure electrical brain

activity generated by coherent inhibitory and excitatory

postsynaptic potentials, principally from cortical pyramidal

cells. EEG rhythmic activity is categorised in distinct

frequency bands (denoted delta, theta, alpha, beta and

gamma), which can be quantitatively measured following

the administration of CNS drugs or drug candidates to provide

a pharmacodynamic readout [11]. For phMRI, it is the blood

oxygenation level dependence that is the main approach used

to measure brain activity through functional MRI. It provides

a good, albeit indirect, measure of pharmacologically induced

changes in neuronal activity and so holds much promise as a

useful pharmacodynamic read-out in clinical trials, particu-

larly for drugs and drug candidates that are not amenable to

PET imaging [12]. Both phEEG and phMRI, along with

measures of cognition and behaviour, can provide proof of

mechanistic action and detect early signs of neuropsychiatric

adverse effects. Therefore, such biomarkers provide early

indicators of efficacy or adverse events or both in Phase I and II

studies [11–13].

iv. Disease modification

The term ‘disease modifying drug’ (DMD) arose from the use

of immunosuppressive medicines that changed the degen-

erative course of rheumatoid arthritis [14]. A biomarker of

disease modification should have a validated causal relation-

ship with a disease mechanism. In the treatment of MS,

interferon-b drugs and glatiramer acetate were termed DMDs

on the basis of reducing the number of relapses, with MRI

measurement of white matter lesions used as a secondary

outcome measure of disease modification. Because of this,

MRI is often used as a primary endpoint in proof of concept

clinical trials and as a surrogate endpoint in Phase III MS trials.

Apart from immunomodulatory drugs for the treatment of MS

and thrombolytic drugs for ischaemic stroke, there are no

DMDs that modify the course of CNS disorders. Nonetheless,

biomarker candidates do exist to monitor the progressive loss

of pyramidal cells from the cerebral cortex and dopaminergic

nerve terminals in the neostriatum in AD and Parkinson’s

disease, respectively [7,15,16].

A recent analysis of R&D productivity highlighted the need for

improvements in understanding the fundamental pharmacoki-

netic and pharmacodynamic principles of exposure at the site

of action, target engagement and the expression of functional

pharmacological activity [17]. This is more complicated for CNS

R&D because the blood and CNS compartments are separated by

the BCNSB [2]. Thus, pharmacokinetic and pharmacodynamic

measures in blood are unlikely to reliably reflect changes in the

CNS. Therefore, additional approaches need to be utilised. The

most powerful of these is neuroimaging, which can be applied to

the intact human brain. It delivers biomarkers to: (i) improve the

homogeneity of patient population in clinical trials, (ii) establish

target engagement, (iii) measure the pharmacodynamic action of

CNS drug candidates, and (iv) monitor pharmacologically induced

changes in disease progression. These can be expected to improve

the chances of CNS drug candidates surviving and succeeding in

clinical trials.

Drug Discovery Today � Volume 19, Number 3 �March 2014 EDITORIAL

Editorial

Appendix A. Supplementary dataSupplementary material related to this article can be found, in the

online version, at http://dx.doi.org/10.1016/j.drudis.2013.11.016.

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Alan M. PalmerCerebroscience Ltd, 145-157 St John Street,London EC1V 4PW, UKemail: alan.palmer@cerebroscience.com

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