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      Pharmacovigilance 2030 : Invited Commentary for the January 2020 “Futures” Edition of Clinical Pharmacology and Therapeutics

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      Clinical Pharmacology and Therapeutics
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          Abstract

          A new healthcare system is emerging that encompasses systems approaches to biology and medicine, radically enhanced capabilities for collecting, integrating, storing, analyzing, and communicating data and information, and increasing numbers of networked and activated patients and consumers. Pharmacovigilance systems around the world have come a long way in the last 60 years. Systems have evolved from reliance on the individual case safety report (ICSR) of suspected adverse drug reactions (ADRs), through addition of the periodic safety update report, and risk management plan, to the current era where many stringent regulators have a pallet of regulatory tools and access to an ever increasing spectrum of data sources, real‐world or otherwise. Modern systems also leverage the collaborative efforts of multiple stakeholders, notably the biopharmaceutical industry, regulators, healthcare professionals, patients, and academia. Pharmacovigilance is well stocked with clairvoyants who have made many claims, sometimes wild, for the future, including that we will rely on artificial intelligence and robotics, that the ICSR is dead (or should be dead), or that mobile health holds the ultimate promise for increasing engagement and impact.1 There is no doubt that technology is advancing rapidly, that the accumulation of data is increasing logarithmically, and that society is changing, particularly the engagement of patients in healthcare decision making. However, some things stay the same. The ultimate goal remains to optimize the safe and effective use of medicines so patients can benefit in terms of health and quality of life while suffering the minimum of side‐effects. The challenges to optimizing safe and effective use of medicines are common to all regulatory and healthcare systems: how to influence the behavior of patients and healthcare professionals based on robust evidence and sound decision making. We make three predictions for pharmacovigilance in 2030. (1) Collection and reporting of ICSRs will be smarter. (2) Measurement of on‐market performance of medicines will inform decision makers and users of medicines. (3) Improved engagement of patients and healthcare professionals will increase the impact of pharmacovigilance. Prediction 1: Smarter Collection and Reporting of ICSRs By the end of 2018 EudraVigilance, the European database of ICSRs held over 14 million case reports and VigiBase, the World Health Organization (WHO) database held over 20 million. Although only representing a snapshot in time, these are electronic health records and have the huge value of capturing a suspicion of a patient or health care professional that a medicine may have caused an adverse reaction. With the onset of the digitalization of health care, there is the opportunity to access more and better data and provide alternative approaches in pharmacovigilance, including both the detection and evaluation of ADRs. This means that we need to design our systems based on an abundance of data rather than a scarcity.2 However, over recent years, the proportion of new drug safety issues detected from ICSRs has been high at around 55%,3 and the number of product withdrawals based partly or wholly on ICSRs has also remained high.4 These observations have occurred despite the increasing interest in other data sources for signal detection. The evidence suggests that ICSRs remain a very useful data source for detecting potential new safety issues, whereas electronic health records (EHRs) are more useful for evaluating the issues already detected. This is in line with the principle of hypothesis testing in a dataset separate from that in which the hypothesis was generated. We do not question that there are opportunities to improve the collection and management of ICSRs,5 and in the way such reports are submitted to regulators. We also acknowledge that the investment in the collection and management of ICSRs has been and continues to be high. However, we believe that by 2030 ICSR reporting will be much smarter. New technologies including e‐Health apps, as well as the international collaboration between industry and regulators to revise International Conference on Harmonization (ICH) guideline E2D provide excellent opportunities to optimize data collection and management. The wider reach of the reformed ICH also provides the chance of a more global implementation of a harmonized approach. Our message is to protect and improve ICSRs, our main source of safety signals. The ICSR is far from dead but it can and should be improved. We do caution that future process improvements, including the update of processes based on artificial intelligence and robots, should be evidence based and the impact of changes should be monitored particularly in terms of data quality and signal detection. Prediction 2: Measurement of On‐Market Performance of Medicines In 2010, the proposition that healthcare is evolving from reactive disease care to care that is predictive, preventive, personalized, and participatory (the “4Ps”) was regarded as highly speculative. Today, the core elements of that vision are widely accepted.6 In parallel with the move to the 4Ps, opportunities have increased to leverage the exponential growth in real‐world data, including data from EHRs, disease registries, claims data, mobile applications, and social media.7 These sources, particularly EHRs and claims data, can provide new insights in health, disease, and, critically, the use and performance of medicines, including both benefits and risks. In 2020, in the global world of medicines regulation, traditional barriers have started to come down, including the binary definition of a medicine to have preauthorization or postauthorization, for studies to use randomization or observation, and, importantly, for safety to be measured and evaluated separately from efficacy. Pharmacovigilance has made great progress in moving from a reactive activity driven by spontaneous reports of suspected ADRs to a more proactive activity with planning starting before the product is on the market. By 2030, to move to the next level, we need the monitoring of medicines to encompass both safety and efficacy on the market (performance) and for this to be planned well before market entry. If this is done well and representative data are available, data can be analyzed and fed into decision making by regulators and pharmaceutical companies for product labeling, to health technology assessment bodies for assessment of value, to payers for reimbursement decisions, and as health information to support individual decisions by healthcare professionals and patients (contributing to the realization of precision medicine).8 Significant progress in accessing and analyzing real‐world data has been made through initiatives, such as Sentinel in the United States, the Observational Health Data Sciences and Informatics (OHDSI) network, and harnessing the rich and diverse longitudinal healthcare data in the European Union. Challenges to accessing and analyzing real‐world data continue9 of which the methodological challenge to evaluating on‐market efficacy is perhaps the greatest. Although acknowledging these challenges, we believe that by 2030, for targeted new medicines, a planned monitoring of performance on the market will take place with nearly real‐time decision making by regulators to optimize the safe and effective use of medicines. Prediction 3: Improved Engagement of Patients and Healthcare Professionals New forms of participation by patients and healthcare professionals are key to delivering the vision for transformation of healthcare in the digitally networked era. One of our society's greatest assets is the increasing determination of healthcare consumers to better manage their own health using the internet to gather information and their ability to self‐organize using social networking tools.10 Therefore, our final prediction for 2030 is that regulators will engage patients and healthcare professionals much more intensively to maximize the positive impact of pharmacovigilance on the safe and effective use of medicine. Both the Holy Grail and the Achilles Heel of pharmacovigilance are to change the behavior of patients and healthcare professionals based on information about a medicine's safety and efficacy (performance). Recent work conducted in the European Union on measuring the impact of pharmacovigilance1 has found sometimes disappointing results of regulatory action taken, a recent example being the 2013 review of pregnancy safety of valproate and the lack of impact of stringent warnings in product information in terms of prescribing practice. Different regulatory authorities around the world have made major efforts to engage with healthcare professionals and patients and this represents a dramatic change compared with 20 years ago when regulation was fundamentally disengaged from the key stakeholders. However, there is much further to go if we are to be truly effective in responding to patients' needs and to enabling patients to use their medicines optimally. Opportunities include electronic product information updated in close to real‐time supporting decision‐support systems for the prescription, dispensing, or use of medicines, and fostering much closer relationships between regulators and patients and healthcare professional organizations. The latter means that, when there is a need for change and a call to arms goes out, stakeholders are ready to listen, to trust, and to change behavior. We believe that in 2030 much more of the regulators' time will be spent engaging with patients and healthcare professionals and ensuring that the information provided to them is effective in supporting the safe and effective use of medicines. Conclusion The pace of change in pharmacovigilance is rapid. We must measure the impact of our work and ensure we make evidence‐based process improvements. We should value what works and strive to meet the challenges and opportunities of our fast‐changing world, a world of increasing openness, data collection, technological power, and patient engagement. We predict that smarter collection and reporting of ICSRs, of measurement of on‐market performance of medicines, and of improved engagement of patients and healthcare professionals will be the most significant changes in pharmacovigilance by 2030. We also believe that these changes will enable faster access to life‐saving treatments for patients around the world and for these treatments to be used more effectively and safely. We look forward to seeing if our predictions come true, and we might just try to make them. Funding No funding was received for this work. Conflict of Interest The authors declared no competing interests for this work. Disclaimer The views expressed in this paper are the personal views of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the regulatory agencies with which the authors are employed.

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          Real-World Evidence - What Is It and What Can It Tell Us?

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            P4 medicine: how systems medicine will transform the healthcare sector and society.

            Ten years ago, the proposition that healthcare is evolving from reactive disease care to care that is predictive, preventive, personalized and participatory was regarded as highly speculative. Today, the core elements of that vision are widely accepted and have been articulated in a series of recent reports by the US Institute of Medicine. Systems approaches to biology and medicine are now beginning to provide patients, consumers and physicians with personalized information about each individual's unique health experience of both health and disease at the molecular, cellular and organ levels. This information will make disease care radically more cost effective by personalizing care to each person's unique biology and by treating the causes rather than the symptoms of disease. It will also provide the basis for concrete action by consumers to improve their health as they observe the impact of lifestyle decisions. Working together in digitally powered familial and affinity networks, consumers will be able to reduce the incidence of the complex chronic diseases that currently account for 75% of disease-care costs in the USA.
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              Real‐World Data for Regulatory Decision Making: Challenges and Possible Solutions for Europe

              Real‐world data (RWD) offers the possibility to derive novel insights on the use and performance of medicines in everyday clinical use, complementing rather than competing with evidence from randomized control trials. While Europe is rich in healthcare data, its heterogeneous nature brings operational, technical, and methodological challenges. We present a number of potential solutions to address the full spectrum of regulatory use cases and emphasize the importance of early planning of data collection. There is increasing interest in the use of real‐world data (RWD) to support regulatory decision making across the product life cycle. Key sources of RWD are electronic health records, claims data, prescription data, and patient registries. Increasingly incorporated into the definition is data from wearables, m‐health apps, and environmental data including data on social status, education, and other lifestyle factors. These latter data offer much promise to deliver a holistic picture of an individual's health status but from a regulatory standpoint present substantial challenges in deriving actionable evidence. From the perspective of the European Medicines Agency (EMA), RWD are defined as “routinely collected data relating to a patient's health status or the delivery of health care from a variety of sources other than traditional clinical trials.” We specifically exclude traditional clinical trials even if single arm but would incorporate data from pragmatic clinical trials if data were collected remotely through an electronic health record or other observational data source and solely under conditions of normal clinical care.1 Real‐world evidence (RWE) is then defined as the information derived from analysis of RWD, and it is the acceptability of this evidence for regulatory decision making in different use cases across the product life that has become the subject of intense debate. The use of RWD to support regulatory decision making is not new. For decades such data have been used for safety signal evaluation, risk management and for studies to support life cycle benefit‐risk evaluation;2, 3 contexts where opportunities to capture data, especially in a timely fashion, are more limited and where multiple sources of information of varying quality from multiple stakeholders must be balanced to inform decision making. In fact, for pharmacovigilance decisions, it could be argued that it is essential that safety is understood in the context of how care is delivered rather than under the stringent and highly monitored conditions of the clinical trial. To directly support EMA committees, the EMA is routinely using three real‐world databases for in‐house studies and over recent years has commissioned 15 external studies, most of them multidatabase and multinational. It is also well recognized that RWD are an underutilized source for assessing the public health impact of risk minimization measures, including any unintended consequences4 and for informing health technology assessment, pricing, and reimbursement decisions.5 The natural extension to these safety‐orientated questions includes disease characterization and prevalence, understanding current standard of care, and confirming the clinical outcome of short term surrogate markers. To date, however, there is a lower acceptability of RWD where the outcome of interest is efficacy/effectiveness.6 Great caution is generally exercised where positive regulatory decisions result in patients being exposed to a new medical product, and hence an estimate of efficacy free from the biases of observational data is required.7 The best available standard of evidence to date has been the randomized control trial (RCT). The RCT will, in our view, remain the best available standard and be required in many circumstances, but the rapid pace of change in the scientific and technological landscapes is shifting the regulatory landscape. We are seeing an increasing number of products that face challenges to align with the traditional drug development pathway; often these are advanced therapies or orphan products for conditions with significant unmet need and for which a traditional RCT may be unfeasible or unethical. Table S1 provides recent examples where RWE has been pivotal for European regulatory decisions in terms of supporting the initial regulatory decision or postmarketing obligations. For many of these examples, the need was to enable both safe and early access to promising medicines for patients with limited treatment options or when uncertainties around the medicines remained. Where sufficient efficacy is demonstrated but uncertainties exist around long‐term safety and efficacy (Strimvelis, nusinersen (Spinraza)), postauthorization evidence generation coupled with adequate pharmacovigilance activities needs to be in place to quickly address uncertainties. However, where available evidence of efficacy requires contextualization, there have been examples where RWD provided an external control arm (Zalmoxis), were used to confirm a response rate in a single‐arm trial (axicabtagene ciloleucel (Yescarta), tisagenlecleucel (Kymirah)) or provided data to extend an indication (eculizumab (Soliris)). As personalized medicine becomes a closer reality, it is anticipated that such examples are likely to increase. Operational, Technical, and Methodological Challenges From a European perspective, utilizing RWD is faced with operational, technical, and methodological challenges, but possible solutions exist (Table  1). Operational challenges include feasibility, governance, and sustainability issues, which complicate access to and the routine use of multiple national data sources, many of which will have different legal and ethical requirements for sharing data. As a minimum, appropriate consents and data anonymization techniques are required to ensure data privacy obligation requirements are met; while of paramount importance, current operational processes designed to address obligations may prevent efficient and timely delivery of data, which may be particularly problematic in the context of safety decisions where urgent access to data is needed to inform a regulatory decision. Table 1 OPerational, TechnIcal, and MethodologicAL framework (OPTIMAL) for regulatory use of real‐world evidence (RWE) Objective Desired criteria for acceptability of RWE Challenges with use of RWD to generate acceptable RWE Possible solutions (EU context) Appropriate use of valid RWE for regulatory purposes (e.g. safety, efficacy, benefit–risk monitoring) Evidence is: Derived from data source of demonstrated good quality Valid (internal and external validity) Consistent (across countries/data sources) Adequate (e.g., precision, adequate range of characteristics of population covered, dose and duration of treatment, length of follow‐up) Operational Feasibility (e.g., data access and cost, availability of relevant data needed, data protection, patients’ consent, availability of hospital data source) Governance (e.g., data‐sharing policy, transparency, policy towards funding source) Sustainability (sustained data collection and analysis) Operational Early and repeated consideration of the need for RWD during drug development Landscaping of potential data sources Long‐term funding for data infrastructures Published documentation of data source characteristics and policy for collaboration and data sharing Management of access in line with European Union General Data Protection Regulation and national legislation Data anonymization processes where required Data sharing agreements at study inception Use of ENCePP Code of Conduct Technical Extent of data collected on clinical outcomes, exposure, and individuals Collection of adequate time elements Data completeness (missing data) Consistent use of appropriate terminologies and data formats Potential for data linkage Consistent, accurate, and timely data collection, recording, and management Technical Use of common data elements, data formats and terminologies, or mapping to international system Partial or full data mapping to CDM, including routine validation process Quality assurance and control procedures—indicators of data quality Internal or external data audit Benchmarking to external data source EMA qualification procedure for data source Methodological Variability in results from multi–data source studies. Understanding the data source environment Adequate data collection on potential confounders (e.g., smoking, indications) and effect modifiers (e.g., drug dose, disease severity) Identifying the potential for selection bias and information bias Management of missing data Sound data analysis and interpretation Methodological Detailed description of study design and data collected in data sources Documentation of feasibility analyses Registration of study in public database, with study protocols and results Use of best methodological standards in statistics and epidemiology Use of EMA Scientific Advice procedures for study protocols CDM, common data model; EMA, European Medicines Agency; ENCePP,European Network for Centres of Pharmacoepidemiology and Pharmacovigilance; RWD, real‐world data. John Wiley & Sons, Ltd Technological challenges describe those associated with the data, and solutions require addressing differences in terminologies, data formats, quality, and content that exist across multiple European databases. Europe is fortunate in the richness of its healthcare data and in particular its longitudinal nature, which stems from the principle of universal healthcare coverage, which remains at the heart of most European healthcare systems. However, the data are heterogeneous as differences in healthcare systems, national guidelines, and clinical practice have driven different content; a recent analysis revealed that the number of European databases that meet minimum regulatory requirements across a broad range of regulatory use cases and which are readily accessible is disappointingly low and geographically skewed to Western and Northern Europe.8 This poses problems when results from multiple datasets must be pooled in order to deliver evidence representative of the wider European population or when larger numbers are needed to explore rare diseases, events, or outcomes. Resolving differences across data sources requires agreement on common sets of data elements, data formats and terminologies, or mapping of these components to an international system. Obvious advantages of common data quality systems and common data analytics are to facilitate data exchange, data analysis, and interpretation of results arising from multiple datasets. New approaches to harmonization that involve a priori transformation of the data into a common data model (i.e., same data structure, format, and terminology) independent of any particular study have become possible in recent years due to improvements in the computational capacity to store, extract, and analyze large datasets. By enabling the use of common standardized analytics, this facilitates a consistency of approach and minimizes the need for decision making at the level of individual data sources. Within Europe, such approaches have the potential to significantly accelerate studies, but a careful characterization is required to determine whether there is loss of information or validity when EU data are transformed into a common data model and to assess any impact on downstream outputs. Methodological challenges arise from the fundamental fact that observational data are not collected with research as their principle purpose, may be derived from different care settings, and therefore suffer from variable amounts of missing data and from multiple different biases and confounders.7 However, in all these scenarios, a significant barrier to acceptability remains concerns around the reliability and validity of the evidence generated through RWD, especially when conducted across multiple countries and databases across Europe. Even when the protocol is standardized, significant variability may remain, increasing the heterogeneity of the results.9 Such issues have long been recognized, but compliance with the best methodological standards, a detailed description of study design and data collected, and full transparency on the protocol and study report (with registration in a publicly available database) would do much to build confidence in results and avoid the confusion created by disparate results. The European Network for Centres of Pharmacoepidemiology and Pharmacovigilance (ENCePP) has developed, and updates annually, standards for pharmacoepidemiology research, and there have been multiple publications recently proposing the establishment of reporting requirements.10 Ideally such reporting would be consistent with common parameters and terminology to enable comparability and be publicly available at a single source. All studies imposed by European regulators must be registered in the European Union electronic Registry of Post Authorisation Studies (EU PAS Register), and extending this requirement to all studies would seem one obvious route. Conclusions The digitization of health care and, increasingly, lifestyle data bring new opportunities to complement and enhance the data traditionally utilized in regulatory decision making. The hope is that this will improve the timeliness, accuracy, and relevance of decisions across the product life cycle. Defining the exact evidentiary standards of such RWE a priori is challenging as necessary standards will vary depending on the context within which the question is asked. Given the broad range of regulatory use cases, it seems clear that a one‐size‐fits‐all approach will not be sufficient; a hybrid approach to evidence generation will be required, depending on the question being asked and the context in which the derived evidence will be used, and early planning of the strengths and limitations of the possible approaches is required. However, whatever the approach, there is a need to address operational, technical, and methodological challenges in both designing, running, and assessing a study to enhance the quality of evidence generated and the consistency of regulatory decision making. Moreover, as more data sources become available and infrastructures are developed to enable access, there is an urgent need to consider and plan for the data needs for the future. Standardizing and validating data retrospectively is expensive, time consuming, and potentially introduces errors and biases, and hence it is important to consider in advance the scope, depth, and quality of data that will be required to generate reliable evidence suitable for multiple regulatory use cases. This work requires effort from the multiple stakeholders who may potentially wish to utilize these data for decision making. With the combination of technological and scientific advances available today, there has never been a more opportune time to address this. Funding No funding was received for this work. Conflict of interest The authors declared no competing interests for this work. Disclaimer The views expressed in this article are the personal views of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the European Medicines Agency or one of its committees or working parties. Supporting information Table S1. Recent regulatory examples in which RWE has been utilized to support regulatory decisions either at authorization or to support an extension of indication. Click here for additional data file.
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                Author and article information

                Contributors
                Peter.Arlett@ema.europa.eu
                Journal
                Clin Pharmacol Ther
                Clin. Pharmacol. Ther
                10.1002/(ISSN)1532-6535
                CPT
                Clinical Pharmacology and Therapeutics
                John Wiley and Sons Inc. (Hoboken )
                0009-9236
                1532-6535
                22 November 2019
                January 2020
                22 November 2019
                : 107
                : 1 , Clinical Pharmacology and Therapeutics 2030 ( doiID: 10.1002/cpt.v107.1 )
                : 89-91
                Affiliations
                [ 1 ] European Medicines Agency Amsterdam The Netherlands
                [ 2 ] Medicines Evaluation Board Utrecht The Netherlands
                Author notes
                [*] [* ] Correspondence: Peter Arlett ( Peter.Arlett@ 123456ema.europa.eu )

                Article
                CPT1689
                10.1002/cpt.1689
                6977396
                31758540
                e6dc74f5-abc2-4a75-ace5-e46689d15621
                © 2019 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/3.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 14 August 2019
                : 15 October 2019
                Page count
                Figures: 0, Tables: 0, Pages: 3, Words: 2022
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                Perspectives
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                2.0
                January 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.5 mode:remove_FC converted:21.01.2020

                Pharmacology & Pharmaceutical medicine
                Pharmacology & Pharmaceutical medicine

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