Tasked with gathering, parsing, storing, and analysing data produced during the trial process, clinical data management professionals are crucial to ensuring that drug and device studies and healthcare research are successful. In addition, their work allows trial staff to comply with all regulatory and reporting guidelines outlined through Good Clinical Practice (GCP). 

Clinical Data Management experts have navigated many developments over the years, with artificial intelligence and machine learning again set to evolve how clinical data is collected and analysed. 

In this guide, we’ll explore how you can prepare for a career as a Clinical Data Manager, discussing the qualifications and experience you’ll be expected to possess, and what career mobility looks like once you’re in the field. We’ll also discuss why the qualitative and quantitative data collected during the trial process is of such importance to professionals across the life sciences. 

The Value of Clinical Data

The practice of clinical data management, as we now recognise it, had its foundations laid in the early decades of the twentieth century. Healthcare practitioners began to understand the importance of documenting treatments and having access to medical histories, enabling them to improve healthcare outcomes and monitor the efficacy of the compounds they were researching. 

In the intervening years, the field has gone from the time-consuming manual entry of participant data, lab reports, and case report forms to the increased incorporation of information and computing systems. 

Whilst the 1970s and 1980s saw this data stored in a central location—often utilising large mainframes—recent years have seen the use of the internet to collect and share data between multiple trial sites and external stakeholders. In the 2020s, this has included a shift towards distributed and cloud solutions, ensuring that data can be accessed on-demand and stored securely.

But why is clinical data so valuable? 

Realistically, the trial process would be for nothing without collecting and analysing clinical data. Evidence-based decision-making is the bedrock of modern healthcare, allowing practitioners, researchers, and policymakers to interpret and understand the efficacy of treatments and the potential impact of public health interventions. 

With 3.6 million points of clinical data created during the average Phase III trial in 2023, it’s crucial that trained, qualified professionals are prepared to handle the increasing volume of information that the process will continue to generate. 

This data is used in a number of ways: 

1. Identifying the efficacy of treatments. Clinical data is vital to understanding how useful a novel drug or device will be for the patient population it’s targeted at. Alongside this, clinical data will be collected on adverse events and side effects, ensuring that patient safety is at the forefront of the process, from early-phase clinical trials to phase IV.
2. Further research. Advancements in medical, pharmaceutical, and biological knowledge proceed in much the same way as other scientific fields. Medical and pharmaceutical researchers build their work on the foundation of existing data, identifying trends and patterns which can lead to insights which improve patient care.
3. Regulatory compliance. Clinical data management is a crucial cog in the machine of regulatory compliance for clinical research delivery. Trial results must be clearly and reliably reported on, ensuring that present and future participants are protected in line with Good Clinical Practice and human testing guidelines. 
4. Drug approval. Further to regulatory compliance matters, a robust and well-analysed clinical data set is crucial when organisations seek approval for their newly-developed therapeutic drugs and devices. Regulatory authorities such as the United States FDA and the UK’s MHRA will require reports assessing trial results before granting approval for commercialisation.
5. Health outcomes evaluation. Clinical data enables life science professionals and policymakers to analyse and understand the progression of disease within the wider population and specific demographics. A Clinical Data Manager can play a major role in improving public well-being by allowing scientists and public health officials to identify the factors that impact health outcomes.

With advances in sensor technology, wearable medtech, and the widespread adoption of telemedicine platforms following the COVID-19 pandemic, clinical data management professionals quickly recognise that the clinical trials process can be largely decentralised and carried out in a hybrid manner. 

Travelling to trial sites often poses a major obstruction to retaining trial participants over the long term. As a result, the shift towards decentralised clinical trials is helping to ensure that many underserved demographics are gaining access to treatment. 

Moreover, these decentralised trials provide an additional benefit to Data Managers, insofar as they allow researchers to see how their therapies are tolerated within participants’ everyday lives—allowing them to collect real-world data that can inform further research and regulatory report submission.

Why is Real-World Data Important?

Real-world data (RWD) is valuable because it allows organisations to understand how their drugs and devices positively or negatively impact participants’ lives beyond the controlled setting of a trial site. There are several forms of RWD, with data obtained from a number of sources, including: 

• Electronic health records (EHRs)
• Insurance claims databases
• Wearable medical devices
• Telemedicine and mobile health applications
• Participant diaries

RWD contrasts with clinical data by allowing the analysis of the wider patient population, including patients from diverse and historically-neglected ethnic and racial backgrounds. Researchers who gain access to real-world data can understand how different characteristics, comorbidities, and medical histories intersect with the treatment being trialled. 

This data is becoming increasingly important within regulatory compliance since it gives the professionals overseeing a treatment’s approval an opportunity to evaluate the effectiveness of a drug or device outside of the clinical setting, where certain participants may be excluded from data-gathering efforts due to certain criteria.

If you want to learn more about clinical data management or trial coordination after reading our guide, see our clinical research page for more related insights. Let’s continue. 

How to Become A Clinical Data Manager

Fundamentally, a Clinical Data Manager is tasked with ensuring that all data collected throughout the trial process is reliable, high-quality, and robust. Since this data will be utilised by multiple internal and external stakeholders, it’s crucial that all of the information collected via electronic data capture (EDC), paper-based diaries and forms, and laboratory results are complete and clear of any errors or discrepancies. 

It can be a challenge to know how to become a Clinical Data Manager, particularly if you’re coming from another field within the life sciences or you’re a recent graduate, so we’ve compiled an up-to-date guide on how you can ensure you meet the core competencies, experience, and education necessary to successfully discover a role within the field. 

Qualifications

Typically, a candidate that is interviewing for a clinical data management role will hold an undergraduate degree in a relevant field of study, which could include: 

• Biology
• Chemistry
• Health Informatics
• Statistics
• Public Health
• Computer Science
• Medicine

Whilst some employers may overlook an unrelated bachelor’s degree if a candidate can evidence relevant experience and understanding, others will require candidates to top-up their work history with a postgraduate qualification in a connected field. 

Luckily, many universities have begun to offer Master’s degrees which are focused on handling and analysing clinical data, such as the MSc in Health Data Science offered by the renowned London School of Hygiene and Tropical Medicine, the MSc in Clinical Research at Lancaster University, and the Health Data Analytics and Machine Learning MSc taught at Imperial College London.

Similarly, universities and educational institutions across the USA also offer world-leading courses for the practice of Clinical Data Management or associated areas, including Rutger’s M.S. in Clinical Research Management, the University of Maryland’s Health Data Analysis programme, and the M.S. in Public Health Research at Harvard University, located in the national—and international—biotech and pharma hub of Boston, Massachusetts. Alongside this, the San Francisco Bay Area is home to many renowned research institutions and private organisations, with University of California’s SF campus offering a Master of Advanced Study for professionals who wish to develop their skills in Clinical Research.

Experience

Candidates that are looking to secure a clinical data management role will be expected to have an in-depth understanding of the clinical research process. In addition, knowledge of regulatory compliance, ethical guidelines and Good Clinical Practice are also vital, alongside other international standards such as those set out by the ICH. 

Employers will likely want to see prior data management experience, including data collection and quality assurance methods that are guided by best practices. Understanding the standards by which clinical data is assessed, like CDISC—or the Clinical Data Interchange Standards Consortium—alongside experience with data management software or coding languages such as SQL, Python, and R will all set a candidate in good stead. 

Since ensuring accuracy and quality in the collected clinical data is vital for all internal and external stakeholders that will utilise that information, Clinical Data Managers must possess meticulous attention to detail, alongside the strong communication skills necessary to interact with investigators, study coordinators, statisticians, and other colleagues within their cross-functional teams. 

Responsibilities and Duties

Clinical Data Managers will have several key duties to attend to during their day-to-day tasks, including: 

• Database Design. A crucial aspect of any study, a well-designed database is created to ensure that all pertinent information and statistics are efficiently collected and stored. By standardising the data collection method through effective database design, Clinical Data Managers can ensure that all staff are aligned, and errors are minimised.
• Data Gathering. As we’ve discussed in our previous section, clinical data is collected through various methods, both at the trial site and in the participants’ everyday lives.
• Data Validation. Data Managers perform the crucial task of ensuring that all gathered statistics are accurate, complete, and consistent. Range checks are carried out to ensure that data falls within the ranges set out during the study setup, whilst cross-referencing checks compare data from different sources and sets to identify variations and missing information.
• Data Cleaning. By identifying and resolving discrepancies through the practice of data cleaning, Data Managers can be certain that all clinical data is error-free and high-quality. This can be a highly-technical duty, but it also requires strong communication skills since Data Managers will be expected to discuss outliers and inconsistencies with trial coordinators, researchers, and healthcare practitioners.
• Data Security. Given the sensitive nature of participant data, Clinical Data Managers must ensure that all the information they’ve gathered is protected. This can involve ensuring that all data is encrypted when not in use, putting access controls in place to manage authorised users, and following the guidance set out by the HIPA Act within the United States and GDPR within the EU and UK. 

Clinical data management professionals are a vital component within the trials process, ensuring that all results are valid and trustworthy—with responsibility for ensuring that products can move on to future trial phases, be approved for commercialisation, and are safe for use.

Career Prospects

Often employed by CROs, CDMOs, biotech, and pharmaceutical firms, the career prospects for a Clinical Data Manager are promising. As with many roles in the life sciences, with experience comes seniority, and many CDMs will move into a team leadership or project management role as they develop their skills and understanding. 

Alongside this, clinical data management professionals have the opportunity to leverage their unique knowledge to transition into several other roles across the clinical spectrum, from specialising in regulatory affairs to data standards and governance roles, helping to define the next set of best practices for this rapidly evolving area.

Whilst not mandatory, senior clinical data management professionals can often set themselves apart from other candidates by obtaining a professional certification within the field, such as the CCDM—or Certified Clinical Data Manager—certification, which can demonstrate passion and commitment to continuous professional development within the industry. 

Average Salary

Within the United States, the average salary a clinical data management professional will earn per year depends heavily on their location and the specific sector they’re employed in, but our 2023 figures show an average of around $95,000 to $115,000 dollars on the West Coast, and $87,000 to $105,000 on the East Coast. 

In the UK, Clinical Data Managers are likely to receive a salary of around £35,000 at the entry-level, with seniority and additional responsibility seeing this figure rise to around £42,500 per year. Meanwhile, in countries across the European Union, Clinical Data Managers can expect to see a yearly figure of between €40,000 and €55,000, leaning towards the higher end in nations such as France, which boasts the largest pharmaceutical sector on the continent and the globe’s second-largest market for clinical trials.

A career in Clinical Data Management offers exciting opportunities for individuals interested in the intersection of healthcare, data analysis, and research. As a crucial pillar of the clinical trial process, data managers play a vital role in ensuring the success of drug and device studies, compliance with regulatory guidelines, and the generation of reliable metrics for evidence-based decision-making.

With the ever-increasing volume of data being generated, professionals in this field must possess the necessary qualifications, experience, and attention to detail to handle and analyse clinical data effectively. The value of clinical data extends beyond the trial process, impacting treatment efficacy, further research, regulatory compliance, and drug approval. 

As the industry evolves with advancements in technology and the continued success of decentralised trials, clinical data managers are well-positioned to contribute to improving public well-being and shaping the future of healthcare. With promising career prospects, opportunities for specialisation, and the potential for valuable professional certifications, a career in clinical data management can lead to fulfilling and rewarding experiences in the life sciences field.

Experts in Recruiting for Clinical Data Management Roles

Warman O’Brien has the industry knowledge to support your search for that next role within the life sciences. Whether you’re focused on clinical data management or interested in exploring another specialism within the data sciences, our consultants work closely with you to connect you with cutting-edge companies across the United States, UK, EU and APAC. We’ve successfully placed candidates with organisations in 25 countries across the globe, so get in touch to discuss your career ambitions.