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International Clinical Trials

Entering the Atomic Age

Hacene Mekerri of Clearstone Central Laboratories explains how the pharma industry may be able to shape the next evolution of data management in the near future through the use of sophisticated applications

Great effort has been made in the last decade to streamline processes and accelerate data availability without compromising on quality. This has propelled clinical trials into a new age – an age where robust tools are made available to collect electronic data and where Lean Six Sigma becomes to the pharma industry what ‘Fordism’ and ‘Taylorism’ were for the manufacturing industry. The industry is in a period where standards are now available to reconcile quality and time. Within this time of perpetual change, one should be asking how the evolution in data management can better help the pharma industry to achieve its ambitious objectives.

For the purposes of illustration within this article, the clinical laboratory data management evolution can be segregated into three phases:
  1. Ice age – a period of laboratory data management that existed during the 1990s
  2. Contemporary age – a period of laboratory data management that existed until the first decade of this millennium
  3. Atomic age – the modernisation and sophistication that are evolving in laboratory data management

During the ice age of clinical trials, laboratory data was always received by the clinical data manager in paper format, which was then entered into the clinical database. During the contemporary age, processes were upgraded slightly and laboratory data was prepared by central laboratories that provide data as electronic files. This eliminated tedious data entry as well as any possible transcription errors. The progression to electronic solutions for laboratory data exchange has also significantly improved data quality.

In the atomic age, reducing the cost of drug development is of paramount importance. With the aid of clinical lab data experience, tools and technology, some distinguished central laboratories are offering the services of directly loading the data into the sponsor’s clinical database and resolving any loading issues instantaneously. As a result, pharmaceutical companies gain time during database lock and can bring the drug to market much quicker.


The chain of custody for a biological specimen and the link between the laboratory results and the patient draw is critical. During the early stages of clinical trials (ice age), samples carried multiple identifiers, which raised the concern of overlabelling. With further development (the contemporary age), sample identification has progressed from multiple labels to sharing unique lab accessions in case report forms (CRF). Now, in the atomic age, with pharmaceutical companies recruiting multiple vendors in an attempt to better manage risks and improve cost efficiencies, there are often multiple organisations participating on the same clinical study. To ensure the highest quality standards with multiple players, some of the leading central laboratories enable the use of a sponsor specimen barcode identifier upfront during study setup, which is incorporated into the central lab database. This allows electronic data exchange using a single unique specimen accession, which is translated into a barcode that is ‘print as you go’. The benefits reaped by pharma companies and analytical laboratories are significant. These include:
  • A robust and lean process for the specimen chain of custody, from kit building and blood draw, to analysis and data reporting
  • Cost savings, as the central laboratory will only print the barcode for the specimen(s) they are shipping, rather than bulk printing barcode samples
  • Eliminating the concerns of chain of custody on the label inventory
  • Electronic shipping from central to analytical laboratories, which carries the same unique specimen identifier
  • Directly loading the electronic file onto the sponsor database by the central laboratory data management team before analysis is performed. This involves looking at the sponsor’s pharmacokinetics, pharmacogenomic or any other speciality laboratories for biomarkers, and so on, which aids in the forecasting of upcoming data points as well as faster turnaround on query resolution


Using a local laboratory to ensure that testing is done within the stability window in a given region of the world could become a challenge for a data manager when it is a question of centralising and collecting the data. Successful collection of results is subject to different considerations relating to the ability of the local lab, which include:
  • Ensuring that validation and checks are performed in order to constantly guarantee quality and consistency
  • Keeping track, justifying and communicating proactively any change (for example, new reference ranges due to reagent change)
  • Providing an electronic data file formatted as per the data manager’s specifications as soon as results are available
In order to avoid data entry of results – and also not exclude the local laboratory in a given protocol – clinical trial management systems (CTMS) are now designed to include in their capabilities data integration in a lean process. Multiple edit checks are in place to ensure that the consistency of data is respected by the local lab. It is also interesting to note that data files needed from the local lab are simplified and do not require multiple programming or adaptation. A simple Excel file containing key sample identifiers and results could be sent to the local lab, which will populate the results, as well as any comments on them, by merging with their existing format or double data entered into the support file.

The current technology is surely going to provide better access to source data in order to respond successfully to challenges related to turnaround time. CTMS installed at local labs and directly linked to the database or to leading indicator systems (LIS) are scenarios that can really answer the requirements of real-time data view.


Real-time data access and live data monitoring are now standards for clinical trials. Regulators are asking for control to be constantly and proactively applied throughout the course of a protocol (for example, the FDA DILI Guidance). These tools are required to provide an overview of the trial – such as a picture on patient recruitment or a list of patients meeting exclusion criteria. This is also now used to better analyse results for a given region of the world using available graphs and models.

Tools are now designed to provide historical and aggregated data by country parameters. Data analytics is becoming more useful as it is based on a high volume of data collected and analysed by therapeutic area. Tools today provide more and more capabilities that we were formerly lacking around the proactivity of information. Alerts, metrics or even forecasts are all additional data that are made available for a better understanding of study status, and useful in making informed and timely decisions. Regulatory authority CRF DCF DCF Lab results NDA Sample DCF CRF

Data warehousing, and the location of study data (that is, sponsor versus labs) is also a topic that could certainly lead to changes around the scenarios of data owning, as centralisation becomes a solution to the challenge of multiple data sources. We noticed earlier that the loading of data into the sponsor database provides benefits regarding turnaround time and cost, and this loading is usually performed by an external provider. Specialising in data centralisation, a CTMS that allows integration of external data really addresses the increasing requirement for receiving data from multiple laboratories and having to deal with redundant queries for the same patient.


In the ice age period, data managers worked on clinical trials using paper CRF, ensuring on-time and accurate data entry. During the contemporary age, the data manager’s responsibilities have evolved into handling electronic data, requiring an in-depth understanding of the database in order to carry out edit checks to ensure data quality, as well as the initial database setup.

With the continuous evolution of the data management role during this atomic age – whereby Clinical Data Interchange Standards Consortium (CDISC) and Health Level Seven International (HL7) standards are being adopted industrywide from a consistency and standardisation perspective – refined, robust data management tools are increasingly being used to ensure quality data. The picture we can envision of the future is one in which data managers, aided by the most sophisticated applications, may focus their time instead on the bigger picture of a successful project that involves managing everything under the umbrella of a thriving clinical trial – from more effective budget management to new drug applications (NDAs), to on-time successful data submission to authorities and approval. This is indeed an exciting future vision that is within our grasp as an industry.

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Hacene Mekerri is the Global Director of Data Management at Clearstone Central Laboratories. He has more than 10 years of experience in data management and operations leadership roles in the Americas, Asia and Europe. In his role, he is responsible for the overall global data management strategy and ensures that the needs of customers are always met by using best practices from his global teams. His global outreach has leveraged the data management tools and processes for seamless study delivery and these have been recognised as best in class within the clinical trials industry. Hacene holds a diploma in Business Management from University of Versailles Saint Quentin en Yvelines, France. Email:
Hacene Mekerri
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