Use of functional imaging across clinical phases in CNS drug development

Abstract

The use of novel brain biomarkers using nuclear magnetic resonance imaging holds potential of making central nervous system (CNS) drug development more efficient. By evaluating changes in brain function in the disease state or drug effects on brain function, the technology opens up the possibility of obtaining objective data on drug effects in the living awake brain. By providing objective data, imaging may improve the probability of success of identifying useful drugs to treat CNS diseases across all clinical phases (I-IV) of drug development. The evolution of functional imaging and the promise it holds to contribute to drug development will require the development of standards (including good imaging practice), but, if well integrated into drug development, functional imaging can define markers of CNS penetration, drug dosing and target engagement (even for drugs that are not amenable to positron emission tomography imaging) in phase I; differentiate objective measures of efficacy and side effects and responders vs non-responders in phase II, evaluate differences between placebo and drug in phase III trials and provide insights into disease modification in phase IV trials.

Figure 1

Specific outcomes for magnetic resonance imaging (MRI) imaging in phase I trials. Top: Measures of CNS penetration and brain activation. Bottom: Indirect measures of central nervous system (CNS) dosing. The latter can be evaluated in two ways—either through such modeling of effective increasing doses based on concentrations evolving to Cmax. Further functional MRI (fMRI) studies using different doses can further define effective dosing as defined by activation. Such dosing has been shown to differentiate drug activity. PK, pharmacokinetics.

Figure 2

Imaging healthy subjects vs patient populations in phase I. Functional magnetic resonance imaging evaluation of drug measures using healthy subjects or patients in early phase trials (for example, (‘1a') can provide information on central nervous system (CNS) penetration and dosing). However, the equivalence in the clinical population may not be the same because of numerous factors (disease state, prior drug effects, altered effects on specific circuits and so on). As noted below, the use of healthy subjects and later comparison in patients will further define the utility of early imaging for newly approved Investigational New Drugs. The later parallel and replicated study in patients will confirm or provide data to suggest finessing dosing for later trails.

Figure 3

Magnetic resonance imaging (MRI) measures in phase II. Top: Normalization of circuits has been observed in a few functional MRI studies, consistent with behavioral effects. Middle: Comparative drug effects allows for a number of observations including (1) comparison with best in class; (2) comparison with known mechanism of action type drugs. Bottom: Side-effect profiles may be subclinical or not significant in smaller cohorts but present as potential issues that can be defined in early studies.

Figure 4

Biomarkers and central nervous system (CNS) drug development (modified from Borsook et al.). Imaging biomarkers for specific CNS disease are the focus of a number of research initiatives (Parkinson's disease; Alzheimer's disease; depression; pain^, ). However, with the exception morphometric imaging in Alzheimer's disease, few have yet to be adopted by regulatory agencies. Nevertheless, the Food and Drug Administration's critical pathway initiative has encouraged the development and use of imaging in drug trials through their Alzheimer's Disease Neuroimaging Initiative program (http://www.adni-info.org). Having validated biomarkers of the disease state (imaging or other) will contribute enormously in clinical trials.

Figure 5

Imaging markers of disease course. Many central nervous system diseases have a progressive and/or undulating course that includes partial or complete remission. A clinical study based on subjective criteria cannot adequately (objectively) evaluate drug effect on disease load (how severe or a relative stage of progression of the disease). These are important factors as for the same dose of a drug (as shown in the lower panels) the effect on brain systems may show diminished efficacy based on disease load. Importantly, such efficacy may be enhanced over time as the drug may have effects over time.

Figure 6

Classification of populations based on propensity to respond to types of treatment (drug (D) or placebo (P)). In controlled trials, differentiation of D from P effects can be difficult. Part of the reason for this is that drugs do not provide high degree of efficacy that make this differentiation obvious. As noted above, reasons include three basic outcomes: outcome 1: clear differentiation of D vs P; outcome 2: unclear differentiation of D vs P; and outcome 3: unclear differentiation of lack of efficacy. Taken together, the contribution of outcome 2 in particular, because of lack of effective methods to differentiate D from P, can contribute to a false negative result of the trial.

Figure 7

Differentiation of drug effects vs placebo effects with imaging. An imaging readout can define a drug effect or placebo effect. More difficult is a placebo response where drug and the induced placebo response may be similar because similar pathways are involved (for example, in opioids analgesics). However, differences in responders vs non-responders based on integrating subjective and objective (imaging readouts) can help segregate true drug effects from placebo responses. Patients could be segregated into responders and non-responders according to psychometric criteria. Imaging their response to a drug challenge will further allow the determination of specific changes in brain activation and networks as compared with a placebo arm or to non-responders. It will be expected that non-responders will present a reduced drug effect as well as potential differences in brain networks responses. The inherent difference of responders vs non-responders will also be reflected as difference in brain activity patterns and networks even to a placebo challenge. One of the issues raised in this differentiation is whether drug non-responders are more resistant and thus require increased doses.

Figure 8

Use of imaging in drug development (adapted from Borsook et al.). Imaging can define brain regions involved in symptomatic effects before these become subjectively apparent because of specific circuits activated and their progress to correlative changes with symptoms at a later stage. CNS, central nervous system.

Figure 9

Integrating imaging for central nervous system (CNS)-related clinical trials (modified from Borsook et al.). (1) Phase Ia and imaging—Defining CNS targeting in small groups (<12 subjects); from these studies information on CNS penetration (as evidenced by activation in putative target brain regions); CNS dosing (as determined by correlative measures of plasma PK and CNS effects); and CNS ‘target interactions' as determined by brain regions activated by drug (particularly useful if drug is not amenable to positron emission tomography methods) that may be positive (therapeutic) or negative (side effects). (2) Phase II and imaging—Early insights into efficacy and side effects. Specifically, knowledge of how a drug activates circuits postulated to affect disease; early objective measures of responder vs non-responder; combined with subjective measures decreases the variance and thus fewer subjects needed to adequately power the study; and imaging defined markers of potential side effects (for example, drowsiness, addiction potential, nausea and vomiting, cognitive changes and so on); (3) Phase III and Imaging—Responders vs non-responders can further be differentiated. (4) Phase IV and Imaging—Disease modification. PD, pharmacodynamics; PK, pharmacokinetics; SE, side effects.