Does Imaging Add Value To The Drug Discovery Process

What is the added value of using resource-intense imaging methods in DDD? The obvious expectation is that the use of noninvasive analytical techniques facilitates the translation of the therapeutic concept from preclinical to clinical development and thus might contribute to shortening of DDD times. Convincing as a concept, there is little evidence today that the use of imaging has greatly impacted development. This is likely to change in the future as all major stakeholders have recognized the importance of speeding up DDD as outline in the FDA Critical Path Initiative. Biomarkers and eventually surrogate markers will allow assessing treatment efficacy and safety aspects significantly earlier than classical clinical endpoint measures. Noninvasive imaging will be a key enabling technology in that context as illustrated in the previous section. It is important to realize that the purpose of translational imaging applications in DDD are not large-scale multicenter phase III trials, which pose high demands on standardization of imaging protocols and potentially would be very expensive. Translation imaging studies serve the purpose of establishing pharmacological proof-of-concept in a selected patient population in a small, well-controlled clinical study—critical information for decision makers before entering large-scale clinical evaluation.

Apart from these translational aspects imaging readouts have turned out to provide essential information to the drug developer. The possibility to derive morphological, physiological, metabolic, cellular, and molecular information in a noninvasive manner from an intact organism is highly relevant, in particular when studying chronic degenerative diseases that require longitudinal evaluation. It is therefore not surprising that the majority of imaging applications refers to disease phenotyping; in view of the increasing number of genetically engineered mouse lines available, this application will certainly become even more important. The information gathered during disease phenotyping should be used to stratify treatment groups: prior to therapy administration, patients or animals can be classified into "homogenous" treatment groups, which should translate into data with better statistical relevance.

Imaging is inherently quantitative although translation from primary imaging parameters to biomedical information is not straightforward and constitutes a major challenge for the imaging community. Quantitative readouts are essential for DDD, where the efficacy of various drug candidates have to be compared in relevant animal models of human disease and ultimately in patients (see Section 7.2.1). Noninvasiveness enables to monitor changes longitudinally in comparison to a baseline state, which significantly reduces the intra-individual variability and thereby increases the statistical power of the experiment.

An important advantage of using imaging readouts is the fact that tissue is analyzed in its host environment with all regulatory processes in place. Any artifacts due to tissue collection and processing, for example, for subsequent histological analysis, are therefore largely reduced. For example, tissue collection is invariably linked to a period of global ischemia for a specimen, which will at least transiently affect metabolite levels. Similarly, histological processing of tissue may lead to morphological distortions that will affect any morphometric measurements.

Undisputed imaging applications are those providing information that could not be gained otherwise. In vivo mapping of physiological parameters in a temporospatially resolved manner falls in this category. An illustrative example is functional analysis of the heart. Dynamic cardiac MRI provides cardiac functional parameters such as diastolic and systolic ventricular volumes, stroke volume, and ejection fraction. Moreover, advanced techniques allow analyzing myocardial wall dynamics, wall stress, as well as hemodynamic flow characteristics. The method has been applied to characterize animal models of cardiac hypertrophy and myocardial infarction and to evaluate potential therapeutic interventions. Similarly, imaging-based studies of brain function are of considerable interest for the characterization of CNS disorders and for the evaluation of therapeutic interventions. The functional CNS response can be recorded with a temporal resolution of seconds, which enables correlative studies to identify networks involved in signal processing and alteration of connectivity in a pathological condition or due to drug administration. Complementing receptor occupancy information with evidence of functional activity opens new perspective for the development of CNS drugs.

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