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2022 ◽  
Vol 9 ◽  
Author(s):  
Javier Atalah ◽  
Ian C. Davidson ◽  
Maike Thoene ◽  
Eugene Georgiades ◽  
Kate S. Hutson

The aquatic ornamental species (AOS) trade is a significant pathway for the introduction and establishment of non-indigenous species into aquatic environments. The likelihood of such occurrences is expected to increase worldwide as industry growth continues and warmer conditions emerge under future climate scenarios. This study used recent (2015 – 2019) New Zealand importation data to determine the composition, diversity, abundance, and arrival frequency of AOS. Our analysis revealed that ca. 300,000 aquatic ornamental individuals are imported annually to New Zealand, with freshwater fish comprising 98% of import quantities. Despite the relatively small market size, the estimated AOS diversity of 865 taxa (89 and 9.5% identified to species and genus level, respectively) is comparable to larger markets with ∼60% of taxa being of marine origin. Species (n = 20) for further investigation were prioritized based on quantity and frequency of import. These prioritized AOS were exclusively tropical and subtropical freshwater fish and align with the most frequently imported AOS globally, including the top three: neon tetra (Paracheirodon innesi), guppy (Poecilia reticulata), and tiger barb (Puntigrus tetrazona). Species distribution modeling of the 20 prioritized AOS predicted that 13 species are suitable for New Zealand’s current climate conditions, most notably sucker-belly loach (Pseudogastromyzon myersi), white cloud mountain minnow (Tanichthys albonubes), and golden otocinclus (Macrotocinclus affinis). Potential changes in habitat suitability were predicted under future climate scenarios, with largest increases (29%) for Po. reticulata. The described approach provides an adaptable framework to assess establishment likelihood of imported AOS to inform regulatory decision making.


2022 ◽  
pp. 84-100
Author(s):  
Samia Hassan Rizk

The advances in biotechnology and computer and data sciences opened the way for innovative approaches to human healthcare. Meanwhile, they created many ethical and regulatory dilemmas such as pervasive global inequalities and security and risk to data privacy. The assessment of health technology is a systematic multidisciplinary process that aims to examine the benefits and risks associated with its use including medical, social, economic, and ethical impacts. It is used to inform policy and optimize decision-making. The advance of technology is creating significant challenges to healthcare regulators who strive to balance patient safety to fostering innovation. The FDA and EMA are modernizing their regulatory approaches to foster innovation in digital technology and improve safety and applicability to patients. On the other hand, data analytic technologies have been introduced into regulatory decision processes.


2021 ◽  
Vol 11 (24) ◽  
pp. 11920
Author(s):  
Clair Blacketer ◽  
Erica A. Voss ◽  
Frank DeFalco ◽  
Nigel Hughes ◽  
Martijn J. Schuemie ◽  
...  

Federated networks of observational health databases have the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Collaboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Fifteen Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance issues but showed less of an impact on completeness and plausibility checks. This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.


BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yoon Duk Hong ◽  
Jeroen P. Jansen ◽  
John Guerino ◽  
Marc L. Berger ◽  
William Crown ◽  
...  

Abstract Background There have been ongoing efforts to understand when and how data from observational studies can be applied to clinical and regulatory decision making. The objective of this review was to assess the comparability of relative treatment effects of pharmaceuticals from observational studies and randomized controlled trials (RCTs). Methods We searched PubMed and Embase for systematic literature reviews published between January 1, 1990, and January 31, 2020, that reported relative treatment effects of pharmaceuticals from both observational studies and RCTs. We extracted pooled relative effect estimates from observational studies and RCTs for each outcome, intervention-comparator, or indication assessed in the reviews. We calculated the ratio of the relative effect estimate from observational studies over that from RCTs, along with the corresponding 95% confidence interval (CI) for each pair of pooled RCT and observational study estimates, and we evaluated the consistency in relative treatment effects. Results Thirty systematic reviews across 7 therapeutic areas were identified from the literature. We analyzed 74 pairs of pooled relative effect estimates from RCTs and observational studies from 29 reviews. There was no statistically significant difference (based on the 95% CI) in relative effect estimates between RCTs and observational studies in 79.7% of pairs. There was an extreme difference (ratio < 0.7 or > 1.43) in 43.2% of pairs, and, in 17.6% of pairs, there was a significant difference and the estimates pointed in opposite directions. Conclusions Overall, our review shows that while there is no significant difference in the relative risk ratios between the majority of RCTs and observational studies compared, there is significant variation in about 20% of comparisons. The source of this variation should be the subject of further inquiry to elucidate how much of the variation is due to differences in patient populations versus biased estimates arising from issues with study design or analytical/statistical methods.


Author(s):  
Cynthia Huber ◽  
Tim Friede ◽  
Julia Stingl ◽  
Norbert Benda

Abstract Background Modern personalized medicine strategies builds on therapy companion diagnostics to stratify patients into subgroups with differential benefit/risk. In general, stratification for drug response implies a treatment-by-subgroup interaction. This interaction is usually suggested by the drug’s mechanism of action and investigated in pharmacological research or in clinical studies. In these candidate genes or pathway approaches, either biological reasons for a differential benefit/risk or statistical interaction regarding a pharmacological or clinical endpoint or both may be given. For successful drug approval, demonstration of a positive benefit/risk balance in the intended patient population is required. This also applies to situations with biomarker-selected populations. However, further regulatory considerations relate to the usefulness and plausibility of the selected patients and benefit/risk extrapolations or alternative therapy options in biomarker-negative populations. Methods To facilitate the specification of regulatory requirements and support the design of clinical development programmes, a systematic classification of biomarker-drug pairs is needed, in particular with regard to the expected underlying molecular mechanism and the clinical evidence. Results A classification of five biomarker-drug categories is proposed related to increasing evidence on the biomarker’s predictive value in relation to a specific drug. We classified biomarkers into five ascending categories with increasing evidence on the predictive nature of the biomarker in relation to a specific drug according to the comparative pharmacological and clinical evidence. Conclusions The proposed classification will facilitate regulatory decision-making and support drug development with respect to biomarker-related subgrouping, both, during clinical programme and at the time of marketing authorization application, since the grade of evidence on the differential power of the biomarker can be considered as an indicator for the usefulness of a biomarker-related subgrouping.


Author(s):  
Genna Reed ◽  
Yogi Hendlin ◽  
Anita Desikan ◽  
Taryn MacKinney ◽  
Emily Berman ◽  
...  

AbstractFor decades, corporate undermining of scientific consensus has eroded the scientific process worldwide. Guardrails for protecting science-informed processes, from peer review to regulatory decision making, have suffered sustained attacks, damaging public trust in the scientific enterprise and its aim to serve the public good. Government efforts to address corporate attacks have been inadequate. Researchers have cataloged corporate malfeasance that harms people’s health across diverse industries. Well-known cases, like the tobacco industry’s efforts to downplay the dangers of smoking, are representative of transnational industries, rather than unique. This contribution schematizes industry tactics to distort, delay, or distract the public from instituting measures that improve health—tactics that comprise the “disinformation playbook.” Using a United States policy lens, we outline steps the scientific community should take to shield science from corporate interference, through individual actions (by scientists, peer reviewers, and editors) and collective initiatives (by research institutions, grant organizations, professional associations, and regulatory agencies).


2021 ◽  
pp. 153537022110522
Author(s):  
Elke Anklam ◽  
Martin Iain Bahl ◽  
Robert Ball ◽  
Richard D Beger ◽  
Jonathan Cohen ◽  
...  

There is an evolution and increasing need for the utilization of emerging cellular, molecular and in silico technologies and novel approaches for safety assessment of food, drugs, and personal care products. Convergence of these emerging technologies is also enabling rapid advances and approaches that may impact regulatory decisions and approvals. Although the development of emerging technologies may allow rapid advances in regulatory decision making, there is concern that these new technologies have not been thoroughly evaluated to determine if they are ready for regulatory application, singularly or in combinations. The magnitude of these combined technical advances may outpace the ability to assess fit for purpose and to allow routine application of these new methods for regulatory purposes. There is a need to develop strategies to evaluate the new technologies to determine which ones are ready for regulatory use. The opportunity to apply these potentially faster, more accurate, and cost-effective approaches remains an important goal to facilitate their incorporation into regulatory use. However, without a clear strategy to evaluate emerging technologies rapidly and appropriately, the value of these efforts may go unrecognized or may take longer. It is important for the regulatory science field to keep up with the research in these technically advanced areas and to understand the science behind these new approaches. The regulatory field must understand the critical quality attributes of these novel approaches and learn from each other's experience so that workforces can be trained to prepare for emerging global regulatory challenges. Moreover, it is essential that the regulatory community must work with the technology developers to harness collective capabilities towards developing a strategy for evaluation of these new and novel assessment tools.


Author(s):  
Zachary B. Massey ◽  
Robert T. Fairman ◽  
Victoria Churchill ◽  
David L. Ashley ◽  
Lucy Popova

Introduction: Modifications to electronic nicoti ne delivery systems (ENDS) can pose health risks to users. This study explored users’ motivations for modifying ENDS devices and how perceived risks of modifications influenced modification behaviors as product availability and device characteristics changed over time. Method: We conducted nine focus groups (February–June 2020) with 32 current ENDS users (18+, used ENDS in the past 30 days, and had been using ENDS for more than 2 months). Results: Participants primarily modified ENDS devices to improve their experiences, such as experimenting with flavor, controlling nicotine levels, or using cannabis products with ENDS. Another reason for modifying was routine maintenance to ensure a satisfactory experience, including maintaining coils and keeping batteries charged. The broader availability of ENDS products shifted modification behaviors over time, with newer devices making some modifications (e.g., coil replacement) easier and making more intricate modifications (e.g., building coil from scratch) less common. Participants were aware of modification dangers and cited perceived risk as the reason for avoiding certain modifications, such as battery alterations. Conclusions: Modifications of ENDS are ongoing and evolving among users and should be considered by the Food and Drug Administration (FDA) and other regulatory decision-makers as product authorization reviews are conducted and product standards are developed.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 5037-5037
Author(s):  
Donna R. Rivera ◽  
Jennifer J Lee ◽  
Melanie Royce ◽  
R. Angelo de Claro ◽  
Nicole J. Gormley ◽  
...  

Abstract Background Aligning with 21st Century Cures legislation, FDA is exploring methodologies to advance appropriate uses of Real World Data (RWD) to generate Real World Evidence (RWE). RWD to support regulatory decision making has markedly increased in oncology. This review specifically focused on the analysis of RWD containing submissions for medical products in development for the treatment of hematological malignancies and associated treatment related conditions (e.g., Cytokine Release Syndrome (CRS), Graft Versus Host Disease (GVHD). Methods A systematic search was conducted using internal FDA databases to identify RWD submissions from 2010 to 2020. Search terms included: real world evidence, real world data, electronic health record, cancer registry, administrative claims, external control arm, observational cohort, historical control arm, real world Overall Survival (rwOS) , real world Response Rate (rwRR), real world Overall Response Rate rwORR and real world Complete Response (rwCR). Regulatory submissions specific to malignant hematology and associated treatment related conditions were reviewed, and pre-defined common data elements were extracted and validated by independent dual review. Descriptive statistics were calculated. Results A total of 142 regulatory submissions included RWD from 2011-2020. A subset of 94 RWD submissions met the criteria for further evaluation, of which 20 (21%) submissions corresponding with 14 molecular entities were for hematologic malignancies or treatment related conditions (e.g., CRS, GVHD). RWD submissions increased substantially over time, with 14 (70%) of submissions received between 2019-2020. Specific evaluation for pediatric indications was referenced in 15% of submissions. The most commonly referenced RWD source was EHR data (55%), followed by use of multiple sources (20%), and registry data (15%). Approximately 90% of the submissions aimed to support treatment effectiveness. Primary RWD study objectives included supporting approval of a new molecular entity (NME) (40%), expanding an approved indication (25%), conversion from accelerated to regular approval (15%), and providing data to inform postmarketing safety evaluation (20%). Among RWD submissions, response endpoints (e.g., rwORR, rwCR, rwPR, Partial Response) and overall survival (e.g., rwOS) were most frequently selected as primary outcomes for 50% and 20% of proposals respectively; however, these outcomes were included as any endpoint in 65% and 75% of submissions. Conclusion This review demonstrates increasing use of various RWD sources to support evidence generation for drug development in hematologic malignancies and associated treatment related conditions with the primary objective of supporting demonstration of effectiveness using rwOS or real world response measures as primary endpoints. Given the increased inclusion of RWD in regulatory submissions, further methodological development is needed, including in the selection and validation of rwEndpoints. Appropriate study design must be aligned with a clear regulatory objective to ensure that RWD can be adequately evaluated. Additionally, the development of standardized metrics for data characterization and transparency in reporting of RWD are foundational steps to the evaluation of fit for purpose RWD to support regulatory decision making. Disclosures No relevant conflicts of interest to declare.


Author(s):  
Clair Blacketer ◽  
Erica A Voss ◽  
Frank DeFalco ◽  
Nigel Hughes ◽  
Martijn J Schuemie ◽  
...  

Background: Observational health data has the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Col-laboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Methods: 15 Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. Results: All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance is-sues but showed less of an impact on completeness and plausibility checks. Conclusions: This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.


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