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Introduction Adverse drug reactions (ADRs) are associated with significant health-related and financial burden, and multiple sources are currently utilized to actively discover them. Social media has been proposed as a potential resource for monitoring ADRs, but drug-specific analytical studies comparing social media with other sources are scarce. Objectives Our objective was to develop methods to compare ADRs mentioned in social media with those in traditional sources: the US FDA Adverse Event Reporting System (FAERS), drug information databases (DIDs), and systematic reviews. Methods A total of 10,188 tweets mentioning adalimumab collected between June 2014 and August 2016 were included. ADRs in the corpus were extracted semi-automatically and manually mapped to standardized concepts in the Unified Medical Language System. ADRs were grouped into 16 biologic categories for comparisons. Frequencies, relative frequencies, disproportionality analyses, and rank ordering were used as metrics. Results There was moderate agreement between ADRs in social media and traditional sources. “Local and injection site reactions” was the top ADR in Twitter, DIDs, and systematic reviews by frequency, ranked frequency, and index ranking. The next highest ADR in Twitter—fatigue—ranked fifth and seventh in FAERS and DIDs. Conclusion Social media posts often express mild and symptomatic ADRs, but rates are measured differently in scientific sources. ADRs in FAERS are reported as absolute numbers, in DIDs as percentages, and in systematic reviews as percentages, risk ratios, or other metrics, which makes comparisons challenging; however, overlap is substantial. Social media analysis facilitates open-ended investigation of patient perspectives and may reveal concepts (e.g. anxiety) not available in traditional sources.

Much of the literature on trends and factors affecting biopharmaceutical innovation has focused overwhelmingly on the development and approval of never-before approved drugs and biologics. Little attention has been paid to new uses for already-approved compounds, which can be an important form of innovation. This paper aimed to determine and analyze recent trends in the number and type of new or modified US indication approvals for drugs and biologics. We also examine regulatory approval-phase times for new-use efficacy supplements and compare them to approval-phase times for original-use approvals over the same period. We developed a data set of efficacy supplements approved by the US Food and Drug Administration (FDA) from 1998 to 2011 that includes information on the type, approval-phase time (time from submission to the FDA of an application for marketing approval to approval of the application), and FDA therapeutic-significance rating for the approved application, which we obtained from an FDA Web site. This data set was merged with a Tufts Center for the Study of Drug Development (CSDD) data set of US new drug and biologics approvals. We developed descriptive statistics on trends in the number and type of new-use efficacy supplements, on US regulatory approval-phase times for the supplements, and on original new drug and biologics approvals over the study period and for the time from original- to new-use approval. The total number of new-use efficacy-supplement approvals did not exhibit a marked trend, but the number of new pediatric-indication approvals increased substantially. Approval-phase times for new-use supplements varied by therapeutic class and FDA therapeutic-significance rating. Mean approval-phase times were highest for central nervous system compounds (13.8 months) and lowest for antineoplastics (8.9 months). The mean time from original to supplement approval was substantially longer for new pediatric indications than for other new uses. Mean approval-phase time during the study period for applications that received a standard review rating from the FDA was substantially shorter for supplements compared to original uses, but the differences for applications that received a priority review rating from the FDA were negligible. Development of and regulatory approval for new uses of already-approved drugs and biologics is an important source of innovation by biopharmaceutical firms. Despite rising development costs, the output of new-use approvals has remained stable in recent years, driven largely by the pursuit of new pediatric indications. FDA approval-phase times have generally declined substantially for all types of applications since the mid-1990s following legislation that provided a new source of income for the agency. However, while the resources needed to review supplemental applications are likely lower in general than for original-use approvals, the approval-phase times for important new uses are no lower than for important original-use applications.

New drugs and biologics have had a tremendous impact on the treatment of many diseases. However, available measures suggest that pharmaceutical innovation has remained relatively flat, despite substantial growth in research and development spending. We review recent literature on pharmaceutical innovation to identify limitations in measuring and assessing innovation, and we describe the framework and collaborative approach we are using to develop more comprehensive, publicly available metrics for innovation. Our research teams at the Brookings Institution and Deerfield Institute are collaborating with experts from multiple areas of drug development and regulatory review to identify and collect comprehensive data elements related to key development and regulatory characteristics for each new molecular entity approved over the past several decades in the United States and the European Union. Subsequent phases of our effort will add data on downstream product use and patient outcomes and will also include drugs that have failed or been abandoned in development. Such a database will enable researchers to better analyze the drivers of drug innovation, trends in the output of new medicines, and the effect of policy efforts designed to improve innovation.

Key Points Pharmaceutical research and development (R&D) has become increasingly challenging for various reasons, including the proliferation of plausible targets to pursue for therapeutic innovation resulting from advances in molecular biology, most of which are yet to be validated. R&D investments tend to focus on new therapeutic targets, which are characterized by high uncertainty and difficulty, but lower expected post-launch competition and higher sales. We find that the reorienting of investments toward high-risk/high-premium targets accounts for most of the recent decline in productivity in pharmaceutical R&D, as measured in terms of attrition rates, development times and the number of NMEs launched. Our analysis also confirms the existence of important differences in the organization of national systems of innovation and regulation in pharmaceuticals. At first glance, the organizations with their headquarters based in European countries are characterized by a higher probability of market launch for compounds entering clinical development. However, when the composition of research portfolios is taken into account, the apparent comparative advantage of European organizations vanishes. By controlling for portfolio composition of research investments, we do not find support to the claim of R&D productivity differences between US and European organizations, as classified according to headquarter location. These findings were confirmed by defining nationality on the basis of the location of patent inventors. When we considered sales of compounds launched in the global marketplace, we found that the average market value of NMEs launched by US companies was higher than European ones. However, the focus on the comparison between Europe and the United States misses an important finding that emerges from our analysis: the most productive organizations in pharmaceutical R&D at present are global companies with innovative activities located on both sides of the Atlantic. Although investment in pharmaceutical research and development (R&D) has increased substantially in recent decades, the lack of a corresponding increase in the output in terms of new drugs being approved indicates that therapeutic innovation has become more challenging. Here, using a large database that contains information on R&D projects for more than 28,000 compounds investigated since 1990, Riccaboni and colleagues examine the factors underlying the decline in R&D productivity, which include an increasing concentration of R&D investments in areas in which the risk of failure is high. Advances in the understanding of the molecular basis of diseases have expanded the number of plausible therapeutic targets for the development of innovative agents in recent decades. However, although investment in pharmaceutical research and development (R&D) has increased substantially in this time, the lack of a corresponding increase in the output in terms of new drugs being approved indicates that therapeutic innovation has become more challenging. Here, using a large database that contains information on R&D projects for more than 28,000 compounds investigated since 1990, we examine the decline of R&D productivity in pharmaceuticals in the past two decades and its determinants. We show that this decline is associated with an increasing concentration of R&D investments in areas in which the risk of failure is high, which correspond to unmet therapeutic needs and unexploited biological mechanisms. We also investigate the potential variations in productivity with regard to the regional location of companies and find that although companies based in the United States and Europe differ in the composition of their R&D portfolios, there is no evidence of any productivity gap.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin – the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as ‘revolutionary’ and ‘disruptive’, is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is ‘fit-for-purpose’ is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

The productivity of the pharmaceutical industry has been widely discussed in recent years, particularly with regard to concerns that substantial expenditures on research and development have failed to translate into approved drugs. Various analyses of this productivity challenge have focused on aspects such as attrition rates at particular clinical phases or the physicochemical properties of drug candidates, but relatively little attention has been paid to how the industry has performed from the standpoint of the choice of therapeutic mechanisms and their intended indications. This article examines what the pharmaceutical industry has achieved in this respect by analysing comprehensive industry-wide data on the mechanism-indication pairs that have been investigated during the past 20 years. Our findings indicate several points and trends that we hope will be useful in understanding and improving the productivity of the industry, including areas in which the industry has had substantial success or failure and the relative extent of novelty in completed and ongoing projects.

In the past two decades, in vitro in vivo correlation (IVIVC) has been considered an important tool for supporting biowaivers, setting dissolution acceptance criteria, and more recently in the Quality by Design (QbD) framework promoting the establishment of clinically meaningful drug product specifications using dissolution as the endpoint. Based on our review experience at the FDA, for the purposes of this article, we analyzed the current state of regulatory submissions containing IVIVC approaches and discussed the successes and failures from the perspectives of study design to methodology. In the past decade, the overall acceptance rate of the IVIVC submissions is about 40%. Moreover, the number of IVIVC studies seen in the submissions per year is not increasing. Establishing clinically meaningful drug product specifications through the linkages between the identified critical quality attributes and in vivo performance is key for developing a quality drug product. To achieve this goal, there is an imminent need for addressing the issues behind a low success rate in IVIVC development. The results from the current analysis revealed that special considerations should be taken in areas such as (1) selection of appropriate number/kind of formulations for IVIVC development/validation, (2) construction of exploratory plots to guide model building and selection, (3) investigation of the reasons of inconclusive predictability, (4) improvement on the quality and richness of the data, and (5) avoidance of over parameterization. The development and incorporation of biopredictive dissolution methods and the use of non-conventional approaches, including mechanistic/physiologically based approaches, should be explored to increase the likelihood of IVIVC success.

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

While multiple pharmacological drugs have been associated with myocarditis, temporal trends and overall mortality have not been reported. Here we report the spectrum and main features of 5108 reports of drug-induced myocarditis, in a worldwide pharmacovigilance analysis, comprising more than 21 million individual-case-safety reports from 1967 to 2020. Significant association between myocarditis and a suspected drug is assessed using disproportionality analyses, which use Bayesian information component estimates. Overall, we identify 62 drugs associated with myocarditis, 41 of which are categorized into 5 main pharmacological classes: antipsychotics ( n  = 3108 reports), salicylates ( n  = 340), antineoplastic-cytotoxics ( n  = 190), antineoplastic-immunotherapies ( n  = 538), and vaccines ( n  = 790). Thirty-eight (61.3%) drugs were not previously reported associated with myocarditis. Antipsychotic was the first (1979) and most reported class ( n  = 3018). In 2019, the two most reported classes were antipsychotics (54.7%) and immunotherapies (29.5%). Time-to-onset between treatment start and myocarditis is 15 [interquartile range: 10; 23] days. Subsequent mortality is 10.3% and differs between drug classes with immunotherapies the highest, 32.5% and salicylates the lowest, 2.6%. These elements highlight the diversity of presentations of myocarditis depending on drug class, and show the emerging role of antineoplastic drugs in the field of drug-induced myocarditis. Multiple drugs have been in the past associated with myocarditis. Here the authors perform a pharmacovigilance study and analyze 5108 reports of drug-induced myocarditis reporting temporal trends and overall mortality and identifying emerging drug classes among the treatments associated with myocarditis.

It takes too long and costs too much to bring new drugs to market. So let's beef up efforts to screen existing drugs for new uses, argue Curtis R. Chong and David J. Sullivan Jr. Second site Drug re discovery is becoming big business. It is so costly to bring a new drug to market that drug companies are looking at their back catalogues and patent expirations with a new eye. As Curtis R. Chong and David J. Sullivan Jr explain, the screening of existing drugs for new activities is a valuable short-cut between the lab and the clinic. And a comprehensive screening campaign could be particularly useful in uncovering treatments for neglected diseases.