Sollers College

Tag: Jobs in Pharma

  • Why Should International Medical Students Choose Drug Safety and Pharmacovigilance

    Why Should International Medical Students Choose Drug Safety and Pharmacovigilance

    Why a career in Drug Safety & Pharmacovigilance may be an option for you?

    Pharmacovigilance and Drug Safety is a thriving industry. In the coming years, regulatory authorities may make it mandatory for all small, medium, and large pharmaceutical companies to have a pharmacovigilance department. The Drug Safety and Pharmacovigilance program is a worthwhile investment of time and energy for those with a foreign medical license attempting to establish a foothold in the country. Medical graduates are well-equipped in terms of knowledge, attitude, and practice regarding adverse drug reactions and their monitoring.

    Opportunities for Drug Safety and Pharmacovigilance Aspirants Abroad

    The good news is that international medical graduates have a plethora of job opportunities in the United States. Drug Safety and Pharmacovigilance is one career route that may offer the most potential for FMGs and anyone who wishes to make a mark in the medical enterprise.

    It is one of the fastest-growing career categories in the country because of the increase in safety measures. The quick speed of change has also resulted in a genuine “skills gap,” The demand for well-paying Drug Safety associate employment vastly outnumbers the supply of skilled individuals.

    As a medical expert, you must address several challenges to assure the safety of medications and medical equipment. Medical practitioners must have a thorough awareness and competence in drug and device safety to effectively contribute to this goal by recognizing, managing, and reporting drug and device safety risks early on. 

    Pharmacovigilance has been increasingly important in recent years, and its relevance in the healthcare system is now well recognized. In the worldwide pharmacovigilance system, medical practitioners play a critical role. They demand a deep understanding and experience in drug and device safety and the ability to contribute to this field by identifying, managing, and reporting drug and device safety concerns early on. Medical practitioners should be officially trained in pharmacovigilance and have a mix of knowledge and abilities in this field.

    There are various entry-level roles available for medical physicians, such as Drug Safety Physician, Medical Reviewer, and Safety Specialist / Scientist, all of which lead to higher positions over time.

    People who love health care are in high demand. Employers in the health sector are looking for individuals with a unique blend of healthcare and information technology (IT) capabilities. It bodes well for FMGs, whose medical background and clinical expertise offer them an advantage in the employment market for drug safety and healthcare informatics.  

    If you want to assist patients without providing direct care, a career in Drug Safety and Pharmacovigilance could be the right choice.  It provides numerous work alternatives at every career stage, thanks to faster-than-average employment growth and job opportunities in a variety of disciplines.

    Career opportunities in the drug safety sector tend to be prevalent in large organizations.  As a result, drug safety jobs are handy for aspiring candidates. Through our Advanced Drug Safety Internship Program, you gain the knowledge you need, and the practical experience employers in this field are demanding. 

  • How Can Drug Safety Platforms Benefit from Practical Automated Systems?

    How Can Drug Safety Platforms Benefit from Practical Automated Systems?

    • The pharmaceutical sector is currently well on its way to reaching complete automation. 
    • Companies within the life science industry are using machine learning, natural language processing, artificial intelligence, and rules to automate their research and development operations. 
    • To meet pharmacovigilance requirements, enterprises need to identify the best automation approach and degree of automation for effective R&D initiatives.
    • When implementing an automation timeline, organizations should consider the time and resources needed to develop and maintain the system and the anticipated advantages. 
    • Once the proper tools and protocols are in place, automation becomes a manageable tool that can be utilized to empower the upcoming generation of pharmacovigilance professionals, reducing the time and effort required for implementation.

    Recognizing the Automation Horizon

    • Understanding the Automation Horizon As better, more flexible technology has developed in recent decades, safety automation capabilities have increased. 
    • It’s helpful to view automation as a continuum when deciding which features will best support your pharmacovigilance initiatives.
    • On one end of the spectrum are the more traditional, structured processes that rely on rule-based automation, such as developing bulk case intake routines. It is common for them to have an integrated safety mechanism.
    • With the help of rule-based automation, which automates typical procedures, data quality can be achieved with lower processing costs.
    • Moreover, it frees up employee time to focus on more valuable responsibilities, such as upholding worldwide compliance.
    • Knowledge-based automation includes artificial intelligence, machine learning, natural language production, and other sophisticated cognitive systems. These automation technologies make it simple to examine large data sets and identify pertinent safety patterns.
    •  Knowledge-based automation uses sophisticated algorithms that can perform tasks related to decision-making and cognitive reasoning. 
    • This intelligent automation is the hardest to incorporate into safety workflows, but it can offer insights into patient safety or compliance data sets that would otherwise require a significant time and labor investment.
    • Deciding which automation level best meets your safety requirements might be challenging. The concept of accessible automation is essential at this point.

    Accessible Automation: What Is It?

    Concentrating on what makes automation accessible is crucial. Safety plans are dynamic and must adapt quickly to new compliance requirements or variations in data volumes. Safety automation must reflect this fluidity, necessitating a degree of adaptability, usability, and approachability to assist teams in any circumstance.

    Which indicators of accessible automation are present?

    Interoperability: You can easily integrate your safety platform with other life science systems to share data and build a single, integrated safety database.

    Ready for Production: Automation that is ready out of the box and validates more quickly is achieved using mature systems pre-trained for pharmacovigilance.

    Implementation Simplicity: When automation is simple and easy to use, fewer staff resources are required, and the total cost of ownership is reduced.

    Flexibility: Standardized and ad hoc reporting options combined with adaptable automated procedures enable teams to be flexible and react to changes in safety case management.

    Built-in Safety Compliance: Automation platforms that are pre-configured with compliance make it easy to comply with national, international, and local requirements.

    When automation is feasible, it can yield efficiencies that are unmatched by manual labor-developed solutions. 

    Facilitating the Automation of Pharmacovigilance (PV)

    In what situations might the use of well-developed and user-friendly automated workflows be most beneficial for pharmacovigilance and patient safety teams?

    Automating the Intake Process: Eliminate the laborious manual process of uploading and verifying large quantities of cases. Utilize robotic, cognitive, and optical character recognition (OCR) technology to automate case intake from both organized and unorganized sources in a variety of languages. Get deep learning from incoming unstructured data sources, generate receipts of adverse event data, and shorten case processing times.

    Obtain PV automation that is accessible.
    As strong tools become more intelligent and capable of handling the increasing complexity of case management in the life sciences, the advantages of approachable automation continue to be felt. 

    To reap the benefits of automation as promised, companies should carefully plan, test, and validate their safety automation strategy with a pharmacovigilance automation solution.

    Selecting the appropriate platform can be difficult, even though it is obvious that automation is the way forward for safety teams. 

    A next-generation safety platform with a track record of delivering pre-validated, end-to-end automation workflows should be the primary option.

    It’s time for the industry to move beyond automation as a catchphrase.

  • Clinical SAS Module Base along with the CDISC, SDTM, and ADAM modules?

    Clinical SAS Module Base along with the CDISC, SDTM, and ADAM modules?

    Clinical SAS is the term used to describe the use of SAS software in clinical research and medical settings. SAS is a potent software suite that is extensively utilized in many different industries, including healthcare and pharmaceuticals, for statistical analysis, data management, and reporting. When managing clinical trial data in the context of clinical trials, a few modules and components of clinical SAS are essential.

    In pharmaceutical and healthcare industries and the life science industry, SAS programmers develop and oversee software that doctors, nurses, and other medical professionals use for diagnostics and treatment. The scientists, researchers, and trial programmers who work on clinical studies typically collaborate with statisticians, analysts, clinical data managers, and data analysts to maintain and evaluate clinical research data.

    Clinical SAS is the use of SAS software in clinical research and healthcare. SAS is powerful software for statistical analysis, data management, and reporting in many industries, including pharmaceuticals and healthcare. In clinical SAS, different modules and components handle clinical trial data.

    Clinical SAS programmers utilize their programming skills to develop and oversee software that physicians, nurses, and other medical professionals use in their work in the pharmaceutical, healthcare, and life science industries. To preserve and analyze clinical research information, clinical trial programmers typically collaborate with statisticians, data analysts, and clinical data managers.

    Taking into consideration the information you have provided regarding Base SAS, Advanced SAS Programming, CDISC, SDTM, and ADAM, a closer look is taken at each of these components.

    A foundational understanding of SAS programming with fundamental data processing and analysis and data cleansing and transformation through DATA STEP programming, along with the PROC step, is used for reporting and statistical analysis for Base SAS.

    In more advanced SAS functions, sophisticated methods for transforming and manipulating data, along with macroprogramming for efficiency and automation, and refined statistical methods and approaches.

    CDISC, the Clinical Data Interchange Standards Consortium, develops global standards for clinical research data. These standards ensure that clinical trial data is consistent and can be easily exchanged. Two common standards are SDTM, the Study Data Tabulation Model, and ADaM, the Analysis Data Model.

    SDTM is a standard that organizes and formats clinical trial data. It defines a structure for datasets that are submitted to regulatory authorities. SDTM datasets include domains like Demographics, Adverse Events, and Concomitant Medications.

    ADaM is a CDISC standard that focuses on creating analysis datasets. It provides guidelines for organizing and formatting data for statistical analysis. ADaM datasets include analysis-ready data for statistical analysis and reporting.

    CDISC standards make it easy to share, integrate, and analyze data across different studies and organizations. SAS programming skills are crucial for implementing these standards and working effectively with clinical trial data.

    Professionals in clinical SAS clean and transform data, perform statistical analysis, and generate regulatory submissions. They must understand regulatory requirements and industry standards to ensure compliance and successful clinical trials.

  • A review of the clinical implications and applications of generative AI

    A review of the clinical implications and applications of generative AI

    Generative AI can now use technology to write code, create art, write coherent paragraphs, and even help scientists with clinical research. What is generative AI, though, and how has it developed? What part can it play in clinical research? Let’s investigate more!

    How does generative AI work?

    • An autonomous form of artificial intelligence referred to as “generative AI” can translate text into images and write texts by itself. 
    • By learning from existing data and using that knowledge to create fresh, innovative content out of that data, generative AI has the potential to be applied to a range of tasks, such as storytelling or graphic design, as well as many other tasks.

    Creation of generative AI

    • Generative AI was initially developed using fundamental forms. 
    • It could only generate single sentences and suggest a few random words using outdated machine learning algorithms.

    Deep learning and neural network applications

    • Artificial intelligence has progressed rapidly since the development of deep learning and neural networks, which mimic the functions of the human brain. 
    • AI models have demonstrated far greater efficacy in learning from data.

    What’s to Come

    • Generative AI is an exciting technology, but just beginning to explore its possibilities. The human brain is very similar in that regard, as its potential isn’t fully explored yet.
    • Generative AI can only provide meaningful and consistent responses if you ask the right questions or provide the right prompts.
    • With the knowledge of AI, the experts are able to provide precise and pertinent answers when dealing with AI.

    Clinical Research’s Use of Generative AI

    Particularly in the areas of clinical research and trials, generative AI has the potential to transform the healthcare sector completely. It can have a major influence in the following areas:

    • Test data generation
    • Drug discovery
    • Patient recruitment
    • Document generation
    • Generating SAS Programs
    • Monitoring and reporting

    Summary

    • A significant amount of progress has been made in generative AI since its humble beginnings. 
    • With its constantly developing capabilities, it holds out the possibility of a time when machines will be able to support human creativity and problem-solving in previously unheard-of ways. 
    • Particularly intriguing are the possible uses in clinical research and trials, which offer quicker, more effective, and morally sound medical solutions.
  • Cloud-based technologies can speed up pharmacovigilance.

    Cloud-based technologies can speed up pharmacovigilance.

    It is possible to improve the monitoring process and ensure the safety of pharmaceutical products through improved monitoring by utilizing cloud computing technologies to accelerate pharmacovigilance innovation. To identify, evaluate, and prevent negative effects of medications and other medical products, 

    Pharmacovigilance is essential in the pharmaceutical and healthcare sectors.

     Here are some ways that the cloud solutions used in pharmacovigilance can promote innovation:

    • Cloud solutions provide scalability, enabling pharmacovigilance systems to handle large volumes of data. 
    • A growing amount of data needs to be stored in pharmacovigilance, such as when reporting adverse events, and this is important for several reasons. 
    • Increased workloads can be quickly adapted to cloud-based systems without the need for significant hardware.
    • Data integration is made possible by the infrastructure and tools that cloud platforms offer to combine data from various sources, including wearable technology, social media, and electronic health records. 
    • This makes it easier for pharmacovigilance teams to compile a thorough picture of patient health and identify adverse events.
    • Real-time analysis and processing of information is made possible by cloud solutions.
    •  By spotting potential safety issues early, we can react much faster and ensure the safety of our patients is better protected.
    •  This is essential for preventing injuries to patients when they occur.
    • It is possible to spot patterns and trends in pharmacovigilance data by utilizing advanced analytics tools such as machine learning and artificial intelligence, which are readily accessible as cloud-based applications to observe patterns and trends in the data.
    •  As a result of the ability of these technologies to predict adverse events, we can increase the safety of pharmaceuticals by providing knowledge about the predictive capability of these technologies.

    Collaboration and communication are made possible by cloud platforms, which help pharmacovigilance specialists, healthcare providers, regulatory organizations, and pharmaceutical companies work together. In addition to ensuring effective communication and knowledge transfer, teams have access to and can share data securely. 

    To ensure that the data is safe and secure in the cloud, cloud service providers must ensure that the data they handle on behalf of pharmaceutical companies is not only protected by strong security measures but also complies with a strict compliance program. 

    The steps have a big influence on how regulatory bodies perceive and how well the accuracy of what you share is protected. Cloud solutions can reduce infrastructure costs by eliminating the need for on-site data centers and hardware maintenance. The ability to only pay for the resources that an organization uses is one of the many benefits of using this cost-effectiveness approach.

    Cloud-based pharmacovigilance systems are globally accessible to anyone with an internet connection. This is particularly beneficial for multinational pharmaceutical companies and regulatory organizations that must collaborate across national boundaries. Everyone who has access to the internet can use it.

    Thanks to the disaster recovery solutions and redundancy options provided by a cloud provider, the pharmacovigilance data will be protected against unforeseen events, such as server failures or natural disasters, while preserving the highest level of data security. 

    The cloud provider typically offers a continuous update and improvement schedule, ensuring that pharmacovigilance systems stay compliant by keeping them up to date with the most recent technologies and compliance standards.

     It is reasonable to conclude that cloud computing has many advantages for boosting innovation and elevating pharmacovigilance. Companies can use the cloud.

    Finally, cloud-based solutions have much to offer to accelerate pharmacovigilance innovation. Organizations can use cloud computing to improve data processing, analysis, collaboration, and security for real-time drug monitoring and regulation to increase pharmacovigilance and patient safety, as well as the efficiency of regulatory monitoring and evaluation. However, when implementing cloud-based solutions in pharmacovigilance, it is important to consider regulatory and data protection requirements.

  • A facility-driven approach to reliable pharmacovigilance

    A facility-driven approach to reliable pharmacovigilance

    Pharmacovigilance and reliable medicine are combined in reliable pharmacovigilance.

    Pharmacovigilance may become more reliable with more precise data collection and computational techniques.

    Intelligent healthcare facilities can collect, analyze, and disseminate patient-specific clinical decisions.

    Reliable pharmacovigilance refers to the provision of a framework for drug safety assessment that is more comprehensive and interactive than standard pharmacovigilance. 

    Pharmacovigilance should benefit the individual patient. It is ambitious since these objectives challenge the prevailing understanding of pharmacovigilance. It is important to first complete several related tasks, including:

    Personalized information leaflets, also known as personalized package inserts, are intended to be compiled with specific reference to a drug’s contraindications, warnings, precautions, and adverse drug reactions (ADRs). 

    These efforts include:

    1. Designing the data collection infrastructure for precision pharmacovigilance.
    2. Investigating novel computational methods to analyze and assess drug safety data.
    3. Providing a computer-aided framework for distributed clinical decisions; and
    4. In addition to these four points, two more factors must be considered for precision pharmacovigilance to be feasible.

    Reliable pharmacovigilance can be best achieved by making the hospital the primary hub of this type of research work and, second, by taking advantage of the expanding significance of secondary use of healthcare data laws, which are already in place in several countries and are anticipated to be more widely adopted in the future.

    A study-driven approach to reliable pharmacovigilance.

    Three research strands are:

    • data collection,
    •  data analysis, and
    •  data exploitation

    They are the foundation of reliable pharmacovigilance. 

    Theoretical and practical research will be required to align abstract modeling with a boots-on-the-ground strategy, where statistically based models will need to handle real-world evidence and work within hospital clinical limitations.

    Compiling the data


    On the one hand, most data will be collected by hospital pharmacoepidemiology and health informatics. Moreover, information engineering and health informatics are also relevant. This system will need to be integrated with the hospital’s current data management practices and systems. 

    A scalable system must accept real-time data on drug consumption, reports of potential adverse drug reactions from doctors, and data from hospital pharmacies as well as electronic health records. 

    Privacy will be a top priority regardless of whether it is acquired locally or not.

    Leveraging data

    Precision pharmacovigilance creates a personalized information leaflet that specifically refers to a drug’s contraindications, warnings, precautions, and ADRs. The use of computational techniques currently employed in precision medicine in its compilation will be advantageous.

    A final reflection and a look ahead to the future

    Precision pharmacovigilance was developed to respond to standard pharmacovigilance problems. Its goals include lowering hospitalizations and fatalities caused by ADRs. In addition, it protects populations that are typically left out of RCTs but still suffer negative effects from medication. 

    This novel approach to pharmacovigilance aims to change the game in drug safety by offering more accurate drug safety assessments. It also prevents serious adverse drug reactions. It is based on clever and effective data collection within hospitals by utilizing innovative and rigorous data analysis.

     This is done by creating a personalized information leaflet with specific reference to a drug’s contraindications, warnings, precautions, and side effects.

  • Evaluation and Detection of Signals in Pharmacovigilance

    Evaluation and Detection of Signals in Pharmacovigilance

    • Pharmacovigilance is the science of recognizing, assessing, comprehending, and preventing hazardous drug reactions.
    • The main objectives of pharmacovigilance are identifying and assessing previously reported adverse drug reactions; assessing previously reported adverse drug reactions, and lowering mortality and morbidity associated with adverse events.
    • PV, also known as post-marketing surveillance, is mostly done throughout the drug development phase.
    •  The most crucial part of pharmacovigilance is signal identification and evaluation.
    • A signal, according to the WHO, is reported information on a potential causal association between an adverse event and medicine, of which the association is undetermined. Frequently, a signal is represented by a small set of reports.
    • Signal identification and evaluation are crucial and intricate procedures. As a result, qualitative signal detection and assessment techniques utilized in pharmacovigilance.

    An Analysis of Signals

    The pharmaceutical industry and regulators are all very interested in the early detection of safety information as soon as feasible. Both qualitative and quantitative components make up signals.

    Different approaches for detection are required for different categories of adverse events. Early signal detection is the main purpose of pharmacovigilance. However, procedures for reporting spontaneous events have been created and are now utilized globally.

    Case-control, cohort, and spontaneous reporting are only a few of the sources that produce safety signals.

    Automatic Reporting System

    • Most of the current pharmacovigilance relies on a spontaneous reporting mechanism. The spontaneous reporting system often includes case reports and case series. Early detection of signals from new, uncommon, and severe ADRs is the primary purpose of SRS.
    • A medically qualified person reports an incident voluntarily to a drug information center, where the reports are analyzed. Spontaneous reports are used to keep track of the underreporting of adverse medication responses and quality deviations. Underreporting is the main reason for the public’s lack of understanding among health professionals and the public.
    • Another issue in this system is selective reporting, which can create the perception of a risk when there isn’t truly one. Therefore, even though spontaneous reporting is inexpensive, it is not the ideal solution for postmarketing drug surveillance.
    • Nevertheless, we cannot dispute the fact that spontaneous reporting was and continues to be the primary method of identifying early drug safety signals. As evidence of SRS’s effectiveness in identifying fresh safety signals, most pharmaceutical goods are pulled off the market on its premise. 

    Recurrent Safety Update Report

    • The PSUR can be a valuable resource to find novelty signals. The purpose of a PSUR is to inform the competent authorities at specific intervals after permission of an update on the global safety experience of a medical product.
    • PSURs must be submitted for all registered products, no matter how the product is marketed. One report may be used to cover all items authorized by one marketing authorization holder that contains the same active ingredient.

    Trigger Tools Are Used to Produce Signals

    • Healthcare professionals are looking for an accurate and trustworthy technique for measuring and identifying adverse drug reactions in hospitalized patients.
    • The clinical pharmacist monitors the efficiency of drugs using electronic systems and is responsible for identifying early adverse drug reactions and other drug-related issues.

    Examination of Signals

    • Multiple criteria are used to assess signals. Before considering a report of a brand-new adverse drug reaction, high-quality report facts must be there.
    • Numerous tools are used to create high-quality data, including various applications and techniques. 
    • Additionally, a few studies have been published to demonstrate the relationship between cause and effect, but regrettably, there is no widely accepted method for identifying the cause of ADRs.

    Quality Control

    • Signals having insufficient information might render determining an event’s cause unfeasible. The information on patients and medications is the essential foundation for the subjective evaluation of the quality of the reports.

    The strength of the adverse event

    • The incident’s description and the data provided in the pertinent section of the ADR forms are used to determine how serious the event is.
    • Adverse occurrences are considered serious if they were fatal, life-threatening, resulted in significant impairment or incapacitation, or required extended hospitalization.

    System for Reporting Adverse Events

    • The FDA’s Adverse Event Reporting System is a database that contains information on reports of drug mistakes and adverse events. The FDA’s post-marketing safety surveillance program for pharmaceutical and therapeutic biologic products is supported by the database.
    • Adverse events and medication errors are classified by Med DRA nomenclature.
    • The AERS can be used by the FDA to perform duties like looking for recent safety concerns that might be related to commercially available products and evaluating a manufacturer’s compliance with reporting requirements.

    The Argus Safety Database

    • One of the most important components of the pharmacovigilance software system is the Argus Safety 3.0.1 database. Employers can use the digital database to support pharmacovigilance and other relevant operations while ensuring compliance with international laws.
    • It provides a pharmacovigilance business process that occurs during the drug’s pre-and post-marketing phases as a full pharmaceutical software solution. The Argus database is housed in an ISO-9001 accredited data center that complies with the safety regulations set forth by the FDA regulations.
    • Oracle Argus Safety products that are related to Oracle Argus Safety include Oracle Argus Insight, Oracle Argus Perceptive, Oracle Argus Affiliate, Oracle Argus Dossier, Oracle Argus Interchange, Oracle Argus Reconciliation, and Oracle Argus Unblinding.

    Recent Advances in Methodologies

    • Risk management plans have recently been established in post-marketing surveillance to systematically characterize, prevent, or limit hazards associated with pharmaceutical products, including the evaluation of the intervention’s efficacy.
    • The benefits-risks of the medicine throughout the post-authorization phase can be better comprehended with the aid of these RMPs.
    • To effectively identify the warning signs of adverse events, health professionals must present accurate information in their adverse event reports. The quality of adverse event reports is improving as more reports are made online.
    • Another crucial breakthrough is patients’ taking part in pharmacovigilance. Patients can now report ADRs to the spontaneous reporting system in many nations. Data can be collected and analyzed quickly with this kind of automation.

    Further Outlooks

    • Academics must create fresh approaches that can improve the current system to further demonstrate pharmacovigilance’s scientific validity. Active observation is required to learn about the drug’s safety at an early stage.
    • One must keep the significance of being able to obtain information promptly in mind when creating new techniques for active post-marketing surveillance. In most cases, the techniques, and the results conflict. Therefore, it’s critical to provide techniques for answering this kind of query.
    • Patients’ roles are progressively evolving. The patient is now well-informed about his illness and eager to take an active role in his care. Therefore, in the future, pharmacovigilance must focus on this group as a key source of information.
    •  Future pharmacovigilance must be capable of quickly recognizing novel safety signals. If this is successful, the patient’s faith in medications will return.

    The scope of the research

    • The most crucial part of pharmacovigilance is accurate signal identification and assessment. Signal detection is accomplished using a variety of techniques. Pharmacovigilance signals come from a variety of sources. 
    • PV may not be dependent on a single technique but rather on a coordinated set of actions. Through effective training and retraining of the staff involved in the pharmacovigilance activity, the quality of the reports can be enhanced. 
    • No single causality assessment technique is accepted by everyone. Therefore, the current desire is for a single effective strategy that is accepted by everyone.

    Sollers College will help you bridge the gap between these lucrative jobs and the skills required by prospective candidates. A career in pharmacovigilance affords you the chance to make a difference in people’s lives due to the current increase in the need for pharmaceutical specialists.

  • A validation study of intelligent automation for pharmacovigilance

    A validation study of intelligent automation for pharmacovigilance

    Pharmacovigilance is the discipline of keeping an eye on the effects of pharmaceuticals to spot and assess potential side effects and provide necessary and prompt risk reduction measures.

    Automating regular tasks and balancing resource consumption across safety risk monitoring and other pharmacovigilance operations are both possible with intelligent automation technology. New technologies like artificial intelligence (AI) hold enormous promise for improving pharmacovigilance because of their capacity to learn from data inputs.

    However, existing validation criteria should be supplemented to test intelligent automation systems. While the fundamental requirements for validation generally stay the same, new tasks designed for intelligent automation are required to provide proof that the system is fit for its intended use.

    The validation of AI-based systems

     There are three types of intelligent automation systems, ranging from rule-based to dynamic AI-based, and each type requires a different validation strategy.

    By building on current best practices for automated production, a risk-based strategy for artificially intelligent static systems is presented. Assistive technology solutions can be developed, applied, validated, and maintained by pharmacovigilance experts using framework. 

    • A successful pharmacovigilance expert must bridge the gap between business operations and technological innovation to prepare for inspections and comply with international regulatory agencies.
    • A significant number of resources is devoted by pharmacovigilance departments to processing adverse event (AE) cases, and according to benchmark data, the number of AE cases is rising.
    • Automating routine tasks and balancing resource use across safety risk management and other pharmacovigilance activities are both possible with intelligent automation technologies. 
    • Intelligent automation can improve the accuracy and reliability of case processing and evaluation, enabling a prompt evaluation of safety signals. 
    • The use of such technological solutions to assist with AE cases must be validated in accordance with regulations.
    • Automating regular tasks and balancing resource consumption across safety risk monitoring and other pharmacovigilance operations are both possible with intelligent automation technology. 
    • Intelligent automation can enhance the accuracy and reliability of case processing and evaluation, enabling a prompt evaluation of safety warnings. When such technological solutions are used to assist in the handling of AE cases, pharmaceutical firms must validate this software in accordance with laws. 
    • Computerized system validation (CSV) is the procedure used to confirm and record that the requirements for a computerized system are continuously met from the time of design until its decommissioning and/or transfer to a new system. 
    • The method to be used for validation should be centred on a risk assessment that considers the system’s intended usage, the possibility that it could have an impact on human subject protection, and the dependability of trial outcomes. 
    • For many years pharmacovigilance has made extensive use of algorithms, rule-based software, computerized workflows, and pattern matching. Robotic process automation has been used by several businesses and suppliers more recently to help manage individual case safety reports.
    • Machine learning (ML) and natural language processing (NLP) approaches are two recent fields of research based on artificial intelligence (AI) technologies that are currently being used to support pharmacovigilance procedures. 
    • The potential of this kind of technology to learn from data inputs offers enormous promise, but to validate intelligent automation systems, already-existing validation frameworks may need to be strengthened. 
    • For the system to meet its intended uses, it is necessary to perform more software development activities specifically geared toward intelligent automation.

    Graduate Certificate in Training in Drug Safety and Pharmacovigilance

    An innovative course created for professionals seeking a career in drug safety that makes use of the in-demand, business-based Oracle Argus Safety Database Software. 

    Invest in pharmacovigilance to start your path to a rewarding career. Learn how to launch your PV project successfully.

  • Could Analytics and Technology Change Pharmacovigilance?

    Could Analytics and Technology Change Pharmacovigilance?

    Pharmaceutical companies utilize pharmacovigilance techniques and procedures to make sure the products in their portfolio meet the necessary safety requirements. PV is the practice of monitoring a drug’s outcomes after discovering unreported adverse effects.

    This can help pharmaceutical firms get innovative insights from safety data to reduce PV costs, improve the efficacy of their products, and discover novel treatment options like the three-point seatbelt, which may be beneficial to their company, the pharma sector, and society.

    The pharmaceutical industry’s top concerns are the efficacy of its products and the security of its customers. Several businesses are advancing PV by making modest investments in process automation.

    Automation could be used for case processing and signaling.

    • Multiple markets and industry trends are putting current PV systems and processes to the test, forcing some pharmaceutical organizations to consider more efficient and cost-effective ways to gather trustworthy safety data and high-quality information.
    • Some survey respondents claimed to be using automation to reduce the cost of case processing and improve signaling.

    Case processing

    • The primary goal is to lower the expense of case processing. The cost of PV varies depending on the processing of each case. Additionally, there are more cases every year. Some manufacturers are actively exploring automation of case processing while using scale and outsourcing. For each case safety report, automation may result in annual cost savings.
    • To increase patient safety, maintain compliance, and achieve cost control over case processing, a corporation must be able to automate more of these operations.
    • Automation investments have a considerable positive impact on case processing teams’ productivity. Productivity boosters are native automation and “bolt-on” solutions that can lessen the work needed to run duplicate checks, speed up coding tasks, and expedite narrative authoring.
    • The capacity to automate complete case-processing processes, however, is restricted. Even for relatively basic instances, end-to-end case automation is still a long way from being a practical production capability.
    • Short-term signaling investments are anticipated to concentrate on visualization, and longer-term efforts are linked to data integration as well as tool and process enhancements as pharmaceutical companies work toward genuine safety management. 
    • Due to limitations in the signal detection and management systems currently in use, safety information to tie back into the discovery process is still lacking. The ability to detect signals is improved by higher data consistency and quality. Predictive signaling is the ultimate objective.

    Automation action

    The study will also demonstrate that even bigger gains are feasible by developing the technology and analytics necessary to build a PV system that focuses on benefit-risk management and proactive monitoring over the whole product lifecycle. This strategy will be advantageous to pharmaceutical firms, the life sciences sector, and society at large, like the three-point seatbelt.

    The development of a future PV system to increase patient safety

    • PV budgets for biopharma firms must include funds for automation, cognitive technologies, and analytic tools to lower case processing costs, enhance signal processing capabilities, and speed up product safety reports.
    • It is possible to build a true, evidence-based hub for safety intelligence throughout the whole product life cycle and to fully understand the benefits and risks of a product by adopting a proactive, patient-centered mindset. Several internal PV groups access safety information from external sources.
    • The function of signaling is to implement a modular learning loop system that makes use of automation and cognitive processing to employ continuous learning to help limit risk and increase compliance.
    • Systems should be equipped with cognitive case processing capabilities that automate data collection and processing to greatly increase the efficiency and calibre of the AE life cycle.
    • For analysts to perform validation and assessment tasks, collect results, and mark signals without leaving the system, signal detection, evaluation, and management that consolidate and streamline processes and systems are needed. As a result, signal handling is more precise and better.
    • Safety metrics that make use of current safety data, fresh real-world sources, supervised and unsupervised machine learning, detection, assessment, and prevention of safety-related problems while revealing advantages that can enhance patient outcomes.

    PV System to Increase Patient Security

    PV operations will change because of the adoption of advanced learning, which will improve decision-making through expanded data cohorts and cognitive innovation.

    Cognitive case processing insights enable intelligent, efficient signaling and aggregate reporting.

    • Enhancements to case quality and compliance
    • Targeted human reviews by bright and perceptive individuals that increase insights and expertise
    • Increased value-based resource allocation

    Case processing and signaling automation are influenced by the lessons learned from the case series evaluations.

    • It produces aggregated report content automatically, with analysis and benefit-risk insights.
    • Automation, uniform analysis, and evaluation of safety results are made possible by a single data universe.
    • Aggregate reporting becomes a process under the direction of professional review.

    Utilizing the knowledge and insights acquired from signaling detections and reviews, case processing and aggregate reporting are automated.

    • Encourage automation and intelligence in the signal management process.
    • Review and judge signals automatically based on patterns and trends and offer benefits and risks proactively to the scientists.
    • Make use of other data sources, including clinical safety.

    Sollers College provides professionals who wish to follow training regarding a career path in pharmacovigilance.

    You may close the skills gap between these attractive occupations and what potential candidates are looking for. 

    Every career has a path and, nowadays, benefits from additional help.

  • The Current Pharmacovigilance System Goals

    The Current Pharmacovigilance System Goals

    • Due to increased concerns about pharmacovigilance, PV has become more crucial in the pharmaceutical industry.
    •  PV, according to the World Health Organization, is the science and methods involved in the ongoing detection, evaluation, and comprehension of adverse events or adverse medication reactions to determine the risk profile of a product.
    •  A primary national regulatory authority and numerous regional or national centers make up the common structure for a national pharmacovigilance system.
    •  According to WHO, National Centers are pharmacovigilance facilities authorized by the organization that are in nations taking part in the WHO Programme for International Drug Monitoring.
    •  Typically, NCs are affiliated with or a component of the national drug regulatory body. Individual case safety reports are sent to a local PV center by healthcare professionals and patients.
    • The drug safety sector is currently under pressure from expanding data quantities and complexity to find solutions that lower case processing costs while maintaining compliance with globally changing standards and preserving or even improving the information quality in ICSRs
    • In parallel to this, regulatory organizations are pressuring doctors to record more instances of PV, and patients are also sharing their accounts of adverse events. 
    •  This entails making use of outsourcing partners’ advantages, which help manage workload demands and limit workforce expansion while delivering scalability. Although the opportunity for outsourcing is limited, the processing still requires manual labor.
    •  Pharmacovigilance is a post-marketing tool that guarantees a drug’s safety. The detection of ADRs and the mitigation of related hazards are its main concerns. Regarding tiers of the social healthcare setting, a well-structured PV system can assist in producing correct safety data.
    • A well-thought-out plan that guarantees flawless execution and tangible benefits is required for the establishment of a pharmacovigilance system.   

    Current Pharmacovigilance Challenges

    PV systems have come a long way over the past few decades, but they still face several obstacles today. A well-designed PV system can assist in accurately generating safety data for several spheres of the social healthcare setting. The establishment of a pharmacovigilance system necessitates the harmonization of several criteria and a carefully thought-out strategy that guarantees flawless execution and physical benefits.

    The Current Pharmacovigilance System Goals

    Situation 1: Inconsistent reporting of adverse events

    • Adverse events, however, do not always occur while visiting the healthcare center. It can happen several hours after the medicine was administered. Patients frequently struggle to appropriately report AEs since they can’t recall every detail about them.
    • When a patient disregards medical advice or experiences negative effects from drugs taken simultaneously with prescribed therapies, this is referred to as an adverse event. Such inaccurate reporting may cause drug safety committees to draw erroneous conclusions, which may result in the suspension or removal of medications.

    Situation 2: Constantly changing laws and business practices

    •   PV systems must scale easily and effectively because of business expansion into newer markets. It has become crucial to ensure that PV systems and procedures continue to advance.
    •   The underlying database, configurability, reporting capacity, and system connection with data sources and other applications are just a few areas where the evolving regulations have an impact on PV operations.
    • Regulation non-compliance and the resulting fines are caused by a lack of support and continually evolving standards. The need varies more widely in non-ICH regions, making reporting even more challenging.

    Situation 3: Data Processing and Detection

    • Because of the steadily increasing amounts of AE data, it is difficult for reviewers to track, identify, and manage all potential developing patterns using only qualitative methods. Since manual processes take a long time, it can take the reviewer a few weeks to study a particular signal.
    •   On the other hand, the regulators’ and life science enterprises’ query and response cycles are rapidly closing, forcing the reviewers to quickly assess the signals.
    • Reviewers must concentrate on current problems while spending less time and effort identifying false signals. Ineffective signal detection and handling make it difficult to meet regulatory reporting requirements, which results in fines.

    Situation 4: Operational efficiency and productivity

    • When transferring and submitting cases across ICH areas, an organization faces many challenges. Some businesses choose to send the submission data back to their main office to keep the central system up-to-date.
    • Routing and maintaining track of ICSRs must be done manually because pharmacovigilance is not automated. The procedure is delayed as a result, and AE processing and reporting are inadequate.

    Situation 5: System Implementation

    • Existing PV systems have problems with system integration, data sharing between unrelated applications, system availability, and system scalability. It leads to a system breakdown because of poor scaling and shaky performance.
    • Data inconsistency results from the manual intervention involved in this. As a result, productivity and efficiency suffer in PV departments.

    Situation 6: Handling a larger volume of data

    • v  Processing the growing amount of data that the ecosystem is producing is posing a serious issue for the worldwide PV business.
    • v  An annual exponential increase in data quantities is being caused by a variety of sources, including journals, publications, social media, patents, and an increasing number of unstandardized data sources.
    • v  However, many businesses continue to manage information using outdated technological platforms and manual procedures. This reduces productivity and is prone to mistakes.

    Situation 7: Ensuring Data Quality

    • The complexity and variety of the technologies used to gather and store the data are growing along with the volume and type of data being collected during the life cycle of the product.
    •  Certain data input and data coding standards are essential for accurate reports and signal detection.
    •  To maintain quality, newly entered or received data must be reviewed for quality.
    • A PV system should adhere to certain specific parameters to reduce errors in signal detection, recorded data, and aggregate reporting.

    ‍ Join Sollers College today to start your career in drug safety and pharmacovigilance. Your PV skills will be helped at every stage of the curriculum. Students who are ready to develop their profiles can choose from training programs offered by Sollers.

    Sollers’ College distinctive curriculum consistently creates a wide range of career options and offers the best professional supervision and swift learning support.

    To learn and share your knowledge, Sollers College created a road to the sizable pharmaceutical sector. Don’t let yourself be limited to meeting your needs in this pharmaceutical market.

  • The Outcomes of Automation on Pharmacovigilance in the Real World

    The Outcomes of Automation on Pharmacovigilance in the Real World

    • Pharmacovigilance’s main objective is to encourage the safest possible use of medications. However, it is under greater pressure to quickly analyze additional data, monitor risks more thoroughly, and accurately report patient occurrences on a worldwide scale. Pharmacovigilance is a field that has experienced rapid expansion in recent years.
    • Traditional PV plans must be changed and revitalized with smarter expenditure in mind due to the constant challenges of cost optimization. Instead of concentrating exclusively on safety operations, attention is being paid to proactive risk management, individualized treatment, and comprehensive data transparency between pharmaceutical companies, patients, healthcare providers, and regulatory bodies.
    • Pharmaceutical PV strategy updates are largely influenced by technological advancements. For instance, more businesses see big data analytics, robotic automation, cloud-based solutions, and mobile applications as essential components of clinical, safety, and regulatory operations in the pharmaceutical sector. To effectively manage the safety of pharmaceutical products, it is becoming increasingly essential to implement cutting-edge technological automation tools and processes for PV methods.

    Enhancing Functionality

    • PV techniques must be optimized for maximum efficiency because they are one of the life sciences fields with the fastest growth.
    •  A solid foundational framework for IT gives organizations great performance, scalability, system validation, and data security for efficient design and dissemination of automation efforts.
    • Operational efficiency can be increased, and a proactive PV strategy can be driven by taking care of organizational needs, process improvements, and IT solution enhancements concurrently.
    • Traditional PV systems now have holes that AI has the potential to fill, such as the need to map patterns and integrate massive amounts of cloud-based data to accurately predict ADRs. This more streamlined strategy can also use genetic data and actual patient data to make PV a more predictive science.
    • Integrated IT solutions that integrate technical and scientific know-how can produce high levels of operational effectiveness, quality, and regulatory compliance.

    A Four-Stage Automation Approach

    •  Even though many of today’s IT systems and apps are capable of automating case processing and reporting tasks, the total process still necessitates a sizable amount of manual labor, especially when it comes to case intake and data entry.
    •  Many levels of automation can be used to streamline end-to-end safety processes and eliminate unnecessary, non-value-added steps in existing processes while boosting the effectiveness of human labor.
    • Basic process automation, which includes task tracking and monitoring and enables the gathering of continuous metrics, is the initial stage. The entry, processing, and analysis of safety data into a database or system still require manual labor.
    • Basic automation offers reporting and dashboards and automates a workflow involving numerous roles. The next stage, robotic process automation, assists in reducing or removing these manual processes.
    •  Robotic Process Automation is frequently paired with cognitive automation, the next level after RPA that uses Natural Language Processing (NLP) to support human decision-making.
    •  The system interacts with people, but the ultimate level, AI, requires little to no human interaction and self-learns via experience to generate predictions based on patterns found in massive amounts of data with the use of machine learning.

    Regulations adapted to industrialization

    • The development and application of technologies that can provide a safe, integrated big data repository are desperately required due to the ever-increasing volumes of drug data. As a result of a major development in the PV industry, cloud-based capture and reporting and a fully integrated database are accessible to all stakeholders.
    •  Cloud technology integration can improve data collection, storage, and analysis even further and potentially offer geographical and temporal insights into ADR patterns.

    Implementing a strategy for automation

    • Higher levels of automation, like RPA and cognitive automation, allow businesses to identify patterns in unstructured data and can automate the entire procedure, from case receipt through reporting.
    •  Implementing an automated plan can enhance the precision and quality of secure data processing by removing the possibility of human error, in addition to lowering expenses.

    Integrated PV processes’ outlook

    • Regulatory authorities adopt more sophisticated methods to gather, characterize, and assess data on AEs because of the evolving PV landscape, enabling pharmaceutical companies to build effective PV programs and more effectively control the safety of their products.
    •  The industry is undergoing a technology revolution, driven in part by an expanding population, an increase in novel and highly specialized remedies for unmet medical needs, and an increase in the number of pharmaceutical organizations.
    •   Automation is essential if clinical trial costs and complexity are to be kept to a minimum and stakeholder engagement for real-time decision-making is to be enhanced.

    One can start a profession in Pharmacovigilance right now. Upskill with excellent learning to kickstart your career in this PV field. Build a rewarding career by learning industry-relevant skills.

  • Challenges and Opportunities in Hiring in the Life Sciences

    Challenges and Opportunities in Hiring in the Life Sciences

    Life sciences organizations confront new difficulties in Clinical Trials, Drug Safety etc., and possibilities every year, but 2021 will be the year when they are front and center more than ever. According to the US Bureau of Labor Statistics, professions in the life, physical, and social sciences will expand by 7% by 2028. It will be quicker than the national average for all other vocations. Within the following decade, this would imply the creation of around 97400 new employment.

    The COVID-19 epidemic has also shifted the job landscape by emphasizing the importance of the biological sciences industry.

    Industry expansion is vital. Because of the pandemic’s need, there is a fierce and considerably more demand for talent than ever before. Employers have faced issues as a result of a rising supply and demand mismatch for trained individuals. Candidates with experience in areas such as healthcare, biotechnology, and pharmaceuticals will be in great demand. Companies would have to undergo a more extended recruitment procedure to fill life sciences, especially in specialist areas.

    The need for technological skills is growing. With the convergence of technology and life sciences, there has been a greater emphasis on recruiting personnel with the skills to offer tech-enabled solutions. Biotech, data analysis, and digital product management will be in high demand in 2021 and beyond. Companies will remain ahead of the curve in a continuously changing industry.

    Remote positions are becoming more prevalent. The pandemic has caused a shift in the rise of small labor in a variety of industries. Many conventional jobs in the life sciences industry have gone online and will continue to be distant in the future. The need for remote positions for healthcare practitioners such as physicians, nurses, and other clinicians has increased as telehealth services have been more widely adopted.

    Biopharma and life sciences businesses are now competing with technology companies for specialized sector personnel, such as computational biologists and bioinformaticians, in addition to seeking the same talent pool as other industrial sectors for general digital skills. 

    Are you prepared to take chances on applicants with less experience but a desire for innovation?

    That is very dependent on the function. In some instances, especially in specialized areas, you cannot afford to take the risk or devote the time to train individuals up. In other cases, hiring for potential and enthusiasm makes excellent sense. 

    Sollers provides certificate programs in various life science fields such as Clinical Research, Clinical Data Science and Drug Safety & Pharmacovigilance. 

  • Are You Looking to Start a Career in Life Sciences?

    Are You Looking to Start a Career in Life Sciences?

    Are you trying to shift towards a major career change path or simply looking for something new and distinct?  a career in life sciences would provide you with all of these opportunities to make a difference in the world by developing a life-saving vaccine or medication, maintaining the quality of foods to prevent widespread illnesses, or pushing society forward with technological breakthroughs. 

    Life sciences are often at the forefront of medical advancements, but they have played critical roles in other disciplines for hundreds of years, such as agriculture and food safety. Because there has always been a general need for the study of life sciences as they push and develop our society forward every day, it produces fresh demands for innovative individuals to keep the momentum going, resulting in an abundance of job security for those in the field. 

    What Are Job Opportunities Available?

    There is something for everyone with so many options across dozens of fields. Biochemists, clinical research associates, research assistants, and microbiologists are some of the most popular occupations in life sciences. Biomedical scientists, computational biologists, industrial pharmacists, and bioinformaticians are lesser-known but equally significant professional alternatives. 

    If you want to work in the medical industry, being a biomedical scientist is the most acceptable option. Examining tissue samples and assisting and advising medical physicians in diagnosing and treating their patients are among their responsibilities. A biomedical scientist must have a thorough understanding of pathology, anatomy, and physiology. Industrial pharmacist and clinical research associate are two more life science jobs significantly involved in the medical field.

    What’s the Best Way to Get Started?

    You must first earn a degree that is relevant to your career choice in order to realise your dream of working in one of the various life science professions.

    Are you prepared to take the first step? Talking to a university counsellor is a good place to start. Career advisors can assist you in determining the best path of study for your interests and needs. Sollers can assist you to find the best career growth. Most people who pursue a career in life science begin with a bachelor’s degree in biology, chemistry, life science, pharmacy, or computer science, and then pursue a master’s degree in a more specialised field, such as industrial pharmacy or biochemistry. Begin small and aspire to a career in life sciences!

    So what are you waiting for? We’ve got the Top booming Life Sciences Fields of 2030. So go ahead and have a look. Do your study, connect it to your persona, career goals, and hobbies, and, most importantly, decide on the type of career you want to create for yourself. Then go ahead and get in. Remember that a small pebble thrown into the ocean of Life Science today will return to you tomorrow in the form of a tsunami of employment prospects.

×