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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
Given the high morbidity and mortality associated with metastatic melanoma, considerable attention has been paid to identifying potential therapies. Until recently, few therapies have been specifically approved for treating metastatic melanoma. In an attempt to increase clinical trial successes, many therapies are implementing biomarkers for patient stratification. This strategy narrows down the population in an effort to identify appropriate subpopulations that have increased efficacy or fewer safety concerns. However, the addition of a biomarker constitutes an additional risk to clinical development and may therefore increase the overall clinical trial risk. Here, we examine the clinical trial success rate for therapies targeting metastatic melanoma. In addition, we identify the impact that biomarkers have had on the clinical development of this disease. Keywords: biomarker • clinical trial risk • drug approval • drug development • metastatic melanoma
In the USA, there will be an estimated 76,100 new cases of melanoma and 9710 deaths due to the disease in 2014. Currently, the average survival rate for patients with metastatic melanoma is only 6–12 months [1] . Despite a modest increase in the incidence of melanoma over the past 30 years in developed countries due to benign lesions [2] , there is high morbidity and mortality associated with the advanced stages of the disease [3] . In addition, the later stages of the disease impart a high healthcare cost [4] . Patients with stage III or IV melanoma only account for 15.2% of all patients diagnosed with melanoma, yet account for 48% of total melanoma costs [5] . Therefore, management of late-stage melanoma has a significant impact on the healthcare system. Furthermore, there have been few new drug approvals specifically for treating metastatic melanoma until recently [6] . At the same time, clinical development has struggled over the past several decades as the number of approved pharmaceutical therapies by the US FDA has not kept up with the
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increasing costs of developing pharmaceutical treatments [7] . Failures during clinical trials greatly contribute to the rising costs and resources during research and development, and there has subsequently been a focus on minimizing potential clinical failures by industry and physicians alike [7,8] . One such mechanism has been the implementation of biomarkers during clinical development. The FDA has defined a biomarker as “an indicator of normal biological processes, pathogenic processes, and/or response to therapeutic or other interventions” [9] . There are a variety of roles that biomarkers can take in medicine, including pharmacodynamic, predictive, prognostic and surrogate biomarkers [10] . It is thought that utilizing a biomarker that narrows the patient population can increase the probability of treatment success by more accurately identifying appropriate subpopulations that have increased efficacy or fewer safety concerns [11] . However, a recent review highlighted that biomarkers may inherently add risk into the clinical development of a therapy [12] .
Biomark. Med. (2015) 9(1), 13–23
Daniel A Rubinger1, Sarah S Hollmann1, Viktoria Serdetchnaia1, D Scott Ernst2 & Jayson L Parker*,1 Biology Department, University of Toronto Mississauga, William Davis Building, Room 2071, Mississauga, ON, L5L 1C6, Canada 2 Division of Medical Oncology, London Regional Cancer Program, 790 Commissioners Road East, London, ON, N6A 4L6, Canada 3 Hoffmann-La Roche, 2455 Meadowpine Boulevard, Mississauga, ON, L5N 6L7, Canada *Author for correspondence: Tel.: +1 289 337 6194 Fax: +1 905 569 4738 jayson.parker@ utoronto.ca 1
part of
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Systematic Review Rubinger, Hollmann, Serdetchnaia, Ernst & Parker Analyses investigating clinical trial success rates for new drug development for cancer subtypes are lacking [13–17] . While there are specific studies analyzing the impact of biomarkers in drug development for breast cancer [18] , non-small-cell lung cancer [19] and in oncology as a whole [16] , there are no systematic analyses to date of the impact of biomarkers on clinical success rates in metastatic melanoma. A clearer understanding of the risk associated with clinical trial development, specifically in a disease with a heterogeneous patient population, could help clinicians manage resource allocation, patient recruitment and expectations of new treatment effects. This study used a risk-based paradigm of clinical trial design to calculate the clinical trial attrition rates for newly developed drugs for metastatic melanoma. Another objective of this study was to determine whether the use of biomarkers or targeted therapies reduces attrition rates for metastatic melanoma. Materials & methods Study eligibility & primary data source for drug development trials
[28])
or www.findarticles.com. Reference lists of the identified literature were scanned for relevant sources. Clinical trial outcome classification
A simple and transparent rule was used to classify the clinical trial outcomes and is consistent with the methods of previous analyses [18–24] . The phases of development were measured using a standardized definition of success and rested on the following assumptions: a Phase I (or I/II) clinical trial was classified as successful if the drug advanced to Phase II for the same indication. Similarly, a Phase II trial was successful if the drug advanced to Phase III clinical testing. Finally, Phase III clinical testing was successful if the drug received approval by the FDA and was available at the time of this analysis. Compounds in active clinical trials were not considered failures or successes. If a treatment had only ongoing trials at a particular phase, that phase was excluded from the analysis while previous phases were deemed successful. For example, if a therapy completed Phase III and had not yet received FDA approval, it was considered to be in Phase III. Conversely, two types of clinical trial failure were defined: medical failure and commercial failure. If a drug failed to meet its primary end point or had significant safety issues in any phases that precluded further testing, it was classified as a medical failure. Commercial failures were those where the drug development program had no public signs of medical failure, yet had no further clinical trial testing for a minimum of 2 years. Commercial failures could be the result of a variety of reasons, including but not limited to competing program priorities, lack of financing or a strategic shift in corporate direction. The clinical trial success rate was calculated by determining the percentage of unique drugs that successfully completed a phase of development out of the total number of drugs tested in a particular phase of development, as demonstrated using the following equation:
Detailed descriptions of the methods used for analysis in this study have been previously described [18–24] . Briefly, data regarding trials that pertained to metastatic melanoma were obtained from the NIH clinical trials database [25] from 1 January 1998 until 1 July 2013. A systematic analysis was conducted from the results of a keyword search for “metastatic melanoma”. Records were assessed for eligibility by two independent investigators. Disagreements between reviewers regarding study inclusion were resolved through c onsensus. Trials were included if the investigational drug was a new therapy or a combination therapy (i.e., with standard care) and treated patients with unresectable stage III or stage IV melanoma. Trials conducted internationally were included if they were registered on the NIH clinical trials database [25] . In addition, trials that were studied in Phase I in all solid tumors and subsequently studied in later phases in advanced melanoma were Success rate for Phase x = included. Trials were excluded from the analysis if they: (# of drugs that passed to Phase x + 1) initiated their Phase I trial for this indication before (# of drugs that pssed to Phase x + 1) + (# drugs that filed t Phase x) 1998; were not industry sponsored; did not treat outcomes related to survival (applicable to Phase II or III trials only); or contained trials for topical therapies or Drugs that were ongoing in Phase x were excluded new formulations of previously approved drugs. in the transition rate for Phase x. The cumulative success rate refers to the probability of completing all the Additional databases & online tools phases of clinical trial testing (i.e., the product of the Additional searches using online databases were used individual probabilities of success for each phase). to supplement the trial information obtained from the NIH clinical trials database [25] . The searches included Compound & company classification publicly available sites as well as Archive-It [26] , PR A single therapy was considered to be a monotherapy news wire (Factiva [27]), Business Wire (Proquest 5000 while a trial containing more than one type of treat-
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
ment was considered to be a combination therapy if it included two unique compounds or the addition of a unique compound to the standard of care. Drugs were also classified as either a small molecule, biologic or therapeutic vaccine. Small molecule drugs were considered as the ‘traditional’ chemically synthesized compounds in drug development. By contrast, biologics were defined according to the classification by the FDA as being “derived from living material – human, animal, or microorganism” [29] . Therapeutic vaccines were classified according to FDA guidance as products “intended to be administered to patients with an existing cancer for the purpose of treatment” [30] . For the biomarker analysis, only trials that used biomarkers to screen patients were included. This analysis focused exclusively on predictive biomarkers, which are defined as a “baseline characteristic that categorizes patients by their likelihood for response to a particular treatment” [31] . Studies that used biomarkers to confirm the presence of disease were not included in the biomarker arm of analysis. A biomarker that has undergone quantitative testing to determine performance characteristics such as
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sensitivity, specificity and reproducibility is called a “validated biomarker” [32] . Ownership of each drug entity was categorized according to its Phase I ownership as either a ‘biotechnology’ or a ‘pharmaceutical’. Firms were considered biotechnology companies if they were listed in the NASDAQ biotechnology index at the time of Phase I initiation of the drug program. Companies not listed on the index yet with a market capitalization of over US$1 billion were classified as pharmaceutical companies. Companies that did not meet the above criteria were not classified. For combination products that included a biotechnology and pharmaceutical company, the assumption was that the biotechnology company initiated the partnership. Statistical methods
A 95% CI based on the normal approximation for binomial random variables was calculated for each analysis. Since this assumption is considered valid only for large n values, we have chosen not to employ the term ‘statistically significant’, but rather to discuss the uncertainty associated with the results.
100 87 90
Melanoma
n = 197
Industry
Transition probability (%)
80 70
64
60
66
58 n = 93
50 39
40
33 n = 12
30
17 n=4 16
20 10 0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 1. Clinical trial success rates. Drugs that entered Phase I clinical testing during or after 1998 were tracked up until 1 July 2013. The percentages reported represent the probabilities of the successful completion of the drugs at the current phase and advancement to the next phase of clinical testing (or approval if currently in Phase III). The cumulative success rate represents the product of probabilities for each prior phase. Metastatic melanoma data are compared with the industry expectations described by DiMasi and colleagues [14] . The error bars represent the 95% CIs.
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180
171 Progressed to next phase
160
Medical failures Commercial failures
140
Products (n)
120 100 80 54
60 40
22
19
20
17
7
4
0 Phase Ι (n = 197)
Phase ΙΙ (n = 93)
6
2
Phase ΙΙΙ (n = 12)
Figure 2. Classification of the types of clinical trial failure according to medical or commercial considerations in the failure. A successful drug is one that continued on to the next phase. For example, in Phase I, 171 drug candidates moved on to Phase II trials, while seven failed because of medical reasons and 19 drugs failed because of commercial reasons. The n values above the bars indicate the number of drugs for each area, while the values on the axis indicate the total number drugs in the current phase of development.
Results Clinical trials reporting drug development in late-stage melanoma
Applying the search criteria for the keyword “metastatic melanoma” in the NIH clinical trials database [25] resulted in 1290 records. A unique drug usually accounted for multiple recorded studies. A total of 197 unique drugs that entered Phase I of clinical testing for metastatic melanoma met the inclusion criteria. Out of this total, 93 drugs advanced from Phase I to Phase II and 12 advanced to Phase III. A total of 78 drugs were in ongoing clinical development in Phase II, while a total of 42 drugs were considered to have ongoing studies in Phase III. Only four drugs, dabrafenib (Tafinlar™; GlaxoSmithKline, UK) [33] , trametinib (Mekinist™; GlaxoSmithKline, UK) [34] , ipilimumab (Yervoy™; Bristol-Myers Squibb, NY, USA) [35] and vemurafenib (Zelboraf™; Hoffmann-La Roche, Switzerland) [36] obtained FDA approval for the treatment of metastatic melanoma. Clinical trial phase pass rates & overall drug success
The clinical trial success rates in metastatic melanoma were compared with a previously reported industry average (Figure 1) [14] . The success rate for Phase I was 87%, for Phase II was 58% and for Phase III was 33%. The trial success rates for metastatic melanoma were
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greater than the industry standard for Phase I and II; however, the metastatic melanoma Phase III success rate (33%) was substantially lower than the industry average (66%). Nevertheless, there was little difference between the overall cumulative success rate for metastatic melanoma of 17% compared with industry expectations of 16%. In addition, there were only 12 treatments classified as a Phase III successes or Phase III failures for metastatic melanoma, resulting in a wide confidence interval for any comparison in Phase III. Types of clinical trial failure
Medical and commercial failure trends were determined for each phase of development (Figure 2) . The most common cause of attrition in Phase I was commercial failures, while in Phase II and III, medical failures were the main cause of clinical trial failure. In this study, early commercial failures were mainly a result of a lack of funding, an absence of drug development in the previous 2 years or mergers and acquisitions (results not shown). Finally, the vast majority of medical failures were due to a lack of efficacy as opposed to safety or toxicity concerns. If commercial failures were removed from the data set and only medical failures were considered, the overall cumulative success rate for new drug development in metastatic melanoma would increase from 17% to a cumulative rate of 27%.
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
Clinical trial failure by type of therapy
The success rates in metastatic melanoma by monotherapy or combination therapy were also elucidated (Figure 3) . An example of monotherapy would be vemurafenib alone, while an example of combination therapy would be vemurafenib and bevacizumab, a novel therapy for melanoma. Overall, the rates for each phase were similar; however, given that there are no combination products approved in metastatic melanoma to date, the cumulative success rate for combination therapy was 0%. Given the low number of studies in Phase III, the confidence intervals around the Phase III success rates are quite wide. Clinical trial failure & the effect of drug type
In an effort to ascertain the impact of drug type on the failure rate, the success rates were stratified by the drug type: biologic, small molecule and therapeutic vaccines (Figure 4) . The majority of drugs in Phase I were small molecules (112), followed by biologics (64). The cumulative pass rates for biologics and small molecules were 20% and 21%, respectively. Despite a high success rate throughout each phase, the cumulative success rate for therapeutic cancer vaccines was 0%, since this class has yet to receive FDA approval in metastatic
100 90
melanoma. Similar to the other analyses, the low number of studies in Phase III resulted in considerable uncertainty around the Phase III success rates. Clinical trial failure & the use of biomarkers
Overall, treatments incorporating biomarkers had a higher cumulative success rate (47%) compared with non-biomarker therapies (6%), as observed in Figure 5. However, there was a very small sample size for therapies that utilized biomarkers, resulting in wide confidence intervals. Ipilimumab was the only therapy that did not involve the use of a biomarker and was approved for metastatic melanoma. By contrast, dabrafenib, trametinib and vemurafenib all require testing for B-Raf mutations. Table 1 lists the types of therapies that utilized biomarkers as well as whether the biomarkers were approved for use in another FDA-approved product. For example, B-Raf mutations are also prevalent in other cancers; however, dabrafenib, trametinib and vemurafenib are the only products approved for use exclusively in B-Raf-positive melanoma patients. Out of the 31 compounds that utilized biomarkers, only 15 were validated biomarkers, with 93% of the validated biomarkers being represented by B-Raf. The remaining biomarkers were novel biomarkers and were not approved in any other indication.
92 n = 63 87 n = 197 83 n = 127
Melanoma (total) Melanoma (monotherapy) Melanoma (combination therapy)
Transition probability (%)
80 70
62 58 n = 60 57 n = 30 n = 93
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44 n=9 33 n = 12
40 30
17 n=4
20 10
0 n=3
23 n=4
0 n=0
0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 3. Clinical trial success rates for monotherapy compared with combination therapy. If the study protocol stipulated that the product is administered with another agent (i.e., a chemotherapeutic substance such at dacarbazine), then it was put in the combination therapy group. Drugs that used both regimens were doublecounted. The error bars represent the 95% CIs.
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100 90
89 86 n = 112 n = 64
Biologic Small molecule
76 n = 21
80 Transition probability (%)
82% n = 11
69 n = 29
70
Vaccine 50 33 n=6 n=3
60 47 n = 53
50
20 n=1
40
21 n=3
30 20 10
0 n=3
0 n=0
0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 4. Clinical trial success rates by biologic, small molecule or cancer vaccine. US FDA definitions were utilized for standardization. The transition probability was stratified by the type of molecule. The error bars represent the 95% CIs.
Clinical trial failure by company
Drug sponsorship was classified into pharmaceutical and biotechnology based on Phase I ownership. The clinical trial success rates for Phase I were 91–92% for both types of companies. Biotechnology companies fared slightly better in bringing their products to Phase III, with a Phase II pass rate of 70% compared with only 61% for their pharmaceutical counterparts (results not shown). Pharmaceutical companies had a cumulative success rate of 28%, while biotechnology firms had no successfully approved compounds, resulting in a cumulative success rate of 0%. Out of 197 drugs, 45% emerged from companies that were excluded from the analysis because they were either private companies or had a market capitalization of less than US$1 billion. Discussion There has been some exploration and quantification of clinical trial success rates for the industry overall and broad disease areas including oncology; however, analyses of specific cancers, including metastatic melanoma, are lacking. Using a systematic approach to analyze all of the clinical trials registered in the NIH clinical trials database [25] , a cumulative success rate was calculated to be 17% for metastatic melanoma treatments, which is similar to the industry average of
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16%. Biomarkers were able to substantially increase the success rate to 47% compared with only 6% for drugs that did not use a biomarker. To the authors’ knowledge, this is the first quantitative analysis that measures the magnitude of improvement with biomarkers in metastatic melanoma. This result is in line with an analysis in breast cancer that determined the cumulative success rate using the biomarker HER2 to be 23% compared with only 15% for non-biomarker drug candidates [18] . Similarly, a study investigating the clinical trial failure during non-small-cell lung cancer drug development found a sixfold increase in success rates with biomarker-targeted therapies [19] . A recent review examining the addition of biomarkers to clinical trial development cautions that there may be increased clinical trial risk associated with codevelopment of a therapeutic with a novel biomarker [12] . Proponents for biomarkers advocate that codeveloping a biomarker with a therapy can increase efficacy or decrease safety events that are essential to approval. However, there are several potential complications associated biomarker implementation. For example, the decreased population can make patient recruitment into clinical studies difficult. In addition, stratified biomarkers can increase development costs for regulatory approval of the biomarker diagnostic tests. Finally, because biomarkers must undergo another
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
100
97 n = 31
90
75 n=4 Biomarker
85 n = 166
80 Transition probability (%)
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Non-biomarker 65 n = 17
70
47 n=3
57 n = 76
60 50 40 30
13 n=8
20
6 n=1
10 0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 5. Clinical trial success rate in metastatic melanoma based on the utilization of a biomarker for patient selection. The transition probability was stratified by biomarker usage. The error bars represent the 95% CIs.
regulatory pathway to become a companion diagnostic [38] , the addition of a biomarker would theoretically increase clinical trial risk. This study adds to the body of evidence that suggests that the addition of predictive biomarkers may not increase clinical trial risk [12] . The Phase III success rate of only 33% was the primary driver for reducing the cumulative success rate for metastatic melanoma. The main reason for the failure in metastatic melanoma drug development was the high number of medical failures in Phase II and III due to a lack of efficacy. One suggestion is that, similar to the results observed in non-Hodgkin’s lymphoma, Phase II studies that often use surrogate markers may not be able to predict the success rate in Phase III trials compared with Phase II trials that measured survival as a primary outcome. Another option is that melanoma has typically been refractory to traditional treatments that seem to be efficacious in other cancers, which has resulted in difficulties in treating metastatic melanoma [39] . One response has been an emphasis by clinicians and industry to bring forth targeted therapies [40] . This notion can be supported by the increase in cumulative approval rates for drug candidates that utilized biomarkers. With the approval of dabrafenib and trametinib in 2013, as well as further targeted therapies currently close to completing Phase III clinical trial testing (e.g., masitinib from AB Science, France), the future is promising for metastatic melanoma therapies. While therapeutic cancer vaccines have yielded no approvals to date, there has been an emphasis on devel-
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oping immune-based therapies to combat various cancers, including metastatic melanoma [41] . There were only 21 successful therapeutic vaccines that emerged from Phase I. Two failures in Phase III were due to commercial reasons, whether it was a lack of financing (M-Vax™; AVAX Technologies, PA, USA) [42] or a lack of reported development (HSPPC-96, Oncophage®, Agenus Inc., MA, USA) while one was due to a lack of efficacy (MDX-1379 + ipilimumab; Bristol-Myers Squibb) [43] . In addition, there are currently three Phase III programs (Allovectin®-7, Vical, CA, USA; OncoVEXGM-CSF, Amgen, CA, USA; POL-103A, Polynoma LLC, CA, USA) still ongoing. To date, the only therapeutic vaccine approved in oncology is sipuleucel-T (Provenge™; Dendreon Corp., WA, USA) for prostate cancer. The lack of approvals to date may be viewed as an opportunity to continue to critically explore the various different pathways of how immune-based therapies can improve oncology patient outcomes. This study has several limitations, most of which have been described in studies with similar methodologies [18–24] . First, due to the nature of this preliminary study and the small sample sizes observed, this study was a descriptive study and statistical tests were not performed, making it difficult to determine with certainty the implications of this study. The confidence intervals were calculated based on the normal approximation, which may be inaccurate in smaller sample sizes. Specifically, the subgroup analyses could warrant continued investigation over time to
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Table 1. List of therapies that utilized a biomarker for patient selection and whether the biomarker is approved by the US FDA for use in an FDA-approved product. Biomarker type
Biomarker received Biomarker US FDA approval received FDA (melanoma) approval (other)
Melanoma therapy
Aurora kinase
No
No
MLN8237
B-Raf V600 mutation
Yes (melanoma)
Yes
Dabrafenib, ixabepilone, lenvatinib, RO4929097, selumetinib, selumetinib + dacarbazine, sorafenib, tanespimycin, trametinib, trametinib + dabrafenib, vemurafenib, vemurafenib + bevacizumab, vemurafenib + GDC-0973, vemurafenib + ipilimumab
CDK (cyclin D1) overexpression No
No
P276-00
CDK4/6
No
No
PD 0332991
c-Kit-activating mutation
No
Yes (leukemia, other cancers)
Imatinib, masitinib, nilotinib
DDR2 mutation or B-Raf mutation
No
No
Dasatinib
HLA-A*0201 haplotype
No
No
CYT004-MelQbG10, CYT004-MelQbG10 + dacarbazine, MDX-1379 + ipilimumab, MKC1106MT, Synchrotope™ TA2M plasmid DNA vaccine
ICAM-1 overexpression and DAF overexpression
No
No
Coxsackievirus A21
MAGE-A3
No
No
GSK1203486A
N-cadherin overexpression
No
No
ADH-1
NF-κB
No
No
Bortezomib
Biomarker utilization was obtained from the FDA [37].
observe whether the trends seen in this study are consistent and enduring with a greater number of treatments and trials. Future analyses utilizing a statistical model or pooled analysis with other therapy areas may be warranted. Second, it is unknown whether there were additional studies evaluating new treatments that were perhaps not captured through the NIH clinical trials database [25] , and therefore, the success rates described here could be an overestimation. Lastly, assumptions had to be made regarding the reasons for trial failure. While medical failures including a lack of efficacy are transparent, it is unclear from public sources whether there are underlying medical reasons for discontinuation of development, which would otherwise be classified as a commercial failure. Taken together, these results are predictive of potential trends in the risk associated with the clinical trial development of treatments for metastatic melanoma. Conclusion In conclusion, recent approvals have resulted in an overall cumulative success rate for metastatic melanoma similar to the industry average. Similarly to the
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results observed in breast cancer and non-small-cell lung cancer, utilizing predictive biomarkers to stratify the patient population may be a viable option for improving the clinical trial success rate. These findings provide clinicians with a clearer picture of the risk of drug development in these indications to date, and how to identify clinical trials that present the best chances of success for their patients. In addition, data from metastatic melanoma add to the growing body of evidence suggesting that biomarker usage may be beneficial to clinical development. Future perspective These findings provide a benchmark against which future therapies will be compared in terms of analyzing the success of clinical trial testing for metastatic melanoma. Additional research is required to determine which methods in addition to targeted therapy and biomarker stratification can improve clinical trial testing outcomes. With increasing biomarker validation as well as testing of compounds with novel mechanisms of action, it would be useful to repeat this analysis in several years and learn about any changes in the clinical development climate.
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
Acknowledgements The authors would like to thank S Shah (University of Toronto) for his support in updating the data set from the NIH clinical trials database.
Financial & competing interests disclosure DA Rubinger and SS Hollmann have worked in the pharmaceutical industry. M Arundine is currently employed by a pharma-
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ceutical company. JL Parker has worked in the pharmaceutical industry and advises a hedge fund that invests in the health sciences. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
Executive summary Unmet need in metastatic melanoma • There is high morbidity and mortality associated with the advanced stages of melanoma despite only a modest increase in the incidence of melanoma over the past 30 years. • Although patients with stage III or IV melanoma only account for a small proportion of the total number of patients with melanoma (∼15%), their management costs represent almost half of the total costs of treating all patients with melanoma.
Biomarkers may improve clinical development • The implementation of biomarkers in clinical development may identify subpopulations that have increased efficacy or fewer safety concerns. • The objectives of this study were to calculate the clinical trial attrition rates for newly developed drugs for metastatic melanoma and to determine whether the use of biomarkers or targeted therapies can reduce attrition rates.
Analysis of registered clinical trials over the past 15 years yield limited US FDA-approved treatments for metastatic melanoma • Of 1290 records analyzed from the NIH clinical trials database, a total of 197 unique drugs meeting the inclusion criteria entered Phase I of clinical testing for metastatic melanoma. • Out of this total, 93 drugs advanced to Phase II, 12 advanced to Phase III and only four drugs obtained FDA approval for the treatment of metastatic melanoma.
Attribution of failures • Failures can be classified according to medical reasons (i.e., primarily lack of efficacy as opposed to safety or toxicity concerns) and commercial reasons (i.e., lack of funding, an absence of drug development in the previous 2 years or mergers and acquisitions). • Interestingly, if commercial failures were removed from the data set and only medical failures were considered, the overall cumulative success rate for new drug development in metastatic melanoma would increase from 17% to a cumulative rate of 27%. • The cumulative pass rates for biologics and small molecules were 20% and 21%, respectively. • By contrast, despite a high success rate throughout each phase, the cumulative success rate for therapeutic cancer vaccines was 0%, since this class has yet to receive FDA approval.
The role of biomarkers for clinical trial success • Treatments that utilized a biomarker for patient selection had higher cumulative success rates (47%) than those treatments that did not utilize a biomarker (6%). • Three FDA-approved treatments (i.e., dabrafenib, trametinib and vemurafenib) used the B-Raf biomarker, while ipilimumab was the only treatment that was FDA approved and did not utilize a biomarker. • However, the small sample size for therapies that utilized biomarkers is a limitation when interpreting these results. • B-Raf mutations are also prevalent in other cancers; however, dabrafenib, trametinib and vemurafenib are the only products approved for use exclusively in B-Raf-positive melanoma patients. • Out of the 31 compounds that utilized biomarkers, only 15 were validated biomarkers, with 93% of the validated biomarkers being represented by B-Raf. The remaining biomarkers were novel biomarkers and were not approved in any other indication.
Conclusion • Given recent FDA approvals for treatments targeting metastatic melanoma, the overall clinical trial success rate for metastatic melanoma was similar to the industry average. • The higher cumulative success rates associated with the use of biomarkers in metastatic melanoma adds to the growing body of evidence suggesting that biomarkers may improve clinical trial transition rates.
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Parker JL, Zhang ZY, Buckstein R. Clinical trial risk in non-Hodgkin’s lymphoma: endpoint and target selection. J. Pharm. Pharm. Sci. 14(2), 227–235 (2011).
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US FDA. Frequently asked questions about therapeutic biological products. www.fda.gov
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US FDA. Guidance for industry (draft): clinical considerations for therapeutic cancer vaccines. www.fda.gov
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US FDA. Guidance for industry: qualification process for drug development tools. www.fda.gov
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Wright CJ, McCormack PL. Trametinib. First global approval. Drugs 73(11), 1245–1254 (2013).
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Reid GGJ, Bin Yameer TA, Parker JL. Impact of biomarkers on clinical trial risk. Pharmacogenomics 14(13), 1645–1658 (2013).
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
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Gray-Schopfer V, Wellbrock C, Marais R. Melanoma biology and new targeted therapy. Nature 445(7130), 851–857 (2007).
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Klebanoff CA, Acquavella N, Yu Z, Restifo NP. Therapeutic cancer vaccines: are we there yet? Immunol. Rev. 239(1), 27–44 (2011).
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McDermott D, Haanen J, Chen TT, Lorigan P, O’Day S. Efficacy and safety of ipilimumab in metastatic melanoma patients surviving more than 2 years following treatment in a Phase III trial (MDX010–20). Ann. Oncol. 24(10), 2694–2698 (2013).
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
Given the high morbidity and mortality associated with metastatic melanoma, considerable attention has been paid to identifying potential therapies. Until recently, few therapies have been specifically approved for treating metastatic melanoma. In an attempt to increase clinical trial successes, many therapies are implementing biomarkers for patient stratification. This strategy narrows down the population in an effort to identify appropriate subpopulations that have increased efficacy or fewer safety concerns. However, the addition of a biomarker constitutes an additional risk to clinical development and may therefore increase the overall clinical trial risk. Here, we examine the clinical trial success rate for therapies targeting metastatic melanoma. In addition, we identify the impact that biomarkers have had on the clinical development of this disease. Keywords: biomarker • clinical trial risk • drug approval • drug development • metastatic melanoma
In the USA, there will be an estimated 76,100 new cases of melanoma and 9710 deaths due to the disease in 2014. Currently, the average survival rate for patients with metastatic melanoma is only 6–12 months [1] . Despite a modest increase in the incidence of melanoma over the past 30 years in developed countries due to benign lesions [2] , there is high morbidity and mortality associated with the advanced stages of the disease [3] . In addition, the later stages of the disease impart a high healthcare cost [4] . Patients with stage III or IV melanoma only account for 15.2% of all patients diagnosed with melanoma, yet account for 48% of total melanoma costs [5] . Therefore, management of late-stage melanoma has a significant impact on the healthcare system. Furthermore, there have been few new drug approvals specifically for treating metastatic melanoma until recently [6] . At the same time, clinical development has struggled over the past several decades as the number of approved pharmaceutical therapies by the US FDA has not kept up with the
10.2217/BMM.14.80 © 2015 Future Medicine Ltd
increasing costs of developing pharmaceutical treatments [7] . Failures during clinical trials greatly contribute to the rising costs and resources during research and development, and there has subsequently been a focus on minimizing potential clinical failures by industry and physicians alike [7,8] . One such mechanism has been the implementation of biomarkers during clinical development. The FDA has defined a biomarker as “an indicator of normal biological processes, pathogenic processes, and/or response to therapeutic or other interventions” [9] . There are a variety of roles that biomarkers can take in medicine, including pharmacodynamic, predictive, prognostic and surrogate biomarkers [10] . It is thought that utilizing a biomarker that narrows the patient population can increase the probability of treatment success by more accurately identifying appropriate subpopulations that have increased efficacy or fewer safety concerns [11] . However, a recent review highlighted that biomarkers may inherently add risk into the clinical development of a therapy [12] .
Biomark. Med. (2015) 9(1), 13–23
Daniel A Rubinger1, Sarah S Hollmann1, Viktoria Serdetchnaia1, D Scott Ernst2 & Jayson L Parker*,1 Biology Department, University of Toronto Mississauga, William Davis Building, Room 2071, Mississauga, ON, L5L 1C6, Canada 2 Division of Medical Oncology, London Regional Cancer Program, 790 Commissioners Road East, London, ON, N6A 4L6, Canada 3 Hoffmann-La Roche, 2455 Meadowpine Boulevard, Mississauga, ON, L5N 6L7, Canada *Author for correspondence: Tel.: +1 289 337 6194 Fax: +1 905 569 4738 jayson.parker@ utoronto.ca 1
part of
ISSN 1752-0363
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Systematic Review Rubinger, Hollmann, Serdetchnaia, Ernst & Parker Analyses investigating clinical trial success rates for new drug development for cancer subtypes are lacking [13–17] . While there are specific studies analyzing the impact of biomarkers in drug development for breast cancer [18] , non-small-cell lung cancer [19] and in oncology as a whole [16] , there are no systematic analyses to date of the impact of biomarkers on clinical success rates in metastatic melanoma. A clearer understanding of the risk associated with clinical trial development, specifically in a disease with a heterogeneous patient population, could help clinicians manage resource allocation, patient recruitment and expectations of new treatment effects. This study used a risk-based paradigm of clinical trial design to calculate the clinical trial attrition rates for newly developed drugs for metastatic melanoma. Another objective of this study was to determine whether the use of biomarkers or targeted therapies reduces attrition rates for metastatic melanoma. Materials & methods Study eligibility & primary data source for drug development trials
[28])
or www.findarticles.com. Reference lists of the identified literature were scanned for relevant sources. Clinical trial outcome classification
A simple and transparent rule was used to classify the clinical trial outcomes and is consistent with the methods of previous analyses [18–24] . The phases of development were measured using a standardized definition of success and rested on the following assumptions: a Phase I (or I/II) clinical trial was classified as successful if the drug advanced to Phase II for the same indication. Similarly, a Phase II trial was successful if the drug advanced to Phase III clinical testing. Finally, Phase III clinical testing was successful if the drug received approval by the FDA and was available at the time of this analysis. Compounds in active clinical trials were not considered failures or successes. If a treatment had only ongoing trials at a particular phase, that phase was excluded from the analysis while previous phases were deemed successful. For example, if a therapy completed Phase III and had not yet received FDA approval, it was considered to be in Phase III. Conversely, two types of clinical trial failure were defined: medical failure and commercial failure. If a drug failed to meet its primary end point or had significant safety issues in any phases that precluded further testing, it was classified as a medical failure. Commercial failures were those where the drug development program had no public signs of medical failure, yet had no further clinical trial testing for a minimum of 2 years. Commercial failures could be the result of a variety of reasons, including but not limited to competing program priorities, lack of financing or a strategic shift in corporate direction. The clinical trial success rate was calculated by determining the percentage of unique drugs that successfully completed a phase of development out of the total number of drugs tested in a particular phase of development, as demonstrated using the following equation:
Detailed descriptions of the methods used for analysis in this study have been previously described [18–24] . Briefly, data regarding trials that pertained to metastatic melanoma were obtained from the NIH clinical trials database [25] from 1 January 1998 until 1 July 2013. A systematic analysis was conducted from the results of a keyword search for “metastatic melanoma”. Records were assessed for eligibility by two independent investigators. Disagreements between reviewers regarding study inclusion were resolved through c onsensus. Trials were included if the investigational drug was a new therapy or a combination therapy (i.e., with standard care) and treated patients with unresectable stage III or stage IV melanoma. Trials conducted internationally were included if they were registered on the NIH clinical trials database [25] . In addition, trials that were studied in Phase I in all solid tumors and subsequently studied in later phases in advanced melanoma were Success rate for Phase x = included. Trials were excluded from the analysis if they: (# of drugs that passed to Phase x + 1) initiated their Phase I trial for this indication before (# of drugs that pssed to Phase x + 1) + (# drugs that filed t Phase x) 1998; were not industry sponsored; did not treat outcomes related to survival (applicable to Phase II or III trials only); or contained trials for topical therapies or Drugs that were ongoing in Phase x were excluded new formulations of previously approved drugs. in the transition rate for Phase x. The cumulative success rate refers to the probability of completing all the Additional databases & online tools phases of clinical trial testing (i.e., the product of the Additional searches using online databases were used individual probabilities of success for each phase). to supplement the trial information obtained from the NIH clinical trials database [25] . The searches included Compound & company classification publicly available sites as well as Archive-It [26] , PR A single therapy was considered to be a monotherapy news wire (Factiva [27]), Business Wire (Proquest 5000 while a trial containing more than one type of treat-
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
ment was considered to be a combination therapy if it included two unique compounds or the addition of a unique compound to the standard of care. Drugs were also classified as either a small molecule, biologic or therapeutic vaccine. Small molecule drugs were considered as the ‘traditional’ chemically synthesized compounds in drug development. By contrast, biologics were defined according to the classification by the FDA as being “derived from living material – human, animal, or microorganism” [29] . Therapeutic vaccines were classified according to FDA guidance as products “intended to be administered to patients with an existing cancer for the purpose of treatment” [30] . For the biomarker analysis, only trials that used biomarkers to screen patients were included. This analysis focused exclusively on predictive biomarkers, which are defined as a “baseline characteristic that categorizes patients by their likelihood for response to a particular treatment” [31] . Studies that used biomarkers to confirm the presence of disease were not included in the biomarker arm of analysis. A biomarker that has undergone quantitative testing to determine performance characteristics such as
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sensitivity, specificity and reproducibility is called a “validated biomarker” [32] . Ownership of each drug entity was categorized according to its Phase I ownership as either a ‘biotechnology’ or a ‘pharmaceutical’. Firms were considered biotechnology companies if they were listed in the NASDAQ biotechnology index at the time of Phase I initiation of the drug program. Companies not listed on the index yet with a market capitalization of over US$1 billion were classified as pharmaceutical companies. Companies that did not meet the above criteria were not classified. For combination products that included a biotechnology and pharmaceutical company, the assumption was that the biotechnology company initiated the partnership. Statistical methods
A 95% CI based on the normal approximation for binomial random variables was calculated for each analysis. Since this assumption is considered valid only for large n values, we have chosen not to employ the term ‘statistically significant’, but rather to discuss the uncertainty associated with the results.
100 87 90
Melanoma
n = 197
Industry
Transition probability (%)
80 70
64
60
66
58 n = 93
50 39
40
33 n = 12
30
17 n=4 16
20 10 0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 1. Clinical trial success rates. Drugs that entered Phase I clinical testing during or after 1998 were tracked up until 1 July 2013. The percentages reported represent the probabilities of the successful completion of the drugs at the current phase and advancement to the next phase of clinical testing (or approval if currently in Phase III). The cumulative success rate represents the product of probabilities for each prior phase. Metastatic melanoma data are compared with the industry expectations described by DiMasi and colleagues [14] . The error bars represent the 95% CIs.
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180
171 Progressed to next phase
160
Medical failures Commercial failures
140
Products (n)
120 100 80 54
60 40
22
19
20
17
7
4
0 Phase Ι (n = 197)
Phase ΙΙ (n = 93)
6
2
Phase ΙΙΙ (n = 12)
Figure 2. Classification of the types of clinical trial failure according to medical or commercial considerations in the failure. A successful drug is one that continued on to the next phase. For example, in Phase I, 171 drug candidates moved on to Phase II trials, while seven failed because of medical reasons and 19 drugs failed because of commercial reasons. The n values above the bars indicate the number of drugs for each area, while the values on the axis indicate the total number drugs in the current phase of development.
Results Clinical trials reporting drug development in late-stage melanoma
Applying the search criteria for the keyword “metastatic melanoma” in the NIH clinical trials database [25] resulted in 1290 records. A unique drug usually accounted for multiple recorded studies. A total of 197 unique drugs that entered Phase I of clinical testing for metastatic melanoma met the inclusion criteria. Out of this total, 93 drugs advanced from Phase I to Phase II and 12 advanced to Phase III. A total of 78 drugs were in ongoing clinical development in Phase II, while a total of 42 drugs were considered to have ongoing studies in Phase III. Only four drugs, dabrafenib (Tafinlar™; GlaxoSmithKline, UK) [33] , trametinib (Mekinist™; GlaxoSmithKline, UK) [34] , ipilimumab (Yervoy™; Bristol-Myers Squibb, NY, USA) [35] and vemurafenib (Zelboraf™; Hoffmann-La Roche, Switzerland) [36] obtained FDA approval for the treatment of metastatic melanoma. Clinical trial phase pass rates & overall drug success
The clinical trial success rates in metastatic melanoma were compared with a previously reported industry average (Figure 1) [14] . The success rate for Phase I was 87%, for Phase II was 58% and for Phase III was 33%. The trial success rates for metastatic melanoma were
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greater than the industry standard for Phase I and II; however, the metastatic melanoma Phase III success rate (33%) was substantially lower than the industry average (66%). Nevertheless, there was little difference between the overall cumulative success rate for metastatic melanoma of 17% compared with industry expectations of 16%. In addition, there were only 12 treatments classified as a Phase III successes or Phase III failures for metastatic melanoma, resulting in a wide confidence interval for any comparison in Phase III. Types of clinical trial failure
Medical and commercial failure trends were determined for each phase of development (Figure 2) . The most common cause of attrition in Phase I was commercial failures, while in Phase II and III, medical failures were the main cause of clinical trial failure. In this study, early commercial failures were mainly a result of a lack of funding, an absence of drug development in the previous 2 years or mergers and acquisitions (results not shown). Finally, the vast majority of medical failures were due to a lack of efficacy as opposed to safety or toxicity concerns. If commercial failures were removed from the data set and only medical failures were considered, the overall cumulative success rate for new drug development in metastatic melanoma would increase from 17% to a cumulative rate of 27%.
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
Clinical trial failure by type of therapy
The success rates in metastatic melanoma by monotherapy or combination therapy were also elucidated (Figure 3) . An example of monotherapy would be vemurafenib alone, while an example of combination therapy would be vemurafenib and bevacizumab, a novel therapy for melanoma. Overall, the rates for each phase were similar; however, given that there are no combination products approved in metastatic melanoma to date, the cumulative success rate for combination therapy was 0%. Given the low number of studies in Phase III, the confidence intervals around the Phase III success rates are quite wide. Clinical trial failure & the effect of drug type
In an effort to ascertain the impact of drug type on the failure rate, the success rates were stratified by the drug type: biologic, small molecule and therapeutic vaccines (Figure 4) . The majority of drugs in Phase I were small molecules (112), followed by biologics (64). The cumulative pass rates for biologics and small molecules were 20% and 21%, respectively. Despite a high success rate throughout each phase, the cumulative success rate for therapeutic cancer vaccines was 0%, since this class has yet to receive FDA approval in metastatic
100 90
melanoma. Similar to the other analyses, the low number of studies in Phase III resulted in considerable uncertainty around the Phase III success rates. Clinical trial failure & the use of biomarkers
Overall, treatments incorporating biomarkers had a higher cumulative success rate (47%) compared with non-biomarker therapies (6%), as observed in Figure 5. However, there was a very small sample size for therapies that utilized biomarkers, resulting in wide confidence intervals. Ipilimumab was the only therapy that did not involve the use of a biomarker and was approved for metastatic melanoma. By contrast, dabrafenib, trametinib and vemurafenib all require testing for B-Raf mutations. Table 1 lists the types of therapies that utilized biomarkers as well as whether the biomarkers were approved for use in another FDA-approved product. For example, B-Raf mutations are also prevalent in other cancers; however, dabrafenib, trametinib and vemurafenib are the only products approved for use exclusively in B-Raf-positive melanoma patients. Out of the 31 compounds that utilized biomarkers, only 15 were validated biomarkers, with 93% of the validated biomarkers being represented by B-Raf. The remaining biomarkers were novel biomarkers and were not approved in any other indication.
92 n = 63 87 n = 197 83 n = 127
Melanoma (total) Melanoma (monotherapy) Melanoma (combination therapy)
Transition probability (%)
80 70
62 58 n = 60 57 n = 30 n = 93
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44 n=9 33 n = 12
40 30
17 n=4
20 10
0 n=3
23 n=4
0 n=0
0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 3. Clinical trial success rates for monotherapy compared with combination therapy. If the study protocol stipulated that the product is administered with another agent (i.e., a chemotherapeutic substance such at dacarbazine), then it was put in the combination therapy group. Drugs that used both regimens were doublecounted. The error bars represent the 95% CIs.
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100 90
89 86 n = 112 n = 64
Biologic Small molecule
76 n = 21
80 Transition probability (%)
82% n = 11
69 n = 29
70
Vaccine 50 33 n=6 n=3
60 47 n = 53
50
20 n=1
40
21 n=3
30 20 10
0 n=3
0 n=0
0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 4. Clinical trial success rates by biologic, small molecule or cancer vaccine. US FDA definitions were utilized for standardization. The transition probability was stratified by the type of molecule. The error bars represent the 95% CIs.
Clinical trial failure by company
Drug sponsorship was classified into pharmaceutical and biotechnology based on Phase I ownership. The clinical trial success rates for Phase I were 91–92% for both types of companies. Biotechnology companies fared slightly better in bringing their products to Phase III, with a Phase II pass rate of 70% compared with only 61% for their pharmaceutical counterparts (results not shown). Pharmaceutical companies had a cumulative success rate of 28%, while biotechnology firms had no successfully approved compounds, resulting in a cumulative success rate of 0%. Out of 197 drugs, 45% emerged from companies that were excluded from the analysis because they were either private companies or had a market capitalization of less than US$1 billion. Discussion There has been some exploration and quantification of clinical trial success rates for the industry overall and broad disease areas including oncology; however, analyses of specific cancers, including metastatic melanoma, are lacking. Using a systematic approach to analyze all of the clinical trials registered in the NIH clinical trials database [25] , a cumulative success rate was calculated to be 17% for metastatic melanoma treatments, which is similar to the industry average of
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16%. Biomarkers were able to substantially increase the success rate to 47% compared with only 6% for drugs that did not use a biomarker. To the authors’ knowledge, this is the first quantitative analysis that measures the magnitude of improvement with biomarkers in metastatic melanoma. This result is in line with an analysis in breast cancer that determined the cumulative success rate using the biomarker HER2 to be 23% compared with only 15% for non-biomarker drug candidates [18] . Similarly, a study investigating the clinical trial failure during non-small-cell lung cancer drug development found a sixfold increase in success rates with biomarker-targeted therapies [19] . A recent review examining the addition of biomarkers to clinical trial development cautions that there may be increased clinical trial risk associated with codevelopment of a therapeutic with a novel biomarker [12] . Proponents for biomarkers advocate that codeveloping a biomarker with a therapy can increase efficacy or decrease safety events that are essential to approval. However, there are several potential complications associated biomarker implementation. For example, the decreased population can make patient recruitment into clinical studies difficult. In addition, stratified biomarkers can increase development costs for regulatory approval of the biomarker diagnostic tests. Finally, because biomarkers must undergo another
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
100
97 n = 31
90
75 n=4 Biomarker
85 n = 166
80 Transition probability (%)
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Non-biomarker 65 n = 17
70
47 n=3
57 n = 76
60 50 40 30
13 n=8
20
6 n=1
10 0 Phase Ι
Phase ΙΙ
Phase ΙΙΙ
Cumulative success rate
Figure 5. Clinical trial success rate in metastatic melanoma based on the utilization of a biomarker for patient selection. The transition probability was stratified by biomarker usage. The error bars represent the 95% CIs.
regulatory pathway to become a companion diagnostic [38] , the addition of a biomarker would theoretically increase clinical trial risk. This study adds to the body of evidence that suggests that the addition of predictive biomarkers may not increase clinical trial risk [12] . The Phase III success rate of only 33% was the primary driver for reducing the cumulative success rate for metastatic melanoma. The main reason for the failure in metastatic melanoma drug development was the high number of medical failures in Phase II and III due to a lack of efficacy. One suggestion is that, similar to the results observed in non-Hodgkin’s lymphoma, Phase II studies that often use surrogate markers may not be able to predict the success rate in Phase III trials compared with Phase II trials that measured survival as a primary outcome. Another option is that melanoma has typically been refractory to traditional treatments that seem to be efficacious in other cancers, which has resulted in difficulties in treating metastatic melanoma [39] . One response has been an emphasis by clinicians and industry to bring forth targeted therapies [40] . This notion can be supported by the increase in cumulative approval rates for drug candidates that utilized biomarkers. With the approval of dabrafenib and trametinib in 2013, as well as further targeted therapies currently close to completing Phase III clinical trial testing (e.g., masitinib from AB Science, France), the future is promising for metastatic melanoma therapies. While therapeutic cancer vaccines have yielded no approvals to date, there has been an emphasis on devel-
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oping immune-based therapies to combat various cancers, including metastatic melanoma [41] . There were only 21 successful therapeutic vaccines that emerged from Phase I. Two failures in Phase III were due to commercial reasons, whether it was a lack of financing (M-Vax™; AVAX Technologies, PA, USA) [42] or a lack of reported development (HSPPC-96, Oncophage®, Agenus Inc., MA, USA) while one was due to a lack of efficacy (MDX-1379 + ipilimumab; Bristol-Myers Squibb) [43] . In addition, there are currently three Phase III programs (Allovectin®-7, Vical, CA, USA; OncoVEXGM-CSF, Amgen, CA, USA; POL-103A, Polynoma LLC, CA, USA) still ongoing. To date, the only therapeutic vaccine approved in oncology is sipuleucel-T (Provenge™; Dendreon Corp., WA, USA) for prostate cancer. The lack of approvals to date may be viewed as an opportunity to continue to critically explore the various different pathways of how immune-based therapies can improve oncology patient outcomes. This study has several limitations, most of which have been described in studies with similar methodologies [18–24] . First, due to the nature of this preliminary study and the small sample sizes observed, this study was a descriptive study and statistical tests were not performed, making it difficult to determine with certainty the implications of this study. The confidence intervals were calculated based on the normal approximation, which may be inaccurate in smaller sample sizes. Specifically, the subgroup analyses could warrant continued investigation over time to
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Table 1. List of therapies that utilized a biomarker for patient selection and whether the biomarker is approved by the US FDA for use in an FDA-approved product. Biomarker type
Biomarker received Biomarker US FDA approval received FDA (melanoma) approval (other)
Melanoma therapy
Aurora kinase
No
No
MLN8237
B-Raf V600 mutation
Yes (melanoma)
Yes
Dabrafenib, ixabepilone, lenvatinib, RO4929097, selumetinib, selumetinib + dacarbazine, sorafenib, tanespimycin, trametinib, trametinib + dabrafenib, vemurafenib, vemurafenib + bevacizumab, vemurafenib + GDC-0973, vemurafenib + ipilimumab
CDK (cyclin D1) overexpression No
No
P276-00
CDK4/6
No
No
PD 0332991
c-Kit-activating mutation
No
Yes (leukemia, other cancers)
Imatinib, masitinib, nilotinib
DDR2 mutation or B-Raf mutation
No
No
Dasatinib
HLA-A*0201 haplotype
No
No
CYT004-MelQbG10, CYT004-MelQbG10 + dacarbazine, MDX-1379 + ipilimumab, MKC1106MT, Synchrotope™ TA2M plasmid DNA vaccine
ICAM-1 overexpression and DAF overexpression
No
No
Coxsackievirus A21
MAGE-A3
No
No
GSK1203486A
N-cadherin overexpression
No
No
ADH-1
NF-κB
No
No
Bortezomib
Biomarker utilization was obtained from the FDA [37].
observe whether the trends seen in this study are consistent and enduring with a greater number of treatments and trials. Future analyses utilizing a statistical model or pooled analysis with other therapy areas may be warranted. Second, it is unknown whether there were additional studies evaluating new treatments that were perhaps not captured through the NIH clinical trials database [25] , and therefore, the success rates described here could be an overestimation. Lastly, assumptions had to be made regarding the reasons for trial failure. While medical failures including a lack of efficacy are transparent, it is unclear from public sources whether there are underlying medical reasons for discontinuation of development, which would otherwise be classified as a commercial failure. Taken together, these results are predictive of potential trends in the risk associated with the clinical trial development of treatments for metastatic melanoma. Conclusion In conclusion, recent approvals have resulted in an overall cumulative success rate for metastatic melanoma similar to the industry average. Similarly to the
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results observed in breast cancer and non-small-cell lung cancer, utilizing predictive biomarkers to stratify the patient population may be a viable option for improving the clinical trial success rate. These findings provide clinicians with a clearer picture of the risk of drug development in these indications to date, and how to identify clinical trials that present the best chances of success for their patients. In addition, data from metastatic melanoma add to the growing body of evidence suggesting that biomarker usage may be beneficial to clinical development. Future perspective These findings provide a benchmark against which future therapies will be compared in terms of analyzing the success of clinical trial testing for metastatic melanoma. Additional research is required to determine which methods in addition to targeted therapy and biomarker stratification can improve clinical trial testing outcomes. With increasing biomarker validation as well as testing of compounds with novel mechanisms of action, it would be useful to repeat this analysis in several years and learn about any changes in the clinical development climate.
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Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma
Acknowledgements The authors would like to thank S Shah (University of Toronto) for his support in updating the data set from the NIH clinical trials database.
Financial & competing interests disclosure DA Rubinger and SS Hollmann have worked in the pharmaceutical industry. M Arundine is currently employed by a pharma-
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ceutical company. JL Parker has worked in the pharmaceutical industry and advises a hedge fund that invests in the health sciences. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
Executive summary Unmet need in metastatic melanoma • There is high morbidity and mortality associated with the advanced stages of melanoma despite only a modest increase in the incidence of melanoma over the past 30 years. • Although patients with stage III or IV melanoma only account for a small proportion of the total number of patients with melanoma (∼15%), their management costs represent almost half of the total costs of treating all patients with melanoma.
Biomarkers may improve clinical development • The implementation of biomarkers in clinical development may identify subpopulations that have increased efficacy or fewer safety concerns. • The objectives of this study were to calculate the clinical trial attrition rates for newly developed drugs for metastatic melanoma and to determine whether the use of biomarkers or targeted therapies can reduce attrition rates.
Analysis of registered clinical trials over the past 15 years yield limited US FDA-approved treatments for metastatic melanoma • Of 1290 records analyzed from the NIH clinical trials database, a total of 197 unique drugs meeting the inclusion criteria entered Phase I of clinical testing for metastatic melanoma. • Out of this total, 93 drugs advanced to Phase II, 12 advanced to Phase III and only four drugs obtained FDA approval for the treatment of metastatic melanoma.
Attribution of failures • Failures can be classified according to medical reasons (i.e., primarily lack of efficacy as opposed to safety or toxicity concerns) and commercial reasons (i.e., lack of funding, an absence of drug development in the previous 2 years or mergers and acquisitions). • Interestingly, if commercial failures were removed from the data set and only medical failures were considered, the overall cumulative success rate for new drug development in metastatic melanoma would increase from 17% to a cumulative rate of 27%. • The cumulative pass rates for biologics and small molecules were 20% and 21%, respectively. • By contrast, despite a high success rate throughout each phase, the cumulative success rate for therapeutic cancer vaccines was 0%, since this class has yet to receive FDA approval.
The role of biomarkers for clinical trial success • Treatments that utilized a biomarker for patient selection had higher cumulative success rates (47%) than those treatments that did not utilize a biomarker (6%). • Three FDA-approved treatments (i.e., dabrafenib, trametinib and vemurafenib) used the B-Raf biomarker, while ipilimumab was the only treatment that was FDA approved and did not utilize a biomarker. • However, the small sample size for therapies that utilized biomarkers is a limitation when interpreting these results. • B-Raf mutations are also prevalent in other cancers; however, dabrafenib, trametinib and vemurafenib are the only products approved for use exclusively in B-Raf-positive melanoma patients. • Out of the 31 compounds that utilized biomarkers, only 15 were validated biomarkers, with 93% of the validated biomarkers being represented by B-Raf. The remaining biomarkers were novel biomarkers and were not approved in any other indication.
Conclusion • Given recent FDA approvals for treatments targeting metastatic melanoma, the overall clinical trial success rate for metastatic melanoma was similar to the industry average. • The higher cumulative success rates associated with the use of biomarkers in metastatic melanoma adds to the growing body of evidence suggesting that biomarkers may improve clinical trial transition rates.
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Systematic Review Rubinger, Hollmann, Serdetchnaia, Ernst & Parker References
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Describes the clinical trial success rates for oncology therapy areas that utilize biomarkers in clinical development.
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