ReviewPharmacovigilance at the Intersection of Healthcare and Life SciencesKostas KidosKostas Kidos is VP of Product Strat...
Pharmacovigilance at the Intersection of Healthcare and Life Sciencesindications, and new patient populations.1 The US equ...
ReviewFigure 2: Knowledge-based Pharmacovigilance Supported by Increase in Data Sources                                   ...
Pharmacovigilance at the Intersection of Healthcare and Life Sciencesenvironment. Leading companies are having to ask the ...
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Pharmacovigilance at the Intersection of Healthcare and Life Sciences


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Pharmacovigilance at the intersection of healthcare and life sciences by Kostas Kidos, VP of Product Strategy, Pharmacovigilance, and Risk Management at Oracle Health Sciences

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Pharmacovigilance at the Intersection of Healthcare and Life Sciences

  1. 1. ReviewPharmacovigilance at the Intersection of Healthcare and Life SciencesKostas KidosKostas Kidos is VP of Product Strategy, Pharmacovigilance, and Risk Management at Oracle. His role is to work with senior thought leaders and standards bodies in the pharmacovigilanceand risk management domain, in order to ensure that Oracle continues to develop technologies that support relevant business needs in a manner that is well integrated with the overall R&Dprocess. Prior to Oracle, Mr Kidos was with Merck & Co. for six years as a member of the IT senior leadership team responsible for a diverse organization setting and executing the overallstrategy on healthcare IT, pharmacovigilance, risk management, regulatory affairs, labeling, biostatistics, epidemiology, clinical content management, collaboration portals, licensing,competitive and regulatory intelligence, and various other areas of drug development. Before that he was with Bristol-Myers Squibb for over 15 years as the Executive Director ofPharmacovigilance Operations supporting areas such as adverse event systems, terminologies, case intake, regulatory submissions, PSURs, risk management and signaling support,co-marketing agreements, product complaints, and training. In parallel to these positions, for 15+ years he has been leading (and with agreement by PhRMA continues to lead) the PhRMAdelegations at ICH and ISO TC215 for various safety-related topics, has served as the rapporteur/co-rapporteur for two of those topics (E2B and M5), and co-chaired with the FDA asubcommittee on the electronic exchange of safety information.Pharmacovigilance and safety surveillance has evolved from yesterday’s focus on transactional activity andinformation flow to today’s awareness of the importance of risk management and proactive signal detection.Risk management activities have come to the fore as the focus of good pharmacovigilance expands beyonddata collection to drug safety surveillance models that have a more inherent value. This evolution willcontinue as the trajectories of both life sciences and healthcare converge towards a common goal ofpredictive, preventive, personalized, and participatory healthcare. In this future landscape, access and insightto data from various sources will be paramount to a knowledge-based system of pharmacovigilance. Thecommon analytic foundation of healthcare and life sciences will lead toward improvements in public healthand a population-based predictive pharmacovigilance model that relies on intelligent signal detection.The Evolution of Pharmacovigilance and Additionally, the drug-safety environment became progressively moreSafety Surveillance risk-averse, with regulators introducing increasingly stringentThe detection, assessment, understanding, and prevention of adverse regulatory requirements. This saw the implementation of a regulatoryevents (AEs) of medicines, in other words pharmacovigilance, are all framework that promoted well-structured and expeditious informationan integral part of clinical research, pre- and post-approval. Good flow. Although adverse event reporting has always been mandatorypharmacovigilance, underpinned by the science of clinical for pharmaceutical companies, on the healthcare side adverse eventpharmacology, is crucial throughout the product lifecycle. A number reporting was, and still remains, voluntary.of recent high-profile drug withdrawals has highlighted the strengthsand weaknesses of the current systems and has provided a good From the mid-to-late 1990s, as reporting became ‘routine’, there wasindication of how much more needs to be done. Significant harm, to a realization that there needed to be an expansion beyond the limitedeven a few patients, can have catastrophic ramifications including a data sources. The arrival of the new millennium also saw anotherloss of trust and credibility for the pharmaceutical industry and significant shift, with the move towards an environment that focusedregulatory agencies. At a time when the industry as a whole is on gaining a greater understanding of the data. Risk managementundergoing tremendous pressure on productivity and revenues the activities came to the fore as the pharmaceutical industry andimportance of effective pharmacovigilance is even more evident. regulators expanded the focus of good pharmacovigilance—beyond data collection to drug safety surveillance models that had moreOver the past two decades, pharmacovigilance has undergone an inherent value (see Figure 1).evolutionary shift from limited systems that mainly focused onregulatory compliance to the richer, more sophisticated systems Focus on Risk Management—currently in place today. In the 1980s systems were based on The Drug Safety Modelprocesses owned by biopharmaceutical sponsors, with data inputs The evolution of pharmacovigilance and safety surveillance, fromcoming in from a limited number of data sources (i.e. yesterday’s focus on transactional activities and information flow toconsumer/healthcare professionals and via clinical trials). These today’s awareness of the importance of risk management, led to thesystems were built around case processing with limited focus on introduction of the Risk Management Plan (RMP) in Europe in 2005.intelligent information consumption and benefit:risk analysis. It was The RMP is a mandatory requirement for marketing authorizationvery much a reactive, event-driven process. During the following applications (MAAs) for new chemical entities, biotechnologydecade, the focus shifted to improving the flow of information. products, new routes of administration, new dosage forms, new1. Volume 9A, Rules Governing Medicinal Products in the European Union, September 2008; available from Food and Drug Administration, Docket No. FDA–2008–N–0174; available from © TOUCH BRIEFINGS 2011
  2. 2. Pharmacovigilance at the Intersection of Healthcare and Life Sciencesindications, and new patient populations.1 The US equivalent, a Risk Figure 1: Evolution of the Drug Safety ModelEvaluation and Mitigation Strategy (REMS), is not a statutoryrequirement unless the US Food and Drug Administration (FDA) Riskspecifically requests its inclusion in certain drug applications.2 Risk Management Mgmt Signal SignalRisk management and rigorous adherence to drug safety has always Management Managementbeen an intrinsic part of the drug development process. Aggregate Increasing AggregateNonetheless, the approach to risk management activities has seen Reporting Value Reportinga significant change as processes become more standardized, Adverse Event AEdriven by the new regulatory requirements. The need for greater Managementaccountability and continuous improvements in identifying and AE = adverse event; mgmt = management.communicating the benefit:risk associated with a drug has led tomore-comprehensive, formalized processes that supportREMS/RMP requirements. Formalized processes also help better Several consortia and partnership initiatives are currently exploring anddefine and identify the information and technologies needed to testing new methods of signal detection, data mining, and analysis offacilitate better decision making around risk management. Thus, electronic healthcare data sources. The Observational Medicalthe next step is to develop an understanding of the safety profile of Outcomes Partnership (OMOP) is a public–private partnership thata medicine through access to additional, richer sources of data. involves multiple stakeholders, including the pharmaceutical industry,Although the traditional data sources—safety data from clinical academic institutions, non-profit organizations, the US FDA, and othertrials and voluntary reporting of spontaneous AEs—continue to US federal agencies. OMOP is assessing the appropriate technologyprovide essential information for conducting pharmacovigilance, it and data infrastructure required for systematic monitoring ofis well recognized that they have their limitations. In the digital era observational data. OMOP is also developing and testing the feasibilitythe increasing availability of large collections of electronic data and performance of the analysis methods.from the healthcare environment, in the form of electronic healthrecords (EHRs), insurance claims databases, outpatient data, a The FDA’s Sentinel Initiative intends to create the Sentinel System: anvariety of longitudinal observational data sources, and clinical trial electronic system that augments existing safety monitoring systems andregistries, provides alternative sources of data that could be used to expands the FDA’s capacity for evaluating safety issues related togain valuable insight about the behavior of the approved product FDA-approved medicines, especially in terms of information onand to support pharmacovigilance processes. This has led to a subgroups/special populations. The Sentinel System will operate acrossgrowing interest in how to leverage these rich data sources to different data sources—provider electronic health records, health planimprove safety signal detection and risk management strategies. claims databases, Medicare databases, and other data sources.Knowledge-based Pharmacovigilance Next Generation Signal DetectionThe science of pharmacovigilance is a continuously evolving The execution of knowledge-based pharmacovigilance will requirediscipline. As previously mentioned, the traditional data sources robust data mining and analytical tools. The long-term vision is tothat the pharmaceutical companies rely on for conducting leverage data sources to facilitate more-intelligent signal detectionpharmacovigilance has limitations. Pre-approval clinical trials cannot activities. This is where the promise of integrated analytic engines thatcapture all AEs causally related to the drug, are only conducted in apply the appropriate methodologies to the appropriate dataset hasrelatively small patient populations, and do not adequately assess the tremendous potential.risks of long-term exposure to the drug. The responsibility ofpost-approval reporting of spontaneous AEs lies primarily with the The incredible variety of data sources available will provide not onlydrug manufacturer or marketing license holder. However, post- potential benefits but also specific challenges. In this vastapproval surveillance activities are passive processes and rely heavily environment of data it would be easy not to see the forest from theon the voluntary participation of physicians and patient groups. trees. To ensure that the benefits of these data sources are correctlyKnowledge-based pharmacovigilance integrates active AE leveraged it will be necessary to interrogate the datasets with thesurveillance methods using rich data sources from the public and appropriate analytical methodologies.private sectors.3 The evolutionary curve of technology invites change.The pharmaceutical industry, the healthcare sector, and regulators Classical signal detection is driven by incidence counts of AEs and ishave all embraced information technology (IT) as a tool to support retrospective and not truly predictive. The vision is to utilize the vastbetter processes. As digitization of healthcare data becomes routine sets of medical data to proactively identify and manage emergingthe pharmaceutical industry and regulators are increasingly looking at safety signals. Embedding analytic engines into core processes canall of those sources of information as potential sources of data (see help stakeholders adopt an analytical orientation and enable speedFigure 2). However, while there is increasing acceptance that digital and quality of insights for complex analyses and reporting. The use ofcapabilities have created more opportunities to improve drug safety, powerful analytical engines will enable a real-time, auditable meansthere is great variability among stakeholders about how to best for automated signal detection. This scenario will also offer real-timeleverage healthcare data sources to improve safety and, ultimately, analysis, documentation, and communication to provide a proactiveimprove outcomes for patients. approach to pharmacovigilance.3. Food and Drug Administration Amendments Act of 2007, Pub. L. No. 110-85, § 905(a), adding Federal Food, Drug, and Cosmetic Act § 505(k), amending 21 U.S.C.A. § 355 (FDAAA).MANAGING RISK—EMBRACING THE NEW PARADIGM IN GLOBAL PHARMACOVIGILANCE 5
  3. 3. ReviewFigure 2: Knowledge-based Pharmacovigilance Supported by Increase in Data Sources Patient Observational Medical Outcomes Partnership Healthcare and Life Sentinel Clinical Trial Science Consortia Healthcare PROTECT Professional Regulator Investigator Electronic Health Record Recruitment New Use Cases Product Patient Development Recruitment Outpatient Data Protocol Design New Data Sources and Amendments Longitudinal Data Sponsor Epidemiology Studies Literature and Research Benefit: Risk Management New Indications Product Lifecycle Claims Database Management Packaging and Labeling Partners New FormulationsFigure 3: Life Sciences and Healthcare Convergence Personalized Healthcare Translational Medicine Targeted Therapies ‘Precision’ Healthcare Patient Care & Disease Management DNA Chemistry and Analytics ‘Evidence-based’ Healthcare Advanced Technology Pharmacovigilance Safety at Increased Regulation & Risk Management Point of Care ‘Managed’ Healthcare and Efficacy Standards Electronic ElectronicBlockbusters and Data Capture Medical Records ‘Trial & Error’Mass-production Healthcare of Novel Drugs Paper-based Paper-based Records Systems LIFE SCIENCES HEALTHCAREThe Future Landscape— (see Figure 3). Thus, pharmacovigilance and safety is the first and mostSecure, Safe, and Harmonious active step in a move toward personalized health.Central to many of the conceits and concepts discussed in this paperis the trajectory of the life sciences and healthcare sectors. The next evolutionary step in pharmacovigilance will be a future whereEach sector is converging on a common goal of predictive, a collaborative environment creates and supports a continuouspreventive, personalized, and participatory healthcare (see Figure 3). knowledge-based feedback loop; data are processed with variousSo what does this mean for pharmacovigilance? The increasing analytics engines; and data are presented through dashboards toimportance of healthcare data as an alternative and complementary generate knowledge—this knowledge is the data that are fed backdata source has already been discussed. The convergence of the two into the continuous feedback cycle.sectors and the common analytic foundation of healthcare and lifesciences will lead toward improvements in public health and One of the driving forces for this change is the real need for thepopulation-based pharmacovigilance. pharmaceutical industry to transform from a fully integrated pharmaceutical company business model to a networked model thatThe intersection of the two fields starts with pharmacovigilance on the derives innovation from value-added partners. Cost pressures andlife sciences side and safety at point-of-care on the healthcare side innovation shortfalls have forced this move toward a networked6 MANAGING RISK—EMBRACING THE NEW PARADIGM IN GLOBAL PHARMACOVIGILANCE
  4. 4. Pharmacovigilance at the Intersection of Healthcare and Life Sciencesenvironment. Leading companies are having to ask the questions: Table 1: Opportunities for Alignment Betweenwhat activities are core to the company and what are not? In order to Healthcare and Life Sciencesachieve a networked healthcare and life sciences industry model, 1. Requires transparent data flows across health scienceshowever, necessary transformations to the traditional clinical 2. Common terminologies must be defineddevelopment paradigm must take place. Sponsors will need to 3. Standards must be able to correlate data sourcesembrace a network of partners—from hospitals and doctors to clinical 4. Best practices can be establishedresearch organizations (CROs), academia, technology providers, and 5. Healthcare must focus on implementing (EHR) infrastructure first!manufacturing companies. Some of the practical steps that still needto be accomplished include the need for transparent data flows across Figure 4: The Next Generation Pharmacovigilance Modelhealthcare and life sciences; defining common terminologies;correlating standards and data sources; establishing best practices;and, most importantly, the increasing focus of healthcare on Data Sourcesimplementing an EHR-based infrastructure (see Table 1). Health Authority PatientThe impact of the changing model on the safety side will include FDA FDA EMA Clinical EMAbetter practices and improved data collection. The pharmaceutical Trial PDMA PDMAindustry has been outsourcing to CROs for many years, but mainly Healthcare Sponsorfor the purpose of clinical trial execution and rarely for safety Professional Safety Sponsor Signalsservices. More recently, this trend has been reversed and the Sponsor Electronic Health Sponsor Recordindustry has seen a dramatic rise in safety service offerings from Sponsor OutpatientCROs. This situation has arisen, in part, because of the Sponsor Datarationalization of core business activities by pharmaceutical CRO CRO CRO Literature Sponsor Global Data CROcompanies. It can be argued that many data collections and data BPO Warehouse CRO CRO Research BPOprocessing activities are not core activities but are transactional. BPO Claims DBThus, it is a commodity that can be performed by a service company Today Longitudinal Tomorrowwith the right competencies better, faster, and cheaper. This Dataenables the pharmaceutical company to focus on the analysis and Partnersexamination of the data; the complex computations that givemeaning to the data; and to provide valuable insights that help toimprove the lifecycle management of the product. risks. The other dimension is to be predictive. Imagine a scenario where a global safety database points patients, healthcareSo what will the next generation pharmacovigilance model look like? professionals, researchers, and safety professionals to populate theThe answer(s) may come from other industries. Other industries have environment with safety data, minimizing the need for sponsors tosuccessfully utilized a networked, collaborative model to stimulate collect and report the data, and to focus their resources in consuminginnovation and improve safety. An excellent example is the aerospace the data for pharmacovigilance purposes. Imagine a scenario whereindustry, more specifically Boeing, which has rapidly shifted to ambulatory data, captured in real-time at a national or regional level,embrace a ‘network’ of partners from across the globe to develop the is accessible and associated with pharmacogenomic and outpatientBoeing 787. In the banking sector technology has been embraced to data that would allow more-intelligent analysis of the pharmacologicalprovide real-time monitoring and analysis of transactions. The effects supported by the patient’s compliance on its therapy. This isquestion is whether there are use cases for utilizing similar pharmacovigilance for the future, based on a distributed Complextechnologies in the life sciences and healthcare environments to Event Process (CEP) (see Figure 4).transform pharmacovigilance from today’s fragmented, inefficient,and heterogeneous environment to a landscape that is simplified, Many of the basic components required to enable this future scenariostandardized, and less fragmented. are in place or being implemented. The technology-driven transformation of pharmacovigilance is being championed byThe same mathematical foundations that are utilized by banks to regulators and the pharmaceutical industry alike. In the healthcareidentify fraud are being used in use cases and pilots to mine AE data sector the switch from a paper system to electronic records is infor safety signals. A significant challenge is that financial data capture perfect alignment with the driving forces from life sciences. In ana vast amount of real-time results, whereas in healthcare and life increasingly demanding and risk-averse environment innovativesciences less real-time data are captured. technological solutions will help to address safety concerns and improve patient confidence and outcomes. There are manyProactive, Predictive Pharmacovigilance challenges along this roadmap toward proactive, predictivePharmacovigilance is still very observational. We see what happens pharmacovigilance but the end goal will see greatly reduced risks andand react to analyze why the event occurs and how to mitigate the improved responses to better protected patients. nMANAGING RISK—EMBRACING THE NEW PARADIGM IN GLOBAL PHARMACOVIGILANCE 7