Biomarkers for the development of new medications for cocaine dependence

Abstract

There has been significant progress in personalized drug development. In large part, this has taken place in the oncology field and been due to the ability of researchers/clinicians to discover and develop novel drug development tools (DDTs), such as biomarkers. In cancer treatment research, biomarkers have permitted a more accurate pathophysiological characterization of an individual patient, and have enabled practitioners to target mechanistically the right drug, to the right patient, at the right time. Similar to cancer, patients with substance use disorders (SUDs) present clinically with heterogeneous symptomatology and respond variably to therapeutic interventions. If comparable biomarkers could be identified and developed for SUDs, significant diagnostic and therapeutic advances could be made. In this review, we highlight current opportunities and difficulties pertaining to the identification and development of biomarkers for SUDs. We focus on cocaine dependence as an example. Putative diagnostic, pharmacodynamic (PD), and predictive biomarkers for cocaine dependence are discussed across a range of methodological approaches. A possible cocaine-dependent clinical outcome assessment (COA)--another type of defined DDT--is also discussed. At present, biomarkers for cocaine dependence are in their infancy. Much additional research will be needed to identify, validate, and qualify these putative tools prior to their potential use for medications development and/or application to clinical practice. However, with a large unmet medical need and an estimated market size of several hundred million dollars per year, if developed, biomarkers for cocaine dependence will hold tremendous value to both industry and public health.

Figure 1

Types of biomarkers. Biomarkers are presented hierarchically within the context of the FDA's set of Drug Development Tools (DDTs) (see ‘Introduction' for additional details). Biomarkers are classified into two primary tracts—‘descriptive' and ‘mechanistic'. Descriptive biomarkers are indirect, consequential correlates of the underlying pathophysiological processes. Mechanistic biomarkers represent a direct measure of the pathophysiological underpinnings of the disease process (see also ‘Future Directions'). Mechanistic biomarkers provide a foundation from which other types of biomarkers can be developed and are hence more ‘actionable'. Actionable biomarkers depicted have several possible clinical applications, and these types of biomarkers are hierarchically arranged. Predictive and pharmacodynamic (PD) biomarkers are measures of a therapeutic response (ie, light red box), whereas prognostic, toxic, and diagnostic markers are biological measures alone (ie, dark red box) (see also Text Box). As an example, a prognostic biomarker might provide a prodromal measure enabling physicians an opportunity to identify and medically manage individuals prior to the potential development of a substance use disorder (SUD). Otherwise, optimally, a predictive biomarker could help tailor the right drug to the right patient, at the right time by predicting disease progression (right patient), providing pharmacodynamic (PD) information to facilitate a therapeutic assessment of safety/efficacy (right drug), and predicting which individuals might respond to a particular therapy (right time). Ultimately, it is these biomarkers that are on the mechanistic pathway that will offer the greatest value for enhanced drug development and personalized medicine. Boxes in the left column refer to those methodologies as described within the text; solid lines refer to those approaches with some preliminary associations for a specific type of biomarker (see text); dotted lines refer to theoretical links across the various approaches (boxes). Within the context of the DDTs, the Cocaine Selective Severity Assessment (CSSA) is most appropriately described as an observer- or clinical-reported Clinical Outcome Assessment (COA) (see text). *Although they are one type of FDA-defined DDT, animal models (right column) are not discussed herein and this portion is therefore grayed out.

Figure 2

A heart rate of ⩽60 beats per minute (bpm) was a significant predictor of the inability to achieve ⩾3 weeks of continuous abstinence (p=0.01), and a significant predictor of not achieving 4 weeks of self-reported abstinence at the end of the trial (p=0.003).

Figure 3

Among subjects with the lowest heart rates at the start of treatment, heart rates increased significantly (lower CSSA bradycardia score) after 3–5 days of abstinence verified by a negative urine-drug screen (UDS). Bradycardia acts like a withdrawal sign.

Figure 4

The proportion of subjects with bradycardia (heart rate<60 bpm) and severe bradycardia (heart rate<50 bpm) in cocaine-dependent subjects and matched controls.

Figure 5

The plasma proteome of cocaine withdrawal. The identified protein spots exhibited differential intensity between acute cocaine withdrawal and control groups and are detailed below. Note that the majority of differentially expressed proteins are low abundance compared with the total protein content. (see also Table 3).

Figure 6

Distal vs proximal biomarkers for cocaine dependence.