Promises of Biomarkers in Drug Development ? A Reality Check

Evolution of proteomic biomarker for chronic liver disease: Promise into reality

Liver is the vital organ for synthesis of proteins whose concentration in blood reflects liver dysfunction. Variations in protein domain can generate clinically significant biomarkers. Biomarker pipeline includes discovery of candidates, qualification, verification, assay optimization, and validation. Advances in proteomic approach can discover protein biomarker candidates based on “up-or-down” regulation or fold change in expression which is correlated with disease state. Despite numerous biomarker candidates been discovered, only few are useful in clinical practice which indicates the need for well-established validation regimen. Hence, the main purpose of this review is to understand the protein biomarker development and pitfalls. Companion diagnostics provide insights into potential cost-effective diagnosis for chronic liver disease.

Glial biomarkers in human central nervous system disease

There is a growing understanding that aberrant GLIA function is an underlying factor in psychiatric and neurological disorders. As drug discovery efforts begin to focus on glia-related targets, a key gap in knowledge includes the availability of validated biomarkers to help determine which patients suffer from dysfunction of glial cells or who may best respond by targeting glia-related drug mechanisms. Biomarkers are biological variables with a significant relationship to parameters of disease states and can be used as surrogate markers of disease pathology, progression, and/or responses to drug treatment. For example, imaging studies of the CNS enable localization and characterization of anatomical lesions without the need to isolate tissue for biopsy. Many biomarkers of disease pathology in the CNS involve assays of glial cell function and/or response to injury. Each major glia subtype (oligodendroglia, astroglia and microglia) are connected to a number of important and useful biomarkers. Here, we describe current and emerging glial based biomarker approaches for acute CNS injury and the major categories of chronic nervous system dysfunction including neurodegenerative, neuropsychiatric, neoplastic, and autoimmune disorders of the CNS. These descriptions are highlighted in the context of how biomarkers are employed to better understand the role of glia in human CNS disease and in the development of novel therapeutic treatments. GLIA 2016;64:1755-1771.

Industry perspectives on biomarker qualification

Biomarkers have the potential to expedite drug development, increase patient safety, and optimize clinical response. Yet few have achieved regulatory qualification. A survey was conducted to clarify industry's perspective on biomarker qualification and identify the most promising biomarkers for drug development. The results across toxicities/clinical areas highlight challenges in regulatory qualification, although early prioritization and alignment on an evidentiary standard framework are key factors in facilitating biomarker development and qualification.

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.

Robust and tissue-independent gender-specific transcript biomarkers

CONTEXT

Correct gender assignment in humans at the molecular level is crucial in many scientific disciplines and applied areas.

MATERIALS AND METHODS

Candidate gender markers were identified through supervised statistical analysis of genome wide microarray expression data from human blood samples (N = 123, 58 female, 65 male) as a training set. The potential of the markers to predict undisclosed tissue donor gender was tested on microarray data from 13 healthy and 11 cancerous human tissue collections (internal) and external datasets from samples of varying tissue origin. The abundance of some genes in the marker panel was quantified by RT-PCR as alternative analytical technology.

RESULTS

We identified and qualified predictive, gender-specific transcript markers based on a set of five genes (RPS4Y1, EIF1AY, DDX3Y, KDM5D and XIST).

CONCLUSION

Gene expression marker panels can be used as a robust tissue- and platform-independent predictive approach for gender determination.

A novel, high-sensitivity and drug-tolerant sandwich immunoassay for the quantitative measurement of circulating proteins

Background: Accurate measurement of a total protein target (free plus bound) is essential to optimize dose selection for monoclonal antibody drugs. Herein, we describe a novel sandwich immunoassay format in which the biotherapeutic antibody itself serves as the primary detection antibody. A signal is then generated through the addition of a labeled secondary antibody that recognizes the biotherapeutic antibody. The secondary antibody is conjugated with ruthenium to facilitate electrochemiluminescent analysis. Results: Data are presented from the analysis of two protein biomarkers having disparate size and structure; a 4.5 kDa peptide and a 60 kDa protein. In both cases, validated, highly specific assays were developed and shown to be tolerant to elevated levels of the therapeutic monoclonal antibody in question. Conclusion: Our novel format allows drug-tolerant measurement of soluble protein biomarkers targeted by monoclonal antibodies when only two independent epitopes for antibody binding are available and one is recognized by the therapeutic antibody.

Proteomics and biomarkers in clinical trials for drug development

Proteomics allows characterization of protein structure and function, protein-protein interactions, and peptide modifications. It has given us insight into the perturbations of signaling pathways within tumor cells and has improved the discovery of new therapeutic targets and possible indicators of response to and duration of therapy. The discovery, verification, and validation of novel biomarkers are critical in streamlining clinical development of targeted compounds, and directing rational treatments for patients whose tumors are dependent upon select signaling pathways. Studies are now underway in many diseases to examine the immune or inflammatory proteome, vascular proteome, cancer or disease proteome, and other subsets of the specific pathology microenvironment. Successful assay verification and biological validation of such biomarkers will speed development of potential agents to targetable dominant pathways and lead to selection of individuals most likely to benefit. Reconsideration of analytical and clinical trials methods for acquisition, examination, and translation of proteomics data must occur before we march further into future of drug development.

Gene expression profiling in organ transplantation

Aim of Review. Huge effort is being made among the transplant community investigating novel biomarkers that enable transplant clinicians to identify patients at risk for allograft rejection or those who will develop tolerance so that immunosuppression could be safely minimized or even ideally withdrawn. Despite the important advances achieved in the identification of several potential biomarkers of tolerance, rejection, or both, validation and demonstration of their clinical utility still needs to be tested, which will need international cooperative networks. It is important to note that the reproducibility of differently expressed genes might be affected by many factors such as gene ranking and selection methods, inherent differences between types, and the choice of thresholds. However, because microarray analyses are expensive and time consuming and their statistical evaluation is often very difficult, gene expression analysis using the RTPCR method is nowadays recommended. Conclusions. In the field of organ transplantation, gene-expression-based decision might help in improving patient and graft outcome and there are a multitude of studies showing that gene-expression profiling is feasible.

Can Functional Magnetic Resonance Imaging Improve Success Rates in CNS Drug Discovery?

INTRODUCTION: The bar for developing new treatments for CNS disease is getting progressively higher and fewer novel mechanisms are being discovered, validated and developed. The high costs of drug discovery necessitate early decisions to ensure the best molecules and hypotheses are tested in expensive late stage clinical trials. The discovery of brain imaging biomarkers that can bridge preclinical to clinical CNS drug discovery and provide a 'language of translation' affords the opportunity to improve the objectivity of decision-making. AREAS COVERED: This review discusses the benefits, challenges and potential issues of using a science based biomarker strategy to change the paradigm of CNS drug development and increase success rates in the discovery of new medicines. The authors have summarized PubMed and Google Scholar based publication searches to identify recent advances in functional, structural and chemical brain imaging and have discussed how these techniques may be useful in defining CNS disease state and drug effects during drug development. EXPERT OPINION: The use of novel brain imaging biomarkers holds the bold promise of making neuroscience drug discovery smarter by increasing the objectivity of decision making thereby improving the probability of success of identifying useful drugs to treat CNS diseases. Functional imaging holds the promise to: (1) define pharmacodynamic markers as an index of target engagement (2) improve translational medicine paradigms to predict efficacy; (3) evaluate CNS efficacy and safety based on brain activation; (4) determine brain activity drug dose-response relationships and (5) provide an objective evaluation of symptom response and disease modification.

The use of formalin fixed wax embedded tissue for proteomic analysis: Table 1

The potential of proteomic approaches to elucidate disease pathogenesis and biomarker discovery is increasingly being recognised. These studies are usually based on the use of fresh tissue samples. Problems in obtaining and storing fresh frozen samples, especially either for the investigation of rare diseases or for the study of microscopic disease foci, have led to the investigation of the possible use of formalin fixed wax embedded tissue for proteomic biomarker detection Overcoming problems with protein cross-linking associated with formalin fixation of tissues, especially by using heat-mediated retrieval techniques combined with highly sensitive methods for protein separation and identification are now emerging, giving promise to the use of formalin fixed wax embedded tissues for proteomic analysis. Formalin fixed wax embedded tissues, together with their associated clinical and pathological information outcome may provide significant potential opportunities for proteomics research. Such studies of formalin fixed wax embedded tissue will allow access to already acquired clinical tissue samples which can be readily correlated with clinical, pathological and outcome data. It also provides access to rare types of tissue/diseases that would be either difficult to collect prospectively in a timely manner or are unlikely to be available as fresh samples. The purpose of this review is to provide an overview of the issues associated with the use of formalin fixed wax embedded tissues for proteomics.

Biomarkers and their consequences for the biomedical profession: a social science perspective

Although biomarkers are not altogether new, they are gaining a new life in our postgenomic present. This article takes this as a good reason to explore biomarkers in depth and to speculate about the consequences that biomarkers might engender in clinical practices. First, the article ventures into an endeavor of ordering the dynamic field of biomarkers, suggesting a possible classification of biomarkers, and then argues that we are currently witnessing a 'biomarkerization' of health and disease - defined as an ongoing future-oriented process that seeks to solve biomedical as well as public health problems through investments into biomarker research at the present time. Subsequently, this article reflects on some possible consequences of this phenomenon. It argues that while the movement of candidate biomarkers into the clinic is arduous, biomarkers might develop a life of their own once they arrive in the clinic. This article outlines the direction of two such possible consequences. It suggests that biomarkers might be involved in a change of the actors that order and categorize diseases, as well as trigger transformations in our understanding of what counts as disease in the first place. Hence, this article seeks to shed light on the paradox that while biomarkers are designed to add more evidence into clinical practice, they might actually increase uncertainty and ambiguity.

Traversing the valley of death: a guide to assessing prospects for translational success

On the basis of our experience in drug and device development, we have identified six broad categories of issues that profoundly affect the probability for successful translation of basic scientific discoveries into effective therapies. Within each category, we propose a series of questions that form the beginnings of a self-guided global risk assessment tool. Although this preliminary tool will require validation and adjustment, we offer it to stimulate a discussion about more rigorous methods for selecting and conducting translational projects.

Future prospects for biomarkers of alcohol consumption and alcohol-induced disorders

The lack of reliable measures of alcohol intake is a major obstacle to the diagnosis, treatment, and research of alcohol abuse and alcoholism. Successful development of a biomarker that allows for accurate assessment of alcohol intake and drinking patterns would not only be a major advance in clinical care but also a valuable research tool. A number of advances have been made in testing the validity of proposed biomarkers as well as in identifying potential new biomarkers through systems biology approaches. This commentary will examine the definition of a biomarker of heavy drinking, the types of potential biomarkers, the steps in biomarker development, the current state of biomarker development, and critical obstacles for the field. The challenges in developing biomarkers for alcohol treatment and research are similar to those found in other fields. However, the alcohol research field must reach a competitive level of rigor and organization. We recommend that NIAAA consider taking a leadership role in organizing investigators in the field and providing a common set of clinical specimens for biomarker validation studies.

Functional genomic analysis of peripheral blood during early acute renal allograft rejection

BACKGROUND

Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long-term graft survival. Peripheral blood biomarkers that provide evidence of early graft rejection may offer an important option for posttransplant monitoring, optimize the utility of graft biopsy, and permit timely and effective therapeutic intervention to minimize the graft damage.

METHODS

In this feasibility study (n=58), we have used gene expression profiling in a case-control design to compare whole blood samples between normal subjects (n=20) and patients with (n=11) or without (n=22) biopsy-confirmed acute rejection (BCAR) or borderline changes (n=5).

RESULTS

A total of 183 probe sets representing 160 genes were differentially expressed (false discovery rate [FDR] <0.01) between subjects with or without BCAR, from which linear discriminant analysis and cross-validation identified an initial gene signature of 24 probe sets, and a more refined set of 11 probe sets found to classify subject samples correctly. Cross-validation suggested an out-of-sample sensitivity of 73% and specificity of 91% for identification of samples with or without BCAR. An increase in classifier gene expression correlated closely with acute rejection during the first 3 months posttransplant. Biological evaluation indicated that the differentially expressed genes encompassed processes related to immune response, signal transduction, and cytoskeletal reorganization.

CONCLUSION

Preliminary evidence indicates that gene expression in the peripheral blood may yield a relevant measure for the occurrence of BCAR and offer a potential tool for immunologic monitoring. These results now require confirmation in a larger cohort.

Physiologically-based Simulation Modelling for the Reduction of Animal Use in the Discovery of Novel Pharmaceuticals

The global pharmaceutical industry is estimated to use close to 20 million animals annually, in in vivo studies which apply the results of fundamental biomedical research to the discovery and development of novel pharmaceuticals, or to the application of existing pharmaceuticals to novel therapeutic indications. These applications of in vivo experimentation include: a) the use of animals as disease models against which the efficacy of therapeutics can be tested; b) the study of the toxicity of those therapeutics, before they are administered to humans for the first time; and c) the study of their pharmacokinetics —i.e. their distribution throughout, and elimination from, the body. In vivo pharmacokinetic (PK) studies are estimated to use several hundred thousand animals annually. The success of pharmaceutical research currently relies heavily on the ability to extrapolate from data obtained in such in vivo studies to predict therapeutic behaviour in humans. Physiologically-based modelling has the potential to reduce the number of in vivo animal studies that are performed by the pharmaceutical industry. In particular, the technique of physiologically-based pharmacokinetic (PBPK) modelling is sufficiently developed to serve as a replacement for many in vivo PK studies in animals during drug discovery. Extension of the technique to incorporate the prediction of in vivo therapeutic effects and/or toxicity is less well-developed, but has potential in the longer-term to effect a significant reduction in animal use, and also to lead to improvements in drug discovery via the increased rationalisation of lead optimisation.

Irritable bowel syndrome: towards biomarker identification

Irritable bowel syndrome (IBS), the most common functional gastrointestinal disorder referred to gastroenterologists, affects 7-10% of the general population worldwide. The lack of suitable disease-defining biological markers coupled with a poorly understood underlying pathophysiology complicates patient diagnosis and seriously hampers drug discovery efforts. Over the past few years, a number of potential biomarkers have emerged, and in this review we critically evaluate such candidates. In particular, we highlight the increasing number of studies supporting a low-grade immune activation in IBS and consider how the latest preclinical developments can contribute to the development of more robust and reliable biological markers of this disorder. The successful identification of biomarkers is critical to progressing our understanding of IBS and addressing the unmet therapeutic needs of this debilitating condition.

Using expression and genotype to predict drug response in yeast

Personalized, or genomic, medicine entails tailoring pharmacological therapies according to individual genetic variation at genomic loci encoding proteins in drug-response pathways. It has been previously shown that steady-state mRNA expression can be used to predict the drug response (i.e., sensitivity or resistance) of non-genotyped mammalian cancer cell lines to chemotherapeutic agents. In a real-world setting, clinicians would have access to both steady-state expression levels of patient tissue(s) and a patient's genotypic profile, and yet the predictive power of transcripts versus markers is not well understood. We have previously shown that a collection of genotyped and expression-profiled yeast strains can provide a model for personalized medicine. Here we compare the predictive power of 6,229 steady-state mRNA transcript levels and 2,894 genotyped markers using a pattern recognition algorithm. We were able to predict with over 70% accuracy the drug sensitivity of 104 individual genotyped yeast strains derived from a cross between a laboratory strain and a wild isolate. We observe that, independently of drug mechanism of action, both transcripts and markers can accurately predict drug response. Marker-based prediction is usually more accurate than transcript-based prediction, likely reflecting the genetic determination of gene expression in this cross.

Novel opportunities for computational biology and sociology in drug discovery

Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.

Quantitative mass spectrometry-based techniques for clinical use: biomarker identification and quantification

The potential for development of personalised medicine through the characterisation of novel biomarkers is an exciting prospect for improved patient care. Recent advances in mass spectrometric (MS) techniques, liquid phase analyte separation and bioinformatic tools for high throughput now mean that this goal may soon become a reality. However, there are challenges to be overcome for the identification and validation of robust biomarkers. Bio-fluids such as plasma and serum are a rich source of protein, many of which may reflect disease status, and due to the ease of sampling and handling, novel blood borne biomarkers are very much sought after. MS-based methods for high throughput protein identification and quantification are now available such that the issues arising from the huge dynamic range of proteins present in plasma may be overcome, allowing deep mining of the blood proteome to reveal novel biomarker signatures for clinical use. In addition, the development of sensitive MS-based methods for biomarker validation may bypass the bottleneck created by the need for generation and usage of reliable antibodies prior to large scale screening. In this review, we discuss the MS-based methods that are available for clinical proteomic analysis and highlight the progress made and future challenges faced in this cutting edge area of research.

From differentiating metabolites to biomarkers

The current developments in metabolomics and metabolic profiling technologies have led to the discovery of several new metabolic biomarkers. Finding metabolites present in significantly different levels between sample sets, however, does not necessarily make these metabolites useful biomarkers. The route to valid and applicable biomarkers (biomarker qualification) is long and demands a significant amount of work. In this overview, we critically discuss the current state-of-the-art of metabolic biomarker discovery, with highlights and shortcomings, and suggest a pathway to clinical usefulness.

Can in vitro assessment provide relevant end points for cognitive drug programs?

Several start-up biotechnology companies have been created with the primary intent of developing cognitive enhancers. In addition, established pharmaceutical companies also frequently focus their efforts on cognitive drug discovery. In many instances, the rationale and evidence for these endeavors are based largely on in vitro assessments. In particular, the experimental paradigm, know as long-term potentiation (LTP), a cellular model of synaptic plasticity and memory encoding, is being increasing used preclinically for assessing potential nootropic drugs in vitro. Central to this thinking is the idea that the modulation of LTP and/or glutamate receptors are the key criteria that must be met for the development of cognitive enhancers. However, programs targeting the NMDA receptor, a glutamate receptor subtype, over the years have been less than fruitful. In addition, skeptics criticize the relevance of some in vitro tests such as LTP for simulating human cognitive function. Given these considerations, one may wonder if in vitro assessments in general, and the LTP paradigm in particular, provide relevant end points for cognitive drug discovery and development programs. The focus of this article is to address this question and to present evidence as to why in vitro assessment is still critical to the success of any cognitive drug program.

Integration and use of biomarkers in drug development, regulation and clinical practice: a US regulatory perspective

The US FDA encourages the integration of biomarkers in drug development and their appropriate use in clinical practice. It is believed that this approach will help alleviate stagnation and foster innovation in the development of new medical products, and, ultimately, lead to more personalized medicine. To facilitate the use of biomarkers in drug development and clinical practice, the FDA organized workshops, issued guidances, established a voluntary submission process, developed online educational tools and, most importantly, strives to ensure the integration of this information into drug labels, for example, via the update of existing labels, or the inclusion of appropriate language in new drug labels. A pilot process has been set up to qualify novel biomarkers that are not associated with specific drug products, but are of more common use (e.g., biomarkers for drug safety). In addition, the FDA has initiated the creation of various consortia that are working towards the identification and characterization of exploratory biomarkers in order to qualify them for a specific use.

New technologies around biomarkers and their interplay with drug development

What conductors are to their orchestras, biomarkers are to their associated technologies. Building fundamental science, supporting early diagnosis of diseases and following their progression, improving efficacy and safety of treatments, optimizing patient selection and adapting dosing of drugs, helping decide which therapy is most appropriate; these are examples of a few contexts in which biomarkers are key players. Technology development can definitely not escape being associated with these steps. In other words, today's biomarkers are the thermometers of tomorrow's therapies. This review provides an overview of recently established platforms as well as new and upcoming technologies for biomarker development in the context of drug development. The roles as well as the pros and cons of different disciplines such as genetics, genomics, proteomics, metabonomics, and assay development will be discussed.