Browsing by Subject "United States Food and Drug Administration"

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    5-α reductase inhibitors and prostate cancer prevention: where do we turn now?
    (BMC Med, 2011-09-15) Hamilton, Robert J; Freedland, Stephen J
    With the lifetime risk of being diagnosed with prostate cancer so great, an effective chemopreventive agent could have a profound impact on the lives of men. Despite decades of searching for such an agent, physicians still do not have an approved drug to offer their patients. In this article, we outline current strategies for preventing prostate cancer in general, with a focus on the 5-α-reductase inhibitors (5-ARIs) finasteride and dutasteride. We discuss the two landmark randomized, controlled trials of finasteride and dutasteride, highlighting the controversies stemming from the results, and address the issue of 5-ARI use, including reasons why providers may be hesitant to use these agents for chemoprevention. We further discuss the recent US Food and Drug Administration ruling against the proposed new indication for dutasteride and the change to the labeling of finasteride, both of which were intended to permit physicians to use the drugs for chemoprevention. Finally, we discuss future directions for 5-ARI research.
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    Compliance with results reporting at ClinicalTrials.gov.
    (N Engl J Med, 2015-03-12) Anderson, Monique L; Chiswell, Karen; Peterson, Eric D; Tasneem, Asba; Topping, James; Califf, Robert M
    BACKGROUND: The Food and Drug Administration Amendments Act (FDAAA) mandates timely reporting of results of applicable clinical trials to ClinicalTrials.gov. We characterized the proportion of applicable clinical trials with publicly available results and determined independent factors associated with the reporting of results. METHODS: Using an algorithm based on input from the National Library of Medicine, we identified trials that were likely to be subject to FDAAA provisions (highly likely applicable clinical trials, or HLACTs) from 2008 through 2013. We determined the proportion of HLACTs that reported results within the 12-month interval mandated by the FDAAA or at any time during the 5-year study period. We used regression models to examine characteristics associated with reporting at 12 months and throughout the 5-year study period. RESULTS: From all the trials at ClinicalTrials.gov, we identified 13,327 HLACTs that were terminated or completed from January 1, 2008, through August 31, 2012. Of these trials, 77.4% were classified as drug trials. A total of 36.9% of the trials were phase 2 studies, and 23.4% were phase 3 studies; 65.6% were funded by industry. Only 13.4% of trials reported summary results within 12 months after trial completion, whereas 38.3% reported results at any time up to September 27, 2013. Timely reporting was independently associated with factors such as FDA oversight, a later trial phase, and industry funding. A sample review suggested that 45% of industry-funded trials were not required to report results, as compared with 6% of trials funded by the National Institutes of Health (NIH) and 9% of trials that were funded by other government or academic institutions. CONCLUSIONS: Despite ethical and legal obligations to disclose findings promptly, most HLACTs did not report results to ClinicalTrials.gov in a timely fashion during the study period. Industry-funded trials adhered to legal obligations more often than did trials funded by the NIH or other government or academic institutions. (Funded by the Clinical Trials Transformation Initiative and the NIH.).
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    Data monitoring and interim analyses in the pharmaceutical industry: ethical and logistical considerations.
    (Stat Med, 1993-03) Rockhold, FW; Enas, GG
    The characteristics of data monitoring and the need for the use of data monitoring committees in clinical trials sponsored by the pharmaceutical industry differ from those of trials sponsored by government. Data monitoring is a continuous process in industry trials due to the regulatory requirements and the need to more thoroughly evaluate safety of new compounds. As part of this process, interim analyses are employed to make decisions about treatment effects. In some cases, such analyses may require the use of an external data monitoring committee to assist in the data review, analysis and decision making. A number of examples of interim analyses, with and without data monitoring committees, are discussed. Issues surrounding the need for external data monitoring committees and recommendations are presented. In particular the issues of sponsor participation in the data monitoring committee and controls of the decision making process are considered.
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    Developing drugs for developing countries.
    (Health Aff (Millwood), 2006-03) Ridley, David; Moe, Jeffrey
    Infectious and parasitic diseases create enormous health burdens, but because most of the people suffering from these diseases are poor, little is invested in developing treatments. We propose that developers of treatments for neglected diseases receive a "priority review voucher." The voucher could save an average of one year of U.S. Food and Drug Administration (FDA) review and be sold by the developer to the manufacturer of a blockbuster drug. In a well-functioning market, the voucher would speed access to highly valued treatments. Thus, the voucher could benefit consumers in both developing and developed countries at relatively low cost to the taxpayer.
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    Economic return of clinical trials performed under the pediatric exclusivity program.
    (JAMA, 2007-02-07) Li, Jennifer; Eisenstein, Eric; Reid, Elizabeth; Mangum, Barry; Schulman, Kevin; Goldsmith, John; Murphy, M Dianne; Califf, Robert; Benjamin, Daniel; Jr
    CONTEXT: In 1997, Congress authorized the US Food and Drug Administration (FDA) to grant 6-month extensions of marketing rights through the Pediatric Exclusivity Program if industry sponsors complete FDA-requested pediatric trials. The program has been praised for creating incentives for studies in children and has been criticized as a "windfall" to the innovator drug industry. This critique has been a substantial part of congressional debate on the program, which is due to expire in 2007. OBJECTIVE: To quantify the economic return to industry for completing pediatric exclusivity trials. DESIGN AND SETTING: A cohort study of programs conducted for pediatric exclusivity. Nine drugs that were granted pediatric exclusivity were selected. From the final study reports submitted to the FDA (2002-2004), key elements of the clinical trial design and study operations were obtained, and the cost of performing each study was estimated and converted into estimates of after-tax cash outflows. Three-year market sales were obtained and converted into estimates of after-tax cash inflows based on 6 months of additional market protection. Net economic return (cash inflows minus outflows) and net return-to-costs ratio (net economic return divided by cash outflows) for each product were then calculated. MAIN OUTCOME MEASURES: Net economic return and net return-to-cost ratio. RESULTS: The indications studied reflect a broad representation of the program: asthma, tumors, attention-deficit/hyperactivity disorder, hypertension, depression/generalized anxiety disorder, diabetes mellitus, gastroesophageal reflux, bacterial infection, and bone mineralization. The distribution of net economic return for 6 months of exclusivity varied substantially among products (net economic return ranged from -$8.9 million to $507.9 million and net return-to-cost ratio ranged from -0.68 to 73.63). CONCLUSIONS: The economic return for pediatric exclusivity is variable. As an incentive to complete much-needed clinical trials in children, pediatric exclusivity can generate lucrative returns or produce more modest returns on investment.
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    Issues in regulatory guidelines for data monitoring committees.
    (Clin Trials, 2004) DeMets, David; Califf, Robert; Dixon, Dennis; Ellenberg, Susan; Fleming, Thomas; Held, Peter; Julian, Desmond; Kaplan, Richard; Levine, Robert; Neaton, James; Packer, Milton; Pocock, Stuart; Rockhold, Frank; Seto, Belinda; Siegel, Jay; Snapinn, Steve; Stump, David; Temple, Robert; Whitley, Richard
    As clinical trials have emerged as the major research method for evaluating new interventions, the process for monitoring intervention safety and benefit has also evolved. The Data Monitoring Committee (DMC) has become the standard approach to implement this responsibility for many Phase III trials. Recent draft guidelines on the operation of DMCs by the Food and Drug Administration (FDA) have raised issues that need further clarification or discussion, especially for industry sponsored trials. These include, the time when DMCs are needed, the role of the independent statistician to support the DMC, and sponsor participation at DMC meetings. This paper provides an overview of these issues, based on the discussions at the January, 2003 workshop sponsored by Duke Clinical Research Institute.
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    Participation of the elderly, women, and minorities in pivotal trials supporting 2011-2013 U.S. Food and Drug Administration approvals.
    (Trials, 2016-04) Downing, Nicholas S; Shah, Nilay D; Neiman, Joseph H; Aminawung, Jenerius A; Krumholz, Harlan M; Ross, Joseph S

    Background

    Pivotal trials, the clinical studies that inform U.S. Food and Drug Administration (FDA) approval decisions, provide the foundational evidence supporting the safety and efficacy of novel therapeutics. We determined the representation of the elderly, women, and patients from racial and ethnic minorities in pivotal trials and whether the FDA is making subgroup efficacy analyses among these subpopulations available to the public.

    Methods

    We conducted a cross-sectional study of novel therapeutics approved by the FDA between 2011 and 2013. Using publicly available FDA documents, we collected information on the demographic characteristics of pivotal trial participants (age ≥65 years, sex [male, female], race [white, black, Asian, other], and ethnicity [Hispanic, non-Hispanic]) and determined the availability of subgroup analyses by age, sex, race, and ethnicity.

    Results

    We identified 86 novel therapeutic that were approved by the FDA between 2011 and 2013 for 92 indications on the basis of 206 pivotal trials. The median age of pivotal trial patients was 53.1 years (interquartile range 40.6-60.6), and the mean proportion of patients ≥65 years of age was 28.9 % (95 % CI 23.5-34.4 %). Similar proportions of pivotal trial participants were male (mean 50.3 %, 95 % CI 45.3-55.2 %) and female (mean 49.7 %, 95 % CI 44.7-54.7 %). Most participants were white (mean 79.2 %, 95 % CI 75.9-82.6 %), while the mean proportion of black patients was 7.4 % (95 % CI 5.5-9.3 %), that of Asian patients was 7.4 % (95 % CI 5.2-9.7 %), and that of patients of other races was 5.9 % (95 % CI 4.4-7.5 %). Information about ethnicity was available for only 59.8 % of indications, and where such data were available, the mean proportion of Hispanic participants was 13.3 % (95 % CI 10.3-16.3 %). FDA reviewers performed and made available subgroup efficacy analyses by age, sex, and race for at least one of the pivotal trials used as the basis of approval for over 80 % of indications.

    Conclusions

    Although women are equally represented in pivotal trials supporting recent novel therapeutic approvals by the FDA, elderly patients and those from racial and ethnic minorities are underrepresented. FDA reviewers generally perform subgroup efficacy analyses by age, sex, and race and make these subgroup analyses available to the public.
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    Priorities for the Priority Review Voucher.
    (Am J Trop Med Hyg, 2017-01-11) Ridley, David B
    The U.S. Congress created the priority review voucher program in 2007 to encourage development of drugs for neglected diseases. Under the voucher program, the developer of a drug for a neglected or rare pediatric disease that is approved by the U.S. Food and Drug Administration receives a bonus priority review voucher for another drug. As of 2016, four vouchers have sold for an average price of $200 million. Recent experience with the voucher program indicates strengths and weaknesses of the program, as well as a need for legislative changes.
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    Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities.
    (Radiology, 2011-06) Buckler, Andrew J; Bresolin, Linda; Dunnick, N Reed; Sullivan, Daniel C; Aerts, Hugo JWL; Bendriem, Bernard; Bendtsen, Claus; Boellaard, Ronald; Boone, John M; Cole, Patricia E; Conklin, James J; Dorfman, Gary S; Douglas, Pamela S; Eidsaunet, Willy; Elsinger, Cathy; Frank, Richard A; Gatsonis, Constantine; Giger, Maryellen L; Gupta, Sandeep N; Gustafson, David; Hoekstra, Otto S; Jackson, Edward F; Karam, Lisa; Kelloff, Gary J; Kinahan, Paul E; McLennan, Geoffrey; Miller, Colin G; Mozley, P David; Muller, Keith E; Patt, Rick; Raunig, David; Rosen, Mark; Rupani, Haren; Schwartz, Lawrence H; Siegel, Barry A; Sorensen, A Gregory; Wahl, Richard L; Waterton, John C; Wolf, Walter; Zahlmann, Gudrun; Zimmerman, Brian
    Quantitative imaging biomarkers could speed the development of new treatments for unmet medical needs and improve routine clinical care. However, it is not clear how the various regulatory and nonregulatory (eg, reimbursement) processes (often referred to as pathways) relate, nor is it clear which data need to be collected to support these different pathways most efficiently, given the time- and cost-intensive nature of doing so. The purpose of this article is to describe current thinking regarding these pathways emerging from diverse stakeholders interested and active in the definition, validation, and qualification of quantitative imaging biomarkers and to propose processes to facilitate the development and use of quantitative imaging biomarkers. A flexible framework is described that may be adapted for each imaging application, providing mechanisms that can be used to develop, assess, and evaluate relevant biomarkers. From this framework, processes can be mapped that would be applicable to both imaging product development and to quantitative imaging biomarker development aimed at increasing the effectiveness and availability of quantitative imaging.http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100800/-/DC1.
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    Regulatory and cost barriers are likely to limit biosimilar development and expected savings in the near future.
    (Health Aff (Millwood), 2014-06) Grabowski, Henry G; Guha, Rahul; Salgado, Maria
    In March 2010 Congress established an abbreviated Food and Drug Administration approval pathway for biosimilars-drugs that are very similar but not identical to a reference biological product and cost less. Because bringing biosimilars to the market currently requires large investments of money, fewer biosimilars are expected to enter the biologics market than has been the case with generic drugs entering the small-molecule drug market. Additionally, given the high regulatory hurdles to obtaining interchangeability-which would allow pharmacists to substitute a biosimilar for its reference product, subject to evolving state substitution laws-most biosimilars will likely compete as therapeutic alternatives instead of as therapeutic equivalents. In other words, biosimilars will need to compete with their reference product on the basis of quality; price; and manufacturer's reputation with physicians, insurers, and patient groups. Biosimilars also will face dynamic competition from new biologics in the same therapeutic class-including "biobetters," which offer incremental improvements on reference products, such as extended duration of action. The prospects for significant cost savings from the use of biosimilars appear to be limited for the next several years, but their use should increase over time because of both demand- and supply-side factors.
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    Returns to R&D on new drug introductions in the 1980s.
    (J Health Econ, 1994-12) Grabowski, HG; Vernon, JM
    This study finds that the mean IRR for 1980-84 U.S. new drug introductions is 11.1%, and the mean NPV is 22 million (1990 dollars). The distribution of returns is highly skewed. The results are robust to plausible changes in the baseline assumptions. Our work is also compared with a 1993 study by the OTA. Despite some important differences in assumptions, both studies imply that returns for the average NCE are within one percentage point of the industry's cost of capital. This is much less than what is typically observed in analyses based on accounting data.
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    The role of machine learning in clinical research: transforming the future of evidence generation.
    (Trials, 2021-08) Weissler, E Hope; Naumann, Tristan; Andersson, Tomas; Ranganath, Rajesh; Elemento, Olivier; Luo, Yuan; Freitag, Daniel F; Benoit, James; Hughes, Michael C; Khan, Faisal; Slater, Paul; Shameer, Khader; Roe, Matthew; Hutchison, Emmette; Kollins, Scott H; Broedl, Uli; Meng, Zhaoling; Wong, Jennifer L; Curtis, Lesley; Huang, Erich; Ghassemi, Marzyeh

    Background

    Interest in the application of machine learning (ML) to the design, conduct, and analysis of clinical trials has grown, but the evidence base for such applications has not been surveyed. This manuscript reviews the proceedings of a multi-stakeholder conference to discuss the current and future state of ML for clinical research. Key areas of clinical trial methodology in which ML holds particular promise and priority areas for further investigation are presented alongside a narrative review of evidence supporting the use of ML across the clinical trial spectrum.

    Results

    Conference attendees included stakeholders, such as biomedical and ML researchers, representatives from the US Food and Drug Administration (FDA), artificial intelligence technology and data analytics companies, non-profit organizations, patient advocacy groups, and pharmaceutical companies. ML contributions to clinical research were highlighted in the pre-trial phase, cohort selection and participant management, and data collection and analysis. A particular focus was paid to the operational and philosophical barriers to ML in clinical research. Peer-reviewed evidence was noted to be lacking in several areas.

    Conclusions

    ML holds great promise for improving the efficiency and quality of clinical research, but substantial barriers remain, the surmounting of which will require addressing significant gaps in evidence.
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    Use of Quantile Treatment Effects Analysis to Describe Antidepressant Response in Randomized Clinical Trials Submitted to the US Food and Drug Administration: A Secondary Analysis of Pooled Trial Data.
    (JAMA network open, 2023-06) Meyerson, William U; Pieper, Carl F; Hoyle, Rick H

    Importance

    Major depressive disorder (MDD) is a leading cause of global distress and disability. Earlier studies have indicated that antidepressant therapy confers a modest reduction in depressive symptoms on average, but the distribution of this reduction requires more research.

    Objective

    To estimate the distribution of antidepressant response by depression severity.

    Design, setting, and participants

    In this secondary analysis of pooled trial data, quantile treatment effect (QTE) analysis was conducted from the US Food and Drug Administration (FDA) database of antidepressant monotherapy for patients with MDD, encompassing 232 positive and negative trials submitted to the FDA between 1979 and 2016. Analysis was restricted to participants with severe MDD (17-item Hamilton Rating Scale for Depression [HAMD-17] score ≥20). Data analysis was conducted from August 16, 2022, to April 16, 2023.

    Intervention

    Antidepressant monotherapy compared with placebo.

    Main outcomes and measures

    The distribution of percentage depression response was compared between the pooled treatment arm and pooled placebo arm. Percentage depression response was defined as 1 minus the ratio of final depression severity to baseline depression severity, expressed as a percentage. Depression severity was reported in HAMD-17-equivalent units.

    Results

    A total of 57 313 participants with severe depression were included in the analysis. There was no significant imbalance in baseline depression severity between the pooled treatment arm and pooled placebo arm, with a mean HAMD-17 difference of 0.037 points (P = .11 by Wilcoxon rank sum test). An interaction term test for rank similarity did not reject the rank similarity governing percentage depression response (P > .99). The entire distribution of depression response was more favorable in the pooled treatment arm than in the pooled placebo arm. The maximum separation between treatment and placebo occurred at the 55th quantile and corresponded to an absolute improvement in depression due to active drug of 13.5% (95% CI, 12.4%-14.4%). The separation between treatment and placebo diminished near the tails of the distribution.

    Conclusions and relevance

    In this QTE analysis of pooled clinical trial data from the FDA, antidepressants were found to confer a small reduction in depression severity that was broadly distributed across participants with severe depression. Alternatively, if the assumptions behind the QTE analysis are not met, then the data are also compatible with antidepressants eliciting more complete response in a smaller subset of participants than is suggested by this QTE analysis.