Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework

Potential markers of oxidative stress in stroke

Free radical production is increased in ischemic and hemorrhagic stroke, leading to oxidative stress that contributes to brain damage. The measurement of oxidative stress in stroke would be extremely important for a better understanding of its pathophysiology and for identifying subgroups of patients that might receive targeted therapeutic intervention. Since direct measurement of free radicals and oxidized molecules in the brain is difficult in humans, several biological substances have been investigated as potential peripheral markers. Among lipid peroxidation products, malondialdehyde, despite its relevant methodological limitations, is correlated with the size of ischemic stroke and clinical outcome, while F2-isoprostanes appear to be promising, but they have not been adequately evaluated. 8-Hydroxy-2-deoxyguanosine has been extensively investigated as markers of oxidative DNA damage but no study has been done in stroke patients. Also enzymatic and nonenzymatic antioxidants have been proposed as indirect markers. Among them ascorbic acid, alpha-tocopherol, uric acid, and superoxide dismutase are related to brain damage and clinical outcome. After a critical evaluation of the literature, we conclude that, while an ideal biomarker is not yet available, the balance between antioxidants and by-products of oxidative stress in the organism might be the best approach for the evaluation of oxidative stress in stroke patients.

Involving the pharmaceutical and biotech communities in medication development for substance abuse

Pharmacotherapy as adjunctive treatment is an integral part of the strategy for treating substance abuse. Although there are several approved drugs for the treatment of opioid, alcohol, and nicotine dependence, the pharmaceutical industry, for a variety of reasons, has been reluctant to enter this area to develop medications for substance abuse indications. Therefore, in 1990, a Medication Development Program was established by NIDA to carry out and assist in stimulating development of new pharmacotherapies. It is vital for NIDA to provide clear leadership and establish a collaborative working relationship with the pharmaceutical industry, providing scientific, development, and financial assistance, depending on the size, resources, and expertise of the company. An important NIDA role in this effort is setting standards, such as establishing Target Product Profiles (TPPs), predictive decision trees for selection of clinical candidates, and animal models to evaluate safety and potential effectiveness prior to human studies. NIDA can further establish standards for clinical studies, including Proof of Concept (PoC), Phase 2 (or Learning) trials to establish initial proof of safety and effectiveness, and Phase 3 (or Confirming) trials to validate Phase 2 findings. NIDA and other government agencies need to work to improve industry incentives to participate in medication development for substance abuse. Specific incentives, such as market exclusivity and patent extension, as provided in BioShield and pediatric drug legislation, should be strongly considered. NIDA can further assist industry to navigate the regulatory and, if needed, controlled substance scheduling processes, by establishing a true Federal partnership between NIDA, FDA, and DEA.

Biological surrogate end-points in cancer trials: potential uses, benefits and pitfalls

New technologies have led to the development of an increasing number of targeted therapies and interest in combining these with conventional therapy to provide individualised patient treatments. New drug or treatment regimens must, however, undergo rigorous testing under strictly controlled conditions before they can be adopted as standard. This can be expensive, time-consuming and inefficient. Surrogate end-points have been proposed as an alternative, which could be measured earlier or more conveniently than true end-points. The aim of this paper is to review the definition, advantages, disadvantages and potential pitfalls of biological surrogate end-points in the context of cancer treatment.

Biomarkers for systemic lupus erythematosus: a review and perspective

PURPOSE OF REVIEW

Despite decades of extensive work in the understanding of the etiopathogenesis of systemic lupus erythematosus, few biomarkers have been validated and widely accepted for this disease. The lack of reliable, specific biomarkers not only hampers clinical management of systemic lupus erythematosus but also impedes development of new therapeutic agents. This paper reviews briefly the historical aspects of systemic lupus erythematosus biomarkers and summarizes recent studies on candidate biomarkers.

RECENT FINDINGS

Recognizing the urgent need for lupus biomarkers, a Lupus Biomarker Working Group has recently been initiated to facilitate collaborative efforts aimed at identifying and validating biomarkers for systemic lupus erythematosus. Based on available data, several laboratory markers have shown promise as biomarkers for susceptibility, diagnosis, and disease activity. These include Fc receptor genes (disease susceptibility), complement C4d-bound erythrocytes (diagnosis or disease activity), CD27 plasma cells (disease activity), 'interferon signature' (disease activity), and anti-C1q antibodies (disease activity and organ involvement).

SUMMARY

There is a longstanding and recently rejuvenated enthusiasm for biomarkers that precisely and specifically reflect the pathophysiologic and clinical changes in systemic lupus erythematosus. Promising candidate biomarkers have been identified but must still be validated through rigorous, large-scale multicenter studies.

Is Prostate-Specific Antigen a Valid Surrogate End Point for Survival in Hormonally Treated Patients With Metastatic Prostate Cancer? Joint Research of the European Organisation for Research and Treatment of Cancer, the Limburgs Universitair Centrum, and AstraZeneca Pharmaceuticals

Purpose

The long duration of phase III clinical trials of overall survival (OS) slows down the treatment-development process. It could be shortened by using surrogate end points. Prostate-specific antigen (PSA) is the most studied biomarker in prostate cancer (PCa). This study attempts to validate PSA end points as surrogates for OS in advanced PCa.

Patients and Methods

Individual data from 2,161 advanced PCa patients treated in studies comparing bicalutamide to castration were used in a meta-analytic approach to surrogate end-point validation. PSA response, PSA normalization, time to PSA progression, and longitudinal PSA measurements were considered.

Results

The known association between PSA and OS at the individual patient level was confirmed. The association between the effect of intervention on any PSA end point and on OS was generally low (determination coefficient, < 0.69).

Conclusion

It is a common misconception that high correlation between biomarkers and true end point justify the use of the former as surrogates. To statistically validate surrogate end points, a high correlation between the treatment effects on the surrogate and true end point needs to be established across groups of patients treated with two alternative interventions. The levels of association observed in this study indicate that the effect of hormonal treatment on OS cannot be predicted with a high degree of precision from observed treatment effects on PSA end points, and thus statistical validity is unproven. In practice, non-null treatment effects on OS can be predicted only from precisely estimated large effects on time to PSA progression (TTPP; hazard ratio, < 0.50).

Evidence from biomarkers and surrogate endpoints

The use of physiological, anatomical, and other biological tests is commonplace in the practice of medicine. In neurology, objectively measured tests termed biomarkers (BMs) are playing an increasing role in diagnosis and management of disease, both in clinical practice and in experimental therapeutics. This article will discuss the various applications of BMs to the assessment of therapies for neurological diseases and will use examples from neurological diseases to elucidate the strengths and potential weaknesses of BMs. As the understanding of the pathophysiology of many neurological diseases has improved, new BMs have been developed, and efforts have been made to use these as proxies for clinical endpoints. A BM used in this manner is referred to as a surrogate endpoint (SE). There are many potential advantages and disadvantages of using SEs in the evaluation of new therapies, and these will be reviewed as well. Furthermore, the evidence required for the development of an SE and the nature of the evidence that can be derived from the use of BMs and SEs will be discussed.

Mechanism-Based Pharmacokinetic–Pharmacodynamic Modeling—A New Classification of Biomarkers

In recent years, pharmacokinetic/pharmacodynamic (PK/PD) modeling has developed from an empirical descriptive discipline into a mechanistic science that can be applied at all stages of drug development. Mechanism-based PK/PD models differ from empirical descriptive models in that they contain specific expressions to characterize processes on the causal path between drug administration and effect. Mechanism-based PK/PD models have much improved properties for extrapolation and prediction. As such, they constitute a scientific basis for rational drug discovery and development. In this report, a novel classification of biomarkers is proposed. Within the context of mechanism-based PK/PD modeling, a biomarker is defined as a measure that characterizes, in a strictly quantitative manner, a process, which is on the causal path between drug administration and effect. The new classification system distinguishes seven types of biomarkers: type 0, genotype/phenotype determining drug response; type 1, concentration of drug or drug metabolite; type 2, molecular target occupancy; type 3, molecular target activation; type 4, physiological measures; type 5, pathophysiological measures; and type 6, clinical ratings. In this paper, the use of the new biomarker classification is discussed in the context of the application of mechanism-based PK/PD analysis in drug discovery and development.

Estimation of dosing strategies aiming at maximizing utility or responder probability, using oxybutynin as an example drug

Methods for optimizing dosing strategies for individualization with a limited number of discrete doses, in terms of maximizing the expected utility of treatment or responder probability, are presented. The optimality criteria require models for both beneficial and adverse effects that are part of the utility definition and published population models describing those effects for oxybutynin (urge urinary incontinence episodes per week and severity of dry mouth, respectively) were used for illustration. Dosing strategies with two dosing categories were defined in terms of sizes of the daily doses (low and high dose) and the proportion of patients that can be expected to be preferentially treated at the low dose level. Utility and responder definitions were varied to investigate the influence on the resulting dosing strategy. By minimizing a risk function, describing the seriousness of deviations from the predefined target, optimal dosing strategies were estimated using mixture models in NONMEM. The estimated dose ranges for oxybutynin were similar to those recommended. The optimal individualization conditions were dependent on the definitions of responder and utility. The predicted gain of individualization given utility and responder definitions used was greater, when a responder criteria was maximized compared with maximizing utility.

Toxicogenomics in the pharmaceutical industry: hollow promises or real benefit?

Almost 10 years ago, microarray technology was established as a new powerful tool for large-scale analysis of gene expression. Soon thereafter the new technology was discovered by toxicologists for the purpose of deciphering the molecular events underlying toxicity, and the term "Toxicogenomics" appeared in scientific literature. Ever since, the toxicology community was fascinated by the multiplicity of sophisticated possibilities toxicogenomics seems to offer: genome-wide analysis of toxicant-induced expression profiles may provide a means for prediction of toxicity prior to classical toxicological endpoints such as histopathology or clinical chemistry. Some researchers even speculated of the classical methods being superfluous before long. It was assumed that by using toxicogenomics it would be possible to classify compounds early in drug development and consequently save animals, time, and money in pre-clinical toxicity studies. Moreover, it seemed within reach to unravel the molecular mechanisms underlying toxicity. The feasibility of bridging data derived from in vitro and in vivo systems, identifying new biomarkers, and comparing toxicological responses "across-species" was also excessively praised. After several years of intensive application of microarray technology in the field of toxicology, not only by the pharmaceutical industry, it is now time to survey its achievements and to question how many of these wishes and promises have really come true.

Therapeutic innovation in the European Union: analysis of the drugs approved by the EMEA between 1995 and 2003

Since January 1995, all European Union applications for marketing approval for medicinal products derived from biotechnology and other drugs considered potentially innovative follow the EMEA centralized procedure. In order to assess the overall degree of therapeutic innovation of these drugs, we considered, for each approved agent, its target, the availability of previous treatments and the extent of its therapeutic effect. The following scores for therapeutic innovation were assigned through a consensus process: 'A' (important), 'B' (moderate) and 'C' (modest). The overall degree of important/moderate therapeutic innovation was 47% of all therapeutic agents (32% important; 15% moderate). Most (80%) of the EMEA-approved therapeutic agents were for serious diseases. The remaining ones were for risk factors (7%) or nonserious diseases (13%).

Disease System Analysis: Basic Disease Progression Models in Degenerative Disease

PURPOSE

To describe the disease status of degenerative diseases (i.e., type 2 diabetes mellitus, Parkinson's disease) as function of disease process and treatment effects, a family of disease progression models is introduced.

METHODS

Disease progression is described using a progression rate (Rdp) acting on the synthesis or elimination parameters of the indirect response model. Symptomatic effects act as disease-dependent or -independent effects on the synthesis or elimination parameters. Protective drug effects act as disease dependent or -independent effects on Rdp.

RESULTS

Simulations with the ten disease models show distinctly different signature profiles of treatment effects on disease status. Symptomatic effects result in improvement of disease status with a subsequent deterioration. Treatment cessation results in a disease status equal to the situation where treatment had not been applied. Protective effects result in a lasting reduction, or even reversal, of the disease progression rate and the resulting disease status during the treatment period. After cessation of treatment the natural disease course will continue from the disease status at that point.

CONCLUSION

Disease system analysis constitutes a scientific basis for the distinction between symptomatic versus protective drug effects in relation to specific disease processes as well as the identification of the exposure-response relationship during the time-course of disease.

Diagnostic biomarkers for oral and periodontal diseases

This article provides an overview of periodontal disease diagnosis that uses clinical parameters and biomarkers of the disease process.This article discusses the use of biomarkers of disease that can be identified at the tissue, cellular, and molecular levels and that are measurable in oral fluids such as saliva and gingival crevicular fluid. Biomarkers identified from these biologic fluids include microbial, host response, and connective tissue-related molecules that can target specific pathways of local alveolar bone resorption. Future prospects for oral fluid-based diagnostics that use micro-array and microfluidic technologies are presented.

Clinical impact of criteria for complete response (CR) of primary site to treatment of esophageal cancer

BACKGROUND

With the development of chemoradiotherapy for esophageal cancer, the complete response (CR) rate would become an important surrogate end-point. However, the Response Evaluation Criteria in Solid Tumors (RECIST) do not provide criteria for a response at the primary site of esophageal cancer. The objective of this study was to assess the validity of the endoscopic CR criteria for the primary site of esophageal cancer treated with chemoradiotherapy.

METHODS

We reviewed 139 patients with T1-T4, N0-1, M0-1a esophageal cancer treated with definitive chemoradiotherapy from August 1992 to April 1999. CR was tentatively defined upon endoscopic observation of the entire esophagus as: (i) disappearance of the tumor lesion; (ii) disappearance of ulceration (slough); and (iii) absence of cancer cells in biopsy specimens.

RESULTS

CR at the primary site (primary-CR) was achieved in 80 patients (58%). Of these, 71 (89%) were evaluated as having primary-CR within 6 months from the start of therapy. With a median follow-up of 53 months, a remarkable difference in the 5-year survival rate was observed between patients evaluated as having primary-CR and having non-CR (46 and 6%, P < 0.0001). Local failure was observed in 15 patients and the local control rate in patients with primary-CR was 78% at 5 years.

CONCLUSIONS

These criteria appear to represent an appropriate surrogate end-point because they are convenient to apply, require only a short time before a primary-CR can be declared and their fulfillment can predict long-term survival. It is recommended that RECIST include precise endoscopic findings for primary lesions in esophageal cancer in the CR criteria.

The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations

Vascular and angiogenic processes provide an important target for novel cancer therapeutics. Dynamic contrast-enhanced magnetic resonance imaging is being used increasingly to noninvasively monitor the action of these therapeutics in early-stage clinical trials. This publication reports the outcome of a workshop that considered the methodology and design of magnetic resonance studies, recommending how this new tool might best be used.

Gene expression in Huntington's disease skeletal muscle: a potential biomarker

Huntington's disease (HD) is an incurable and fatal neurodegenerative disorder. Improvements in the objective measurement of HD will lead to more efficient clinical trials and earlier therapeutic intervention. We hypothesized that abnormalities seen in the R6/2 mouse, a greatly accelerated HD model, might highlight subtle phenotypes in other mouse models and human HD. In this paper, we identify common gene expression changes in skeletal muscle from R6/2 mice, Hdh(CAG(150)) homozygous knock-in mice and HD patients. This HD-triggered gene expression phenotype is consistent with the beginnings of a transition from fast-twitch to slow-twitch muscle fiber types. Metabolic adaptations similar to those induced by diabetes or fasting are also present but neither metabolic disorder can explain the full phenotype of HD muscle. The HD-induced gene expression changes reflect disease progression. This raises the possibility that muscle gene expression may be used as an objective biomarker to complement clinical HD-rating systems. Furthermore, an understanding of the molecular basis of muscle dysfunction in HD should provide insight into mechanisms involved in neuronal abnormalities and neurodegeneration.

Pharmacokinetic-pharmacodynamic correlations and biomarkers in the development of COX-2 inhibitors

The mechanism by which COX inhibitors exert their analgesic effect is well established. However, data show no direct correlation between drug concentrations in plasma and the analgesic or adverse effects in chronic inflammatory conditions. This represents a major problem in the development of COX inhibitors, since it is difficult to predict the appropriate dosing regimen for the treatment of chronic inflammatory pain, based upon information from pre-clinical studies and eventually early clinical studies. The factors that determine response in inflammatory pain must be understood in order to make predictions about the time course of the analgesic effect. In this review the determinants of drug response and their variability will be discussed: physicochemical properties, pharmacokinetics (PK), pathophysiology and disease progression. From a mechanistic point of view, endogenous mediators of inflammation might be used as a biomarker for the analgesic effect and safety assessment. Such a biomarker can be an intermediate step between drug exposure and response. In addition, its concentration-effect relationship could be characterized by pharmacokinetic-pharmacodynamic (PK/PD) modelling. Indeed, recent investigations have shown that COX-2 inhibition, as determined by modelling of prostaglandin E2 (PGE2) levels in the whole blood assay in vitro can be used as a marker to predict drug effects (analgesia) in humans. A model-derived parameter, IC80, (total and unbound) was found to correlate directly with the analgesic plasma concentration of different COX inhibitors varying in enzyme selectivity. These findings indicate that PGE2 and thromboxane B2 inhibition can be used to predict and select efficacious doses in humans.

Method Validation and Measurement of Biomarkers in Nonclinical and Clinical Samples in Drug Development: A Conference Report

Biomarkers are increasingly used in drug development to aid scientific and clinical decisions regarding the progress of candidate and marketed therapeutics. Biomarkers can improve the understanding of diseases as well as therapeutic and off-target effects of drugs. Early implementation of biomarker strategies thus promises to reduce costs and time-to-market as drugs proceed through increasingly costly and complex clinical development programs. The 2003 American Association of Pharmaceutical Sciences/Clinical Ligand Assay Society Biomarkers Workshop (Salt Lake City, UT, USA, October 24-25, 2003) addressed key issues in biomarker research, with an emphasis on the validation and implementation of biochemical biomarker assays, covering from preclinical discovery of efficacy and toxicity biomarkers through clinical and postmarketing implementation. This summary report of the workshop focuses on the major issues discussed during presentations and open forums and noted consensus achieved among the participants on topics from nomenclature to best practices. For example, it was agreed that because reliable and accurate data provide the basis for sound decision making, biomarker assays must be validated in a manner that enables the creation of such data. The nature of biomarker measurements often precludes direct application of regulatory guidelines established for clinical diagnostics or drug bioanalysis, and future guidance on biomarker assay validation should therefore be adaptable enough that validation criteria do not stifle creative biomarker solutions.

Utilisation of human pharmacology studies with biomarkers for new drug applications in Japan

OBJECTIVE

This study evaluated the utilisation of human pharmacology studies with biomarkers for either efficacy or safety estimation conducted for new drug applications (NDAs) submitted to the Japanese regulatory authority, the Ministry of Health, Labour and Welfare (MHLW).

METHODS

A total of 50 new chemical entities (NCEs) posted on the Websites, which were approved from June 2000 to November 2001, were evaluated by investigating their approval information. The utilisation of human pharmacology studies with biomarkers was evaluated by focusing on the classification referred to biomarkers for either efficacy or safety estimation and timing of studies.

RESULTS

The human pharmacology studies with biomarkers for either efficacy or safety estimation were conducted in 20 compounds classified by utilising measures of either efficacy (17 compounds) or safety (seven compounds). In 4 of 17 NCEs, some of the biomarkers in human pharmacology studies were similar to the clinical endpoints for efficacy assessment in therapeutic exploratory and/or therapeutic confirmatory studies. For safety assessment in therapeutic exploratory and/or therapeutic confirmatory studies, clinical endpoints rather than biomarkers in human pharmacology studies were used in all seven NCEs. The timing of each type of clinical study could only be obtained for 15 NCEs. Of these 15 NCEs, human pharmacology studies with biomarkers for either efficacy or safety estimation were conducted on six compounds. There were only two compounds for which human pharmacology studies with biomarkers for efficacy estimation were conducted before pivotal studies such as a therapeutic exploratory study or a bridging study.

CONCLUSION

Our survey suggests that with Japanese NDAs, human pharmacology studies with biomarkers for either efficacy or safety estimation do not play a key role in accelerating drug development and maximising the knowledge gained from confirmatory trials. The relationship between a biomarker and a clinical endpoint should be investigated appropriately for accelerating drug development. We think that the utilisation of human pharmacology studies with biomarkers for either efficacy or safety estimation in the regulatory review process for NDAs should be encouraged with the advancements of drug evaluation research using an appropriate biomarker based on clinical pharmacology.

Immunosuppressants in advanced clinical development for organ transplantation and selected autoimmune diseases

Immunosuppressants dampen the immune response or restore balance among immune system components. They are primarily used to prevent allograft rejection after organ transplantation and to prevent or treat disease flares in autoimmune diseases. Immunosuppressants available at present include the calcineurin inhibitors (cyclosporin, tacrolimus), antimetabolites (azathioprine, leflunomide, methotrexate, mycophenolate mofetil), antiproliferatives (sirolimus), monoclonal antibodies to T lymphocyte (basiliximab, daclizumab, muromonab-CD3) and anticytokines (anakinra, etanercept, infliximab). The immunosuppressive market grows at a rate of > 10% yearly, with total sales in 2001 of US$2.7 billion. Immunotherapy in transplantation and autoimmune diseases is tending towards the use of multi-drug regimens tailored for the individual patient. At least 23 new immunosuppressants are currently in advanced clinical testing or preregistration, and can be divided into three groups. First, emerging drugs targeting intracellular ligands in immune cells are primarily analogues of currently-marketed agents, which attempt to provide improved pharmaceutical or safety profiles compared with the prototype compound. They are largely being developed in organ transplantation. Second, emerging drugs targeting cell surface ligands on immune cells attempt to antagonise novel molecular sites to interfere with immune cell activation via costimulatory signals, immune cell adhesion to tissues or the vasculature and immune cell trafficking. These agents are being primarily developed in rheumatoid arthritis, psoriasis and/or multiple sclerosis. Finally, emerging drugs acting as anticytokines, which largely follow on from the success of those on the market, by antagonising the function of tumour necrosis factor or a narrow selection of interleukins. All are being assessed in rheumatoid arthritis. Drug development of immunosuppressants is increasingly attempting to intervene in disease progression over the long term. These efforts bring with them trial design and regulatory issues, such as what markers can be used as trial outcome measures, over what duration do trials need to be conducted and what labelling claims are allowed. With the intensive activity in this field, it is likely that several new drugs will reach the market in the coming decade. One caveat, however, is that emerging immunosuppressants that are likely to capture a reasonable share of this increasingly-fragmented market must demonstrate the ability to achieve disease remission or long-term slowing of disease progression.

Integration and modelling of pharmacokinetic and pharmacodynamic data to optimize dosage regimens in veterinary medicine

In veterinary drug development procedures, pharmacokinetic (PK) and pharmacodynamic (PD) data have generally been established in separate, parallel studies to assist in the design of dosage schedules for subsequent evaluation in clinical trials. This review introduces the concept of PK/PD modelling, an approach in which PK and PD data are generated in the same study, and used to derive numerical values for PD parameters based on drug plasma concentrations. The PD parameters define the efficacy, potency and slope (sensitivity) of the concentration-effect relationship. It is proposed that the parameters derived from PK/PD modelling may be used as an alternative and preferred approach to dose titration studies for selecting rational dosage regimens (both dose and dosing interval) for further evaluation in clinical trials. In PK/PD modelling, the explicative variable for effect is the plasma concentration profile. The PK/PD approach provides several advantages over dose-titration studies, including determination of a projected dosage regimen by investigation of a single dose, in contrast to dose-ranging studies which by definition require testing of multiple dosage. Implementation of PK/PD modelling in the veterinary drug development process is currently constrained by the limited number of veterinary studies performed to date, and the consequently limited understanding of PK/PD concepts and their absence from regulatory authority guidelines. Nevertheless, PK/PD modelling has major potential for rational dosage regimen determination, as it considers and quantifies the two main sources of interspecies variability (PK and PD). It is therefore applicable to interspecies extrapolation and to multiple species drug development. As well as the currently limited appreciation of PK/PD principles in the veterinary scientific community, a further constraint in implementing PK/PD modelling is the need to validate PK/PD approaches and thereby gain confidence in its value by pharmaceutical companies and regulatory authorities.

Strategies for designing clinical trials for oligonucleotide therapeutics

Recent Phase III clinical trials for oligonucleotide therapeutics have yielded disappointing results. There is growing evidence that trial designs that consider the specific mode of action of these compounds are of crucial importance for their clinical testing. Early trials for oligonucleotide therapeutics should consider additional endpoints for the definition of a biologically active dose rather than focusing on the traditional concept of maximal tolerated dose. In later phases, alternative clinical endpoints and enriching sensitive study populations through innovative trial designs could improve the efficiency of clinical trials for oligonucleotide therapeutics.

Biomarker discovery and validation: technologies and integrative approaches

The emerging field of biomarkers has applications in the diagnosis, staging, prognosis and monitoring of disease progression, as well as in the monitoring of clinical responses to a therapeutic intervention and the development and delivery of personalized treatments to reduce attrition in clinical trials. Moreover, biomarkers have a positive impact on health economics. The word "biomarker" has been used extensively across therapeutic areas and many disciplines, and its nature takes into consideration clinical, physiological, biochemical, developmental, morphological and molecular measures. In drug trials, biomarkers have been proposed for use in efficacy determination and patient population stratification, in deducing pharmacokinetic-pharmacodynamic relationships and in safety monitoring. The interfacing and integration of different technologies for data collection and analysis are pivotal to biomarker identification, characterization, validation and application. "Integrative functional informatics" represents a novel direction in such technology integration.

Biomarkers in systemic lupus erythematosus

Despite the longstanding interest and large number of publications on biomarkers in lupus, there are no validated and widely accepted biomarkers of systemic lupus erythematosus to date. To achieve the ultimate goal, to have a biomarker as a surrogate endpoint in clinical studies, candidate biomarkers have to first be validated in a statistically rigorous way. However, to qualify as a surrogate endpoint, even validated biomarkers have to go through a process that demonstrates that they accurately reflect a clinically important outcome. These goals can only be achieved in large multicenter, properly conducted studies. We reviewed the difficulties involved in developing validated biomarkers for systemic lupus erythematosus and summarized the available data on the most promising biomarker candidates of disease susceptibility and disease activity. We also report on the current status of a multicenter initiative to concentrate efforts of biomarker development.

Can a marker be a surrogate for development of cancer, and would we know it if it exists?

Carcinogenesis proceeds through a very long preclinical period. Our collective hope is that multiple opportunities exist for chemoprevention to arrest or reverse progression towards malignancy. In the hope of faster progress with fewer subjects and lower total cost, much effort is being expended on the search for reliable biomarkers to predict the likelihood of developing cancer and/or to signal the effectiveness of chemopreventive therapy. Considerable attention is paid to identifying those markers that can act as surrogate markers for cancer development, since favorable modulation of the surrogate end-point biomarker (SEBM) may demonstrate effectiveness of a putative preventive treatment. However, the complexity of the biology challenges our ability to measure the effectiveness of attempts to arrest or reverse carcinogenesis, other than through costly and time-consuming prospective trials with disease state as the endpoint. Despite much work, to date no prehistologic biological or molecular intermediate marker has been validated for sporadic cancers. Several factors accounting for the difficulties encountered in SEBM development are reviewed. Discussion is focused on the common thread of the complexity of the underlying biological changes in carcinogenesis limiting the effectiveness of any single biomarker. Additionally, the incidence of sporadic cancers is also low, further limiting the positive predictive value of any putative prognostic marker. Recent successes in development of chemopreventive agents show the concept is valid and worth pursuing, but the current strategies to develop biochemical and genetic markers to identify surrogate biomarkers is flawed, and need to be reassessed in light of the difficulties faced over the last 20 years.

Reticulocytes bearing C4d as biomarkers of disease activity for systemic lupus erythematosus

OBJECTIVE

There is an urgent need for biomarkers with which to monitor disease activity in patients with systemic lupus erythematosus (SLE). We recently showed that abnormal levels of C4d, an activation-derived fragment of complement component C4, are deposited on the surface of erythrocytes from patients with SLE. This study focused on reticulocytes, the youngest and shortest-lived erythrocytes (lifespan 24-48 hours), with the objective of testing our hypothesis that when reticulocytes emerge from the bone marrow, they are immediately exposed to and acquire C4d at levels proportionate to the extent of complement activation at that time, thereby reflecting disease activity in SLE.

METHODS

We conducted a cross-sectional study of 156 patients with SLE, 140 patients with other diseases, and 159 healthy controls. Levels of C4d on the surface of reticulocytes were examined using a 2-color flow cytometric assay. The results were analyzed for correlations with SLE disease activity.

RESULTS

A wide range of increased levels of reticulocyte C4d was specifically detected in SLE patients. These levels fluctuated in SLE patients and correlated with clinical disease activity, as determined by the Safety of Estrogens in Lupus Erythematosus: National Assessment (SELENA) version of the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and the Systemic Lupus Activity Measure (SLAM). Specifically, in cross-sectional analyses, patients with reticulocyte C4d levels in the highest quartile compared with those in the lowest quartile had significantly higher SELENA-SLEDAI (P = 0.00002) and SLAM (P = 0.02) scores. Longitudinal observation demonstrated that the reticulocyte C4d levels changed in relation to the clinical course in individual patients.

CONCLUSION

These findings support our hypothesis that C4d-bearing reticulocytes may serve as biomarkers of disease activity in patients with SLE.

From bench to clinic and back: Perspective on the 1st IQPC Translational Research conference

Translational Research (TR) provides a set of tools and communication context for scientists and clinicians to optimize the drug discovery and development process. In the proceedings of a Princeton conference on this timely topic, the strengths and needs of this developing field were debated. Outcomes and key points from these discussions are summarized in this article which covers the topics of defining what we mean by translational research (both theoretically and in operational terms), ways in which to engender the TR mindset and embed it in organizations such as the pharmaceutical industry in order to optimize the impact of available technologies (including imaging methods), the scientific basis and under-pinnings of TR including genomics knowledge, information sharing, as well as examples of application to drug discovery and development. Importantly, it should be noted that collaborations and communications between the stakeholders in this field, namely academia, industry and regulatory authorities, must be strengthened in order for the promise of TR to be delivered as better therapies to patients.

The role of imaging in the clinical development of antiangiogenic agents

Early clinical development of novel antiangiogenesis agents is hampered by the fact that classic response end points are unlikely to be relevant and there is a lack of validated surrogate markers of efficacy. Toxicity-based decisions for dose setting and tumor size measurements by standard imaging probably are not be applicable. Because these agents modify a multitude of biologic processes that may cause early measurable effects, there is great interest in developing imaging tests that are sensitive to changes in tissue function. This article discusses the development of such "functional" clinical imaging and attempts to address the questions that are being asked of imaging departments by oncologists and pharmaceutical companies.

Molecular biomarkers in drug development

Arguably, the most immediately promising reverberation of the genomics era has been the application of biomarkers to drug development. The promise of applying biomarkers to early drug development is that they might aid in preclinical and early clinical decisions such as dose ranging, definition of treatment regimen, or even a preview of efficacy. Later in the clinic, biomarkers could be used to facilitate patient stratification, selection and the description of surrogate endpoints. Information derived from biomarkers should result in a better understanding of preclinical and clinical data, which ultimately benefits patients and drug developers. If the promise of biomarkers is realized, they will become a routine component of drug development and companions to newly discovered therapies.

Development and use of biomarkers in oncology drug development

Successful development and use of biomarkers will improve the productivity of oncology drug development. Recognition of the importance of biomarkers for speeding drug development is reflected in the precise definitions and concepts proposed by an NIH Working Group to standardize terminology and promote a more coherent and systematic approach to the development and use of biomarkers. Potential clinical biomarkers of drug efficacy are often identified through pre-clinical studies or basic research. Identification of potential biomarkers for use in oncology is moving rapidly forward through continuing advances in clinical imaging technologies, especially molecular and functional imaging. Other rapid advances are a product of the growing availability of new scientific reagents for established technologies and of high-throughput genomic and proteomic technologies that can generate hundreds of potential biomarkers for further evaluation. In certain cases, conventional clinical diagnostic techniques or assays can be adapted for use in pre-clinical models to evaluate their ability to serve as biomarkers for predicting clinical responses to new drug candidates. Evaluation (pre-clinical and clinical) of a potential biomarker is often the longest stage of biomarker development, and standards for evaluation or validation depend on the intended use and stage of clinical development. Biomarkers verified for use in preclinical studies can be used to help select appropriate animal models and lead compounds. Biomarkers verified for use in clinical trials can confirm a drug's pharmacological or biological mechanism of action, guide protocol design, aid patient and dose selection, and help to minimize safety risks. Oncology drug development can be optimized by using a tiered set of clinical biomarkers that predict compound efficacy and safety with increasing confidence at each rise in tier thereby aiding corporate decision-making about advancing compounds. In oncology, a special class of extensively evaluated biomarkers of efficacy (surrogate endpoints) that generally correlate with desired clinical outcomes can be used as a basis for corporate decisions as well as for gaining accelerated provisional regulatory approval of a drug.

Surrogate end points for pulmonary arterial hypertension

Pulmonary arterial hypertension is a rare disease that is characterized by increased pulmonary vascular resistance and right heart failure. Recent advances in the understanding of pulmonary arterial hypertension have been translated into effective therapies tested in clinical trials. These trials have used surrogate end points as the primary outcomes of interest. However, it is not clear which potential surrogate end points are reliable and valid for studying pulmonary arterial hypertension. Identification of suitable end points not only would help investigators design appropriate clinical trials but would assist clinicians in caring for this patient population. Hemodynamic, echocardiographic, neurohormone, and exercise measures hold some promise as potential surrogate end points for clinical trials of therapy for pulmonary arterial hypertension. Hemodynamic measures have the most evidence to support their use. Functional studies, such as the distance walked in 6 minutes, also may be meaningful. We present the available data as well as the strengths and weaknesses of each metric. Further studies should focus on validating the most promising of these surrogate end points, so that future investigators, subjects, and patients may benefit from the advantages they confer on clinical trials and patient care.

A perspective on surrogate endpoints in controlled clinical trials

The last couple of decades have seen a large amount of activity in the area of surrogate marker and surrogate endpoint validation, both from a clinical and a statistical perspective. Prentice made a pivotal contribution in the context of a single trial. Subsequently, the framework he proposed has been discussed, criticized, and extended. An important class of extensions considers several rather than a single trial. Recently, a lot of work has been done in this so-called hierarchical or meta-analytic framework. In this paper, we review both the single trial and the hierarchical framework. A number of applications, scattered throughout the literature, are brought together. We outline the statistical issues involved in trying to validate surrogate endpoints. Clearly statistical evidence should only be seen as a component in a decision making process that also involves a number of clinical and biological considerations.

Biomarker identification in neurologic diseases: improving diagnostics and therapeutics

Identification of biomarkers in neurological disease remains impeded by many obstacles. Among them are the availability of tissue at the site of pathology, poor clinical diagnostics, the complexity of the brain and a general dearth of functional end points and models for validation. However, advances in technology have helped to overcome these challenges. Some of these advances include standardization and increased efficiency in brain banking, novel techniques for brain imaging, improved methods for reducing tissue heterogeneity including laser capture microdissection, high-throughput genomics, new functional validation techniques such as RNA interference, and the development of new animal models of neurologic disease. In order to efficiently handle the wealth of information that will be gleaned from these new technologies, new integrated databasing protocols will be necessary. Access to these databases by researchers and clinicians is critical to the continued progress being made in biomarker identification in neurological disease. These challenges and ways to overcome them are presented here in the context of a disease known to be a robust model for biomarker identification, Alzheimer's disease.

BIOMARKERS OF CONGENITAL OBSTRUCTIVE NEPHROPATHY: PAST, PRESENT AND FUTURE

PURPOSE

Congenital obstructive nephropathy constitutes one of the major causes of renal insufficiency in infants and children. This review addresses the need to define biomarkers that serve as surrogate end points for measuring the severity of obstruction, the evolution of renal maldevelopment and injury, and the response to medical or surgical intervention.

MATERIALS AND METHODS

The literature from the last 10 years was reviewed for biomarkers of congenital obstructive nephropathy. Sources of biomarkers included urine, blood, amniotic fluid, tissue and imaging techniques.

RESULTS

Previous markers of congenital obstructive nephropathy include sonographic renal pelvic diameter, quantitative diuretic renography, and markers of glomerular and tubular function. Attempts to correlate renal histological changes with differential renal function have been disappointing. Immunohistochemical analysis and laser capture microscopy should improve specificity. Most promising is the application of new insights into the cellular response of the developing kidney to urinary tract obstruction. These findings include components of the renin-angiotensin system, transforming growth factor-beta 1, monocyte chemoattractant protein-1 and epidermal growth factor. Microarray studies show unique patterns of gene expression by the neonatal rat kidney subjected to ureteral obstruction, and proteomics should provide even more sensitive biomarkers of obstructive nephropathy.

CONCLUSIONS

We must define the cellular and molecular bases of renal maldevelopment, focusing on the link between functional and developmental pathophysiology. These findings will lead to biomarkers that will optimize our management of congenital obstructive nephropathy.

TMS and drugs

The application of a single dose of a CNS active drug with a well-defined mode of action on a neurotransmitter or neuromodulator system may be used for testing pharmaco-physiological properties of transcranial magnetic stimulation (TMS) measures of cortical excitability. Conversely, a physiologically well-defined single TMS measure of cortical excitability may be used as a biological marker of acute drug effects at the systems level of the cerebral cortex. An array of defined TMS measures may be used to study the pattern of effects of a drug with unknown or multiple modes of action. Acute drug effects may be rather different from chronic drug effects. These differences can also be studied by TMS measures. Finally, TMS or repetitive TMS by themselves may induce changes in endogenous neurotransmitters or neuromodulators. All these possible interactions are the focus of this in-depth review on TMS and drugs.

Development of biomarkers in multiple sclerosis

Multiple sclerosis is a complex disease, as several pathophysiological processes (including inflammation, demyelination, axonal damage and repair mechanisms) participate in the disease process. Furthermore, as new pathological evidence reveals, these processes are not uniformly represented across patient populations but can selectively predominate in individual patients, thus contributing to the heterogeneity in phenotypic expression of the disease, its prognosis and response to therapies. While the armamentarium of available therapies for multiple sclerosis broadens, little is known about factors that predict treatment response in individual patients to a specific drug. More importantly, we are beginning to understand that, analogous to cancer therapy, the successful therapeutic strategy in multiple sclerosis might ultimately involve the combination of different therapeutics targeting several dominant pathophysiological processes. The development of these process-specific therapies will be impossible without the use of biomarkers that reflect the targeted process, can select patient population in which the targeted process is prevailing and can aid during the more rapid screening of therapeutic agents in the early phase of their development. This review summarizes the general concepts of biomarkers and their potential use as surrogate endpoints and tailors these concepts to specific applications in multiple sclerosis research.

Considerations when designing a clinical trial of haematopoietic stem cell transplantation for autoimmune disease

The design and conduct of clinical trials of haematopoietic stem cell transplantation (HSCT) for autoimmune diseases requires investigators to address issues unique to this therapeutic approach and patient population. The proper composition of the protocol team is central to success. It is important to recognize that transplant physicians are no longer also the disease experts when transplanting patients with autoimmune diseases, and a close collaborative relationship between these groups early in the design stage must continue through the care of patients on trial to the assessment of toxicity and response. The early involvement of statisticians expert in clinical trial design and patient representatives are also vital to developing the optimal protocol. Each step in design and implementation requires particular consideration of the unique aspects of applying HSCT to autoimmune diseases. Some areas discussed are the role of disease and transplant databases in designing and analysing clinical trials, design options for early-phase trials, maintaining clinical equipoise, eligibility criteria, blinding, outcome measures and statistical analysis, and the composition and role of the data safety and monitoring boards. Although no blueprint for designing and conducting a trial of HSCT for autoimmune diseases can be laid out, the process should take into consideration the issues highlighted herein.

Biomarker discovery by comprehensive phenotyping for autoimmune diseases

There is a well-recognized but unmet need for biological markers to characterize disease type, status, progression, and response to therapy in autoimmune diseases. We are developing and applying an integrated bioanalytical platform and clinical research program to facilitate comprehensive differential phenotyping of patient samples and enable the discovery of biomarkers. Our measurement platform includes microvolume laser scanning cytometry for the quantification of hundreds of cellular parameters in whole blood and other samples, liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry for the quantification of proteins and low molecular weight biomolecules in serum and other fluids or tissues, and specific immunoassays for the quantification of trace proteins in serum. We describe the technologies and discuss initial applications to the analysis of subjects with rheumatoid arthritis (RA) and healthy controls.

Biomarkers, validation and pharmacokinetic-pharmacodynamic modelling

Four elements are crucial to successful pharmacokinetic-pharmacodynamic (PK/PD) modelling and simulation for efficient and effective rational drug development: (i) mechanism-based biomarker selection and correlation to clinical endpoints; (ii) quantification of drug and/or metabolites in biological fluids under good laboratory practices (GLP); (iii) GLP-like biomarker method validation and measurements and; (iv) mechanism-based PK/PD modelling and validation. Biomarkers can provide great predictive value in early drug development if they reflect the mechanism of action for the intervention even if they do not become surrogate endpoints. PK/PD modelling and simulation can play a critical role in this process. Data from genomic and proteomics differentiating healthy versus disease states lead to biomarker discovery and identification. Multiple genes control complex diseases via hosts of gene products in biometabolic pathways and cell/organ signal transduction. Pilot exploratory studies should be conducted to identify pivotal biomarkers to be used for predictive clinical assessment of disease progression and the effect of drug intervention. Most biomarkers are endogenous macromolecules, which could be measured in biological fluids. Many exist in heterogeneous forms with varying activity and immunoreactivity, posting challenges for bioanalysis. Reliable and selective assays could be validated under a GLP-like environment for quantitative methods. While the need for consistent reference standards and quality control monitoring during sample analysis for biomarker assays are similar to that of drug molecules, many biomarkers have special requirements for sample collection that demand a well coordinated team management. Bioanalytical methods should be validated to meet study objectives at various drug development stages, and possess adequate performance to quantify biochemical responses specific to the target disease progression and drug intervention. Protocol design to produce sufficient data for PK/PD modelling would be more complex than that of PK. Knowledge of mechanism from discovery and preclinical studies are helpful for planning clinical study designs in cascade, sequential, crossover or replicate mode. The appropriate combination of biomarker identification and selection, bioanalytical methods development and validation for drugs and biomarkers, and mechanism-based PK/PD models for fitting data and predicting future clinical endpoints/outcomes provide powerful insights and guidance for effective and efficient rational drug development, toward safe and efficacious medicine for individual patients.

Biomarqueurs et étude pharmacocinétique-pharmacodynamique des immunosuppresseurs

Biomarkers are characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. Biomarkers of pharmacological responses allow pharmacokinetic-pharmacodynamic modelling based on what is known of the mechanism of action of the drug. Characteristics predictive of the pharmacological response, such as a genotype, constitute a specific category of biomarkers and can be used as covariates in the model. In the case of "classical" immunosuppressive agents, the biomarkers of response most studied are lymphocyte calcineurin activity for ciclosporin and tacrolimus, and inosine monophosphate dehydrogenase activity for mycophenolate. Pharmacokinetic-pharmacodynamic analysis of monoclonal antibodies with immunosuppressive properties requires complex models and immunological biomarkers such as, for example, the number of circulating lymphocytes with a given surface antigen. Pharmacodynamic indirect response models are particularly relevant in this instance.