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International Clinical Trials

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Sponsors need to ensure that their product’s knowledge store is complete, searchable, traceable and accurate in a changing environment – a task that brings both challenges and benefits.

Traceability can be defined in various ways, depending on the environment and process under consideration. It describes the ability to verify the origin, location or application of an item by means of documented, recorded identification. Traceability facilitates transparency, which is an essential component in building confidence in a result or conclusion (1).

With regard to clinical information, traceability means knowing where data are located, as well as how information is derived and from which data. At a higher level, it also applies to the information that was used for a decision that led to a label being submitted for approval to the authorities. At the point of regulatory submission, it is important to recognise ‘the one version of the truth’ in support of a label. Centralising and standardising the process from first trials in man through to the submission, approval, label extension and marketing phases of the product will also ensure that whenever a question is asked about a label, the response will be fast, traceable and above all, accurate.

Why Is Traceability Important for Clinical Information?

The way in which a company creates, stores and retrieves clinical information has a significant impact on its reputation, efficiency and ability to keep products on the market. Therefore it is essential that the traceability of planned information (clinical trial data) is considered at a very early stage of a product’s clinical development life cycle.

It is only natural for clinical teams to focus on the information required for submission and approval, whereas the product’s entire clinical life cycle needs to be considered from a traceability and information storage perspective. At any point in time, authorities may ask for a product’s total trial profile, and this is where traceability becomes paramount.

Key considerations in this respect include:

  • Regulations governing the conduct and management of clinical trials in a given country (10). For example, in the UK, ‘all clinical trial information shall be recorded, handled and stored in a way that allows its accurate reporting, interpretation and verification’ (2)
  • Timescales – many years will pass from first-in-man testing, through submission, approval and marketing, to eventual product death. During this time, there are many occasions when the product’s information may be required for efficacy and safety profiling
  • Changing environment – standards are never standard for long; regulations evolve and technology improves, often becoming more complex. During the product’s life cycle, a sponsor may change technology provider, collaborate with a new CRO, in-license, partner or perhaps even merge with another company

Traceability of Information from a Clinical Development Perspective

Traceability means that every unique piece of clinical data can be traced through the entire software flow of all relevant application programmes, from data capture to final submission documents. Documents and files at any point in the system can be audited for accuracy and completeness against the raw data.

As a starting point, sponsors could ask the question ‘where is our clinical information?’ Across a portfolio of studies that may span years from Phase 1 to Phase 4, across various countries, companies and systems, has there been sufficient upfront planning and management to recognise the one version of the truth at the time it is needed? That is traceability in itself.

At another level, a sponsor may be looking for traceability across the information trail within a study for a particular product. For example, information in the statistical analysis plan (SAP) that also appears in the Clinical Study Report (CSR) and Common Technical Document (CTD) summaries, can become traceable and reusable (from a metadata perspective the Clinical Data Interchange Standards Consortium (CDISC) analysis data model (ADaM) is a good example of this). Storing that piece of information once and referencing it from the documents or summary tables provides a centralised, reusable piece of information. Think about where you store one of the most important information points for your study, the p-value. Is it stored in a reusable information store for future use, or is it buried in a table generated from your in-house reporting environment and copied numerous times across numerous text documents?

One final aspect to consider is the decision-making process during the life cycle of the product. Information and decisions made during the course of a submission need to be traceable back to the raw data. Under the tight timelines during submission, it may not seem efficient to record the reasons for taking a particular approach. These captured gems of information, if preserved for future reference, will save time, credibility and perhaps the label.

Managing Standards from the Beginning

The biggest problem in managing data is time: a product’s life cycle can last for many years. The clinical data from a single portfolio can end up being stored in multiple locations with different technology providers, utilising different systems and formats. Technology is now available to manage the vast amounts of information created during a clinical trial, and companies and vendors are investing heavily in this area. However, technology alone cannot solve the problem; it is critical to get stakeholder buy-in from the governance and functional teams, to consider what communications and behavioural changes are required, and to ensure that the process is auditable.

Clinical Information Principles

In general, this article will use ‘information’ as a term applying to all aspects and all levels. However, it can be useful to think of four different levels of clinical information that contribute to a product’s label:

  1. Raw data collected during the conduct of the clinical trials
  2. Summarised and reported, the derived data become ‘information’
  3. Apply expertise to that ‘information’ and it becomes the ‘knowledge/conclusions’
  4. That overall knowledge then forms the basis for the label of a product or ‘wisdom’

A label submitted for approval is done so on the basis that the sponsor has proven that a product intended for use in a certain population is safe, is effective in its defined use, and is manufactured to an acceptable quality. A vast amount of information goes into a submission, in the preclinical and clinical research areas, chemistry, manufacturing and controls and, of course, the regulatory area. In fact, the majority of regulatory knowledge is generated outside of the regulatory affairs function.

In order to be readily available for the right audience at the right time, the information generated from a clinical programme needs to be structured in the correct way. The inclusion of metadata (‘data about data’) to surround the information provides the opportunity to create and maintain the one version of the truth. It also provides the user of the information with a common store referenced from many different types of media, hence becoming more efficient.

Clinical Information Storage and Traceability

During the conduct of a clinical study, many information points are created using various methods and computer systems. Information gets diluted as data is drawn from the raw data into the CSR and other regulatory documents.

Locating the information point in an information store and referencing it using metadata is an elegant solution to this issue. This approach ensures that documents do not simply become the creation and storage mechanisms of information, but the users of the information. Information that is tagged through metadata can then be traced right back to the raw data. This ability may be critical in certain situations, such as in defence of a product label.

Working in this way means that information also becomes traceable back to the raw data. This will enable faster access, and improve response times to regulatory authorities as a result.

Providing the Constant in a Variable Environment

Many different factors influence the decision-making process when a sponsor considers where to conduct their clinical studies. For example:

  • Specific therapeutic experience or knowledge
  • History of success
  • Access to specific populations
  • Location
  • Cost-effectiveness
  • Expertise with certain phases of development

It is unlikely that one unit/CRO will be the optimum choice for every study in a portfolio and therefore, studies for any individual compound will continue to be performed across several different units/companies. Since the cost of actually conducting the trial is the largest part of the overall study budget, it is understandable that the focus is on this aspect. However, these units/CROs are not necessarily the best choice for housing and reporting the data.

Taking the approach of including the data collection, storage and reporting for a study with a full service CRO means that programme information becomes scattered across various companies and systems using a variation on a standard with little or no traceability. This compromises on the quality of the input and output from a biometrics perspective and loses the vital consistency required at a later stage of the product’s life cycle.

Why Not Make the Information Traceability the Constant?

Solution providers can supply not only the technology and the standardisation, but also, and most importantly, knowledge of the clinical trial process and therapy area. Consider the advantages of having the same medical writer provide input to a Phase 1 protocol, prepare a CSR, and eventually prepare the publications that are created for the marketing of the product. The saving in terms of the reuse of intellectual property across a brand is obvious from a data management perspective and output generation perspective. Combine that with the consultancy input from a knowledgeable statistician across the development programme – a study can be designed so that the data fit together seamlessly if required for submission.

Think of it as a bank of information. When selecting a bank to support a business, organisations often look for one that can provide a secure place for money, with accessible interfaces to work on a global scale; in other words, one that will turn foreign currency transactions into the currency of choice. They will help companies do business with many different companies but will always provide the applications and interfaces to standardise the money and ability to pay out in different currencies to your customers. A centralised biometrics organisation will do the same for you with your clinical information.

With data collected from all sources – the company’s own records, partners such as CROs, laboratories, research institutes – and over the life cycle of a product, a centralised clinical data specialist will be able to supply the information that is needed, in the right format, at the right time and to different regulatory customers.

Generating the Traceability Up Front

Creating a standard to follow can be difficult to do within an organisation, but maintaining it is even harder. The introduction of standards such as CDISC has given companies major challenges to implement and uphold. Standards then need to be maintained through new versions and the task of traceability becomes progressively more complicated. Systems driven by metadata are becoming increasingly important in delivering long-term benefits.

Metadata control the way that standards are managed and the traceability between your data and information. These types of tools provide great advantages in terms of traceability, although they do require maintenance and governance, which can be resource-heavy.

Traceability of an information point can start to make use of such environments. It is possible to identify the data used in the generation of such information when a query is raised. The one version of the truth is found with confidence and in a timely manner.

Through some environments, it is possible to use a reverse-impact analysis across a mapped workflow in order to show visually how a summarised piece of information was generated, from what data points and using which algorithms. Managing this internally as part of your ongoing submission timescales can be daunting if you are using multiple partners. It is possible, however, if you are relying on one CRO to manage your data. Centralising this process becomes your constant and customers of the data are provided with access to the information they need, when they need it. This model also reduces your technology burden internally and compliance with 21 CFR Part 11 is all handled for you.

There are many different systems offering such functionality. Sponsors spend a great deal of time and effort choosing the environment and then need to implement and maintain the system. They also have to re-train or recruit resources to manage the process. All of this happens during the same time that they are delivering on the requirements of the clinical trials. Companies that provide access to the best-ofbreed industry tools and have trained resources for these environments will obtain great benefits.

Conclusion

Centralising clinical data services provides sponsors with a constant within their clinical trial submission process. The traceability of that information over time is managed from day one of a product’s life cycle and information points along the timeline are stored once, progressed to stay inline with the evolution of the standard, and are always accessible.

When questions are asked about the product, the responses are managed through the information trail that has been generated, and sponsors can be reassured that they have the one version of the truth. Every life science company faces the same challenges in the management of their clinical information. To be more effective in the management of clinical knowledge and information, it is important to consider the basic principles of how data, information, knowledge and wisdom are generated and how these can be traced throughout the life cycle of a product. Additionally, knowing how information flows across and within functions is important to gain a true understanding of what information is in place to support the label of a product and the speed and accuracy at which it will be accessed.

The ultimate metrics around the submission relates to the approval timeframe and the quality. In essence, if by providing data of real quality our response times are kept to a minimum, this is a true measure of the quality of information supporting the statements in the label.

References
  1. CDISC Analysis Data Model (ADaM) Team, CDISC Analysis Data Model, Version 2.1, 2009, available at www.cdisc.org/standards
  2. www.legislation.gov.uk/uksi/2004/1031/schedule/12/made Schedule 1, Part 2

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Michael Whitworth is VP, Centralized Clinical Data Sciences, with the clinical biometrics CRO Quanticate. Prior to Quanticate, Michael worked in a variety of positions with AstraZeneca Pharmaceuticals for over 20 years. His experience encompasses R&D operations including statistical programming, business development, and a range of management positions. Michael’s experience has focused primarily on the submission of clinical trials to regulatory authorities and he now works in a consultative manner with sponsors who seek more strategic outsourcing practices. He has a degree from Leeds Metropolitan University in Mathematics, Statistics and Programming.
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