Developing tissue-based predictive biomarkers in oncology
Authors: Paul Waring
Journal: Clinical Cancer Research (2008)

ED05-01   Over the past 30 years, the number of new drugs approved each year has steadily declined while the cost of developing each new drug has grown almost exponentially. It currently costs approximately US $900 million to bring a drug to market, mainly because the industry has such a high failure rate and because this failure occurs so late in development. A survey of the 10 largest pharmaceutical companies conducted between 1991 and 2000 showed that the overall failure rate for oncology drugs was 40% during Phase I, 70% during phase II, 60% during Phase III and of the few showing success in Phase III, 30% were not approved (1). This means that a new oncology drug entering clinical trials has a one in fourteen chance of being used in clinical practice. The pharmaceutical and biotechnology industry cannot be sustainable with the high attrition rates currently operable in drug discovery and development.  To reduce this high attrition rate, and the associated costs, pharmaceutical companies need to be able to make confident decisions regarding efficacy and toxicity as early as possible during the drug development process and to ensure that those patients most likely to benefit from the drug are enrolled into the pivotal Phase III trials. Unfortunately, there are few tools available that enable “quick to kill” and “quick to proof of concept” decisions to be made during the early phases of drug development. Most oncology trials rely on CT scan measurement of tumor size or serum tumor markers to assess early clinical response; however, tumor shrinkage or falling serum tumor marker levels are often poor predictors of survival benefit and may not reveal the clinical benefit of cytostatic drugs. Randomized Phase II trials are frequently used to seek early signals of efficacy, however these are accompanied by high false positive and false negative rates, conferring considerable risk when making the critical decision to proceed, or not to proceed, to a pivotal Phase III trial.  Underlying these issues are the dual realities that most cancers are heterogeneous and most drugs only benefit a subset of patients with a particular disease. The traditional “trial and error” practice of treating “all comers” in pivotal trials means that many patients have to be treated in order to identify the few that derive clinical benefit. This approach is being progressively replaced by targeted therapies that are coupled to biomarkers which help identify patients more likely to show a treatment benefit or experience adverse events. The hope is that by identifying tumors that are dependent upon the targeted pathways and by demonstrating that the drug modulates the pathway it will be possible to identify the right patients for the pivotal trials and hence significantly increase the probability of success. Although there have been a few promising examples, the successful broad implementation of this approach, however, is proving to be challenging, especially in oncology where biomarker assays are often performed on tumor samples.  Once a biomarker has been identified, the technology platform selected, the assay analytically validated and its intended use defined, the challenge becomes how to incorporate the biomarker assay into the drug development program and design of the Phase II and III clinical trials. Decisions have to be made regarding whether to evaluate the biomarker prospectively or retrospectively; whether to collect and test tumor or surrogate tissue samples; whether to retrieve archival tumor samples from pathology laboratories or arrange for fresh biopsies to be taken; how best to power the trial to test both the drug and the biomarker; and how to design the study to determine whether the biomarker has prognostic as well as predictive value.  Prospective clinical validation of a biomarker to be used to select or stratify patients being enrolled in a pivotal trial is not a trivial undertaking. Most importantly, it requires a high level of  a priori  confidence in the biomarker’s predictive value. Furthermore, the assay has to be in a commercializable form and the testing laboratories shown to be proficient in performing the assay prior to enrolling the first patient. For a novel biomarker or assay platform, this could take at least three years, so assay development needs to begin as early as possible. If archival tumor samples are to be tested, efficient processes have to be in place to quickly retrieve the patients’ samples, often from hundreds of pathology laboratories, otherwise there will be unacceptable enrollment delays. With fresh tumor biopsies, ethical and logistical challenges invariably restrict their use to certain indications and a few carefully selected Phase II trial sites. Surrogate samples, such as blood and serum, while being much more accessible carry more risk because the biomarker may not be representative of the tumor (e.g., serum proteomics) or may only be informative in a small subset of patients (e.g., circulating tumor cells or DNA). Accordingly, few surrogate biomarkers have been adequately validated to enable decision making in clinical trials.  Retrospective biomarker analysis has the advantage that patient enrollment is not compromised; the assay does not need to be ready prior to study commencement; and multiple hypotheses, biomarkers, and assay cut points can be evaluated. However, this approach is only suitable for exploratory biomarker studies and is rarely a path to regulatory approval. Furthermore, it may not be possible to perform a follow-on prospective biomarker validation study because it would be ethically unacceptable to deny the control group a drug with now proven efficacy. Retrospective biomarker studies performed on retrieved archival tumor samples are often inconclusive because samples can only be retrieved on a proportion of the trial subjects and the quality and volume of tissue limits the type and power of biomarker analyses.  This combined therapeutic and diagnostic paradigm holds great promise but also creates new challenges. In this talk, I shall explore several issues that arose during the development of biomarker assays that highlight the need for greater awareness among patients, patient advocates, institutional review boards, clinicians, and pathologists of the critical need to obtain tumor samples in order to identify which patients are most likely to benefit.   References  1. Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discovery 2004;3:711-5.