IntroductionThe under-reporting of adverse drug events (ADEs) is an international health concern. A number of studies have assessed the root causes but, to our knowledge, little information exists relating under-reporting to practices and systems used for the recording and tracking of drug‐related adverse event observations in ambulatory settings, institutional settings, and retail pharmacies.ObjectivesOur objective was to explore the process for reporting ADEs in US hospitals, ambulatory settings, and retail pharmacies; to explore gaps and inconsistencies in the reporting process; and to identify the causes of under-reporting ADEs in these settings.MethodsThe Tufts Center for the Study of Drug Development (Tufts CSDD) interviewed 11 thought leaders and conducted a survey between May and August 2014 among US-based healthcare providers (HCPs) in diverse settings to assess their experiences with, and processes for, reporting ADEs.ResultsA total of 123 individuals completed the survey (42 % were pharmacists; 27 % were nurses; 15 % were physicians; and 16 % were classified as ‘other’). HCPs indicated that the main reasons for under-reporting were difficulty in determining the cause of the ADE, given that most patients receive multiple therapies simultaneously (66 % of respondents); that HCPs lack sufficient time to report ADEs (63 % of respondents); poor integration of ADE-reporting systems (53 % of respondents); and uncertainty about reporting procedures (52 % of respondents).DiscussionThe results of this pilot study identify that key factors contributing to the under-reporting of ADEs relate to a lack of standardized process, a lack of training and education, and a lack of integrated health information technologies.Electronic supplementary materialThe online version of this article (doi:10.1007/s40264-016-0455-4) contains supplementary material, which is available to authorized users.

The study findings provide insights into optimizing development planning, protocol design, and clinical trial management practices.

We developed an algorithm (ANDI) for predicting regulatory marketing approval for new cancer drugs after phase II testing has been conducted, with the objective of providing a tool to improve drug portfolio decision-making. We examined 98 oncology drugs from the top 50 pharmaceutical companies (2006 sales) that first entered clinical development from 1999 to 2007, had been taken to at least phase II development, and had a known final outcome (research abandonment or regulatory marketing approval). Data on safety, efficacy, operational, market, and company characteristics were obtained from public sources. Logistic regression and machine-learning methods were used to provide an unbiased approach to assess overall predictability and to identify the most important individual predictors. We found that a simple four-factor model (activity, number of patients in the pivotal phase II trial, phase II duration, and a prevalence-related measure) had high sensitivity and specificity for predicting regulatory marketing approval.

We gathered data from three pipeline databases and other public sources on development stage and clinical trial metrics for 1,914 investigational drugs, biologics, and vaccines and 2,769 clinical trials intended to treat a wide variety of infectious diseases. We included new molecular entities (NMEs), new formulations, and new combinations. Clinical trial times decreased from 2000–2008 to 2009–2017, varied by disease class, and were longer for trials with more subjects or more sites. Clinical approval success rates were higher for this set of diseases than those in the published literature for drugs across all therapeutic categories. NMEs to treat HIV had a success rate (16.0%) that was similar to those for drugs in general, whereas NME success rates for influenza and pneumonia were much higher (48.1% and 50.5%, respectively).

The Food and Drug Administration's MedWatch system--a voluntary surveillance program--received 600,000 adverse event reports on marketed drugs and devices in 2011. The Food and Drug Administration credits the MedWatch system with improving awareness, and expediting early detection, of drug and device risks and in illuminating the adoption of medical treatments. Reporting bias has been acknowledged as a limitation of the MedWatch system. No systematic assessment of the accuracy and completeness of adverse event reporting has been conducted, yet inaccurate adverse event reporting may lead drug safety professionals to draw incorrect conclusions, manufacturers may be wrongly forced to suspend and withdraw medications and interventions, health professionals may mistakenly alter their clinical practices, and patients may be denied safe and effective treatments. In 2011, the Tufts Center for the Study of Drug Development gathered and analyzed 10.2 million adverse event reports filed with the MedWatch system. Patient information was generally complete and accurate. Suspect product information, on the other hand, showed high levels of incomplete and inaccurate data. Start and end dates of suspect product use had 37% and 23% completion rates, respectively. Dosage level was completed only 31% of the time, and product lot numbers had only a 9% completion rate. More than 25% of the names of reported suspect products were inaccurate, and 31% of suspect product start dates were inaccurate. Higher levels of completion and accuracy were associated with reports filed closer to the date when the adverse event was observed. Implications of the results and suggested improvements are discussed.

Although most research professionals believe that protocol designs contain a growing number of unnecessary and redundant procedures generating unused data, incurring high cost, and jeopardizing study success, there are no published studies systematically examining this issue. Between November 2011 and May 2012, Tufts Center for the Study of Drug Development conducted a study among a working group of 15 pharmaceutical companies in which a total of 25,103 individual protocol procedures were evaluated and classified using clinical study reports and analysis plans. The results show that the typical later-stage protocol had an average of 7 objectives and 13 end points of which 53.8% are supplementary. One (24.7%) of every 4 procedures performed per phase-III protocol and 17.7% of all phase-II procedures per protocol were classified as "Noncore" in that they supported supplemental secondary, tertiary, and exploratory end points. For phase-III protocols, 23.6% of all procedures supported regulatory compliance requirements and 15.9% supported those for phase-II protocols. The study also found that on average, $1.7 million (18.5% of the total) is spent in direct costs to administer Noncore procedures per phase-III protocol and $0.3 million (13.1% of the total) in direct costs are spent on Noncore procedures for each phase-II protocol. Based on the results of this study, the total direct cost to perform Noncore procedures for all active annual phase-II and phase-III protocols is conservatively estimated at $3.7 billion annually, not including the indirect costs associated with collecting and managing Noncore procedure data and the ethical costs of exposing study volunteers to unnecessary risks associated with conducting extraneous procedures.

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Key Points Question Is the implementation of the Medicare national coverage determination (NCD) associated with use of next-generation sequencing by insurance and racial and ethnic categories? Findings In this cohort study of 92 687 patients with lung, breast, colon, and skin cancer, NCD implementation was associated with a slower rate of increase in next-generation sequencing use for patients with patient assistance programs compared with Medicare beneficiaries. Implementation of the NCD was not associated with narrowing of racial and ethnic disparities among Medicare beneficiaries alone or the overall insured population. Meaning These findings suggest that implementation of the Medicare NCD for next-generation sequencing did not result in equal increased use across insurance types or racial and ethnic groups.