EDITORIAL

Oncology Trial Design: More Accurately and Efficiently Advancing the Field RJ Hohl Clinical trials to support the development and application of new therapeutics in oncology have been in rapid evolution in recent years. This has largely resulted from increased understanding of the biology of cancer as well as the development of new chemical and biologic entities targeting the molecular basis for this new biology. In this issue, overviews of some innovative clinical trial designs are presented, including those of the ALCHEMIST1 and LUNG-MAP2 trials. These and many others not presented herein (such as the National Cancer Institute Molecular Analysis for Therapy Choice [MATCH] and SIGNATURE trial) will likely forever change the historic prospective, randomized, well-controlled, double arm trial design as being the “goldstandard” for regulatory approval and utilization of a novel agent. Of import and as background, Clinical Pharmacology and Therapeutics recently presented a comprehensive State of the Art piece by Venkatakrishnan et al.3 earlier this year that highlights many of the basic issues related to optimizing oncology therapeutics. Initial optimization of oncology therapeutics may be considered to have largely originated in the 1960s with seminal trials, such as that by Vince Devita et al.4 demonstrating efficacy of nitrogen mustard (or cyclophosphamide), vincristine, procarbazine, and prednisone therapy for Hodgkin’s

lymphoma. Of interest, this was a small phase 2 trial that included 43 patients. This clinical trial established that multiagent approaches with drugs having different mechanisms of anticancer activities were of greater benefit than single agent approaches. Quick to follow was that combinations of agents with different mechanisms of resistance for anticancer benefit were also useful, even if mechanisms of action were similar as evidenced by multiagent strategies with DNA alkylator combinations.5 Along with these studies directed to enhance efficacy were those to reduce toxicity. This started, for example, with trials in the 1980s of sentinel studies aimed at reducing exposure of women treated in the adjuvant setting for breast cancer to chemotherapy by assessing standard vs. lower toxicity or dosed treatments, cyclophosphamide, methotrexate, and fluorouracil or cyclophosphamide, adriamycin, and fluorouracil dose-reduced regimens.6 There is also ongoing evolution in choosing better predictive study endpoints. Questions that have been asked are whether objective response rate, progression-free survival, or overall survival be the endpoint. Although the objective response rate may measure acute effect, it may not measure overall benefit. Progression-free survival may or may not translate into overall survival with examples for positive correlation being

Penn State Cancer Institute, Penn State University, Hershey, Pennsylvania, USA. Correspondence: RJ Hohl (rhohl@ hmc.psu.edu) doi:10.1002/cpt.94

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EDITORIAL

for lower gastrointestinal tract cancers7 and discordance being in breast cancers.8 Early markers of potential benefit have also been looked at and include reduction in tumor size and decreased tumor growth rate. Considerations are whether a reduction in tumor growth is considered to be “good enough.”9 In parallel to these approaches is the improved understanding of the biological basis for cancer, most notably with the discovery by Peter Nowell of the Philadelphia Chromosome in Chronic Myelogenous Leukemia and Subsequent Discovery that this reciprocal translocation led to a fusion gene (BCRABL) that encoded for a fusion protein (BCRABL) tyrosine kinase that was the driver for the disease. This led to the US Food and Drug Administration approval of imatinib for the treatment of chronic myelogenous leukemia in May of 2001. Recognition that this agent also inhibited the tyrosine kinase c-kit and that c-kit was active in gastrointestinal stromal cell tumors led to imatinib’s approval six months later in 2002. However, what worked well for chronic myelogenous leukemia proved not to be so easy for much of the oncology world because of early and marked heterogeneity of disease, especially with solid tumors. For example, the amplification and overactivity of epidermal growth factor receptor in many cancers has led to a flurry of agents to inhibit this tyrosine kinase, such as initially gentinib and erlotinib. What initially was touted as highly desirable, the specific and selective tyrosine kinase inhibitors quickly gave way to multitargeting agents. Presumably this is a consequence of simultaneous expression of differing drivers for cancer cell proliferation. Not to be lost in the biology is the recognition that the cancer stem cell is the target that precludes curability in even apparent highly responsive tumors. Dramatic therapy-induced response of all but the cancer stem cell likely fails to provide cure unless the cancer stem cell itself CLINICAL PHARMACOLOGY & THERAPEUTICS | VOLUME 97 NUMBER 5 | MAY 2015

can be eliminated or, at a minimum, restrained. Given this complexity, it is indeed remarkable that traditional clinical trial design has so advanced the field. Measured and incremental advances have been made but with ever increasing cost and requirements for numbers of patient volunteers. The days of the large clinical trials would, if for no other reason than economics, be limited. The major advance in the clinical trial design was the adaptive Bayesian approach highlighted in the I-Spy trials. Specifically, novel therapeutic arms are tested initially with randomized subject accrual. Accrual is altered in response to early measures of negative outcome in randomization arms. With the new targeted therapies, the more recent approach has been to classify trials as either an umbrella or basket type, with each having different accrual needs. Umbrella trials are like the I-Spy and LUNG-MAP trials, for which single tumor types from patients are analyzed and patients are assigned to agents specifically targeting an actionable mutation. Basket trials rely on detecting a common underlying mutation that may arise in many tumor types. Patients with these assorted tumor types are then assigned therapy. The National Cancer Institute MATCH and Novartis SIGNATURE trials are examples of this type of trial. The challenge with these newer approaches is that the results derived from these trials may or may not be a pathway to regulatory approval, may or may not be recognized as a basis for insurers, including Centers for Medicare and Medicaid Services, to support such approaches with coverage, and for the few who are immune to cost, will lead to off-label use without a way to track responsiveness or benefit. Two highly relevant articles in this issue, Simon et al.10 and McClellan et al.,11 address these concerns in very thoughtful manners. 431

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In this context, it is indeed a complicated time for oncology trial design. The future will need to embrace even more novel methodological strategies to assess for clinical benefit. In addition, biomarkers for very early predictive response will be needed. Inherent is that fundamental clinical pharmacology principles will still be needed to guide therapeutic development. Thus, the advances in oncology therapeutic trials are likely more widely applicable to other diseases. One does still need to reflect on how physicists, starting with Isaac Newton, and including such greats as James Faraday, James Maxwell, and Albert Einstein, to name but a few, discovered fundamental laws that afforded prediction about how the particles and energy of the universe behaved and could be expressed in mathematical terms. It would seem that the discipline of clinical pharmacology and therapeutics still has the potential for realization of similar fundamental laws that govern the biology of disease and response to therapy. The new age of clinical trial design in oncology therapeutics may help lead the way to such discovery. For oncology therapeutics, we may be rapidly approaching such a discovery and it may be evident in the careful analysis of the progress and results of these innovative clinical trials. This favors a “systems” as compared to “reductionist” approach. Earlier this year, President Obama in his State of the Union address recognized the value of precision medicine as a path for more effectively combating diseases. It would seem that precision therapeutics targeting the right abnormality, at the right point in the disease, in the right patient, and at the right time, is the key. Like Devita’s early study with vincristine, procarbazine, and prednisone therapy, elucidating these right

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combinations might lead to curability of some, perhaps all, cancers.

CONFLICT OF INTEREST The author declared no conflict of interest. C 2015 ASCPT V

1.

Gerber, D.E., Oxnard, G.R. & Govindan, R. ALCHEMIST: bringing genomic discovery and targeted therapies to early-stage lung cancer. Clin. Pharmacol. Ther. (2015); e-pub ahead of print 1 February 2015. 2. Steuer, C.E. et al. Innovative clinical trials: the LUNG-MAP study. Clin. Pharmacol. Ther. (2015); e-pub ahead of print 10 February 2015. 3. Venkatakrishnan, K. et al. Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and opportunities. Clin. Pharmacol. Ther. 97, 37–54 (2015). 4. Devita, V.T. Jr, Serpick, A.A. & Carbone, P.P. Combination chemotherapy in the treatment of advanced Hodgkin’s disease. Ann. Intern. Med. 73, 881–895 (1970). 5. Petros, W.P. et al. Association of high-dose cyclophosphamide, cisplatin, and carmustine pharmacokinetics with survival, toxicity, and dosing weight in patients with primary breast cancer. Clin. Cancer Res. 8, 698–705 (2002). 6. Wood, W.C. et al. Dose and dose intensity of adjuvant chemotherapy for stage II, node-positive breast carcinoma. N. Engl. J. Med. 330, 1253– 1259 (1994). 7. Giessen, C. et al. Progression-free survival as a surrogate endpoint for median overall survival in metastatic colorectal surgery: literature-based analysis from 50 randomized first-line trials. Clin. Cancer Res. 19, 225–235 (2013). 8. Burzykowski, T. et al. Evaluation of tumor response, disease control, progression-free survival, and time to progression as potential surrogate end points in metastatic breast cancer. J. Clin. Oncol. 26, 1987–1992 (2008). 9. Bruno, R., Mercier, F. & Claret, L. Mode-based drug development in oncology: what’s next? Clin. Pharmacol. Ther. 93, 303–305 (2013). 10. Simon, R. et al. The role of non-randomized trials in the evaluation of oncology drugs. Clin. Pharmacol. Ther. (2015); e-pub ahead of print 9 February 2015. 11. McClellan, M.B. et al. Improving evidence from population-level experience with targeted agents. Clin. Pharmacol. Ther. (2015); e-pub ahead of print 9 February 2015.

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Oncology trial design: More accurately and efficiently advancing the field.

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