the power of ctms - Oracle

THE POWER OF CTMS

HEALTH SCIENCES

INTEGRATION, INTEROPERABILITY, AND COLLABORATION

CLINICAL TRIAL MANAGEMENT SYSTEMS—A DECISIONSUPPORTING ENGINE FOR THE FUTURE Chris Huang, Oracle Health Sciences

THE CLINICAL TRIAL MANAGEMENT SYSTEM—THE CENTRAL INTELLIGENCE HUB Henry Levy, Accenture

CLINICAL TRIAL MANAGEMENT SYSTEMS IN THE WORLD OF MERGERS AND ACQUISITIONS— MANAGING OPERATIONAL CHALLENGES Christopher Heider, Merck Research Labs

FLEXIBILITY, INTEROPERABILITY, AND ORGANIC GROWTH—THE CHALLENGES OF CLINICAL TRIAL MANAGEMENT IN EMERGING GEOGRAPHIES Lynda Shelley, Novotech

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Contents

FOREWORD Clinical Trial Management Systems—Moving with the Times3 Sian Bithell

REVIEW Clinical Trial Management Systems—A Decision-supporting Engine for the Future 4 Chris Huang Product Strategy Director, Oracle Health Sciences

The Clinical Trial Management System—The Central Intelligence Hub7 Henry Levy Managing Partner, Accenture, Life Sciences R&D

Clinical Trial Management Systems in the World of Mergers and Acquisitions—Managing Operational Challenges11 An interview with Christopher Heider Director of Information Technology supporting Division-wide Services for Merck Research Labs

Flexibility, Interoperability, and Organic Growth—The Challenges of Clinical Trial Management in Emerging Geographies14 Lynda Shelley Executive Director of Clinical Operations, Novotech

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THE POWER OF CTMS—INTEGRATION, INTEROPERABILITY, AND COLLABORATION

Foreword

Clinical Trial Management Systems—Moving with the Times Sian Bithell

T

o ensure that clinical trials achieve their primary purpose of collecting data effectively, stakeholders have always looked for solutions that facilitate the management of data, trial logistics, and project flow. The way that clinical trials are conducted is being transformed to a remarkable degree. Of the many challenges facing the pharma industry today, the need for greater operational efficiency in clinical drug development is of paramount importance. With flat and even declining productivity, rising R&D costs, more-complex pre-approval trials, and large post-approval studies driven by increasing regulatory demands, it is essential that clinical trials are managed more effectively and efficiently. The increasingly global nature of clinical trials has also created unique challenges and complex logistic needs. Technology solutions, such as electronic data capture (EDC), clinical data management systems (CDMS), and randomization and trial supply management systems such as interactive voice response systems (IVRS) and interactive web response systems (IWRS) have been used to enhance the conduct of clinical trials. However, a clinical trial management system (CTMS) is the central hub that manages the functions and drives the convergence of the many systems that form the clinical trial ecosystem. A CTMS can empower organizations to enhance productivity and effectiveness of clinical development by expediting and better managing clinical trials. With a look to the future, and across the globe, as the eClinical environment continues to evolve and mature, organizations will need to keep in mind a number of significant considerations, regardless of whether it is an upgrade path or de novo implementation. In our report, The Power of CTMS—Integration, Interoperability, and Collaboration, we have commissioned a series of articles that provide expert opinion, analysis, and insight into the firm belief that CTMS will support clinical trials well into the future. The first article, ‘Clinical Trial Management Systems—A Decision-supporting Engine for the Future’, written by Chris Huang, Oracle Health Sciences, examines the potential of CTMS as it evolves from a perceived logistics system to a powerful decision-support engine. Here, Chris Huang also provides foresights into how the evolving solutions will add future value to investments. From Accenture, Henry Levy’s review, ‘The Clinical Trial Management System—The Central Intelligence Hub’, reflects on the benefits of CTMS as an end-to-end turn-key solution and its potential as the central hub in an integrated clinical system that serves the needs of all stake holders in the process; from the sponsor right down to the patients themselves. Following on from this, ‘Clinical Trial Management Systems in the World of Mergers and Acquisitions—Managing Operational Challenges’ by Christopher Heider, Merck, highlights critical decision points within the M&A process, as well as discussing the challenges faced. The final article in the series, ‘Flexibility, Interoperability, and Organic Growth—The Challenges of Clinical Trial Management in Emerging Geographies’ written by Lynda Shelley, Novotech, views the decision processes for making the right investment in CTMS from a CRO perspective operating in an emerging territory. We would like to thank all of our authors for their contributions and trust that you, our readers, will find our report informative and engaging. n

© TOUCH BRIEFINGS 2011

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Review

Clinical Trial Management Systems—A Decision-supporting Engine for the Future Chris Huang

Chris Huang has worked in the life sciences and software industries for the past 20 years, including in clinical data management, preclinical information technologies, product management, and product strategy. He is a Product Strategy Director within Oracle Health Sciences, with responsibility for several eClinical so lutions, which include Siebel CTMS, Mobility, and Oracle Clinical/Remote Data Capture. As a product strategist he is responsible for the overall vision and roadmap for the eClinical pr oducts. Chris has an MSc. in Electrical Engineering from the New Jersey Institute of Technology.

eClinical solutions are now firmly established in the drug-development process. Electronic data capture has largely been achieved—interactive voice/interactive web response systems are common place and used for the majority of studies, and the use of medical imaging in clinical trials is advancing. Essentially, barriers to the adoption of new technology were removed as the solutions evolved and within the industry the use of technology is considered a competitive advantage. However, improved capabilities also mean that users are more demanding of their solutions. The greater focus on planning, forecasting, cost analysis, and containment throughout development programs requires access to actionable information to support early decisionmaking. Moreover, with the adoption of digital technologies there is a need for integration with a wider base of systems, and thus integration expectations are higher.

Clinical trial management systems (CTMS) are one component in the eClinical solutions value chain that addresses important processes in drug development. Until recently, the role of CTMS was considered to be mainly a transactional one, rather than that of a decision-support system. Early CTMS were mainly ‘back office’ systems, a key marketplace requirement at the time, and still focus largely on data gathering and data entry. Now that the sector has matured and clinical trials are growing in complexity, the capabilities of CTMS themselves need to grow if they are to impact trial and study costs and help life-science organizations adapt to more sophisticated business requirements. This review provides a broad examination of the current landscape and challenges faced across global trial management, providing foresight into how the evolving solutions will enable the industry to address these hurdles.

consistent view of trial data that can be shared across the entire organization (see Figure 1).

The Role of CTMS in the eClinical Value Chain

The benefits of a CTMS are ve ry tangible in terms of realizing valuable efficiencies and cost savings. Current CTMS solutions help to standardize the management of trials by allowing users to create a consistent approach across clinical development programs. Thus, companies can optimize clinical operations and proactively manage trials. The use of t he same temp lates and ap proaches can be applied to monitoring reports, payment schedules, payment requests, and site-visit activities—all the components of the clinical trial. This ensures that complia nce can be ma naged systematically and consistently. As mentioned previously, centralizing all study information in a s ecure location can improv e efficiency—everyone in the team works from the same information. CTMS enables u sers to access the mos t recent in formation on site statu s, activation information, enrollment, and schedule for monitoring visits.

Clinical development accounts for over 50 % of drugdevelopment costs, 1 in part because of the resource-intensive nature of running clinical trials. Compounding the issue, clinical trials continue to grow in complexity, with the median number of procedures per clinical trial increasing by 49 % between the periods 2000–2003 and 2004–2007. 2 The challenge to contain the ever-rising cost of developing new drugs and to optimize processes has led to the growing adoption of CTMS solutions, with many biopharmaceutical companies having purchased, are evaluating, or have CTMS solutions on their roadmap. The need for a CTMS is well understood and accepted throughout the industry. A CTMS provides a single, centralized system to manage operational and administrative activities and gives a

1. 2.

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Prior to the implementation of CTMS solutions, companies were heavily dependent on the use of spreadsheets, email, Word documents, etc., to manage clinical operations. This could lead t o a lack of consistency across trials, with differing document formats and the need to generate new, custom spreadsheets for each trial. This increased the potential for validation gaps and critical document-versioning issues. Early CTMS adopters faced a different challenge: how to scale home-grown or heavily customized CTMS to meet changing requirements. Although the systems may have served the company well during a certain phase of the company’s development, they may not be the best solution going forward.

Gilbert J, Henske P and Singh A, Rebuilding Big Pharma’s Business Model, In Vivo, 2003;21. Available at: www.bain.com/I mages/rebuilding_big_pharma.pdf (accessed 08/30/2011). Tufts Center for the Study of Drug Development Press Release, Rising Clinical Trial Complexity Continues to Vex Drug De velopers, May 2010. Available at: http://csdd.tufts.edu/news/complete_story/pr_ir_may-jun_2010 (accessed 08/30/2011).


Clinical Trial Management Systems—A Decision-supporting Engine for the Future

Figure 1: CTMS Business Processes

Project intelligence

Investigator payments

Site feasibility and selection

Study startup and initiation

Subject recruitment

Streamlining Study Activities The function of a CTMS solution is to provide the tools to optimize the manag ement of the clinical study process. S tudy start-up activities, such as site ident ification, initiation visits, and collection of all th e necessary regulatory documents, can be a critical bottleneck that results in delays in the overall study timelines. Early dep loyment of C TMS within th e process can help improve this impor tant aspect. CTMS i nvestigator databases can provide information that expedites suitable site identification, such as relevant experience and facilities, and the past performance of a potential site. Onc e a study is running, C TMS can assist u sers to keep track of all the relev ant regulatory documents and provide a strong snapshot of progress in terms of site activation. The ability to track this informatio n ensures th at any pot ential delays can be identified quickly and addressed. The CTMS can also fa cilitate site-recruitment goals. Difficu lties in enrolling subjects for a trial can have a huge impact on the ov erall development program. By providing constant visibility into recruitment status and trial enrollment, the CTMS allows the clinical team to inter vene early if a potent ial for enrol lment delay is identified.

Interim monitoring

Study closedown

member to the central database next time the user logs in to the CTMS helps ensure that the CTMS can be used to monitor visits in any location. This important functionality means that the CTMS is a tool that can be used for the whole continuum of data during a clinical program. A good CTMS system can also help to manage and track investigator payments accurately, an activity that is critical both to managing a strong financial performance and maintaining a good relationship with investigators and site personnel. Furthermore, the added functionality of managing (from w ithin CTMS) specific p ayment schedules for each site, based on specific activities, reduces the manual effort needed to generate investigator payments. At study close-out, the process is more efficient because study teams have been utilizing standardized tracking templates within the system throughout the study, which ensures improved collection of materials and information for final regulatory packages. The standardized process also ensures that study close-out is compliant with the company’s standard operating proced ures and with federal or international regulations.

CTMS Evolution in a Changing Industry Every study has its own unique design. Accordingly, customization of document templates that address study-specific design elements within the CTMS allows clinical users the flexibility in designing the study without having to support complicated application customization, which can have a negative impact on study start-up schedules. Additionally, this process maintains standardization across key elements of study management. Users are able to use the same templates within the same study program.

The benefits of a CTMS are very tangible in terms of realizing valuable efficiencies and cost savings. Nevertheless, the next logical evolutionary step for CTMS is to unlock the power resonant within the system to allow it to become the central intelligence engine that supports decision-making and allows sponsors and contract research organizations (CROs) to manage intelligently the growing complexities of clinical trials.

A CTMS also provides visibility into all ongoing study activities and thus facilitates the ongoing management of the study and ensures that projects remain on track. In general, the CTMS enables tracking of information at the study, region, or site level to allow maximum visibility and flexibility. With the help of a CTMS, users can develop targeted monitoring strategies that will help reduce cost and timelines by efficiently scheduling monitoring visits based on enrollment and completed visits. A CTMS can also help track adherence to study milestones, trigger investigator payments, create and track monitoring reports, ma intain contact lists, and also track correspondence with each site within the application.

To achieve this, CTMS must become more about presenting data, driving decisions, and managing costs more actively and less about collecting data and d ata-entry efforts. Ad ditionally, CTMS must leverage the tools and available data to support actionable signals and alerts. This will require support by robust analytics and forecasting capabilities. Moreover, if the CTMS is to become a ‘command and control center’ for study managers it will need to be integrated fully with the relevant upstream and downstream systems. A highly flexible data-integration engine that supports multiple standard interfaces will ensure that the CTMS data can be connected to other data sources, especially as the number and types of systems is expected to increase in the new eClinical landscape.

Monitoring reports are one of the key operational and regulatory components and deliverables of every study. A CTMS solution can provide the ability to automatically generate monitoring reports from the information gathered during monitoring visits. The ability to synchronize automatically data entered off-line by a traveling team

Importantly, many of the elements to achieve this scenario are already in place. Current CTMS have study dashboards that provide clear insight into study status and progress. Importantly, data generated during the course of a study can be stored centrally. The ability to track multiple studies in the same database plus the ability to have


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Review central access to all active and historical trials data can be utilized to make informed decisions in future studies. Thus, every study conducted using CTMS allows an organization to build a database to support decision-making for future studies. Data-integration modules can provide a seamless transfer of information from electronic data capture (EDC) to CTMS. The benefits of this process are a near real-time visibility of study status plus a reduction in the reentry of data, which prevents data-entry errors and ensures that systems are operating with the same information.

Enabling the Decision-making Process CTMS are currently playing an integral role in addressing inefficiencies on the operational side, which include collaboration and communication between sites. The next step in creating a truly collaborative environment is to extend it upward within the organization to communicate with senior management, and the program- and portfolio-management systems. The realization of the CTMS as a decision-support engine will also require all systems in the development process to evolve, from EDC to interactive voice/interactive web response systems and web portals. An integrated, open, scalable framework that has a single sign-on andfewer entry points and is easily sustainable will be a necessary requirement. Furthermore, standards, such as those being developed by the Clinical Data Interchange Standards Consortium, need to be used universally and across vendors. This requirement is key to supporting the integration of data and systems from a multiple-vendor scenario. System integration needs to be managed to enable decision support at all levels. At the operational level, data transferred seamlessly into the CTMS provide accurate and real subject-enrollment status, a complete view of study logistics, and support quick action on potential study delays. Integration at the management level improves visibility into the overall financial state of a development program, study progress, and total cost of study. It also provides the ability to use data for benchmarking and future planning, which in turn helps an organization to gain valuable understanding of how essential elements impact on overall development programs. The use of metadata will also increase in importance: data changed in one system perpetuates through other appropriate systems, which removes reconciliation efforts. To become a true management tool, the CTMS will also need to become the primary source for many of the critical elements in clinical projects: • managing overall study costs; • determining study feasibility; • projecting and managing patient-enrollment goals;

3.

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• planning, scheduling, conducting, and reporting monitoring visits; and • managing payments from start to finish. CTMS can contribute effectively in the d ecision-making process by focusing on information delivery and decision support. This means ensuring that CTMS easily provides information needed for decision-making in dig estible formats. CTMS will ne ed to prov ide actionable data summaries, visualize the entire process, and streamline the neces sary information from all t he relevant systems in a fl ow that is logical to t he user. Th e functionality of the C TMS needs to be e xtended both up- and downstream. By co nnecting information to pr ogram and broader goals C TMS can facilita te portfolio management. From a site perspective the CTMS becomes the ‘command and con trol center’ for site ac tivities—facilitating interaction with sites and managing ongoing communication. Essentially, the CTMS will need to be easy-to-use support for all approved users who provide or use system data and information—from sponsor/CRO to suppliers and sites. Integration of content-management systems with the CTMS will help to streamline the complicated document-management process and reduce the manual effort associated with loading and managing spreadsheets.

CTMS for the Future The continuing evolution of CTMS has been supported by rapid progress in web technology. CTMS can now be deployed as a secure web application that can be accessed via any worldwide web consortium standards-compliant web browser. Extending this functionality is the ‘CTMS on demand’ model, which provides agile CTMS implementation through Software as a Service (SaaS). Moreover, the SaaS model is highly configurable and customizable, with extensive modular functionality, and benefits organizations by reducing up-front capital investment. With the growing influence of the mobile c omputing environment and the high ado ption rate of new mo bile technology with the medical community,3 the ability to acce ss CTMS dat a, such as changes to the study and the st atus of current a nd planned future activities, through mobile por tals may no t be too distant. Mobile technology will also support better collaboration and communication through alert syst ems delivered by phone, email, text, or tweet. CTMS will continue to be an integral component of clinical development. However, CTMS has the potential to become a stronger decision-support engine fueled by robust forecasting, analytics, and modeling. The future of CTMS lies in advanced, well-designed integration and strong user interfaces to support key processes in clinical trials. n

American Medical News, Doctors driving IT development with their mobile technology choices, 2011. Available at: http:// manhattanresearch.com/News-and-Events/In-TheNews/amednews-052311 (accessed 08/30/2011).


Review

The Clinical Trial Management System—The Central Intelligence Hub Henry Levy

Henry Levy is the Managing Partner for Accenture’s Life Sciences R&D Practice in Europe, based out of Zurich, Switzerland. Henry has worked in the Pharmaceutical Industry for the last 17 years, providing services across Strategic Consulting, Technology and Outsourcing to most top 20 biopharmaceutical companies. Henry has focused on helping sponsors achieve high performance in driving new therapies to the market. Henry is considered an industry expert in the clinical trial process and speaks often at key industry conferences. E: [email protected]

Evolutions in technology, such as point-to-point data integration and centralized data capabilities, are enabling clinical trial management systems (CTMS) to increase the value they add as pivotal tools for streamlining clinical development operations. Accenture believes that collaboration functionality, bringing clinical trial stakeholders closer together, and the use of analytics to drive improved insights into the clinical trial progress, are major drivers of the evolution in the CTMS environment. CTMS is in a prime position to support critical decision-making by becoming the central intelligence hub in an integrated eClinical system that serves the needs of all stakeholders in the process. Furthermore, Accenture asserts that CTMS will also support clinical trials of the future by offering greater insight into the drug development process.

The biopharmaceutical industry is experiencing a challenge; as research and development (R&D) expenditure within the industry has increased tenfold over the past twenty years the number of new drugs approved continues to be flat or, as is the case recently, to decrease.1,2 Moreover, it is Accenture’s opinion that the continued merger and acquisition activity will not be enough to address the long-term impact on the industry’s valuation in the market. Therefore the situation has forced the industry to become highly focused on cost reduction. Current clinical trials expenditure accounts for approximately 60 % of the total development spend, with the development spend itself accounting for 70 % of the overall R&D budget.3 With 40–50 % of overall expenditure allocated to the clinical trial process,4 the improvements in clinical trial execution and productivity, coupled with how clinical trials are managed, has now become a key area for the biopharmaceutical industry to optimize and address. The industry must shift from a pure cost-reduction model to focus on innovation-driven efficiency. The main question to be answered by the industry is: ‘How do I get more done without increasing resources?’

The Merging eClinical Ecosystem Accenture finds that clinical trials are supported by a variety of technologies that capture, process, and share data. CTMS is one of the many components alongside different technologies in the clinical development infrastructure, such as clinical data management systems (CDMS), electronic data capture (EDC), electronic patient reported outcome devices (ePRO), interactive voice response (IVR), laboratory processing, statistics and programming, and various submission components.

1. 2. 3. 4.

These elements form the interconnected environment that can be identified as the eClinical ecosystem. It is an environment in which high-quality data is of the essence. At its end, it must support the analysis required to provide a safe drug for the patient population but, through the clinical development process, it must also help the industry in maximizing investment by driving the highest efficiency process possible. By having an ecosystem in which information can flow, data can be taken and used not only for analysis but also for management to comprehend the trial progress, as well as trial-specific predicted events. In essence, within the eClinical framework the technology components need to enable two fundamental processes: 1. data handling (data management, data analysis and reporting, data analytics, and data mining); and 2. trial management (planning, execution, management, and decision making). Accenture notes that advances in data warehousing and data analytics technology are enabling the evolution of data hubs that can support data handling and the creation of operational data marts that better support trial decision making. With these capabilities in place, the two focal points—one data focused and one execution focused—can come together and CTMS can become the operational ‘heart’ of the clinical trial process. The direction of future approaches will determine just how much CTMS will gain in strength as it is established as the master system within the eClinical infrastructure.

Baum A, et al., Pharmaceuticals: Exit research and create value, Morgan Stanley Research Report, January 2010. NMEs Approved by CDER. Available at: www.fda.gov/downloads/AboutFDA/Transparency/Basics/UCM247465.pdf (accessed June 2011). Pharmaceutical Industry Profile 2010. Available at: www.phrma.org/sites/default/files/159/profile_2010_final.pdf (accessed June 2011). DiMasi et al, The price of innovation: new estimates of drug development costs, J Health Econ, 2003;22(2):151–85.


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Review The future position of CTMS in the market will be dictated by how these technologies leverage key opportunities created by changes in the technology landscape, as well as changes in the way the industry executes clinical trials. The main factors that will contribute to the future positioning of CTMS include: • • • •

capitalizing on analytics improving and driving the workflow consolidating master data; and becoming the central, integrated management solution.

The Impact of Analytics on CTMS Functionality Considerable value can be added to optimize decision-making and making the process more strategic by implementing data analytics tools. CTMS becomes more than just a project or trial management environment when clinical and performance data can be used to help predict the success of a trial, understand the feasibility of the trial design, or even change the parameters of a protocol or study design. The ultimate result is a more successful and efficient clinical trial. Cost reductions can be achieved by modifying various parameters including the number of patients recruited in a trial, the number of trials executed, and the number of sites used—all of which can drive a cost reduction of ~30 % in trial expenditures. Analytics will prove even more valuable for clinical trial execution where the value of external data, including electronic health records (EHRs), and payer and other pharmaco-economic data, can contribute to the protocol design and feasibility analysis of a trial. In analyzing the data from previous trials, these findings could be applied to make decisions regarding future trials, thus increasing the chances of success. To meet future requirements, as described above, CTMS needs to take advantage of all existing data, not just CTMS data. The insights deduced can assist in making decisions about clinical trials before they commence. This is considered predictive analytics or predictive feasibility analytics. Information about a clinical trial, such as: the type of trial; the therapeutic area; country of conduct; patient numbers; and details of what the exclusion/inclusion criteria are, can be determined by advanced CTMS capable of mining data from previous trials to determine the current trial feasibility and the chances of meeting overall deadlines. At the fundamental level, a CTMS needs to evolve to a point where it is not just the execution center but also a core to leverage data to perform predictive analysis and improve the overall design of the trials from the start. Lastly, CTMS can become a central hub that enables adaptive trials. Providing the dashboards required to make the rapid decisions that shape and guide the path of adaptive trials design requires access to key data from clinical systems, rapid analytics, effective visualization, and future modeling of the expected changes. This capability is currently being managed through ad hoc tools, and a packaged, consistent solution would allow the adaptive trial model to be scaled appropriately within an individual company.

The Role of CTMS in Improving Workflow The strength of CTMS lies in addressing shortfalls in the operational side of clinical research. This can include site performance tracking and management, resource and supply chain management, and regulatory document management. It can be argued that non-clinical

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workflow inefficiencies have as much impact on the cost of clinical research as working with paper case-report forms (CRFs). CTMS can excel in its ability to calculate performance metrics and subsequently support rapid business decisions. Performance data can be utilized to aid in constructing proposals that offer the sponsor a truer picture of what can be achieved within agreed timescales. If an organization can observe its performance in certain tasks—or how effectively it carries out tasks in a certain location—this data can be harnessed to optimize workflow, thereby creating a predictive, rather than a reactive, system. This use of data can have positive implications for optimizing decision-making processes and, ultimately, benefiting the contract research organization (CRO)/sponsor relationship. One area that can be harmonized—and is on the way to being so within biopharmaceutical—is the definition of models in which the execution or engagement of the information provided by a site is being standardized. By incorporating a global registration of sites across clients and sponsors the model would be vastly simplified. By simplifying the clinical trial model a site should be able to perform trials more easily as opposed to going through the significant effort seen currently. To achieve the best levels of performance, CTMS will also need to play an increasingly significant part in driving high-performance clinical trial execution. The central position of the CTMS in the overall information cycle is further complicated by the wide range of stakeholders involved in CTMS implementation. Although it can be noted that study management must drive the implementation, the study management group must collect and consider input from other groups such as data management, finance, and contract management. CTMS that is built on open architecture and facilitates data exchange with third-party applications can bring significant cost savings to biopharmaceutical companies and CROs.

Consolidating Master Data Most biopharmaceutical companies utilizing CTMS are looking at master data management opportunities, where key, non-transactional data, such as investigator names and addresses that are often recorded in multiple places, are handled once and unnecessary repetition is therefore avoided. Master data management allows for key data to be stored in a higher quality format across multiple systems while a centrally-managed approach allows for significantly better control over the key data. The ability to handle large quantities of changing core data will be a vital element to optimizing the clinical trial process. Master data management strategies can ensure that key data are consistent, definitive, and of high quality. The benefits of a master data management solution can be realized by utilizing technology to bring all of the key data together in an integrated fashion. Currently, data is now coming directly from source systems and standardized, which vastly improves the data quality. In the past, key data, such as an investigator’s professional details, were entered manually and biopharmaceutical companies could have several different variations of an investigator’s name recorded even though they were the same person. Its central position in data flow makes CTMS ideally suited to drive master data management processes and utilize the master data to support quicker decision-making.


The Clinical Trial Management System—The Central Intelligence Hub

A Master System in the eClinical Framework Evolution requires modifications to adapt to a changing environment. In the clinical trials technology ecosystem, key changes include the number of technologies in play by sponsors, CROs, vendors, and sites (even within a single study), and the demand to work quicker and more efficiently. This demand has been responsible for accelerating CTMS tools to the next level of performance, use, and functionality. No one could argue that managing research programs and studies with configurable off-the-shelf software is not a challenge. Those involved in running a trial include the sponsor, contract research organizations (CROs), ethics committees, local and central laboratories, and the investigative sites and patients themselves. Because each of these stakeholders have their own needs and specific tasks to be recorded by the different eClinical components (ePRO, EDC, IVR, etc.), the CTMS is in a position to become a central system to coordinate data and workflows and present dashboards for relevant stakeholders. By its current definition CTMS is not yet ready to be a master system but, if it evolves and integrates with other parts of the eClinical continuum, it could well make a compelling case to be just that in the future. To achieve this scenario Accenture asserts that several changes need to occur. Trial execution has to be standardized and not significantly customizable or configurable. The CTMS is a strong contender to become the central master system to coordinate meaningful information within the clinical trial progress. However, whether it will fulfill this role is still up for debate. From a technology perspective, the creation or consolidation of operational systems and a data warehouse that can provide clinical trial management capabilities is another possibility. This scenario is pertinent because a CTMS is not a data warehouse, thus a warehouse is still required for the integration and management of data. Accordingly, the existence of a data warehouse that incorporates CTMS capabilities may be a more realistic central master system.

The Value of a Data Hub Accenture notes that the biopharmaceutical industry is moving away from the concept of a data management system being the sole place for data to reside and toward a data warehousing or data hub view. Current industry thinking also dictates that if data can be efficiently mined for analysis and reporting it does not really matter what type of on-premise system one has. Data warehousing and the ability to have message-driven technology, in which messages are not constantly replicated, should theoretically be very valuable in the clinical trial space. The clinical trial process is highly complex and often data are simply moved from one system to another. There is also the added complication of constantly evolving data forms and models, with the potential for new types of data and new usage. While data standards exist, challenges still abound, especially as standards are yet to fully mature and be universally accepted. Therefore, data warehousing and the integration of data into one environment could enable data accessibility across studies and various clinical trial programs. This would allow companies to create complex data models that help to inform best practices that improved clinical trial execution, from determining how best to design a trial to possibly predicting the likelihood that a compound will not work.

Notably a data warehouse is, first and foremost, a working middle ground where a significant number of incompatible hardware, software, and operational systems, accumulated over many decades, are linked to a group of platforms utilized by the end user. To realize real benefit from data warehousing, it will be necessary to define the appropriate data model for the data warehouse. By applying a common data model to all data regardless of its origins, Accenture asserts that data become easier to analyze and interpret. A data warehouse then becomes a driver toward standardization and becomes a bridge for pharmaceutical companies to exchange data with CROs, partners, and regulatory agencies. As soon as datasets are stored in an agreed format it becomes possible to transfer them to a data warehouse in a standard that is acceptable by regulatory authorities. It should also be noted that, in the data warehouse space, metadata management also poses a significant challenge. Metadata will be a critical enabler of data warehousing functionality, and will help drive the push for data transparency. Metadata, and particularly automated metadata, makes data analysis a much easier task. Therefore, deciding early on, which metadata to utilize, will be critical. Near-perfect metadata content will be required to drive data integration, as imperfect metadata will cause the data integration tasks to fail. A centralized approach to metadata management is preferred as it allows for significantly better control over the metadata. One of the biggest challenges for a CTMS is to ensure the relocation and maintenance of up-to-date, quality data. Larger biopharmaceutical companies with vast amounts of legacy data have found this to be a particular problem. The overall aim is to maximize the value of data—a task made infinitely easier when data are transparent, reusable, and readily integrated. CTMS is able to generate better quality data if transparency and reusability are factored in. In this scenario, aiding automation of data integration through a master source of metadata that is definitive, consistent, and authoritative will allow sponsors to make better and faster decisions about the status of a clinical development program.

Future CTSM Challenges Today most CTMS solutions are customizable to a large degree and observations have indicated that this is not a completely standardized area. Common requirements include project management, budgeting, financials, patient management, investigator management, ethical approvals, compliance, and integration with other clinical systems. One impending challenge questions the task of balancing the need to customize/configure with the need to introduce a degree of standardization between systems, software, and sites. The biopharmaceutical industry needs to start making choices about what is required to create the best possible tools. As these tools evolve, companies will eventually work with the vendor population to develop the next generation of systems so that the need to customize is negated. By leveraging the vendor population to push for changes covered by the license, the drive may well be the start of new and innovative releases of industry utilities. Increasingly, software and service models are emerging in which a vendor or software company hosts and provides access to trial management technologies. Another challenge is the need to manage more complex and adaptive trials. Adaptive trials have the potential to improve clinical drug development; however, they will also introduce more complexities.


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Review With the concepts involved in adaptive trial design, tracking the status of the study against a planned objective would be difficult for CTMS if planned objectives changed on a regular and frequent basis. Lastly, Accenture research indicates that budgets for information technology continue to shrink and the opportunity to expand the capabilities of CTMS technologies to suit individual company needs are becoming less. Therefore, packaged solutions that are configurable will need to deliver the expected value with minimal cost for implementation and long-term support. If the total cost of ownership of CTMS systems does not significantly decrease, the business case for CTMS expansion will become weaker, threatening its long-term need and survival. Over the past two years there has been a slowdown in the number of new CTMS implementations, which may signal the lower value assigned to its capabilities in comparison with the costs required to implement them.

Concluding Remarks The competitive nature of the current marketplace is driving the biopharmaceutical industry to search for more-effective ways of decreasing drug development times and increasing productivity.

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Accenture believes that CTMS technology has stimulated new demands for enhancement, configurability, and intelligent features. The call to further develop clinical efficiencies and expedite study times continues to gather pace, motivating industry sponsors to find an eClinical environment that enables adaptive trial design, solid data management, real-time data visibility, reporting and analysis, and global trial management. By adopting and embedding CTMS technology into the eClinical infrastructure these technologies will play a greater part in drug research and development—becoming more prominent as clinical trials become larger and more complex. In a globalized and multi-faceted environment, technology has to respond accordingly evolving to a point where data is collected in the most passive manner possible, exchanging data seamlessly between applications and services and requiring only minimal data entry from anyone. It is not enough to purchase and install the system. To maximize its value and return on investment an organization should be innovative and progressive, looking to take advantage of all of its systems to support the business. From an architectural perspective, the optimal environment for trial conduct success will be the vendor that offers the most cost-effective integrated solution to a data-centric market. n


Review

Clinical Trial Management Systems in the World of Mergers and Acquisitions—Managing Operational Challenges An interview with Christopher Heider

Chris Heider is a Director of Information Technology supporting Division-wide Services for Merck Research Labs. He has been with Merck (formerly Schering-Plough) since 2002, always supporting the R&D space and clinical operations. Chris has managed strategic initiatives including the implementation of 100 % electronic data capture using InForm and a global clinical trial management system using Siebel Clinical. Prior to working for Schering-Plough, Chris was an e-commerce architect at Dun & Bradstreet and the Chief Technology Officer for a dotcom start-up. Chris can be reached via www.linkedin.com/in/chrisheider

The biopharmaceutical industry is currently facing unprecedented global challenges: the patent cliff, the innovation gap, rising research costs, and a squeeze on healthcare spending are critical factors that will threaten profit margins and successful portfolios. The pressure to deliver profits in such a challenging environment necessitates that organizations continually restock product pipelines and deliver these pipelines to market in a cost-effective and timely fashion. The business challenges have set in motion a renewed cycle of mergers and acquisitions (M&A). M&A have always been part of the fabric of the biopharmaceutical industry, and it is a strategy that has been used successfully to augment and complement internal innovation. In 2009, Merck sought to diversify its product portfolio and maneuver into a stronger market position by entering into a $41 billion merger with Schering-Plough. The transaction also bolstered Merck’s presence in key international markets, particularly in high-growth emerging markets.1 More importantly, the merger served to boost Merck’s research and development (R&D) pipeline, expanding a portfolio of medicines that reflected the strength of the merged company’s clinical research programs in diabetes, obesity, oncology, and infectious disease. In total, the newly integrated pipeline consists of approximately 55 % of molecules originating from legacy Merck and 45 % from legacy Schering-Plough.2 This includes 16 Phase II and 18 Phase III candidates. The merger between Merck and Schering-Plough posed substantial challenges, especially in terms of streamlining differing processes, and addressing different user and management needs. The merger also posed substantial challenges for uniting different information technology (IT) infrastructures. To get the expected benefits, the merged company would need to undergo a significant restructuring and rationalizing of the IT architecture and standardize systems and platforms. Critically, integration of systems and processes needed to be achieved with minimal disruption to operational work flow. In clinical development, which remains the costliest component of R&D innovation, smooth integration is critical. Managing and supporting complex global clinical research is a major challenge in itself. The challenge significantly increases when two companies merge. With strict regulatory environments that may vary across

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geographies, companies need to ensure that trials are efficiently organized and managed, with clear visibility across the multitude of research programs. Thus, aligning processes to ensure that clinical programs/operational processes are not disrupted during the transition is fundamental to a successful merger.

One Company—Two Systems IT-enabled data capture and data management platforms have become ubiquitous in the clinical trials process. Increasingly, organizations are using clinical trial management systems (CTMSs) to improve the management of the overall eClinical process. CTMSs can provide the tools to optimize the electronic work flow and gain better oversight of a global portfolio of clinical research programs. Prior to the merger, Schering-Plough and Merck used different CTMSs. Schering-Plough was using a CTMS called SPECTRUM, which was built around Oracle’s Siebel CTMS platform. Merck had been employing Perceptive Informatics’s CTMS solution IMPACT. For Christopher Heider, Merck’s IT Director and current Program Director overseeing the firm’s global CTMS integration and redeployment, a key decision had to be made on how to rationalize the CTMS, post-merger. Schering-Plough had previously undertaken a similar integration/migration of clinical IT infrastructure during the company’s acquisition of Organon. However, the dynamics of that restructuring were radically different to the present project, especially in terms of scale. As the larger of the two companies in the ScheringPlough/Organon merger, Schering-Plough had the relatively simpler task of absorbing the smaller Organon and its operational procedures and IT infrastructure; a typical merger scenario. Moreover, it was identified early in the process that Organon’s home-grown CTMS, which had been built with strong input from the user community, would not be able to meet the needs of the merged company. Thus the strategic decision to migrate to the Schering-Plough system was made much easier. In comparison, the merger between Merck and Schering-Plough was a merger between two similarly sized companies, with similar-sized clinical development programs. Accordingly, any decisions regarding the harmonization of the CTMSs had to be balanced with each legacy company’s processes and culture. Although both legacy companies were similar in size and stature, each company had different

Remarks by Richard T Clark, Chairman, President, and CEO, Merck & Co., Inc., at the Annual Meeting of Stockholders, North Branch, NJ. A presentation, April 28, 2009. Available at: www.merck.com/newsroom/presentations/executive-speeches/2009_0428.html (accessed June 12, 2011). Merck Highlights Robust Late-Stage Pipeline, Global Business Strategy and Progress of Integration. Press Release, May 11, 2010. Available at: www.merck.com/newsroom/news-releasearchive/corporate/2010_0511.html (accessed June 26, 2011).


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Review requirements that its CTMS needed to satisfy. Nevertheless, despite procedural differences, several CTMS requirements remain persistent, including: project planning and management, program budgeting and financial management, patient and investigator management, protocol approvals, compliance with regulations, and compatibility with other systems such as electronic data capture (EDC), data management systems, and adverse event reporting systems. As two multinational companies, Merck and Schering-Plough each followed strict processes. Rather than adopt one company’s macro-processes over the other, it was decided, for the clinical development programs, to examine the component parts—the micro-processes associated with trial management, monitoring, site readiness, drug supply, and ancillary supplies—and select the best of breed, or the better of breed, from the two legacy companies. “We selected the best processes from each company,” commented Heider. This approach was also taken for the systems used by both legacy companies. Where systems overlapped, the decision-making process included consultation on how the particular system was used. For example, both companies used Oracle Health Sciences’ InForm Global Trial Management platform that harnessed EDC and data management functionality with centralized and integrated software modules, and the strategy going forward was to retain the system. “However, Merck and Schering-Plough were using InForm in different ways”, noted Heider. “By taking the approach whereby each process owner provided input into which processes should be retained post-merger, plus the involvement of the IT department in relation to which systems would survive, Merck essentially undertook a hybrid approach that would adopt best practices from both legacy companies.” Where parallel systems in the two legacy companies were considered obsolete or end-of-life, the decision was undertaken to replace the systems with a new unifying solution. For example, a review of both companies’ safety systems led to the decision to implement Oracle Health Sciences’ Argus Safety Suite. The replacement or migration to any system will occur over a period of time. Currently a stable of 40 or 50 systems are working in tandem, with the prospect of half of these being gradually phased out over time. For the interim period these systems will need to be working together. From an IT perspective this has proved a very challenging ongoing process.

Critical Clinical Trial Management System Considerations In terms of the CTMS, the decision was taken to adopt and upgrade the Schering-Plough Siebel-based system. As mentioned previously, the legacy companies had synergies in certain eClinical solutions, such as InForm. With the CTMS, the synergy arose from legacy Merck’s pre-merger assessment of its IMPACT system. The company had carried out an evaluation of its future CTMS requirements and considered whether to upgrade IMPACT or implement a new solution with the Siebel CTMS. Strategically, legacy Merck’s decision to adopt the Siebel CTMS had already been made before the merger. The legacy Merck system IMPACT had been developed over a number of years into a highly customized system that leveraged a host of features that did not exist in the out-of-the-box product. By successfully automating certain processes, data entry errors would be eliminated or, at the very least, reduced. For example, management

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of ancillary supplies for clinical trials was optimized through a customized interface from the Merck enterprise planning system with IMPACT. This was considered a superior process to the one used by Schering-Plough but required a dedicated interface that would need to be implemented in the upgraded Siebel CTMS. Similarly, SPECTRUM has an interface which is not present in IMPACT, which optimizes investigator payments: when a payable event is entered in InForm, the SPECTRUM CTMS picks it up and creates a payment request that flows to a grants management system for approval. The optimized process ensures a good relationship with investigators. IMPACT uses manual processes from the trial financial management perspective. IMPACT tracks payable events but data are transferred manually to the payment management system. The issue of creating interfaces is a significant challenge. Legacy Merck used a central data entry organization to maintain data in the CTMS. Creating the details of a new trial required a trial manager or a therapy head to enter all the critical information into specific forms before the data entry group inputted the data. Because IMPACT lacked certain interfaces the data entry group is often required to input the same data into multiple systems, for example into a separate reference data repository. At Schering-Plough the CTMS is the source of reference data for all the clinical trial information. In comparison to the current legacy Merck process, the critical information required to set up a new trial is entered directly into SPECTRUM by the end-user. Nevertheless, ensuring good data integration requires the development of key interfaces which need to be tested and validated in the working environment of the eClinical infrastructure while simultaneously migrating trials from IMPACT into the Siebel CTMS. Within the eClinical ecosystem, connectivity between point solutions is the major challenge. As more and more eClinical tools become commonplace, there is a greater need for the interfaces to facilitate interaction and communication between these systems. With a CTMS implementation, there are three main phases: core product implementation; data migration from the previous system; and data integration through application interfaces. “The latter phase is probably the most critical and the one that gives you the best return on investment because these interfaces represent automation and improved efficiency,” noted Heider. “It’s a double-edged sword because interfaces are complicated to implement. Adding a new interface to the CTMS is typically a project in itself.” As previously mentioned, the CTMS implementation includes the best processes from both legacy companies. For example, the Siebel CTMS will use the legacy Merck protocol numbering and drug numbering process. This will involve changes in reference data standards and configuration changes in SPECTRUM and all the downstream systems, which in turn means the modification of existing interfaces. “With Schering-Plough’s merger with Organon we had approximately 20 interfaces to integrate,” said Heider. “With the current project we are not only interfacing with legacy Merck systems, but we have also had to revise and modify those interfaces to the existing Schering-Plough systems.”

Optimizing the Implementation Process— A Phased Approach With important ongoing global clinical development programs, Merck needed an implementation and data migration strategy that would have minimal impact on clinical operations. “One of the basic tenets


Clinical Trial Management Systems in the World of Mergers and Acquisitions

when devising a system implementation plan is that it cannot impact any major milestones to our clinical programs. We would always have a plan in place that would defer certain trials if they were undergoing any kind of major milestones. But the business has been very proactive and we can plan deployments months in advance,” said Heider. Training was similarly planned to be absorbed without impacting any clinical commitments. To assist with the implementation challenge Merck engaged Oracle Life Sciences Consulting. “They were selected due to their close alignment with the product,” Heider remarked. “Oracle’s consulting team also possessed a direct line to the software engineering side of Oracle and associated support teams.” These teams were crucial in leveraging Oracle’s extensive collection of consulting assets and accelerators, prioritizing tasks such as providing a patch for a point release. In addition to Oracle’s global team of product experts, a strong internal program management team was put in place to work on the Siebel CTMS implementation, providing the necessary domain expertise and in-depth experience. “Our data migration team was selected due to the previous experience gained with our legacy CTMS implementation.” The success of the implementation strategy also depended greatly on the structure of the project team. Additionally, it was important that the team focused on three distinct phases: implementation, migration, and integration. A staged migration was agreed as the most appropriate strategic approach as it allowed the design configuration, testing, and deployment of a limited Siebel CTMS release to a subset of users, adding more functionality and enlarging the user base over time. According to Heider, “one country, Canada, was chosen to carry out preliminary live testing of which feedback was received and acted upon.” The feedback allowed Merck to address issues in the system with a point release before going live with the final wave. This experience also allowed the teams to quickly address issues in the system post-production before the majority of users were migrated. Following the initial deployment and testing phase, the CTMS strategy will be deployed in four waves: local studies in Asia, European migration, and then the final waves will be US and global studies. The

rationale for having the US in the latter phases is because many of the global studies are managed from the US. The phased approach also meant a training schedule for the Siebel CTMS and the merged eClinical trial management technology could be devised that would inform and educate intended users and personnel within the time constraints. End-users such as documentation specialists and database administrators needed to acquire the required Siebel knowledge and skills through training. “Most of the training parameters were dependent on the volume, and number of users,” explained Heider. “Sufficient analysis had to be initiated and tested to ensure that the process and the system were ready to launch for everybody.” In terms of training requirements, a staged migration allowed a staggered approach with internal training resources that met expected needs. From a logistical perspective, training users to an acceptable standard within the given timeframe proved a challenging task that carried with it a high degree of uncertainty. “Training approximately 2,000 people is not possible within a short space of time. Likewise, it would’ve been unwise to train people too far in advance otherwise the training goes stale and they would require a refresher,” explained Heider. Other factors to consider were the training materials that needed to be developed for each specific study that used the new system. Crucially, it was important to determine who would have the responsibility in creating and delivering training programs/materials, and the responsibility in maintaining training records.

Conclusion CTMS solutions are becoming increasingly integrated within the eClinical infrastructure. Chris Heider sees the CTMS as “the glue that binds together all the other processes across the clinical organization. It tracks the status of all of your trials; it is the single source of the truth that can give management a good overview.” At present, CTMS appears to be a technology that is now coming into its own, excelling as a vital enabling tool in the management of global clinical programs. Looking ahead, there is a strong case for the CTMS becoming the cornerstone in any pharmaceutical organization. n


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Review

Flexibility, Interoperability, and Organic Growth—The Challenges of Clinical Trial Management in Emerging Geographies Lynda Shelley

Lynda Shelley joined the pharmaceutical industry in 1991 as a Clinical Research Associate (CRA) with Wellcome Australia. She then held the positions of Senior CRA and Clinical Project Manager with Serono Australia, managing local clinical trials and health economics projects, before transferring to Serono International in Geneva in 1999 as Clinical Trial Leader on an international Phase III study. In 2002 she joined Serono’s clinical management team as Associate Director responsible for a team of project managers and clinical trials assistants across Europe and the US. She has also participated in a clinical process ‘re-design’ project, which took a quantitative and qualitative approach to evaluating departmental performance before and after implementation of newly designed, standardized clinical processes. In 2005 she returned to Australia and joined Covance as the Head of Project Management for Asia Pacific. In mid-2006 she moved to Novotech Australia and is currently Executive Director of Clinical Operations, with responsibility for Novotech’s growing clinical operations and biometrics teams across Australasia and Asia. She holds a Bachelor of Science degree (Biochemistry/Microbiology) and a Masters of Public Health (Health Economics).

As global clinical development programs become more ubiquitous, contract research organizations (CROs) and sponsors are increasingly searching for tools that will improve decision-making and the management of clinical trials across multiple sites.

The next frontier for the clinical development market concentrates on the emerging economies in the Asia-Pacific region, where biopharmaceutical companies see new opportunities to meet growing medical needs and where sponsors and clinical research organizations (CROs) can enjoy access to diverse patient populations for clinical trial recruitment. Indeed, Novotech data show that over 200 new clinical studies were started in 2009 in the Asia-Pacific region. This is a fourfold increase over the number of new studies started in 2006. The greatest uptake has been in India, South Korea, and China. The company has also observed a similarly high demand in countries such as Thailand and Taiwan. The number of clinical trials in Australia has also increased during the same period. Access to a large, diverse patient population within the Asia-Pacific region is in stark contrast to the established clinical trial markets, such as Western Europe and the US, which are currently saturated. While patient recruitment is the most important issue, the lower cost of conducting clinical trials in the Asia-Pacific region, relative to the US and Europe, is also a benefit. These factors have the potential to reduce timelines, the time-to-market, and the cost-to-market.

The Novotech Perspective Novotech, the largest independent clinical CRO in Australia, offers a full range of ICH-compliant clinical services, from first human exposure through to completion of Phase III trials. The organization currently counts several of the top 20 biotech companies among its clients, in addition to a host of other US-based biotech and pharma companies. Based in the Asia-Pacific rim, with operations in India, South Korea, Malaysia, Thailand, Taiwan, and Singapore, Novotech is ideally positioned to meet the growing demand for clinical outsourcing services in the region. With biopharmaceutical companies based outside the region naturally hesitant about making large-scale investments in infrastructure, locally based CROs can increase their value proposition with a mixture of extensive local knowledge and the infrastructure to manage complex projects. Thus, it is a natural progression for Novotech to expand its presence in the region.

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Aligned with Novotech’s size and the reach within the region is its investment in best-in-class eClinical solutions. The company’s philosophy is that a robust technology platform and infrastructure is the key to success. By using technology to consolidate project times, and streamline multiple workflows, CROs can collaborate better with clients and gain deeper insight from critical information as a result of enhanced data quality. Clinical trial management systems (CTMS) help to manage business and operational processes. They are designed to help users increase productivity by providing a project management functionality that supports multi-site, multi-geography trials. Additionally, a CTMS can provide automated processes to reduce the need for costly back-end queries and reconciliation, thus lowering overall cost through improved use of resources. CTMS also play a prominent part in the decision-making process; importantly, the CTMS gives clients near real-time access to information. For Novotech, the existing proprietary CTMS, Novotrak, did not accommodate the organic growth and evolving business needs of the organization. To support the company’s continued expansion and an increasingly complex business environment, Novotech needed a system that was robust, flexible, and could grow with the company’s operations. Accordingly, the company investigated the option of replacing Novotrak.

Establish Business Needs and Objectives In the preliminary stages of selecting a replacement for the proprietary CTMS, Novotech set out to identify the specific business needs and objectives of the organization and its clients in the context of a changing clinical development landscape. In today’s clinical trials environment, clients demand a closer connection to their CRO. As trials become more complex, with more countries and sites involved, having information immediately available is vitally important for the project manager, the project team, and the senior management, to ensure that the project remains on track. Offering an added level of visibility to clients via CTMS provides a competitive edge. It provides assurances that the oversight is present internally and externally. In the global environment, the trial being


The Challenges of Clinical Trial Management in Emerging Geographies

conducted in one region will be, more often that not, part of a much larger multi-site, multi-geography program. Novotech’s bespoke CTMS had served the company well through a number of years of growth. However, it became apparent that Novotech was outgrowing Novotrak and the company ran the risk of approaching a potential ‘plateau point’—where the limitations of the system threatened to negatively impact growth. As a CRO, Novotech recognizes the importance of focusing on its core business strategy—the business of running clinical trials. Because the CTMS market has matured since Novotrak was developed, with a number of high-end, enterprise-class, commercial products available ‘off-the-shelf’, Novotech looked to commercial software vendors to source a replacement for the proprietary system. This decision was the start of a crucial evaluation process. The company needed a CTMS system that would support Novotech’s growth strategy; it would need to cope with the growth and development of the company and its expansion into new regions.

Benchmarking for Scalability and Flexibility Once the decision had been made to transition away from a proprietary system to a commercial product, the company began to establish its main procurement criteria by conducting a benchmarking exercise, using the functionalities and experience of the older system as the baseline. As the owner of a proprietary CTMS, the inherent advantages and limitations of the system were well known to the company. Novotrak was developed in-house over a number of years and consisted of a basic structured query language (SQL) back-end with a dotNET front-end. The bespoke system incorporates a suite of modules covering every aspect of a clinical trial project and was designed to manage projects conducted in a number of geographic locations. Novotrak has been operational for five years but inevitably has encountered scalability and maintenance issues. Novotech recognized that by continuing with a CTMS based on a dated platform the company would increasingly encounter integration inflexibility with evolving iterations of solutions that feed into the CTMS, such as interactive voice response systems (IVRS), financial systems, SharePoint, and adverse event reporting procedures. For Novotech, linking the organic growth and expansion plans for the business with a dated system design and inferior interfaces could result in a misalignment of technical architecture to evolving business needs. The replacement CTMS would need to provide functionality that facilitated the current workflow. It would also need to improve on the functionality of Novotrak with new features that were absent from the proprietary system. Novotech had to be confident that future requirements of the system, such as streamlining multiple workflows and gaining deeper insights into processes through analytics, would also be supported. Another important criterion was that the new CTMS could easily integrate with the company’s existing technology. Novotech currently uses two electronic data capture (EDC) systems, Medidata and Viedoc, both of which have interactive web response system (IWRS) capabilities. The CTMS system would also be required to manage investigator payments and subsequent tracking. Further along the implementation roadmap is the prospect of integrating the CTMS with enterprise resource planning (ERP) software.

One of the key limitations of Novotrak was its inability to allow direct access to clients to specified areas of the system, which is essential for ensuring good visibility. To implement this capability, Novotrak would have required major investment in terms of software development. As mentioned previously, this would have detracted from the company’s core focus of facilitating clinical trials and was a major factor in the decision to procure a commercial CTMS system. Consequently, Novotech selected Oracle’s Siebel CTMS to support the company’s clinical drug development and research capabilities.

Implementation Challenges HCL, an IT services company, has been selected to assist with the project management of the Siebel CTMS implementation. An important function within HCL’s remit has been to assess the capabilities of Novotrak, thus defining a benchmark for where the new system should be in terms of scalability and flexibility. HCL will also assist in validating the new Siebel CTMS, liaising with Oracle technicians, and will provide training to Novotech personnel. Replacing a familiar, bespoke system requires investing significant resources in implementation planning. A critical factor for a successful implementation is to ensure that the right internal people with the right background are picked to work on the project. Accordingly, Novotech has designated a dedicated project team to work with HCL for the implementation process. Another important element for a smooth implementation is to ensure the support and confidence of stakeholders within the company. This is an integral part of the change management aspect of implementing any new system and needs to be a component of the implementation strategy; identifying champions and key stakeholders. In Novotech’s implementation process the project team identified that the project managers were key to winning the support of those stakeholders, which will be critical for the successful implementation and adoption of the new CTMS. A significant challenge in the process, in terms of the decision-making, concerns system configuration. The importance of this area should not be underestimated. A major investment in time and effort is required to ensure that the system is configured to meet business needs: all the different aspects and permutations of how the organization will optimally use the system. The challenge is planning these configuration requirements early in the implementation process, when access to the system is limited. Detailed configuration can only occur when the implementation is more advanced.

A Future-orientated Approach Implementing the new CTMS represents a major plank in Novotech’s continuing strategy to equip the organization with optimal technology that will enable the company to reach its key business objectives. The Siebel CTMS will serve as a centralized repository for all investigators, which will allow the study management teams at Novotech to collect and track all relevant information about the studies in near real-time. The organization’s expectations include eliminating the need for, or reducing the use of, manual and paper-intensive methods, such as one-off spreadsheets, and using email as a means to communicate and share documents. Integration, as previously mentioned, is an important factor. As part of the Phase III implementation, Novotech will


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Review define more advanced integration issues and examine whether the company’s many data arrays can be leveraged using the Siebel CTMS. From an internal perspective, the prospect of enabling site teams to manage and update their own information on their own sites is a valuable benefit. The CTMS will also provide project managers with a clear overview of the information that is available in the system. From a management perspective, the ability to pull together all the information from multiple trials, analyze the data, and review metrics helps to guide the business and keep it on track. Importantly, from a client perspective, the CTMS ensures that clients will have richer visibility on their projects.

Summary The decision to transition away from an aging, bespoke CTMS to a commercial system is aligned with Novotech’s strategy for continued growth and expansion in the Asia-Pacific region. The Oracle Siebel CTMS will help to:

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• centralize the management of clinical trials by serving as a centralized repository to collect and track relevant information about clinical trials; • allow management of clinical trials at different tiers—local, regional, and global; • offer an aggregate view of clinical trials undertaken by Novotech and provide up-to-date information for Novotech’s clients on project progress; and • provide timely and accurate reports and dashboards to support tactical and strategic decision-making. From an internal perspective, improving the management of relationships with trial investigators is especially appealing. Having good, robust systems that will enhance the company’s growth is critical for Novotech’s business strategy. In the global era of clinical drug development, having good tools ensures that we can more efficiently and effectively manage multiple trials around the world. n


LATE PHASE DEVELOPMENT ES ENCE IEN SCIE TH SC LTH AL HEA

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MAXIMIZING THE VALUE OF REAL WORLD DATA

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ENABLING OBSERVATIONAL AND LONG-TERM POST-MARKETING STUDIES Scott Dixon, Oracle

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OPTIMIZING PATIENT-REPORTED OUTCOMES IN LATE-PHASE STUDIES— START AT THE END

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Eric Gemmen and Louise Parmenter, Quintiles

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PATIENT REGISTRIES, REAL-LIFE SETTINGS—THE USE OF PREGNANCY REGISTRIES IN LATE PHASE DEVELOPMENT Deborah Covington, PPD

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Connectivity, interoperability and convergence embody the new digital ecosystem in the biopharmaceutical and healthcare industries. This series of expert-led reports, published in collaboration with Oracle Health Sciences, provides unique insights on the key issues affecting the new healthcare paradigm and the biopharmaceutical R&D value chain. With contributions from Merck, GlaxoSmithKline, Pfizer, Amgen, sanofi aventis, Quintiles, PPD and other principal industry leaders, these reports set the future agenda for healthcare and life sciences executives.

Oracle Corporation 500 Oracle Parkway, Redwood Shores, CA 94065 [email protected]

www.oracle.com/healthsciences

HEALTH SCIENCES

HEALTH SCIENCES Oracle Corporation 500 Oracle Parkway Redwood Shores CA 94065 GENERAL INQUIRIES +1.800.392.2999 INTERNATIONAL +1.650.506.7000 E: [email protected] www.oracle.com/healthsciences

Saffron House 6–10 Kirby Street London EC1N 8TS EDITORIAL Tel: +44 (0) 20 7452 5600 Fax: +44 (0) 20 7452 5050 SALES Tel: +44 (0) 20 7452 5332 Fax: +44 (0) 20 7452 5606 E: [email protected] www.touchbriefings.com

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