Pharmacogenomics at the post-pandemic: If not now, then when?
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ABSTRACT:
SUBMITTER: Al-Mahayri ZN
PROVIDER: S-EPMC9549401 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Pharmacogenomics at the post-pandemic: If not now, then when?
Frontiers in pharmacology 20220926
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Project description:Pharmacogenomics of Statin Therapy (POST)
| PRJNA1093552 | ENA
Project description:Pharmacogenomics of Statin Therapy (POST)
| PRJNA1093553 | ENA
Project description:Heart failure is becoming increasingly prevalent in the United States and is a significant cause of morbidity and mortality. Several therapies are currently available to treat this chronic illness; however, clinical response to these treatment options exhibit significant interpatient variation. It is now clearly understood that genetics is a key contributor to diversity in therapeutic response, and evidence that genetic polymorphisms alter the pharmacokinetics, pharmacodynamics, and clinical response of heart failure drugs continues to accumulate. This suggests that pharmacogenomics has the potential to help clinicians improve the management of heart failure by choosing the safest and most effective medications and doses. Unfortunately, despite much supportive data, pharmacogenetic optimization of heart failure treatment regimens is not yet a reality. In order to attenuate the rising burden of heart failure, particularly in the context of the recent paucity of new effective interventions, there is an urgent need to extend pharmacogenetic knowledge and leverage these associations in order to enhance the effectiveness of existing heart failure therapies. This review focuses on the current state of pharmacogenomics in heart failure and provides a glimpse of the aforementioned future needs.
| S-EPMC4329642 | biostudies-literature
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| S-EPMC7557300 | biostudies-literature
Project description:Social distancing through the COVID-19 pandemic has impacted sexuality and relationships, which may also change risk perceptions beyond traditional definitions (e.g. sexually transmitted infections). This study examines risk perceptions related to sexuality during the pandemic. We present qualitative analyses of a survey of adults in the United States (N = 333) to identify impacts of COVID-19 on individuals' risk perceptions. Risky sexual behavior definitions included: (1) COVID-19-related, (2) STI/pregnancy, (3) relationship-related, (4) physical boundaries, (5) drug or alcohol, and (6) multiple risks. Conventional public health messaging may need to incorporate changing risk definitions to address sexual health during the pandemic.
| S-EPMC8685755 | biostudies-literature
Project description:BackgroundInvestment in pandemic preparedness is a long-term gamble, with the return on investment coming at an unknown point in the future. Many countries have chosen to stockpile key resources, and the number of pandemic economic evaluations has risen sharply since 2009. We assess the importance of uncertainty in time-to-pandemic (and associated discounting) in pandemic economic evaluation, a factor frequently neglected in the literature to-date.MethodsWe use a probability tree model and Monte Carlo parameter sampling to consider the cost effectiveness of antiviral stockpiling in Cambodia under parameter uncertainty. Mean elasticity and mutual information (MI) are used to assess the importance of time-to-pandemic compared with other parameters. We also consider the sensitivity to choice of sampling distribution used to model time-to-pandemic uncertainty.ResultsTime-to-pandemic and discount rate are the primary drivers of sensitivity and uncertainty in pandemic cost effectiveness models. Base case cost effectiveness of antiviral stockpiling ranged between is US$112 and US$3599 per DALY averted using historical pandemic intervals for time-to-pandemic. The mean elasticities for time-to-pandemic and discount rate were greater than all other parameters. Similarly, the MI scores for time to pandemic and discount rate were greater than other parameters. Time-to-pandemic and discount rate were key drivers of uncertainty in cost-effectiveness results regardless of time-to-pandemic sampling distribution choice.ConclusionsTime-to-pandemic assumptions can "substantially" affect cost-effectiveness results and, in our model, is a greater contributor to uncertainty in cost-effectiveness results than any other parameter. We strongly recommend that cost-effectiveness models include probabilistic analysis of time-to-pandemic uncertainty.
| S-EPMC7574603 | biostudies-literature
Project description: Not available
| S-EPMC9077025 | biostudies-literature
Project description:ObjectiveClinical trial data sharing has the potential to accelerate scientific progress, answer new lines of scientific inquiry, support reproducibility and prevent redundancy. Vivli, a non-profit organisation, operates a global platform for sharing of individual participant-level trial data and associated documents. Sharing of these data collected from each trial participant enables combining of these data to drive new scientific insights or assess reproducibility-not possible with the aggregate or summary data tables historically made available. We report on our initial experience including key metrics, lessons learned and how we see our role in the data sharing ecosystem. We also describe how Vivli is addressing the needs of the COVID-19 challenge through a new dedicated portal that provides a direct search function for COVID-19 studies, availability for fast-tracked request review and data sharing.Data summaryThe Vivli platform was established in 2018 and has partnered with 28 diverse members from industry, academic institutions, government platforms and non-profit foundations. Currently, 5400 trials representing 3.6 million participants are shared on the platform. From July 2018 to September 2020, Vivli received 201 requests. To date, 106 of 201 requests received approval, 5 have been declined, 27 withdrew and 27 are in the revision stage.ConclusionsThe pandemic has only magnified the necessity for data sharing. If most data are shared and in a manner that allows interoperability, then we have hope of moving towards a cohesive scientific understanding more quickly not only for COVID-19 but also for all diseases. Conversely, if only isolated pockets of data are shared then society loses the opportunity to close vital gaps in our understanding of this rapidly evolving epidemic. This current challenge serves to highlight the value of data sharing platforms-critical enablers that help researchers build on prior knowledge.
| S-EPMC7597502 | biostudies-literature
Project description:Despite the clear need, progress toward a vaccine for congenital cytomegalovirus (CMV) has been slow. However, recent events have provided new interest, and several vaccine candidates are either in clinical trials or the trials are close to starting. In this issue of Clinical and Vaccine Immunology, Schleiss and colleagues show that a nonreplicating lymphocytic choriomeningitis virus (rLCMV)-vectored vaccine expressing CMV glycoprotein B (gB) and/or pp65 induces B and T cells and improves pup survival in a guinea pig model of congenital CMV infection (Clin Vaccine Immunol 24:e00300-16, 2017, https://doi.org/10.1128/CVI.00300-16). The combination vaccine appeared to be the most effective.
| S-EPMC5216425 | biostudies-literature
Project description:Influenza vaccination aims at reducing the incidence of serious disease, complications and death among those with the most risk of severe influenza disease. Influenza vaccine effectiveness (VE) through sentinel surveillance data from the PIDIRAC program (Daily Acute Respiratory Infection Surveillance of Catalonia) during 2010-2011, 2011-2012, and 2012-2013 influenza seasons, with three different predominant circulating influenza virus (IV) types [A(H1N1)pdm09, A(H3N2) and B, respectively] was assessed. The total number of sentinel samples with known vaccination background collected during the study period was 3173, 14.7% of which had received the corresponding seasonal influenza vaccine. 1117 samples (35.2%) were positive for IV. A retrospective negative case control design was used to assess vaccine effectiveness (VE) for the entire period and for each epidemic influenza season. An overall VE of 58.1% (95% CI:46.8-67) was obtained. Differences in VE according to epidemic season were observed, being highest for the 2012-2013 season with predominance of IV type B (69.7% ;95% CI:51.5-81) and for the 2010-2011 season, with predominance of the A(H1N1)pdm09 influenza virus strain (67.2% ;95%CI:49.5-78.8) and lowest for the 2011-2012 season with A(H3N2) subtype predominance (34.2% ;95%CI:4.5-54.6). Influenza vaccination prevents a substantial number of influenza-associated illnesses. Although vaccines with increased effectiveness are needed and the search for a universal vaccine that is not subject to genetic modifications might increase VE, nowadays only the efforts to increase vaccination rates of high-risk population and healthcare personnel let reduce the burden of influenza and its complications.
| S-EPMC4514250 | biostudies-other