Comparative performance of between-population vaccine allocation strategies with applications for emerging pandemics.

Vaccine allocation decisions during emerging pandemics have proven to be challenging due to competing ethical, practical, and political considerations. Complicating decision making, policy makers need to consider vaccine allocation strategies that balance needs both within and between populations. When vaccine stockpiles are limited, doses should be allocated in locations to maximize their impact. Using a susceptible-exposed-infectious-recovered (SEIR) model we examine optimal vaccine allocation decisions across two populations considering the impact of characteristics of the population (e.g., size, underlying immunity, heterogeneous risk structure, interaction), vaccine (e.g., vaccine efficacy), pathogen (e.g., transmissibility), and delivery (e.g., varying speed and timing of rollout). Across a wide range of characteristics considered, we find that vaccine allocation proportional to population size (i.e., pro-rata allocation) performs either better or comparably to nonproportional allocation strategies in minimizing the cumulative number of infections. These results may argue in favor of sharing of vaccines between locations in the context of an epidemic caused by an emerging pathogen, where many epidemiologic characteristics may not be known.

Evaluation of VTE, MACE, and Serious Infections Among Patients with RA Treated with Baricitinib Compared to TNFi: A Multi-Database Study of Patients in Routine Care Using Disease Registries and Claims Databases.

INTRODUCTION: The aim of this work is to evaluate baricitinib safety with respect to venous thromboembolism (VTE), major adverse cardiovascular events (MACE), and serious infection relative to tumor necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA). METHODS: Patients with RA from 14 real-world data sources (three disease registries, eight commercial and three government health insurance claims databases) in the United States (n = 9), Europe (n = 3), and Japan (n = 2) were analyzed using a new user active comparator design. Propensity score matching (1:1) controlled for potential confounding. Meta-analysis of incidence rate ratios (IRR) and incidence rate differences (IRD) for each outcome, from each data source was executed using modified Poisson regression and Cochran-Mantel-Haenszel analysis. RESULTS: Of 9013 eligible baricitinib-treated patients, 7606 were propensity score-matched with TNFi-treated patients, contributing 5879 and 6512 person-years of baricitinib and TNFi exposure, respectively. Across data sources, 97 patients (56 baricitinib) experienced VTE during follow-up, 93 experienced MACE (54 baricitinib), and 321 experienced serious infection (176 baricitinib). Overall IRRs comparing baricitinib with TNFi treatment were 1.51 (95% CI 1.10, 2.08) for VTE, 1.54 (95% CI 0.93, 2.54) for MACE, and 1.36 (95% CI 0.86, 2.13) for serious infection. IRDs for VTE, MACE, and serious infection, respectively, were 0.26 (95% CI -0.04, 0.57), 0.22 (95% CI -0.07, 0.52), and 0.57 (95% CI -0.07, 1.21) per 100 person-years greater for baricitinib than TNFi. CONCLUSIONS: Overall results suggest increased risk of VTE with baricitinib versus TNFi, with consistent point estimates from the two largest data sources. A numerically greater risk was observed for MACE and serious infection when comparing baricitinib versus TNFi, with different point estimates from the two largest data sources. Findings from this study and their impact on clinical practice should be considered in context of limitations and other evidence regarding the safety and efficacy of baricitinib and other Janus kinase inhibitors. TRIAL REGISTRATION: EU PAS Register ( http://encepp.eu ), identifier #32271.

Comparative performance of between-population vaccine allocation strategies with applications for emerging pandemics.

Vaccine allocation decisions during emerging pandemics have proven to be challenging due to competing ethical, practical, and political considerations. Complicating decision making, policy makers need to consider vaccine allocation strategies that balance needs both within and between populations. Due to limited vaccine stockpiles, vaccine doses should be allocated in locations where their impact will be maximized. Using a susceptible-exposed-infectious-recovered (SEIR) model we examine optimal vaccine allocation decisions across two populations considering the impact of population size, underlying immunity, continuous vaccine roll-out, heterogeneous population risk structure, and differences in disease transmissibility. We find that in the context of an emerging pathogen where many epidemiologic characteristics might not be known, equal vaccine allocation between populations performs optimally in most scenarios. In the specific case considering heterogeneous population risk structure, first targeting individuals at higher risk of transmission or death due to infection leads to equal resource allocation across populations.

Patient Participation in Clinical Trials of Oncology Drugs and Biologics Preceding Approval by the US Food and Drug Administration.

Importance: Several studies have estimated the financial inputs for successful drug development. Such analyses do not capture the large investment that patient study participants commit to drug development. Objective: To estimate the volume of patients required to achieve a first US Food and Drug Administration (FDA) approval for a new anticancer drug or biologic therapy. Design, Setting, and Participants: This cohort study included a random sample of prelicense oncology drugs and biologics with a trial site in the United States that were launched into clinical efficacy testing between January 1, 2006, and December 31, 2010. Drugs and biologics were identified using ClinicalTrials.gov registration records. Total patient enrollment was captured over an 8-year span, and each intervention was classified based on whether it received FDA approval and was deemed as having intermediate or substantial value according to the American Society of Clinical Oncology Value Framework (ASCO-VF) score. Secondarily, the association between patient numbers and intervention characteristics was tested. Data were analyzed in February 2020. Main Outcomes and Measure: The prespecified primary outcome was the number of patients enrolled in prelicense trials per FDA approval. Results: A total of 120 drugs and biologics were included in our study, with 84 (70.0%) targeted agents, 20 (16.7%) immunotherapies, and 71 (59.2%) novel agents. A total of 13 drugs and biologics (10.8%; 95% CI, 5.3%-16.8%) in our sample gained FDA approval within 8 years, of which 1 (7.7%) was deemed of intermediate value and 3 (23.1%) were deemed of substantial value using ASCO-VF scoring. Overall, 158 810 patients were enrolled in 1335 trials testing these drugs and biologics, 47 913 (30.2%) in trials that led to FDA approval and 110 897 (69.8%) in trials that did not. An estimated 12 217 (95% CI, 7970-22 215) patient study participants contributed to prelicense trials per FDA approval. The estimated number of patients needed to produce a single FDA-approved drug or biologic of intermediate or substantial ASCO-VF clinical value was 39 703 (95% CI, 19 391-177 991). Conclusions and Relevance: The results of this cohort study make visible the substantial patient investment required for prelicense oncology drug development. Such analyses can be used to devise policies that maximize the clinical impact of research on a per-patient basis.

Group II Introns Generate Functional Chimeric Relaxase Enzymes with Modified Specificities through Exon Shuffling at Both the RNA and DNA Level.

Group II introns are large self-splicing RNA enzymes with a broad but somewhat irregular phylogenetic distribution. These ancient retromobile elements are the proposed ancestors of approximately half the human genome, including the abundant spliceosomal introns and non-long terminal repeat retrotransposons. In contrast to their eukaryotic derivatives, bacterial group II introns have largely been considered as harmful selfish mobile retroelements that parasitize the genome of their host. As a challenge to this view, we recently uncovered a new intergenic trans-splicing pathway that generates an assortment of mRNA chimeras. The ability of group II introns to combine disparate mRNA fragments was proposed to increase the genetic diversity of the bacterial host by shuffling coding sequences. Here, we show that the Ll.LtrB and Ef.PcfG group II introns from Lactococcus lactis and Enterococcus faecalis respectively can both use the intergenic trans-splicing pathway to catalyze the formation of chimeric relaxase mRNAs and functional proteins. We demonstrated that some of these compound relaxase enzymes yield gain-of-function phenotypes, being significantly more efficient than their precursor wild-type enzymes at supporting bacterial conjugation. We also found that relaxase enzymes with shuffled functional domains are produced in biologically relevant settings under natural expression levels. Finally, we uncovered examples of lactococcal chimeric relaxase genes with junctions exactly at the intron insertion site. Overall, our work demonstrates that the genetic diversity generated by group II introns, at the RNA level by intergenic trans-splicing and at the DNA level by recombination, can yield new functional enzymes with shuffled exons, which can lead to gain-of-function phenotypes.

The proportion of North American cancer trials that evaluate novel targets.

Major advances in cancer care often emerge from the development of novel targets. We randomly sampled 10% of cancer trials on clinicaltrials.gov with start dates 2013-2016 to determine the proportion of trials and research subjects directed at evaluating novel targets. We found that 87 of 378 trials (23.0%) enrolling 9225 of 44,525 patients (20.7%) tested interventions that are directed towards novel targets. 146 of 378 trials (38.6%) enrolling 19,132 of 44,525 patients (43.0%) investigated treatments that were not FDA approved but utilized a previously studied target for treating cancer. Combined, 233 of 378 trials (61.6%) enrolling 28,357 of 44,525 patients (63.9%) investigated treatments that were not FDA approved. Furthermore, 36 of 378 trials (9.5%) enrolling 6592 of 44,525 patients (14.8%) investigated FDA approved anticancer drugs in their approved indication and combination while 109 of 378 trials (28.8%) enrolling 9576 of 44,525 patients (21.5%) investigated FDA approved anticancer drugs outside of their approved indication or combination. Logistic regression found that phase 1 trials were significantly more likely to test novel target interventions than phase 2 and 3 trials (p value = 0.00197 and 0.00130 respectively). Industry sponsored trials were also significantly more likely to involve novel target interventions than non-industry trials (p value <0.001). In conclusion, most cancer trials involve unapproved treatments, but a majority of these treatments are well-characterized or involve a previously studied target to treat cancer.