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Evolving Clinical Trial Strategies
Clinical trials remain the most important vehicle for improving the care of oncology patient. Success of an oncology trial depends on optimal utilisation of time, budget, and resources. This article describes evolving clinical trial strategies to determine the optimal criteria for rapidly evaluating new cancer therapies.

Pharmaceutical and healthcare companies are continuously evolving to adapt to the changing market and policy dynamics. New business, research, and operational models follow the philosophy of “targeted efforts for optimal benefits”. This philosophy, in the Research and Development (R&D) scenario, translates into an optimal utilisation of time, budget, and resources to conduct research that yield positive results. Extending this doctrine to clinical research means aiming for shorter trial duration, increased patient stratification for therapy, and careful selection of outcome measures for higher regulatory success.

Biomarker-based Patient Stratification
Advances in translational medicine have led to significant discoveries about the origin of diseases that were previously not well understood. The underlying genetic causes along with the advances in biotechnology have enabled drug makers to develop targeted therapies, thus paving the way for personalised medicine.
From a regulatory standpoint, the US Food and Drug Administration (FDA) has molded its review criteria to effectively review drugs and approve therapies specific to patients who are most likely to benefit from them. The trial design has become extremely important because any flaw in design would mean a lack of critical data or loss of time and resources or both.

Retrospective versus Prospective Analysis
Up to a decade ago, some of the critical biomarker-related analysis was performed largely retrospectively. The shortcoming of this approach was that it lacked statistical power to demonstrate benefits; for example, K-ras mutation as biomarker for cetuximab. Several studies have shown that cetuximab, an antiepidermal growth factor receptor drug, is effective only in patients with colorectal cancers (CRCs) having wild-type K-ras and not in patients with CRCs having mutant K-ras. The consistency and reliability of data obtained from the retrospective analysis of samples from therapeutic-driven (as opposed to biomarker-driven) randomised clinical trials have paved the way for both the US FDA and the National Institute for Health and Clinical Excellence (NICE) of UK to approve K-ras mutation testing by performing deoxyribonucleic acid (DNA) sequencing or quantitative polymerase chain reaction to guide patient selection. This is the first example of the use of a predictive biomarker in oncology without a specific prospective trial, and it offers a ‘proof-of-principle’ for this approach that is based on the retrospective evaluation of samples from a randomised controlled trial.

Companion Diagnostic Co-development
As more and more targeted therapies for specific subgroups of patients are being developed, it is only logical to have diagnostic testing methods for specific mutations or over expressions. Companion diagnostics provide a set of tools and solutions for some of the problems faced by pharmaceutical companies. The US FDA has mandated a close and parallel development of several diagnostics along with targeted therapies (Table 1). In the recent draft guidance, the US FDA has mentioned its preference for simultaneously approving a therapeutic agent and its companion diagnostic agent. The approval of Pfizer’s targeted therapy Xalkori (crizotinib) for lung cancer and Roche’s personalised therapy Zelboraf (vemurafenib) for melanoma indicates both the value of companion diagnostics to guide the therapies and the FDA’s support for their use.1 Companion diagnostics help to identify target patient population, and clinical trials conducted with selected patient populations are more likely to demonstrate efficacious results. Such trials often include small patient populations because of which they are often completed quickly and at a low cost.

Faster Approvals of Drugs
Shrinking R&D budgets and a competitive product landscape mean higher emphasis on obtaining meaningful data in a short time that is acceptable to regulatory authorities. Along with the emphasis on improving the logistics and planning of a trial, it is also important to ensure that the design of the trial does not lead to any fundamental modification midway.

The rate and number of approvals by the US FDA have steadily increased in the past few years. Approximately 1 per cent of all pharmaceutical drugs have companion diagnostics. In all, 33 pharmacogenomic biomarkers are included in the US FDAapproved drug labels. Approximately 30 per cent of all late stage (phase 2-3) molecules have biomarker-based endpoints, and 50 per cent of all early stage (preclinical to phase 1) molecules have biomarker analysis as endpoint. Approximately 60 per cent early stage molecules are in preclinical stage and have biomarker-based endpoints.3 The US FDA has constituted the following special processes for drugs that address unmet medical need4:
• Breakthrough therapy designation
• Fast-track designation
• Accelerated approval

Breakthrough Therapy Designation
Breakthrough therapy designation is aimed at facilitating the growth and review of drugs for serious or life-threatening conditions. Breakthrough therapy designation has all the features of a fasttrack programme along with higher FDA assistance for developing efficient drugs.

Fast-track Designation
Fast-track designation may be provided on the basis of preclinical data. Companies with fast-track products can publish portions of their marketing programme - called 'rolling review' - before publishing the complete programme.

Accelerated Approval
The accelerated approval pathway is most often used in configuring which disease course is lengthy and whether more time is needed to evaluate the clinical advantage of a designed drug, even if the impact on surrogate or advanced clinical endpoint occurs quickly.

Case Study
Zelboraf is an interesting example of how the identification of a molecular target that drives the disease and parallel development of a companion diagnostic test can lead to rapid launch timelines. The initial phase 1 data for Zelboraf were reported in 2009, and the drug received US FDA approval in August 2011; such a short timeline is not typically observed for oncology drugs. (Figure 1)

Merged Phase Trials
Novel strategies to reduce approval time include emergence of merged phase trials with expanded cohorts. Combining 2 traditionally separate studies into a single study is the most commonly used adaptive design. Optimal dose selection is the prime goal of the phase 2 portion of the combined-phase study. Once the most promising dose is selected, the study continues directly into phase 3 (without any stoppage) where more subjects are enrolled to meet the goals of the pivotal study.6 The combined phase 2–phase 3 study is designated as a registration study from the beginning of the dose-pruning portion. In this study, regulators provide less flexibility for blinding level and information accessibility than that provided in typical standalone phase 2 studies. Such studies that involve combining of clinical trial phases have both financial and timeline advantages. The important advantages of a combined-phase study are identification of the most promising arm or arms, increased enrollment, and direct continuation into phase 3. Combined phase 2–phase 3 studies result in approximately one-third savings in both timelines and budget.

Outcomes and Comparative Effectiveness Research
Another offshoot of this clever approach to trials is the incorporation of as many meaningful endpoints as possible. Typically, outcomes in cancer patients are not captured uniformly in trials, and performance status measurements are conducted to determine the suitability of the subsequent treatment course. The objective of these assessments is not to critically evaluate the impact of a particular treatment on the Quality of Life (QOL) and to link the same to health economic assessments.
Comparative effectiveness research in the typical sense is never practiced to determine the benefit vis-à-vis an existing alternative, primarily because in the past, such a variety of options was not available to patients. For example, Julie Lemieux, MD, Université Laval, Québec, Canada, conducted a research to determine the QOL measures used in a randomised clinical trial of breast cancer treatment in which the QOL was an endpoint.7 The outcome of the study showed that QOL measures were most useful for clinical decisions in trials of nonbiomedical interventions. The study also suggested that QOL measurements should be included as secondary endpoints in adjuvant therapy trials only when medical outcomes are expected to be approximately the same, when these trials focus on vulnerable populations such as the elderly, or when these trials test a new intervention for which determination of QOL is important.
Most therapy choices in cancer care are made with a modern purpose or with a likelihood of comparing the treatment with its harmful side effects. Although utmost care is taken to obtain the most favorable side-effect profile by using targeted therapies, sustainability of life and QOL remain the primary focus of cancer research. In oncology, comparative effectiveness research has made QOL as the top priority rather than the usual metrics of mortality and disease-free survival.
Patients, physicians, and policy makers are given a choice to not only choose treatments with similar survival benefits but also to judge whether the tradeoffs in side effects may be worth any gains in life expectancy or mitigation of cancer symptoms in the absence of cure. As payers and providers become increasingly aware of the QOL benefit of the drug in oncology and the standardisation of care as a part of the healthcare reform, such research will become increasingly important.

Conclusion
Clinical trial strategies affect the economic balance of large pharmaceutical companies by establishing economic risk-sharing in test development and trial operations and building designated markets for final products. Highly effective clinical trials will help drive healthcare toward an era of prognostic medicine, with absolute benefits of earlier treatments translating to superior long-term outcomes.