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Table 3 Details of the CT scan images under test. Proposed superpixel coupled fuzzy ACSO approach-based segmentation The conventional fuzzy C-means clustering approach often overlooks some important spatial information that can be costly in terms of the segmentation performance. Dataset description CT scan images of the chest region are collected from the COVID positive patients from different geographic regions.
Experimental results The experiments are performed in the MatLab Ra on a computer that is equipped with an Intel i3 processor and 4 GB main memory. Table 4 Performance evaluation of different approaches using Davies—Bouldin index The highlighted values indicates acceptable values. Image Id Algorithm No. Table 5 Performance evaluation of different approaches using Xie—Beni index The highlighted values indicates acceptable values.
Table 6 Performance evaluation of different approaches using Dunn index The highlighted values indicates acceptable values. Table 8 Comparison of the proposed approach with the active contour method. Study of the convergence rate The rate of convergence is an important parameter to be studied. Analysis of the complexity The time complexity is an important aspect that is to be analyzed.
Discussion 6. Threats to validity The obtained results indicate that the proposed approach is suitable for real-life scenarios and also performs efficiently. Limitations Although the proposed approach is efficient enough to segment the CT scan images automatically and produces realistic segmented outcomes still, some important drawbacks can be observed in this proposed approach that can be addressed in the subsequent works.
Conclusion This article proposes a novel, simple and elegant solution that uses some of the important features of the chest CT scan images to screen the COVID suspected patients easily and at an early phase which can be considered as an effective tool to reduce the drastic spread of this virus. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments The authors would like to express their gratitude and thank the editors, anonymous reviewers, and referees for their valuable comments and suggestions which are helpful in further improvement of this research work. Software setup The system in which the experiments are carried out is equipped with the Microsoft Windows 7 64 bit operating system.
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Fuzzy electromagnetism optimization FEMO and its application in biomedical image segmentation. Yang X. Typical characteristics-based type-2 fuzzy C-means algorithm. Comaniciu D. Mean shift: A robust approach toward feature space analysis. Achanta R. SLIC Superpixels compared to state-of-the-art superpixel methods. Watershed superpixel; pp. Finding contours of hippocampus brain cell using microscopic image analysis. Davies D. A cluster separation measure.
A validity measure for fuzzy clustering. Dunn J. Well-separated clusters and optimal fuzzy partitions. Pal S. Segmentation of remotely sensed images with fuzzy thresholding, and quantitative evaluation. Remote Sens. Jia H. A modified genetic algorithm for distributed scheduling problems. Moghaddam B. Vehicle routing problem with uncertain demands: An advanced particle swarm algorithm. Cai X. Improved bat algorithm with optimal forage strategy and random disturbance strategy. Bio-Inspired Comput.
Modified cuckoo search algorithm in microscopic image segmentation of hippocampus. Copy Download. Jentzen et. This approach segments the CT scan images to easily interpret and study the lung nodules. This work is targeted to extract gastrointestinal lumen from the endoscopic images. Engadget was similarly positive, noting that the upgrade process was painless and that Windows 10's user interface had balanced aspects of Windows 8 with those of previous versions with a more mature aesthetic.
Cortana's always-on voice detection was considered to be its "true strength", also citing its query capabilities and personalization features, but noting that it was not as pre-emptive as Google Now. Windows 10's stock applications were praised for being improved over their Windows 8 counterparts, and for supporting windowed modes. The Xbox app was also praised for its Xbox One streaming functionality, although recommending its use over a wired network because of inconsistent quality over Wi-Fi.
In conclusion, it was argued that "Windows 10 delivers the most refined desktop experience ever from Microsoft, and yet it's so much more than that. It's also a decent tablet OS, and it's ready for a world filled with hybrid devices. And, barring another baffling screwup, it looks like a significant step forward for mobile. Heck, it makes the Xbox One a more useful machine.
On the other hand Ars Technica panned the new Tablet mode interface for removing the charms and app switching, making the Start button harder to use by requiring users to reach for the button on the bottom-left rather than at the center of the screen when swiping with a thumb, and for making application switching less instantaneous through the use of Task View.
Microsoft Edge was praised for being "tremendously promising", and "a much better browser than Internet Explorer ever was", but criticized it for its lack of functionality on-launch. In conclusion, contrasting Windows 8 as being a "reliable" platform albeit consisting of unfinished concepts, Windows 10 was considered "the best Windows yet", and was praised for having a better overall concept in its ability to be "comfortable and effective" across a wide array of form factors, but that it was buggier than previous versions of Windows were on-launch.
Critics have noted that Windows 10 heavily emphasizes freemium services, and contains various advertising facilities. Some outlets have considered these to be a hidden "cost" of the free upgrade offer. Due to the high system requirements of its Windows 10's successor Windows 11 , some critics have cited Windows 10 being better than its successor and have warned not to switch to Windows 11 given its high system requirement despite very limited new features compared to Windows Up to August , Windows 10 usage was increasing, with it then plateauing , [] while eventually in , it became more popular than Windows 7 [] [] though Windows 7 was still more used in some countries in Asia and Africa in As of March [update] , the operating system is running on over a billion devices, reaching the goal set by Microsoft two years after the initial deadline.
Twenty-four hours after it was released, Microsoft announced that over 14 million devices were running Windows According to StatCounter, Windows 10 overtook Windows 8. For one week in late November , Windows 10 overtook first rank from Windows 7 in the United States, before losing it again. In mid-January , Windows 10 had a slightly higher global market share than Windows 7, [] with it noticeably more popular on weekends, [] while popularity varies widely by region, e.
Windows 10 was then still behind in Africa [] and far ahead in some other regions e. Windows 10 Home is permanently set to download all updates automatically, including cumulative updates, security patches, and drivers, and users cannot individually select updates to install or not. Concerns were raised that because of these changes, users would be unable to skip the automatic installation of updates that are faulty or cause issues with certain system configurations—although build upgrades will also be subject to public beta testing via Windows Insider program.
An example of such a situation occurred prior to the general release of the operating system, when an Nvidia graphics card driver that was automatically pushed to Windows 10 users via Windows Update caused issues that prevented the use of certain functions, or prevented their system from booting at all. Criticism was also directed towards Microsoft's decision to no longer provide specific details on the contents of cumulative updates for Windows Some users reported that during the installation of the November upgrade, some applications particularly utility programs such as CPU-Z and Speccy were automatically uninstalled during the upgrade process, and some default programs were reset to Microsoft-specified defaults such as Photos app, and Microsoft Edge for PDF viewing , both without warning.
Further issues were discovered upon the launch of the Anniversary Update "Redstone" , including a bug that caused some devices to freeze but addressed by cumulative update KB, released on August 31, , [] [] and that fundamental changes to how Windows handles webcams had caused many to stop working. A Gartner analyst felt that Windows 10 Pro was becoming increasingly inappropriate for use in enterprise environments because of support policy changes by Microsoft, including consumer-oriented upgrade lifecycle length, and only offering extended support for individual builds to Enterprise and Education editions of Windows Critics have acknowledged that Microsoft's update and testing practices had been affecting the overall quality of Windows In particular, it was pointed out that Microsoft's internal testing departments had been prominently affected by a major round of layoffs undertaken by the company in Microsoft relies primarily on user testing and bug reports via the Windows Insider program which may not always be of sufficient quality to identify a bug , as well as correspondence with OEMs and other stakeholders.
In the wake of the known folder redirection data loss bug in the version , it was pointed out that bug reports describing the issue had been present on the Feedback Hub app for several months prior to the public release. Following the incident, Microsoft updated Feedback Hub so that users may specify the severity of a particular bug report.
When announcing the resumption of 's rollout, Microsoft stated that it planned to be more transparent in its handling of update quality in the future, through a series of blog posts that will detail its testing process and the planned development of a "dashboard" that will indicate the rollout progress of future updates.
Microsoft was criticized for the tactics that it used to promote its free upgrade campaign for Windows 10, including adware -like behaviors, [] using deceptive user interfaces to coax users into installing the operating system, [] [] [] [] downloading installation files without user consent, [] [] and making it difficult for users to suppress the advertising and notifications if they did not wish to upgrade to In September , it was reported that Microsoft was triggering automatic downloads of Windows 10 installation files on all compatible Windows 7 or 8.
Microsoft officially confirmed the change, claiming it was "an industry practice that reduces the time for installation and ensures device readiness. Other critics argued that Microsoft should not have triggered any downloading of Windows 10 installation files without user consent.
In October , Windows 10 began to appear as an "Optional" update on the Windows Update interface, but pre-selected for installation on some systems. A Microsoft spokesperson said that this was a mistake, and that the download would no longer be pre-selected by default.
In March , some users also alleged that their Windows 7 and 8. It was concluded that these users may have unknowingly clicked the "Accept" prompt without full knowledge that this would begin the upgrade. On January 21, , Microsoft was sued in small claims court by a user whose computer had attempted to upgrade to Windows 10 without her consent shortly after the release of the operating system.
The upgrade failed, and her computer was left in a broken state thereafter, which disrupted the ability to run her travel agency. However, in May , Microsoft dropped the appeal and chose to pay the damages. Shortly after the suit was reported on by the Seattle Times , Microsoft confirmed it was updating the GWX software once again to add more explicit options for opting out of a free Windows 10 upgrade; [] [] [] the final notification was a full-screen pop-up window notifying users of the impending end of the free upgrade offer, and contained "Remind me later", "Do not notify me again" and "Notify me three more times" as options.
In March , Microsoft announced that it would display notifications informing users on Windows 7 devices of the upcoming end of extended support for the platform, and direct users to a website urging them to upgrade to Windows 10 or purchase new hardware. This dialog will be similar to the previous Windows 10 upgrade prompts, but will not explicitly mention Windows Privacy advocates and other critics have expressed concern regarding Windows 10's privacy policies and its collection and use of customer data.
Users can opt out from most of this data collection, [] [] but telemetry data for error reporting and usage is also sent to Microsoft, and this cannot be disabled on non-Enterprise editions of Windows Rock Paper Shotgun writer Alec Meer argued that Microsoft's intent for this data collection lacked transparency, stating that "there is no world in which 45 pages of policy documents and opt-out settings split across 13 different settings screens and an external website constitutes 'real transparency'.
The Russian government had passed a federal law requiring all online services to store the data of Russian users on servers within the country by September or be blocked. But Microsoft is held to a different standard than other companies". The Microsoft Services agreement reads that the company's online services may automatically "download software updates or configuration changes, including those that prevent you from accessing the Services, playing counterfeit games, or using unauthorized hardware peripheral devices.
In September , Microsoft hid the option to create a local account during a fresh installation if a PC is connected to the internet. This move was criticized by users who did not want to use an online Microsoft account.
In late-July , Windows Defender began to classify modifications of the hosts file that block Microsoft telemetry servers as being a severe security risk. From Wikipedia, the free encyclopedia. Redirected from Windows 10 Fall Creators Update. This is the latest accepted revision , reviewed on 20 December This article is about the operating system for personal computers. For the related now discontinued operating system for mobile devices, see Windows 10 Mobile. For the series of operating systems produced from to , see Windows 9x.
Closed-source source-available through the Shared Source Initiative Some components free and open-source [1] [2] [3] [4]. List of languages. For the Windows versions produced from to , see Windows 9x. For the Windows version following Windows 8, see Windows 8. Main article: Features new to Windows See also: List of features removed in Windows Main article: List of typefaces included with Microsoft Windows. Main article: Windows 10 editions.
See also: Windows Insider. Main article: Windows 10 version history. Main article: Criticism of Windows This section duplicates the scope of other articles , specifically Criticism of Windows Please discuss this issue on the talk page and edit it to conform with Wikipedia's Manual of Style by replacing the section with a link and a summary of the repeated material or by spinning off the repeated text into an article in its own right.
June Windows PC market share of Windows statistics Windows Business and economics portal. Retrieved August 31, Microsoft Support. Windows Insider Blog. November 10, Retrieved June 13, NET Core 3. NET Foundation. June 5, Ars Technica.
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February 13, Retrieved March 18, Retrieved February 14, Xbox Wire. May 14, Retrieved May 15, Archived from the original on December 1, Retrieved April 2, Retrieved November 15, MKV and. FLAC files all on its own". PC Games Hardware in German. May 5, Retrieved April 11, DirectX Developer Blog.
Archived from the original on October 4, Retrieved October 3, October 3, March 21, Retrieved June 20, PC Perspective. Archived from the original on September 5, Methods: A cross-sectional descriptive study was conducted in representative samples of all beauty salons available in Asmara between May and July The study participants were selected using two-stage stratified cluster sampling technique.
The data collected through face-to-face interview was entered and analyzed using CSPro 7. Results: The study enrolled females. The majority of the respondents agreed that SLAs can make someone white About two-third Of those who ever used SLAs, About half of the respondents With the use of SLAs, Employed females AOR: 1. Conclusion: Utilization of SLAs among females was prevalent. They were satisfied with its use despite experiencing adverse effects which urges coordinated efforts in tightening the regulation of cosmetics in general and establishment of cosmetovigilance systems in particular.
Widespread use of toxic skin lightening compounds: medical and psychosocial aspects. Dermatologic Clinics, Afr Health Sci. The global prevalence and correlates of skin bleaching: a meta-analysis and meta-regression analysis.
Int J Dermatol. Introduction: Drug therapy in paediatrics is often associated with uncertainties due to lack of data from clinical trials. Due to this off-label use, missing paediatric dosage forms and complex dose calculations, medication errors ME occur up to three times more frequently compared to adults [3].
Objective: The aim of the study was to investigate the nature, characteristics and preventability of drug-related hospital admissions in paediatrics. If parents had given consent for data transfer and further analysis, the suspected ADRs resp. MEs were subsequently validated by a blinded, independent expert team [6]. All ADRs and MEs were assessed with regard to their nature, preventability, severity and drug association.
Results: Of Consent for further analysis was obtained for 9. Allergic conditions, seizures incl. Treatment noncompliance, accidental exposure to product and dosing problems mainly underdosing were primarily identified as MEs in connection with the use of antiepileptic drugs, insulins and analogues and other beta-lactam-antibacterials. Conclusion: Drug-related hospital admissions play a significant role in paediatrics. Moreover, almost half of them are considered preventable and therefore result in unnecessary harm and treatment costs.
Dosing databases, training, and systematic screening for ADRs and MEs have great potential to increase the safety of drug therapy in children. Kimland, E. Odlind, Off-label drug use in pediatric patients. Clin Pharmacol Ther, Magalhaes, J.
Eur J Clin Pharmacol, Kaushal, R. JAMA, Smyth, R. PLoS One, Gallagher, R. Schulze, C. J Patient Saf, The lack of staff trained in PV is one of the most serious limiting factors affecting the development of PV in resource-constrained settings. Previous experiences suggest that blending learning programmes can be implemented in resource-limited countries to train health care professionals HCP with remarkable gains in terms of knowledge acquisition.
Methods: We developed the blended-courses integrated with a Train of Trainers scheme [1]. Two e-learning courses were made available on a web-based application, together with a manual on how to combine the e-learning courses together with face-to-face interactions. The blended course were given in Tanzania, Eswatini and Nigeria.
Results: In the three countries 95 participants were trained Table 1. All participants completed the two courses and the mean score of the post-test was significantly greater than on the pre-test Table 1. In the second level, the participants from the first training were training others.
The majority of respondents to questionnaires have been satisfied, declared they felt more involved in PV and reported at least an ADR after the training both in the first and second level. The trends of reporting increased in the twelve months after the training if compared to the previous twelve months: vs and vs ICSRs were reported to Vigibase for Tanzania and Eswatini National Agency respectively. Conclusion: Our results demonstrated that a blended course can reach an important number of participants and improve their knowledge.
It is difficult to establish how much of the increase of reports was attributed to the blended learning training. Alammary A. Blended learning models for introductory programming courses: a systematic review. Plos one.
The views and opinions of authors expressed herein do not necessarily state or reflect those of EDCTP. Introduction: Considering data from the literature in favor of active educational intervention to teach pharmacovigilance, we describe an innovative model of distance learning clinical reasoning sessions CRS of pharmacovigilance with 3rd year medical French students. Objective: The three main objectives were to identify the elements necessary for the diagnosis of an adverse drug reaction, report an adverse drug reaction and perform drug causality assessment.
Methods: The training was organized in 3 stages. First, students practiced clinical reasoning CRS by conducting fictive pharmacovigilance telehealth consultations. Second, students wrote a medical letter summarizing the telehealth consultation and analyzing the drug causality assessment. This letter was sent to the teacher for a graded evaluation. In the third stage was a debriefing course with all the students. Results: Of the third-year medical students enrolled in this course, participated in the distance learning CRS.
The evaluation received feedback from students, with an average score of 8. The qualitative evaluation had only positive feedback. The students appreciated the different format of the teaching, with the possibility to be active. Conclusion: Through distance CRS of pharmacovigilance, medical students' competences to identify and report adverse drug reactions were tested.
The students experienced the pharmacovigilance skills necessary to detect adverse drug reactions in a manner directly relevant to patient care.
The overall evaluation of the students is in favor of this type of method. Methods: This research used a qualitative inductive methodology through thematic analysis. The first step was to identify, through a literature review, current practices for herbal pharmacovigilance. Based on the findings a semi-structured interview guide was designed, and purposive sampling was used to recruit the interview participants.
By using a snowballing technique more potential participants were reached. Most of these recommendations are applicable worldwide, while some are limited to certain regions.
Tong, A. Consolidated criteria for reporting qualitative research COREQ : a item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19 6 , — Introduction: Although medical cannabis MC has been available in Canada since , lack of recognition of MC as a drug has restricted patient access.
The Quebec College of Physicians, between and , authorized MC use only within a research framework. Follow-up ended due to either MC discontinuation, loss to follow-up, 3 years follow-up, or end of data collection May , 6 months after the last patient in.
Data were collected at inclusion and at follow-up visits every 3 months for the first 2 years, then at least once per year in the third year. MC mode of administration ingestion, inhalation, other , and cannabinoid content ratio tetrahydrocannabinol THC -dominant, cannabidiol CBD -dominant, or balanced were documented.
Results: 2, patients were enrolled in the registry mean age Over follow-up, 3. Reports included a total of AEs average 1. The most common PTs were dizziness Conclusion: There were no new safety concerns identified in the Registry, although notable differences in AE profile between modes of administration and cannabinoid content ratios should be considered by health professionals.
Further work identifying and managing risk factors for AEs is warranted to maintain a favorable risk-benefit ratio for MC. Introduction: Dengue is one of top ten global health threats and is a serious burden in the Philippines. Dengvaxia immunization program was launched on April for children 9—year-olds in three regions with high statistics of dengue, hospitalization, and deaths.
This was coincidentally the campaign period for national elections. Use of vaccine, once available, was part of a strategy to control epidemic. Current measures were inadequate. What started as vaccine-vigilance information sparked a public outcry. This led to a series of parliamentary investigations, traditional and social media misinformation and disinformation vilifying the health decision makers and the company, and criminal charges filed against over 20 individuals by the state over alleged unproven vaccine caused deaths.
Despite attempts to correct these narratives by a few health professionals, the damage to institution, the program, the product, and individuals have been done. The consequences of such actions of emotional approach without understanding the science have resulted in creating general vaccine rejection, hesitancy, other outbreaks such as measles, lowered confidence even with recent COVID vaccines. Objective: This abstract aim to describe the situation at that time in the Philippines and extract lessons that will inform better risk communications during crisis.
Results: Some of the important lessons learned are in risk management and communications. Adverse health product information should be announced with circumspect considering the level of health literacy and risk appreciation in a country. Partisan politics interfered with poorly understood science, fueled by imprudent comments by officials and health professionals who spoke out of turn, amplified by the media and created chaos. The fear was so palpable that enlightened health professionals refused to provide countervailing facts.
Reinstating the vaccine would be perceived as the government had back-pedaled on a mistake. In the meantime, the drama contributed to vaccination hesitancy and outbreaks. Conclusion: Public health decisions are policy and regulatory decisions anchored in ethical and utilitarian principles. Edillo et al. Economic Cost and Burden of Dengue in the Philippines. Vannice, et al Mendoza, Dayrit, Valenzuela. Dengue researcher faces charges in vaccine fiasco. Lasco et.
Medical populism and immunisation programmes: Illustrative examples and consequences for public health. Trolleyology and the Dengue Vaccine Dilemma.
Dayrit, Mendoza, Valenzuela The importance of effective risk communication and transparency: lessons from the dengue vaccine controversy in the Philippines. Dengue vaccination: a more balanced approach is needed. Introduction: Vaccines are vital tools to control epidemic and pandemic diseases, such as COVID, demonstrating safety and effectiveness. However, rare adverse events of special interest AESIs following vaccination arise with every new emerging pathogen vaccine program.
Adversomics, a set of technologies that measure the inventory of molecules e. The International Network of Special Immunization Services INSIS brings together vaccine safety, public health, and systems biology experts in middle- and high-income countries to investigate the causes of, and identify strategies to mitigate AESIs following vaccination insisvaccine.
Brighton Collaboration case definitions and harmonized protocols will be employed to collect detailed clinical data and serial blood samples suitable for adversomics e.
Integration of clinical and biological data will enable comparisons of analyte levels and immune responses within groups over time and between cases and controls. Global collaboration across five continents will ensure adequate sample size.
Conclusion: INSIS-led studies will provide insight into pathways triggered in these AESIs and susceptible populations to inform vaccine development strategies to reduce the potential to trigger pathways involved in AESIs, risk-benefit assessment, and personalized vaccination strategies. Introduction: During the covid 19 period, several countries needed to set up or develop their pharmacovigilance systems, unfortunately containment and the closure of borders prevented the organisation of classic training sessions.
Objective: The objective of this work is to present the pharmacovigilance simulation game developed by CAPM, RCC and the results of its pilot use with pharmacovigilants from 10 French-speaking African countries.
The game is based on good practices in Pharmacovigilance PV , and inspired by the different WHO guidelines, the experience of the Moroccan PV center, and behaviors consensually considered as the norm in PV. In fact, they are put in a real-life situation to choose actions and strategies for the development of a PV center and must be able to optimize the human and material resources at their disposal to make their center shine within their national health system but also at the level of the international PV network.
Better understand the challenges and outlooks linked to the creation and management of a PV center. Put into practice the theoretical concepts in causality assessment, signal detection and risk minimization actions. During the game, within 10 levels, participants have to set up a PV center following WHO pharmacovigilance indicators: a practical manual for the assessment of pharmacovigilance systems as structural indicators, process indicators and outcome indicators, and following the pharmacovigilance process from collecting data, analyzing them, detecting signals, and setting up national technical pharmacovigilance committee to discuss about safety signals and risk minimization actions to put in place.
Conclusion: The use of the game by the pharmacovigilantes during the pilot phase gave good feedback on the ease of use and the effectiveness of the game in capacity building in pharmacovigilance. University of Huddersfield, Huddersfield, pp. Introduction: Pharmacovigilance has traditionally been a reactive science with a significant dependence on spontaneous adverse event reporting.
The pandemic on the other hand has accelerated application of novel technologies and approaches to engaging with the patient, remote connected care at their home and dependence on technologies to supplement regular communication channels.
Telemedicine is evolving rapidly and playing a key role in clinical interventions. Objective: Digital Health and novel technologies offer a significant opportunity to enhance pharmacovigilance thru proactive patient monitoring, risk communication, personalized care plans and access to real world data. Leveraging such approaches will not only lead to early detection of risks but also to personalized interventions and improved patient outcomes.
Educational material which is more interactive, visual and multi-dimensional can replace paper or text based risk communication material. This could provide early signal detection in individual patients and enable proactive patient level pharmacovigilance. Educational and risk related material can be dynamically updated based on patient preferences, interactions and profiles.
Machine learning approaches which link material with outcome can enhance impact of pharmacovigilance methods and tools. In order to utilize the full potential of such options it is critical that the regulatory framework is updated to enable such approaches which complement traditional PV and can drive efficiencies and higher effectiveness in the risk communication process.
Collaboration within the network of industry and regulators is essential to further such research and maximize the impact on value for patients, HCPs and sponsors. Introduction: Large amounts of data associated with safety issues are generated along the entire lifetime of drugs, from its infancy as preclinical leads, through its adolescence as clinical candidates, all the way up to its adulthood as marketed drugs exposed to the human population. Across the different stages in the life of a drug, some of the data collected initially may be confirmed and consolidated with data at an advanced stage, whereas other data may not be translated, and in some cases may even contradict, those safety signals that are ultimately observed in the human population.
Collecting and properly integrating such an heterogenous pool of data is a complex and tedious task. But even if one manages to put all data together, the construction of useful models to anticipate and detect drug safety signals remains a challenge. Objective: The presentation will cover our efforts to connect data from in vitro safety pharmacology, preclinical toxicology, clinical safety and post-marketing spontaneous reports for over 9, small molecule drugs, combination drugs, and biologics.
A novel consensus approach using various statistical and machine learning methods to anticipate side effects of potential safety concern, detect adverse drug reaction signals and perform pharmacovigilance analyses will be introduced. Use case application examples to individual drugs and drug classes will be discussed. Methods: Our consensus approach to post-marketing surveillance integrates four different methodologies based on detection of prior safety markers, identification of class reactions, statistical projection of disproportionalities based on reporting frequencies and velocities, and machine learning models of translational safety data.
Results: Results on the validation of our approach to anticipating adverse drug reactions of safety concern to the population at the postmarketing stage based on i in vitro safety pharmacology data, ii preclinical toxicology data, iii clinical safety data and iv the first sample of 25 postmarketing spontaneous reports will be presented.
Based on data available in each case, the performance of the different methods varies for different drugs, drug classes, and side effects. A discussion on performances in selected use cases will be included. As an example, the analysis of long-term PARP inhibition on circadian patterns and its dependence on the reporting bias by consumers will be discussed. Conclusion: Integration and modelling of the large amount of translational safety data currently available from all phases of drug discovery, development and post-marketing to anticipate and follow adverse drug reactions opens an avenue to a whole new perspective in pharmacovigilance.
Introduction: Psychedelics are unique psychoactive chemicals that can change consciousness by acting on 5-HT2A receptors []. There is limited knowledge concerning the online interest in psychedelics that we can extrapolate via trends websites. Objective: We aim to examine the online information-seeking behavior concerning the most popular psychedelics, including cannabis—a quasi-psychedelic—in the European Union EU members of interest and the UK before and during the pandemic.
Methods: We designed a "dictionary" of terms to extract online search data from Google Trends concerning psychedelics and cannabis from Jan to 1-Jan We conducted a triple Holt-Winters exponential smoothing—additive model—for time series analysis to infer seasonality [4, 5]. We utilized hierarchical clustering—an unsupervised machine learning method—to explore clusters of countries concerning the spatial geographic mapping of these chemicals.
We also implemented—a t-test—for comparing the slope difference of two trends before versus during the pandemic. Results: There was an evident seasonal pattern for cannabis, NBOMe, and psilocybin in almost all nations of interest. Similar patterns existed in France and the UK, while those in Germany, Sweden, and Romania had relatively shorter periodicity.
Analysis of slopes and hierarchical clustering conveyed differentiated patterns concerning the temporal and spatial mapping, respectively, while contrasting the two periods before versus during the pandemic.
Conclusion: Cannabis and psychedelics follow somewhat a consistent pattern concerning seasonality across Europe; some correlate with the seasonal harvesting of mushrooms, and others with public holidays, including Christmas, the new year holiday, or school breaks. The pandemic influenced some significant changes concerning the online interest in the EU and the UK; nonetheless, we should rely on more rigorous longitudinal and experimental study designs—possessing a superior level of evidence—to confirm the causal relationship.
However, these patterns might be insightful for decision-makers and regulatory authorities—like the EMCDDA—to prognosticate and prevent addiction catastrophes. Understanding and using time series analyses in addiction research. Carhart-Harris RL. How do psychedelics work?. Current Opinion in Psychiatry. Novel psychoactive substances: types, mechanisms of action, and effects. British Medical Journal. Robust forecasting with exponential and Holt—Winters smoothing.
Journal of Forecasting. Gardner Jr ES. Exponential smoothing: The state of the art—Part II. International Journal of Forecasting. Introduction: Continuous monitoring of the safety profile of drugs is one of the critical processes of pharmacovigilance.
As medical literature might be valuable source of safety data, especially for rare, unlisted, serious cases, all MAHs are obliged to medical literature monitoring MLM in all marketing countries [1]. This approach can be changed through modern automation techniques. Objective: To develop and test a tool for automated monitoring of local literature and enhance drug safety data identification.
Methods: Modern programming approaches were used to create PV platform, intended for automated literature screening. GAMP 5 recommendations were used to prove the validation status. Results: We developed a tool—DrugCard PV platform which screens local medical sources for updates on a weekly basis. Till May we added around local journals originated from 10 countries that cover different therapeutic areas. Our tool automatically searches for defined keywords drug trade names, active substances in published articles.
Different file formats can be screened including text, pdfs, images etc. In case a new issue of a journal is published—a PV specialist will receive an email notification.
The mandatory features of a validated computerized system, like audit trail, logs, reports are also present here. Instead of manual reading of the whole journal issue the user only should read a separate article, analyze whether there is a valuable safety data and label it depending on the content. PV specialists may work together inside the platform and provide a quality check for labeled articles.
Our pilot study of how a new tool may improve the efficiency revealed interesting results. Despite the dramatically decreased amount of time needed, the number of identified ICRSs from literature increased. During the abovementioned pilot study of automated local literature monitoring lasting 2 months, 31 safety cases were identified valid and non-valid ICSRs.
This is much more than usual rate of safety cases finding. It offers increasing efficiency in safety information identification with less time spent on routine activities.
Certificate of copyright in Ukraine. Hyperacute toxicity is a recent newly described entity, albeit incompletely characterized [3]. We selected reports with available information to calculate a plausible time-to-onset. Events of interest were classified into fulminant within 7 days and hyper-acute cases within 21 days, i. Cases were described in terms of demographic and clinical features: age, gender, anticancer regimen combination vs monotherapy , therapeutic indications, seriousness hospitalization , case fatality rate CFR, namely the proportion of cases where death was reported as outcome , co-reported symptoms, co-reported irAEs.
The Immune-Adversome was estimated considering events as nodes and co-reporting as links. Hyperacute cases 18, represented Monotherapy was reported in the majority of cases Pyrexia, diarrhea, fatigue, dyspnea were the most frequently reported symptoms.
Hyperacute myocarditis was reported in Among fulminant cases, most frequent irAEs were interstitial lung disease , colitis , hypothyroidism , and myocarditis Other co-occurring irAEs were colitis-hepatitis-thyroiditis, and arthritis and psoriasis.
Our network approach may complement traditional disproportionality analyses in pharmacovigilance for a more effective signal detection technique, thus supporting regulatory and clinical monitoring, especially in complex scenario such as oncology.
Target Oncol ; — Oncologist ; — Hyperacute toxicity with combination ipilimumab and anti-PD1 immunotherapy. Eur J Cancer ; — Introduction: The prolongation of the QT interval is a serious and potentially fatal adverse reaction that has led to the discontinuation of many drugs including some opioids. Data mining on pharmacovigilance databases can detect signals that identify early the risk associated with some drugs. Results: A total of drug-reaction pairs was found in opioid reports.
Analysis of individual opioids show significant signals for QT prolongation for each drug. The temporal evolution of the different signals according to the number of reports included from to shows early significant positivization of signals in the first 6 to 12 months.
Underlying mechanism is unknown, but it seems to be linked to hERG channel blocking. We propose the evaluation of the trend of change in the confidence intervals of the disproportionality parameters as a measure that can predict the occurrence of clinical events at the population level and a posible usefull strategy to minimize adverse reactions. Introduction: Language and speech are increasingly debated as potential markers for diagnosing and monitoring patients with affective and psychotic disorders 1—3.
However, many neglected factors may confound communicative atypicalities. A comprehensive list of potential confounding drugs will support the design of robust communicative marker studies. Objective: We aim at identifying a list of drugs potentially associated with speech and language disorders, within psychotic and affective disorders.
Within the FAERS, we considered separately 3 populations psychotic, affective and non-neuropsychiatric disorders , to account for the confounding role of different underlying conditions. Robustness analyses were performed to account for the biases. Results: We identified a list of potential expected and 91 unexpected confounding medications for the identification of communication markers of affective and psychotic disorders e.
We developed also a MedDRA query proposal for speech and language conditions, formalization of possible biases, and related analyses to account for them.
Conclusion: We provided a list of medications to be accounted for in future studies of communicative bio-behavioral markers in affective and psychotic disorders.
The methodological procedure we developed does not simply facilitate future investigations of communicative biomarkers in other conditions, more crucially it provides a case-study in more rigorous procedures for digital phenotyping in general. Insel TR. Automated assessment of psychiatric disorders using speech: A systematic review. Laryngoscope Investigative Otolaryngology.
Voice patterns in schizophrenia: A systematic review and Bayesian meta-analysis. Schizophr Res. Introduction: The comparison of safety profiles for products recently on the market is difficult. There is a lack of methodology for quantifying the potential differences between products that have the same indication.
Objective: Provide the tools to quantify the differences in spontaneous reporting between two products. An Euclidian distance from the EBGM to the diagonal line measures the deviation from what would have been expected under the null assumption of similar safety profiles. As the deviation does not capture the statistical uncertainty around the estimate, we propose as measure of the deviation the minimal distance of the four Euclidian distances calculated from each of the credibility intervals around the EBGM post Product A and Product B.
A visualization capturing the global trend of the most substantial differences in reporting was generated. Conclusion: This relatively simple method can provide quantification of the differences in reporting and could help prioritize one product over the other for some population subgroups.
Introduction: The application of text mining approaches to identify adverse events AEs from electronic health records EHRs is a growing area of interest in pharmacovigilance research. In veterinary medicine, the majority of EHRs consist of unstructured clinical narratives, hence the development of appropriate methods for identifying AEs of interest is an important step in the research process. Identifying renal disease poses a specific challenge as the event may be described in narrative form or implied by reported test results or the use of renal disease specific medications.
In this study we developed regular expressions regexes to identify relevant mentions of renal disease in veterinary free text clinical narratives. Objective: To develop a method for identifying veterinary patients with renal disease in free text clinical narratives. Methods: Using VeDDRA terminology as a starting point, we used an iterative approach to develop a series of regexes which were then applied to a random sample of 10, clinical narratives.
In order to measure precision, clinical narratives containing a match to the regexes were reviewed against a case definition by two independent reviewers and disagreement was settled by consensus. Terms in the final regex were derived from three sources—VeDDRA, a word embedding model and expert opinion. To determine recall, the final regex was applied to a sample of consults where the main presenting complaint was deemed to be renal disease by a veterinary clinician. Expanding this terminology using a word embedding model improved the PPV to 0.
Following changes suggested by a veterinary expert, the PPV of the final regex was improved to 0. When the regex was divided into three components, the PPV for these individual portions was mentions of renal disease 0. When compared against the veterinary clinician validated sample of renal disease consults recall was 0.
Conclusion: The developed regex can be used to identify animals with renal disease, with mentions of renal disease treatment being the most specific indicator of clinical disease. This method can be employed to filter potential cases of interest from large datasets for use in observational studies. Introduction: We use AI in our everyday lives probably without even realising it.
There are many discussions about the use of AI in PV and the potential innovation that it could bring but given the conservative nature of our business and having to work in a highly regulated environment, how can we build confidence to get us over that barrier.
Will having the regulators use the same AI make us more comfortable or will legislation be necessary to drive us forward? Objective: Explore why PV has lagged behind with AI technology that is commonplace in other parts of our lives and business.
Aspects of AI, such as machine learning, are used in areas such as early disease prediction, clinical diagnosis, outcome prediction and prognosis evaluation, personalized treatments, drug discovery, manufacturing, clinical trial research, and more.
In our personal lives, services like Amazon and Google use AI to understand and target their customers and we accept that as normal. The objective of this presentation is to explore the reluctance of accepting AI in PV and how we can move towards overcoming those obstacles.
We will look at some real-life practical examples where AI in PV has worked and what it took to get there. Conclusion: We will show that the practical application of AI is achievable and has been achieved in the high volume environment of a regulatory authority. Many of the AI features used by the RA, and the lessons learned from that project, can also be applied in industry, so why are we waiting?
Introduction: Access to case narratives during signal assessment is crucial to provide a more complete picture of the cases [1], however patient confidentiality needs to be considered. Sharing of narratives while preserving privacy requires de-identification—the removal or replacement of personal identifiers. Automating this task can help with increasing data load. To ensure patient confidentiality throughout the full pharmacovigilance process, the narratives should be de-identified early in the process.
Person names—one of the more common identifiers in case narratives—can lead to in- direct identification of patients but are challenging to recognise in free text. Objective: To develop and evaluate a method for automated de-identification of names in case narratives.
Methods: We use an ensemble of BERT [2]—a state-of-the-art language model using deep-neural network—combined with hand-engineered rules for detecting names.
Our model is trained on i2b2 deidentification challenge data [3] combined with unprocessed data from the Yellow Card system[4] provided by the MHRA. Because names are rare in the Yellow Card data, the training dataset is prepared using active learning through an independent model.
Model testing is done on a separate, manually annotated dataset. Evaluation of the deidentification is guided by: 1 how often clinically relevant information is removed and 2 how identifiable the narratives that the model fails to completely de-identify are.
We define three categories of identifiability: a Directly identifiable, where subject identification is very likely with the leaked information e. Results: Out of the 71 narratives with names and initials, only 12 contained occurrences missed by the system. Manual evaluation found only one directly and one indirectly identifiable narrative due to leaks. It should be noted that the leaked direct identifier was a foreign, non-English name.
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