Bernd Rosenkranz, FFPM, MD, PhD, is vice president, Clinical Development, Jerini AG, Invalidenstr. 130, D-10115, Berlin, Germany, +49 30 97893 500, fax +49 30 97893 599, email: mbrosenkranz@t-online.de.

Bernd Rosenkranz

Both large and small pharmaceutical companies have learned that the value of their development candidates increases once clinical research has demonstrated their proof of concept. Sponsor companies face the challenge of moving new blockbuster drugs to market as rapidly as possible. During development, they try to recognize, and minimize their spending on, products that can never make it through the registration process because of toxicity or lack of efficacy. Focused drug development using the best scientific approach accepted by regulatory authorities has become (or at least should become) a major objective for clinical research departments. That approach can include the use of appropriate biomarkers during preclinical and clinical drug development. 

As a general principle, a suitable clinical biomarker must be selected for which a reasonable relationship has been demonstrated to the clinically relevant endpoint. A few biomarkers are so closely linked to the clinical outcome that regulatory authorities have considered them valid primary variables in pivotal clinical trials and a substitute for a hard clinical endpoint during the marketing authorization process. It generally takes considerably less time and fewer subjects-and therefore less money-to demonstrate a significant effect of a drug on such a surrogate than on a "hard" endpoint. Based on these clinical biomarkers, preclinical models should be chosen that have some relevance to the effect of the drug in patients with the target disease. 

In April 1999, the National Institutes of Health (NIH) and the Food and Drug Administration (FDA) cosponsored a conference on "Biomarkers and Surrogate Endpoints: Advancing Clinical Research and Applications."1 The concepts of biomarkers and surrogates have been summarized by the NIH Definitions Working Group as follows:  

A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.

A clinical endpoint is a characteristic or variable that reflects how a patient feels, functions, or survives.

A surrogate endpoint is a biomarker that is intended to substitute for a clinical endpoint. 2

Although more complex definitions have been suggested since then, the NIH definitions present a concise summary of the basic concepts. Preclinical project team members should choose appropriate (and, if possible, "humanized") biomarkers that are relevant to normal and/or pathological biology or physiologically associated with the target disease and the action of the new drug in humans.

In early clinical studies, suitable biomarkers should be applied to help to demonstrate proof of concept and identify appropriate dose regimens for efficacy studies. Doing so-and learning, for example, which subpopulations are most likely to benefit from the new treatment-can help in planning later efficacy studies. Although the approach may seem straightforward, the use of biomarkers and surrogates carries with it a number of practical problems and pitfalls. Cardiovascular research will be used as an example here, because the concepts have often been applied in this clinical field. 

It should be noted that any clinical observation in a given subject might serve different purposes, and each purpose can have implications for the way these characteristics are used, documented, validated, and interpreted. In clinical practice, for example, blood pressure (BP) is measured to assess the individual risk for a given patient and to decide upon that patient's further diagnostic and therapeutic management. The same characteristic may be determined in epidemiological research, for example. Finally, blood pressure may be used as an outcome measure for a company's decision making in a research project. It may help to answer such questions as "Does the antihypertensive drug work?" or "Does the new drug create any side effects related to blood pressure?" The same measure may become a valid surrogate and an essential element in the regulatory review process to be used for the decision about marketing approval for the new drug. Researchers in cardiovascular drug development have access to clearly defined and rigorously validated biomarkers, surrogate endpoints, and clinical endpoints. 

Biomarkers include biochemical and functional characteristics or signals; ideally they should be noninvasive. Examples for biochemical biomarkers for cardiovascular conditions are high-density lipoprotein (HDL) cholesterol, lipoproteins, creatine kinase MB band (CK-MB), troponins (markers for myocardial cellular damage), high-sensitivity C-reactive protein (hs-CRP, a marker for inflammatory processes), fibrinogen, or plasminogen activator inhibitor-1 (PAI-1, an indicator of the activity of the blood coagulation system-and thus a risk for intravascular thrombus formation).3, 4 Functional or physiological characteristics include endothelial function, arterial or venous blood flow, arterial stiffness, and left ventricular systolic or diastolic volume or function. Finally, examples for signaling characteristics are ST depression recorded in the ECG (exercise or pharmacological stress testing, for example), and findings obtained by an imaging method such as quantitative coronary perfusion, coronary calcification (electron beam tomography), intravascular ultrasound, magnetic resonance imaging (MRI), or nuclear imaging (99mTc-SPECT) that include exercise or pharmacological stress testing. 

The most important criteria for valid biomarkers to be used in drug development are their clinical relevance; their sensitivity, specificity, and reliability (do they measure what they are supposed to); and their practicality and simplicity.5 

The list of cardiovascular biomarkers that have been accepted as surrogate endpoints is much shorter, of course, and includes such characteristics as blood pressure, cholesterol, and low-density lipoprotein (LDL). 

The most important criteria for valid surrogates are summarized in the International Conference on Harmonisation (ICH) Guideline E9, Statistical Principles for Clinical Trials.6 These mainly define the relationship between the surrogate endpoint (high blood pressure, for example) and the "hard" clinical endpoint (such as stroke) actually relevant when treating the condition. To show this relationship, the following must be demonstrated:  

statistical relationship in epidemiological studies 

evidence from clinical studies that treatment effects on the surrogate correspond to the clinical outcome.

For the same disease, the relationship between surrogate and clinical endpoints may depend on the mode of action. This means that for the same condition, regulatory authorities may accept that the surrogate is valid for one class of drugs, but not for other classes. 

"Hard" clinical endpoints for cardiovascular disease include such events as death, myocardial infarction, and stroke. These require no further validation, but are clinically relevant per se. However, use of these measures is often impossible in early proof-of-concept studies, because those studies require a large number of subjects and a long time period-often years from the beginning treatment until the event. 

Drug development was traditionally described as a sequential occurrence of formal, well-defined phases-usually described as preclinical development followed by clinical Phases 1 through 4. Today, drug development is seen as an integral data-driven process in which the phases overlap and-more importantly-use all information gained to create an optimal design for the next steps.7 Furthermore, unexpected findings at a later stage of development may necessitate planning new preclinical studies or Phase 1 and Phase 2 trials.  

In preclinical development, biomarkers are an essential element of the processes used to optimize the science of drug development. These include a number of modern technologies, such as functional genomics, proteomics, imaging, modeling and simulations, computational methods/informatics, modern analytical technologies, and specific humanized preclinical models. 

A well-documented example for the selection of appropriate and validated preclinical biomarkers is cardiac safety models to assess the potential of a drug causing prolongation of QTc, an ECG biomarker for life-threatening ventricular arrhythmia. Several regulatory guidance documents have recently been published on appropriate biomarkers for the proarrhythmic potential of drugs, and a harmonized guideline for the United States and Europe is expected for this year.8â11 Relevant preclinical models include in vitro tests such as ionic channel assays and hERG (human ether-a-gogo) channel binding, guinea pig myocytes, rabbit or dog Purkinje fibers, anesthetized guinea pig or dog, and conscious dog studies. These models are considered reliable and practical. They fulfill the requirements for suitable biomarkers and are related to the corresponding clinical biomarker, QTc prolongation. 

Preclinical or clinical studies frequently are performed without assessing the concentration dependency of the observed effects. This information would be very valuable, however, to predict appropriate dosage regimens in initial studies that use pharmacokinetic/pharmacodynamic (PK/PD) modeling techniques. Thus, in vitro concentrations or in vivo exposure, by sparse sampling methods (example: toxicokinetics), should regularly be determined in preclinical models. 

A recent "Position Paper on the Non-Clinical Safety Studies to Support Clinical Trials with a Single Low Dose of a Compound" drafted by the Committee for Proprietary Medicinal Products (CPMP) proposed minimum requirements for early pilot studies on the pharmacokinetics of a new chemical entity in human subjects using subpharmacological doses.12 This procedure allows for selecting appropriate animal species for preclinical studies-especially safety studies-and also for better use of preclinical information to predict dose dependency of efficacy or toxicity data in humans. 

Biomarkers play an especially critical role during Phase 2a of drug development (that is, during early proof-of-concept studies in a well-defined target population). This phase has been defined as "human trials providing sound evidence supporting the postulated effects of a new therapeutic drug product." The effects may be a relevant pharmacological action or a change in disease biomarkers, established surrogate endpoints, or clinical outcomes. Particularly, it should be noted that the relevant drug effects might be beneficial (that is, related to efficacy) and/or toxic (related to potential side effects).  

To properly interpret the outcome of clinical studies in which the primary outcome variable is a biomarker that substitutes for the relevant clinical outcome, researchers must consider the complex relationship between the medical condition, the biomarker, and the clinical outcome. Simplified relationships between disease, biomarker (surrogate endpoint), and clinical outcome (clinical endpoint) are shown in Figures 1 and 2. 

Hypertension is a straightforward example; it is associated with the biomarker elevated blood pressure-one of the few generally accepted surrogate endpoints in cardiovascular drug development-is associated with a clinically relevant outcome such as stroke, myocardial infarction, or renal failure. But the apparently straightforward association between disease, biomarker, and outcome oversimplifies the underlying (patho-) physiology. Thus, a disease generally is associated with several clinical manifestations, which may or may not serve as biomarkers, and which may be associated with the relevant clinical outcome. An example of a complex clinical condition is the metabolic syndrome, which is defined as insulin resistance (with or without manifest type 2 diabetes) and at least two of the following criteria-hypertension, dyslipidemia, obesity, and microalbuminuria. Clinically, this disease is associated with an increased cardiovascular risk. 

The possibility that the clinical outcome is time dependent must also be taken into account when interpreting the outcome of studies using biomarkers (Figure 3). An example is the pharmacological group of phosphodiesterase (PDE) 3 inhibitors (amrinone and milrinone, for example) for which a significant increase in cardiac contractility could be demonstrated in subjects with congestive heart failure. Following chronic administration of these drugs, mortality increased in this subject population. 

It can be concluded that biomarkers and clinical endpoints are not completely dependent on one another, but that there is a more or less well-defined relationship between the two. The use of a clinical biomarker as the primary outcome of a pharmacological intervention must therefore be interpreted very cautiously, taking into account the underlying (patho-)physiology, the possibility of false positive or false negative results, and time dependency of the clinical outcome. 

In cardiovascular medicine, blood pressure is a biomarker with a clearly demonstrated relationship to clinically relevant endpoints. BP has been accepted as surrogate endpoint for cardiovascular morbidity and mortality, by both the medical community (as reflected in current World Health Organization guidelines) and regulatory authorities. Major prospective, randomized clinical studies (including meta-analyses) and epidemiological evidence (the Framingham Heart Study conducted over more than 40 years13) have clearly demonstrated that high blood pressure is associated with increased morbidity and mortality, and that lowering blood pressure is beneficial. Some of the main findings: 

Treated hypertensive subjects have a 10-year mortality rate about 25% (for men) to 33% (for women) lower than that of untreated hypertensive subjects.

Reducing diastolic blood pressure by 5 mm Hg results in a decreased incidence of stroke (down 42%) and coronary artery disease (down 14%).

The maximum benefit seems to be achieved with a target blood pressure of 130â140/80â85 mm Hg.14

Antihypertensive treatment is indicated in both men and women and both young and elderly people.

To use a biomarker as a surrogate endpoint in a regulatory submission, researchers must validate the clinical study method for reproducibility, sensitivity, specificity, interrater reliability, variability, and bias. When using blood pressure as biomarker, for example, a considerable diurnal fluctuation exists. Because the maximum BP values occur in the late morning and early evening, ambulatory blood pressure monitoring (ABPM) is more appropriate than occasional office blood pressure recording. 

If a company wants to use additional claims in its marketing application, it needs to use auxiliary biomarkers in the clinical program, such as: 

Articles

Both large and small pharmaceutical companies have learned that the value of their development candidates increases once clinical research has demonstrated their proof of concept. Sponsor companies face the challenge of moving new blockbuster drugs to market as rapidly as possible.

Bernd Rosenkranz

Articles

Biomarkers and Surrogate Endpoints in Clinical Drug Development