Biomarkers in drug discovery and development: from target identification through drug marketing

Biomarker sensing platforms based on fluorescent metal nanoclusters

Metal nanoclusters (NCs) and their unique properties are increasing in importance and their applications are covering a wide range of areas. Their remarkable fluorescence properties and easy synthesis procedure and the possibility of functionalizing them for the detection of specific targets, such as biomarkers, make them a very interesting biosensing tool. Nowadays the detection of biomarkers related to different diseases is critical. In this context, NCs scaffolded within an appropriate molecule can be used to detect and quantify biomarkers through specific interactions and fluorescence properties of the NCs. These methods include analytical detection and biolocalization using imaging techniques. This review covers a selection of recent strategies to detect biomarkers related to diverse diseases (from infectious, inflammatory, or tumour origin) using fluorescent nanoclusters.

Meta-analysis of global and high throughput public gene array data for robust vascular gene expression discovery in chronic rhinosinusitis: Implications in controlled release

BACKGROUND

Chronic inflammation is known to cause alterations in vascular homeostasis that directly affects blood vessel morphogenesis, angiogenesis, and tissue permeability. These phenomena have been investigated and exploited for targeted drug delivery applications in the context of cancers and other disease processes. Vascular pathophysiology and its associated genes and signaling pathways, however, have not been systematically investigated in patients with chronic rhinosinusitis (CRS). Understanding the interplay between key vascular signaling pathways and top biomarkers associated with CRS may facilitate the development of new targeted delivery strategies and treatment paradigms. Herein, we report findings from a gene meta-analysis to identify key vascular pathways and top genes involved in CRS.

METHODS

Proprietary software (Illumina BaseSpace Correlation Engine) and open-access data sets were used to perform a gene meta-analysis to systematically determine significant differences between key vascular biomarkers and vascular signaling pathways expressed in sinonasal tissue biopsies of controls and patients with CRS.

RESULTS

Thirteen studies were initially identified, and then reduced to five after applying exclusion principle algorithms. Genes associated with vasculature development and blood vessel morphogenesis signaling pathways were identified to be overexpressed among the top 15 signaling pathways. Out of many significantly upregulated genes, the levels of pro angiogenic genes such as early growth response (EGR3), platelet endothelial cell adhesion molecule (PECAM1) and L-selectin (SELL) were particularly significant in patients with CRS compared to controls.

DISCUSSION

Key vascular biomarkers and signaling pathways were significantly overexpressed in patients with CRS compared to controls, suggesting a contribution of vascular dysfunction in CRS pathophysiology. Vascular dysregulation and permeability may afford opportunities to develop drug delivery systems to improve efficacy and reduce toxicity of CRS treatment.

Determination of sialic acid levels by using surface-enhanced Raman spectroscopy in periodontitis and gingivitis

OBJECTIVES

To compare the sialic acid (SA) levels in saliva among periodontitis-affected, gingivitis and control patients.

METHODS

The study involved 93 subjects. The participants were divided into three groups: (1) 30 subjects without periodontal disease (control group); (2) 30 subjects with gingivitis; and (3) 33 subjects with periodontitis. The oral parameters examined were as follows: (a) Simplified Oral Hygiene Index; (b) Calculus Index; (c) Gingival Index; (d) probing pocket depth; and (e) level of epithelial attachment. SA levels in saliva were measured by means of surface-enhanced Raman spectroscopy (SERS). This method has demonstrated the capacity to detect extremely low concentrations of molecules. The spectrum was calibrated using analytical reagent SA.

RESULTS

The obtained median values for SA concentrations were 5.98, 7.32, and 17.12 mg/dl for control, gingivitis, and periodontitis patients, respectively.

CONCLUSIONS

Our measurements by SERS corroborate that in periodontitis-affected patients, the SA concentration is larger than their concentrations in either control or gingivitis patients. This confirms previous reports and opens the possibility of using SERS as a diagnostic tool.

Autologous Hematopoietic Stem Cell Transplantation for Autoimmune Diseases: From Mechanistic Insights to Biomarkers

Phase I/II clinical trials of autologous hematopoietic stem cell transplantation (AHSCT) have led to increased safety and efficacy of this therapy for severe and refractory autoimmune diseases (AD). Recent phase III randomized studies have demonstrated that AHSCT induces long-term disease remission in most patients without any further immunosuppression, with superior efficacy when compared to conventional treatments. Immune monitoring studies have revealed the regeneration of a self-tolerant T and B cell repertoire, enhancement of immune regulatory mechanisms, and changes toward an anti-inflammatory milieu in patients that are responsive to AHSCT. However, some patients reactivate the disease after transplantation due to reasons not yet completely understood. This scenario emphasizes that additional specific immunological interventions are still required to improve or sustain therapeutic efficacy of AHSCT in patients with AD. Here, we critically review the current knowledge about the operating immune mechanisms or established mechanistic biomarkers of AHSCT for AD. In addition, we suggest recommendations for future immune monitoring studies and biobanking to allow discovery and development of biomarkers. In our view, AHSCT for AD has entered a new era and researchers of this field should work to identify robust predictive, prognostic, treatment-response biomarkers and to establish new guidelines for immune monitoring studies and combined therapeutic interventions to further improve the AHSCT protocols and their therapeutic efficacy.

A Bayesian model to estimate the cutoff and the clinical utility of a biomarker assay

To enable targeted therapies and enhance medical decision-making, biomarkers are increasingly used as screening and diagnostic tests. When using quantitative biomarkers for classification purposes, this often implies that an appropriate cutoff for the biomarker has to be determined and its clinical utility must be assessed. In the context of drug development, it is of interest how the probability of response changes with increasing values of the biomarker. Unlike sensitivity and specificity, predictive values are functions of the accuracy of the test, depend on the prevalence of the disease and therefore are a useful tool in this setting. In this paper, we propose a Bayesian method to not only estimate the cutoff value using the negative and positive predictive values, but also estimate the uncertainty around this estimate. Using Bayesian inference allows us to incorporate prior information, and obtain posterior estimates and credible intervals for the cut-off and associated predictive values. The performance of the Bayesian approach is compared with alternative methods via simulation studies of bias, interval coverage and width and illustrations on real data with binary and time-to-event outcomes are provided.

Current practices and future outlook on the integration of biomarkers in the drug development process

Over the last decade, there has been broad incorporation of translational biomarkers into the early drug development process to predict safety concerns, measure target engagement and monitor disease progression. One goal of translational biomarkers is to create a cycle whereby preclinical readouts influence candidate selection and subsequent clinical data are fed back into research to facilitate better decision making. Successes have been limited and not as broad in scope as desired. Collaborations between industry and regulators have increased the number of qualified biomarkers; but the process is lengthy and expensive. A high level overview of translational biomarkers as well as a discussion of some of the successes and failures encountered in development is discussed here.

Live-single-cell phenotypic cancer biomarkers-future role in precision oncology?

The promise of precision and personalized medicine is rooted in accurate, highly sensitive, and specific disease biomarkers. This is particularly true for cancer-a disease characterized by marked tumor heterogeneity and diverse molecular signatures. Although thousands of biomarkers have been described, only a very small number have been successfully translated into clinical use. Undoubtedly, there is need for rapid, quantitative, and more cost effective biomarkers for tumor diagnosis and prognosis, to allow for better risk stratification and aid clinicians in making personalized treatment decisions. This is particularly true for cancers where specific biomarkers are either not available (e.g., renal cell carcinoma) or where current biomarkers tend to classify individuals into broad risk categories unable to accurately assess individual tumor aggressiveness and adverse pathology potential (e.g., prostate cancer), thereby leading to problems of over-diagnosis and over-treatment of indolent cancer and under-treatment of aggressive cancer. This perspective highlights an emerging class of cancer biomarkers-live-single-cell phenotypic biomarkers, as compared to genomic biomarkers, and their potential application for cancer diagnosis, risk-stratification, and prognosis.

Pharmacokinetics and Pharmacodynamics in Breast Cancer Animal Models

The study of pharmacokinetics (PK) and pharmacodynamics (PD) in cancer drug discovery and development is often paired and described in reciprocal terms, where PK is the analysis of the change in drug concentration with time and PD is the analysis of the biological effects of the drug at various concentrations over different time courses. While PK is defined by how a compound is absorbed, distributed, metabolized, and eliminated, PD refers to the measure of a compound's ability to interact with its intended target, leading to a biologic effect. Recent advances in anti-breast cancer drug discovery have resulted in several new drugs, but there is still a high attrition rate during clinical development. One reason for this failure is attributed to inappropriate correlation between the PK and PD parameters and subsequent extrapolation to human subjects. In this chapter, we describe the protocols of PK and PD studies in breast cancer models to assess the efficacy of an anti-breast cancer compound, noting the types and endpoints employed, and explain why it is important to link PK and PD in order to establish and evaluate dose/concentration-response relationships and subsequently describe and predict the effect-time courses for a given drug dose.

The Demonstration of Immunohistochemical Biomarkers in Methyl Methacrylate-Embedded Plucked Human Hair Follicles

Plucked human hair follicles have been proposed as a potential surrogate for tumour tissue for measuring the effect of drugs on pharmacodynamic biomarkers in drug intervention studies. We describe a new technique of embedding plucked hair follicles in the acrylic resin, methyl methacrylate, and the immunohistochemical demonstration of six potential biomarkers (Ki67, EGFR, phospho-p27, phospho-histone H3, phospho-MAPK and phospho-Rb) in de-plasticised sections. The advantages of this technique over those that have been used in support of clinical drug trials, such as skin and tumour biopsies, whole blood and whole hair samples is discussed.

When close is not close enough: a comparison of endogenous and recombinant biomarker stability samples

Dr Stephanie Fraser is an Associate Research Fellow in the Pharmocokinetics, Dynamics and Metabolism department at Pfizer, Groton, Connecticut. Since 2010 she has led a small but ambitious group of scientists that provide ligand-binding and immunoassay-based support to clinical biomarker programs across multiple therapeutic areas. Prior to joining Pfizer, Stephanie spent 5 years in preclinical toxicology at Charles River Laboratories where she managed a flow cytometry laboratory. She received her PhD in cellular and molecular biology from the University of Nevada, Reno in 1999 and has since focused on biomarker development and fit-for-purpose bioanalytical assays.

Stability for biomarkerassays should be established during method validation using actual samples. Due to contradictory reference papers and a near absence of biomarker guidance documents actual samples are commonly replaced with spiked validation samples. This practice often fails to identify the stability of the endogenous biomarker. Spiked QC and endogenous biomarker sample data were collected for two immunoassays, TGF- β1 and IL-13. Following one freeze/thaw cycle purified TGF-β1 recovery ranged between 87-110% whereas endogenous TGF-β1 was 5-96%. Spiked recombinant IL-13 validation samples were stable for 4 months, whereas placebo samples were stable for 15 months. In these two cases stability established with purified and recombinant protein did not reflect the endogenous protein stability.

Estimation of salivary and serum total sialic Acid levels in periodontal health and disease

BACKGROUND

Chronic gingivitis and periodontitis are inflammatory diseases. An important function of host sialic acid is to regulate innate immunity. The aim of the study was to assess the concentration of Total sialic acid (TSA) in saliva and serum and also to find out their association if any, in periodontal health and disease.

MATERIALS AND METHODS

A total of 90 subjects were clinically examined and distributed into three groups (n=30) according to the periodontal status namely healthy, chronic gingivitis and chronic periodontitis.Clinical measurements including probing depth, clinical attachment level, gingival index, oral hygeine index were recorded .TSA concentration was determined in saliva and serum of all subjects.

RESULTS

In healthy group the mean salivary TSA level was 39.05mg/dl ±6.35(p<0.0001), mean serum TSA level was 49.75 mg/dl ± 4.87 (p<0.0001). In the chronic gingivitis group the mean salivary TSA level was 68.23 mg/dl ± 2.71 (p<0.0001), mean serum TSA level was 65.65 mg/dl ±3.56 (p<0.0001). In the chronic periodontitis group the mean salivary TSA was 81.33 mg/dl ±3.94 (p<0.0001), mean serum TSA level was 75.98 mg/dl ±3.58 (p<0.0001).

CONCLUSION

The present data indicates that salivary & serum TSA levels can differentiate between chronic periodontitis patients and normal individuals. Thus it can be used as an adjunct to diagnose, monitor response to therapy, to determine the current periodontal disease status and to assess the treatment outcomes.

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

Characterizing the relationship between the pharmacokinetics (PK, concentration vs. time) and pharmacodynamics (PD, effect vs. time) is an important tool in the discovery and development of new drugs in the pharmaceutical industry. The purpose of this publication is to serve as a guide for drug discovery scientists toward optimal design and conduct of PK/PD studies in the research phase. This review is a result of the collaborative efforts of DMPK scientists from various Metabolism and Pharmacokinetic (MAP) departments of the global organization Novartis Institute of Biomedical Research (NIBR). We recommend that PK/PD strategies be implemented in early research phases of drug discovery projects to enable successful transition to drug development. Effective PK/PD study design, analysis, and interpretation can help scientists elucidate the relationship between PK and PD, understand the mechanism of drug action, and identify PK properties for further improvement and optimal compound design. Additionally, PK/PD modeling can help increase the translation of in vitro compound potency to the in vivo setting, reduce the number of in vivo animal studies, and improve translation of findings from preclinical species into the clinical setting. This review focuses on three important elements of successful PK/PD studies, namely partnership among key scientists involved in the study execution; parameters that influence study designs; and data analysis and interpretation. Specific examples and case studies are highlighted to help demonstrate key points for consideration. The intent is to provide a broad PK/PD foundation for colleagues in the pharmaceutical industry and serve as a tool to promote appropriate discussions on early research project teams with key scientists involved in PK/PD studies.

Molecular biomarkers in clinical development: what could we learn from the clinical trial registry?

Aim: Objective of this research is to assess whether the trend of stratified medicine widely discussed in scientific literature is translated into real clinical trials registered in ClinicalTrials.gov . Methods: By semi-automatic screening of over 150,000 trials, we filtered trials with stratified biomarker to analyze their therapeutic focus, major drivers and elucidated the impact of stratified biomarker programs on trial duration and completion. Results: >5% of trials are using molecular biomarker for stratification; duration of such trials is longer. 21% of them are done in late stages and Oncology is the major focus. Conclusion: Trials with stratified biomarker in drug development has quadrupled in last decade but represents a small part of all interventional trials reflecting multiple co-developmental challenges of therapeutic compounds and companion diagnostics.

Nitrite and nitrate levels of gingival crevicular fluid and saliva in subjects with gingivitis and chronic periodontitis

OBJECTIVES

Nitrosative stress plays an essential role in the pathogenesis of periodontal disease. The aim of this study is to analyze the gingival crevicular fluid and saliva nitrite and nitrate levels in periodontally healthy and diseased sites.

MATERIAL AND METHODS

A total of 60 individuals including, 20 chronic periodontitis and 20 gingivitis patients and 20 periodontally healthy controls participated in the present study. Probing depth, clinical attachment level, bleeding on probing, gingival index and plaque index were assessed, gingival crevicular fluid (GCF) and saliva samples were obtained from the subjects, including 480 GCF samples and 60 unstimulated whole saliva samples. Nitrite and nitrate were analyzed by Griess reagent.

RESULTS

Total GCF nitrite levels were higher in gingivitis and periodontitis groups (1.07 [SD 0.62] nmol and 1.08 [SD 0.59] nmol) than the control group (0.83 [SD 0.31] nmol) (P < 0.05) but did not differ significantly between gingivitis and periodontitis groups (P > 0.05). The difference in GCF nitrate level was not significant among the control, gingivitis and periodontitis groups (7.7 [SD 2.71] nmol, 7.51 [SD 4.16] nmol and 7.38 [SD 1.91] nmol). Saliva nitrite and nitrate levels did not differ significantly among three study groups. Saliva nitrate/nitrite ratios were higher in periodontitis and gingivitis groups than the control group. A gradual decrease in nitrate/nitrite ratio in GCF was detected with the presence of inflammation.

CONCLUSIONS

It may be suggested that nitrite in gingival crevicular fluid is a better periodontal disease marker than nitrate and may be used as an early detection marker of periodontal inflammation, and that local nitrosative stress markers don't show significant difference between the initial and advanced stages of periodontal disease.

Kinase selectivity profiling by inhibitor affinity chromatography

As new drugs rapidly advance into clinical trials, comprehensive identification of their intracellular targets becomes fundamental for the full understanding of the molecular basis of their efficacy and toxicity. This is particularly important when the targets belong to a large family and the inhibitors recognize a conserved site among different members of the class. A typical example is the kinase family, where efforts are aimed at the development of inhibitors of distinct kinases for therapeutic applications in oncology, inflammation and other disease areas. In this case, inhibitors targeting the ATP pocket may cross react with different kinases, as well as with other proteins that bind ATP. This review critically discusses the available approaches for kinase selectivity profiling. It also reviews some examples of inhibitor affinity chromatography applied to inhibitors of kinases and other protein families as a tool to identify and characterize their intracellular targets.

Companion biomarkers: paving the pathway to personalized treatment for cancer

BACKGROUND

Companion biomarkers are biomarkers that are used in combination with specific therapies and that prospectively help predict likely response or severe toxicity. In this article we review the role of companion biomarkers in guiding treatment in patients with cancer.

CONTENT

In addition to the established companion biomarkers such as estrogen receptors and HER2 (human epidermal growth factor receptor 2) in breast cancer, several new companion biomarkers have become available in recent years. These include v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations for the selection of patients with advanced colorectal cancer who are unlikely to benefit from anti-epidermal growth factor receptor antibodies (cetuximab or panitumumab), epidermal growth factor receptor (EGFR) mutations for selecting patients with advanced non-small cell lung cancer (NSCLC) for treatment with tyrosine kinase inhibitors (gefitinib or erlotinib), v-raf murine sarcoma viral oncogene homolog B1 (BRAF) mutations for selecting patients with advanced melanoma for treatment with anti-BRAF agents (vemurafenib and dabrafenib), and anaplastic lymphoma receptor tyrosine kinase (ALK) translocations for identifying patients with NSCLC likely to benefit from crizotinib.

SUMMARY

The availability of companion biomarkers should improve drug efficacy, decrease toxicity, and lead to a more individualized approach to cancer treatment.

Microvesicles/exosomes as potential novel biomarkers of metabolic diseases

Biomarkers are of tremendous importance for the prediction, diagnosis, and observation of the therapeutic success of common complex multifactorial metabolic diseases, such as type II diabetes and obesity. However, the predictive power of the traditional biomarkers used (eg, plasma metabolites and cytokines, body parameters) is apparently not sufficient for reliable monitoring of stage-dependent pathogenesis starting with the healthy state via its initiation and development to the established disease and further progression to late clinical outcomes. Moreover, the elucidation of putative considerable differences in the underlying pathogenetic pathways (eg, related to cellular/tissue origin, epigenetic and environmental effects) within the patient population and, consequently, the differentiation between individual options for disease prevention and therapy - hallmarks of personalized medicine - plays only a minor role in the traditional biomarker concept of metabolic diseases. In contrast, multidimensional and interdependent patterns of genetic, epigenetic, and phenotypic markers presumably will add a novel quality to predictive values, provided they can be followed routinely along the complete individual disease pathway with sufficient precision. These requirements may be fulfilled by small membrane vesicles, which are so-called exosomes and microvesicles (EMVs) that are released via two distinct molecular mechanisms from a wide variety of tissue and blood cells into the circulation in response to normal and stress/pathogenic conditions and are equipped with a multitude of transmembrane, soluble and glycosylphosphatidylinositol-anchored proteins, mRNAs, and microRNAs. Based on the currently available data, EMVs seem to reflect the diverse functional and dysfunctional states of the releasing cells and tissues along the complete individual pathogenetic pathways underlying metabolic diseases. A critical step in further validation of EMVs as biomarkers will rely on the identification of unequivocal correlations between critical disease states and specific EMV signatures, which in future may be determined in rapid and convenient fashion using nanoparticle-driven biosensors.

Case studies from the use of commercial biomarker/protein test kits

Large-molecule drugs (therapeutic proteins, peptides, various forms of antibodies) are more frequently being seen in drug-development pipelines, the majority of which are measured using immunochemical/ligand-binding techniques. The assays utilized for analysis of large-molecule drugs rely heavily upon the quality of the components (e.g., reference materials, antibodies) that are critical to the performance of the assays. Commercially available research-grade materials and kits offer a convenient and simple solution, but also present some unique challenges. This article will explore some examples of issues encountered while employing commercially available kits and reagents.

Gene expression profiling and its practice in drug development

The availability of sequenced genomes of human and many experimental animals necessitated the development of new technologies and powerful computational tools that are capable of exploiting these genomic data and ask intriguing questions about complex nature of biological processes. This gave impetus for developing whole genome approaches that can produce functional information of genes in the form of expression profiles and unscramble the relationships between variation in gene expression and the resulting physiological outcome. These profiles represent genetic fingerprints or catalogue of genes that characterize the cell or tissue being studied and provide a basis from which to begin an investigation of the underlying biology. Among the most powerful and versatile tools are high-density DNA microarrays to analyze the expression patterns of large numbers of genes across different tissues or within the same tissue under a variety of experimental conditions or even between species. The wide spread use of microarray technologies is generating large sets of data that is stimulating the development of better analytical tools so that functions can be predicted for novel genes. In this review, the authors discuss how these profiles are being used at various stages of the drug discovery process and help in the identification of new drug targets, predict the function of novel genes, and understand individual variability in response to drugs.

Functional biomarkers for the acute effects of alcohol on the central nervous system in healthy volunteers

The central nervous system (CNS) effects of acute alcohol administration have been frequently assessed. Such studies often use a wide range of methods to study each of these effects. Unfortunately, the sensitivity of these tests has not completely been ascertained. A literature search was performed to recognize the most useful tests (or biomarkers) for identifying the acute CNS effects of alcohol in healthy volunteers. All tests were grouped in clusters and functional domains. Afterwards, the effect of alcohol administration on these tests was scored as improvement, impairment or as no effect. Furthermore, dose-response relationships were established. A total number of 218 studies, describing 342 different tests (or test variants) were evaluated. Alcohol affected a wide range of CNS domains. Divided attention, focused attention, visuo-motor control and scales of feeling high and of subjective drug effects were identified as the most sensitive functional biomarkers for the acute CNS effects of alcohol. The large number of CNS tests that are used to determine the effects of alcohol interferes with the identification of the most sensitive ones and of drug-response relationships. Our results may be helpful in selecting rational biomarkers for studies investigating the acute CNS effects of alcohol or for future alcohol- interaction studies.

Modelling and simulation as research tools in paediatric drug development

Purpose

Although practical and ethical constraints impose special requirements for the evaluation of treatment safety and efficacy in children, the main issue remains the empirical basis for patient stratification and dose selection at the early stage of the development of new chemical and biological entities. The aim of this review is to highlight the advantages and limitations of modelling and simulation (M&S) in supporting decision making during paediatric drug development.

Methods

A literature search on Pubmed’s database Medical Subject Headings (MeSH) has been performed to retrieve relevant publications on the use of model-based approaches in paediatric drug development and therapeutics.

Results

M&S enable the assessment of the impact of different regimens as well as of different populations on a drug’s safety and efficacy profile. It has been widely used in the last two decades to support pre-clinical and early clinical drug development. In fact, M&S have been applied to drug development as decision tools, as study optimization tools and as data analysis tools. In particular, this approach can be used to support dose adjustment in specific subgroups of a population. M&S may therefore allow the individualisation of drug therapy in children, improving the risk–benefit ratio in this population.

Conclusions

The lack of consensus on how to assess the impact of developmental factors on pharmacokinetics, pharmacodynamics, efficacy and safety has so far prevented a broader use of M&S. This problem is compounded by the limited collaboration between stakeholders, which prevents data sharing in this field. In this article, we emphasise the need for a concerted effort to promote the effective use of this technology in paediatric drug development and avoid unnecessary exposure of children to clinical trials.

Microfluidics using spatially defined arrays of droplets in one, two, and three dimensions

Spatially defined arrays of droplets differ from bulk emulsions in that droplets in arrays can be indexed on the basis of one or more spatial variables to enable identification, monitoring, and addressability of individual droplets. Spatial indexing is critical in experiments with hundreds to millions of unique compartmentalized microscale processes--for example, in applications such as digital measurements of rare events in a large sample, high-throughput time-lapse studies of the contents of individual droplets, and controlled droplet-droplet interactions. This review describes approaches for spatially organizing and manipulating droplets in one-, two-, and three-dimensional structured arrays, including aspiration, laminar flow, droplet traps, the SlipChip, self-assembly, and optical or electrical fields. This review also presents techniques to analyze droplets in arrays and applications of spatially defined arrays, including time-lapse studies of chemical, enzymatic, and cellular processes, as well as further opportunities in chemical, biological, and engineering sciences, including perturbation/response experiments and personal and point-of-care diagnostics.

A novel PET marker for in vivo quantification of myelination

C-11-labeled N-methyl-4,4'-diaminostilbene ([(11)C]MeDAS) was synthesized and evaluated as a novel radiotracer for in vivo microPET imaging of myelination. [(11)C]MeDAS exhibits optimal lipophilicity for brain uptake with a logP(oct) value of 2.25. Both in vitro and ex vivo staining exhibited MeDAS accumulation in myelinated regions such as corpus callosum and striatum. The corpus callosum region visualized by MeDAS is much larger in the hypermyelinated Plp-Akt-DD mouse brain than in the wild-type mouse brain, a pattern that was also consistently observed in Black-Gold or MBP antibody staining. Ex vivo autoradiography demonstrated that [(11)C]MeDAS readily entered the mouse brain and selectively labeled myelinated regions with high specificity. Biodistribution studies showed abundant initial brain uptake of [(11)C]MeDAS with 2.56% injected dose/whole brain at 5 min post injection and prolonged retention in the brain with 1.37% injected dose/whole brain at 60 min post injection. An in vivo pharmacokinetic profile of [(11)C]MeDAS was quantitatively analyzed through a microPET study in an Plp-Akt-DD hypermyelinated mouse model. MicroPET studies showed that [(11)C]MeDAS exhibited a pharmacokinetic profile that readily correlates the radioactivity concentration to the level of myelination in the brain. These studies suggest that MeDAS is a sensitive myelin probe that provides a direct means to detect myelin changes in the brain. Thus, it can be used as a myelin-imaging marker to monitor myelin pathology in vivo.

Transcriptional analysis of an E2F gene signature as a biomarker of activity of the cyclin-dependent kinase inhibitor PHA-793887 in tumor and skin biopsies from a phase I clinical study

A transcriptional signature of the pan-cyclin-dependent kinase (Cdk) inhibitor PHA-793887 was evaluated as a potential pharmacodynamic and/or response biomarker in tumor and skin biopsies from patients treated in a phase I clinical study. We first analyzed the expression of a number of known E2F-dependent genes that were predicted to be modulated after Cdk2 and Cdk4 inhibition in xenograft tumor and skin samples of mice treated with the compound. This panel of 58 selected genes was then analyzed in biopsies from seven patients treated with PHA-793887 in a phase I dose escalation clinical trial in solid tumors. Quantitative real-time PCR or microarray analyses were done in paired skin and tumor biopsies obtained at baseline and at cycle 1. Analysis by quantitative real-time PCR of the signature in skin biopsies of patients treated at three different doses showed significant transcriptional downregulation with a dose-response correlation. These data show that PHA-793887 modulates genes involved in cell cycle regulation and proliferation in a clinical setting. The observed changes are consistent with its mechanism of action and correlate with target modulation in skin and with clinical benefit in tumors.

Morphological, functional and metabolic imaging biomarkers: assessment of vascular-disrupting effect on rodent liver tumours

OBJECTIVES

To evaluate effects of a vascular-disrupting agent on rodent tumour models.

METHODS

Twenty rats with liver rhabdomyosarcomas received ZD6126 intravenously at 20 mg/kg, and 10 vehicle-treated rats were used as controls. Multiple sequences, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) with the microvascular permeability constant (K), were acquired at baseline, 1 h, 24 h and 48 h post-treatment by using 1.5-T MRI. [(18)F]fluorodeoxyglucose micro-positron emission tomography ((18)F-FDG microPET) was acquired pre- and post-treatment. The imaging biomarkers including tumour volume, enhancement ratio, necrosis ratio, apparent diffusion coefficient (ADC) and K from MRI, and maximal standardised uptake value (SUV(max)) from FDG microPET were quantified and correlated with postmortem microangiography and histopathology.

RESULTS

In the ZD6126-treated group, tumours grew slower with higher necrosis ratio at 48 h (P < 0.05), corresponding well to histopathology; tumour K decreased from 1 h until 24 h, and partially recovered at 48 h (P < 0.05), parallel to the evolving enhancement ratios (P < 0.05); ADCs varied with tumour viability and perfusion; and SUV(max) dropped at 24 h (P < 0.01). Relative K of tumour versus liver at 48 h correlated with relative vascular density on microangiography (r = 0.93, P < 0.05).

CONCLUSIONS

The imaging biomarkers allowed morphological, functional and metabolic quantifications of vascular shutdown, necrosis formation and tumour relapse shortly after treatment. A single dose of ZD6126 significantly diminished tumour blood supply and growth until 48 h post-treatment.

Pharmacogenetics of membrane transporters: an update on current approaches

This review provides an overview of the pharmacogenetics of membrane transporters including selected ABC transporters (ABCB1, ABCC1, ABCC2, and ABCG2) and OATPs (OATP1B1 and OATP1B3). Membrane transporters are heavily involved in drug clearance and alters drug disposition by actively transporting substrate drugs between organs and tissues. As such, polymorphisms in the genes encoding these proteins may have significant effects on the absorption, distribution, metabolism and excretion of compounds, and may alter pharmacodynamics of many agents. This review discusses the techniques used to identify substrates and inhibitors of these proteins and subsequently to assess the effect of genetic mutation on transport, both in vitro and in vivo. A comprehensive list of substrates for the major drug transporters is included. Finally, studies linking transporter genotype with clinical outcomes are discussed.

Systematic analytical validation of commercial kits for the determination of novel biomarkers for clinical drug development

The use of biomarkers during clinical drug-development programs may expedite pipeline decision making by adding critical information about the pharmacological mechanism and efficacy of a potential therapeutic agent. Currently, advice for laboratorians conducting method development and analytical validation of biomarker methods is provided by published White Paper recommendations from industry thought leaders. The adaptation of commercial test kits to generate biomarker data to support regulated studies offers unique challenges and limitations. In this perspective, we address these issues, including factors to consider when identifying a kit manufacturer and adapting commercial test kits for use in regulated studies. We offer a logical and systematic approach for defining the extent of analytical validation needed for application of commercial kits based upon the intended use of the biomarker data.

Industrialized MS-based proteomics in the search for circulating biomarkers

Proteomics is the study of the expression, structure and function of proteins under a range of cellular conditions. A rapidly evolving component of this field is clinical proteomics, which focuses on proteins involved in human disease and how they are affected by therapeutic intervention. MS is the main analytical technology for identifying and quantifying proteins whose expression is modulated across the normal to disease continuum. Applying this technology to clinical samples, however, is particularly challenging due to high biological variability in the population, a variety of disease stages, nonuniform response to therapy, multiple concomitant treatments and special requirements for handling samples from clinical trials. Given these challenges, an ‘industrialized’ approach is best suited to clinical biomarker development, with its standard operating procedures, process control and ‘chain of custody’. This review will focus, therefore, on MS-based industrialized proteomics for the discovery and verification of circulating candidate clinical protein biomarkers.

Searching for 'omic' biomarkers

Cardiovascular diseases impose enormous social and economic burdens on both individual citizens and on society as a whole. Clinical indicators such as high blood pressure, blood cholesterol and obesity have had some utility in identifying those who are at increased risk of cardiovascular events. However, there remains an urgent need for sensitive and specific indicators, preferably acquired through minimally invasive means, to help stratify patients for more personalized health care. As such, there has been a steadily growing interest in searching for 'omic' biomarkers of cardiovascular diseases. Historically, the transition of cardiac biomarker discovery to implementation has been a lengthy and somewhat unregulated process. Recent technological advancements, as well as concurrent efforts by regulatory agencies such as the Food and Drug Administration (United States) and Health Canada to establish policies and guidelines in the 'omic' arena, have helped propel the discovery and validation of biomarkers forward. The present paper provides perspective on current strategies in the biomarker development pathway, as well as the potential limitations associated with each step from discovery to clinical uptake. Canadian biomarker studies now underway illustrate the possibilities for assessment of risk, diagnosis, prognosis and response to therapy, and for the drug discovery process.

Biomarkers for the effects of cannabis and THC in healthy volunteers

An increasing number of novel therapeutic agents are targeted at cannabinoid receptors. Drug development programmes of new cannabinoid drugs may be facilitated by the identification of useful biomarkers. This systemic literature review aims to assess the usefulness of direct biomarkers for the effects of cannabis and tetrahydrocannabinol (THC) in healthy volunteers. One hundred and sixty-five useful articles were found that investigated the acute effects of cannabis or THC on the central nervous system (CNS) and heart rate in healthy volunteers. Three hundred and eighteen tests (or test variants) were grouped in test clusters and functional domains, to allow their evaluation as a useful biomarker and to study their dose-response effects. Cannabis/THC affected a wide range of CNS domains. In addition to heart rate, subjective effects were the most reliable biomarkers, showing significant responses to cannabis in almost all studies. Some CNS domains showed indications of depression at lower and stimulation at higher doses. Subjective effects and heart rate are currently the most reliable biomarkers to study the effect of cannabis. Cannabis affects most CNS domains, but too many different CNS tests are used to quantify the drug-response relationships reliably. Test standardization, particularly in motor and memory domains, may reveal additional biomarkers.

Tumor models and specific contrast agents for small animal imaging in oncology

Despite the widespread use of various imaging modalities in clinical and experimental oncology without or with combined application of commercially available nonspecific contrast agents (CAs), development of tissue- or organ- or disease-specific CAs has been a continuing effort for pursuing ever-improved sensitivity, specificity, and applicability. This is particularly true with magnetic resonance imaging (MRI) due to its intrinsic superb spatial/temporal/contrast resolutions and adequate detectability for tiny amount of substances. In this context, research using small animal tumor models has played an indispensible role in preclinical exploration of tissue specific CAs. Emphasizing more on methodological and practical aspects, this article aims to share our cumulated experiences on how to create tumor models for evaluation and development of new tissue specific MRI CAs and how to apply such models in imaging-based research studies. With the results that are repeatedly confirmed by later clinical applications in cancer patients, some of our early preclinical studies have contributed to the designs of subsequent clinical trials on the new CAs, some studies have predicted new utilities of these CAs; and other studies have led to the discoveries of new tissue- or disease-specific CAs with novel diagnostic or even therapeutic potentials. Among commonly adopted tumor models, the chemically induced and surgically implanted nodules in the liver prove very useful to simulate primary and metastatic intrahepatic tumors, respectively in clinical patients. The methods to create tumor models have eased procedures and yielded high success rates. The specific properties of the new CAs could be outshined by intraindividual comparison to the commercial CAs as nonspecific controls. Meticulous imaging-microangiography-histology matching techniques guaranteed colocalization of the lesion on in vivo MRI and postmortem tissue specimen, hence correct imaging interpretation and longstanding conclusions. As exemplified in the real study cases, the present experimental set-up proves applicable in small animals for imaging-based oncological investigations, and may provide a platform for the currently booming molecular imaging in a multimodality environment.

Validation of analytic methods for biomarkers used in drug development

The role of biomarkers in drug discovery and development has gained precedence over the years. As biomarkers become integrated into drug development and clinical trials, quality assurance and, in particular, assay validation become essential with the need to establish standardized guidelines for analytic methods used in biomarker measurements. New biomarkers can revolutionize both the development and use of therapeutics but are contingent on the establishment of a concrete validation process that addresses technology integration and method validation as well as regulatory pathways for efficient biomarker development. This perspective focuses on the general principles of the biomarker validation process with an emphasis on assay validation and the collaborative efforts undertaken by various sectors to promote the standardization of this procedure for efficient biomarker development.

Insights in the application of research-grade diagnostic kits for biomarker assessments in support of clinical drug development: bioanalysis of circulating concentrations of soluble receptor activator of nuclear factor kappaB ligand

Application of research-grade diagnostic kits in clinical drug development has grown commensurate with the increased interest in utilization of biomarkers as drug development tools. Since novel biomarkers are frequently macromolecular, immunoassay methodology comprises the 'technology-of-choice' for biomarker quantification. In particular, commercial research-grade immunoassay kits are appealing for use in biomarker quantification during clinical phase drug development because of their ready availability, ease of operation and perceived convenience. However, bioanalytical validation issues arise often during the application of commercial kits, as GLP regulatory-compliant application places greater demands on kit design and performance. In this review, we have used the receptor activator of nuclear factor kappaB ligand (RANKL) as a model system to offer some insights into the challenges that can be encountered in the application of 'research-grade' diagnostic kits in support of clinical drug development. Currently only a few assays are available commercially for the determination of circulating concentrations of sRANKL. Of these, two immunoassay designs have been most often. The first design employs human osteoprotegerin to capture unbound sRANKL from serum and, thereby, provides a measure of circulating free concentrations. In contrast, the other common assay design first involves preincubation of serum samples with human osteoprotegerin to convert the free fraction of sRANKL to the osteoprotegerin-bound complex. The bound fraction is subsequently captured by an anti-osteoprotegerin antibody. In both immunoassay designs, detection is accomplished with an anti-sRANKL enzyme conjugation system. In this report we review these sRANKL immunoassay designs critically from the perspective of their potential suitability as drug development biomarker tools. In addition, analytical challenges relevant to the application of these 'research-grade' diagnostic kits for regulatory-compliant determination of sRANKL concentrations are discussed.

Pharmacogenetics of membrane transporters: a review of current approaches

This chapter provides a review of the pharmacogenetics of membrane transporters, including adenosine triphosphate-binding cassette (ABC) transporters and organic anion transporting proteins (OATPs). Membrane transporters are heavily involved in drug disposition by actively transporting substrate drugs between organs and tissues. As such, polymorphisms in the genes encoding these proteins may have a significant effect on the absorption, distribution, metabolism, and excretion of compounds. The techniques used to identify substrates and inhibitors of these proteins and subsequently assess the effect of genetic mutation on transport, both in vitro and in vivo, are outlined and discussed. Finally, studies linking transporter genotype with clinical outcomes are discussed.