Clinical Approval Success Rates for Investigational Cancer Drugs

Abstract

We examined development risks for new cancer drugs. For the full study period, the estimated clinical approval success rate for cancer compounds was 13.4% (9.9% for the first half of the study period, 19.8% for the second half). Small molecules had a somewhat higher clinical approval success rate than did large molecules (14.3 vs. 11.5%). Compounds studied solely in hematologic indications had markedly higher estimated clinical approval success rates than did compounds studied only in solid tumor indications (36.0 vs. 9.8%). The first, second, and third cancer indications pursued had estimated clinical approval success rates of 9.0, 8.2, and 6.9%, respectively. Success rates of second and third indications were found to be highly dependent on the success or failure of the first indication pursued (54.9 and 42.4%, respectively, for second and third indications if the first indication is a success, but 2.5 and 1.8%, respectively, if the first indication is a failure).

Innovation in the pharmaceutical industry: New estimates of R&D costs

“…One important finding emerging from the survey of cost studies in Table 1 is that clinical success rates are substantially lower for the studies focused on more recent periods. This observed trend is consistent with other analyses of success probabilities (DiMasi et al, 2010;DiMasi et al, 2013;Hay et al, 2014;Paul et al, 2010) and our analysis below. Average R&D (inflationadjusted) cost estimates are also higher for studies focused on more recent periods, suggesting a growth in real R&D costs.…”

Expanding Public-Private Collaborations to Enhance Cancer Drug Development: A Report of the Institute of Medicine's Workshop Series, “Implementing a National Cancer Clinical Trials System for the 21st Century”

“…By 2012, the activities of an operational efficiency working group eliminated redundancy in the review process and reduced median time to trial activation by 50% for phase III trials and 30% for early phase trials [21]. These timelines continue to improve, with a goal of achieving a median time to trial activation of 7 months for phase I and II trials and 10 months for phase III trials [4]. A significant contributor to shortened trial-activation time has been streamlined processes for the two NCI central institutional review boards (IRBs), one for adult trials and one for pediatric trials, in addition to updated consent templates [22].…”

“…Because therapeutic response in the treatment of metastatic disease is often the most rapid path to regulatory approval, there have been relatively few adjuvant treatment trials for solid tumors in recent years. In a study of oncology drug development from 1999 to 2012, DiMasi et al found that of the 77 cancer drugs evaluated in phase III studies of any solid tumor type, only 12 (16%) had been studied in an adjuvant setting [4].…”

“…A better understanding of the signaling pathways that drive malignant behavior has led to a large number of targeted therapeutics available for testing in clinical trials. Of the new oncology drugs that began clinical testing from 1999 to 2004, 449 (72%) were small molecules and 176 (28%) were monoclonal antibodies, recombinant proteins, or biologics [4]. For these agents, the overall clinical success rate of transition from phase I to New Drug Application/ Biologic License Application approval was 13.4%, only slightly less than the 16% success rate for all compounds originated by the top 50 pharmaceutical companies during that time [5].…”

Patient-Derived-Tumor-Xenograft: modeling cancer for basic and translational cancer research

“…Despite remarkable advances, elucidating the mechanisms underlying tumor establishment and progression still appears incomplete [1]. This lack of deep understanding is responsible for the partial success in the cure of cancer patients and our failure to eradicate cancers in the vast majority of patients [2][3][4]. Among many of the caveats, which have weakened major successes, a major issue remains in the lack of reliable models that can extensively reproduce human cancers and all their multifaceted features [3,5].…”