Equipping biometrics teams for an era of clinical data science

To harness the full potential of technology and advanced analytics within clinical trials, many organizations are now evolving from traditional clinical data management processes towards a clinical data science approach. Clinical data science, as defined by the Society for Clinical Data Management (SCDM), encompasses “domain, process, and technology expertise… data analytics skills and Good Clinical Data Management Practices.” According to the SCDM, this evolution is intended to ensure faster, better decision making throughout the research life cycle while enabling the execution of more complex protocol designs along with patient-centricity and risk-based, data-driven approaches.

Since people, alongside technology and processes lie at the heart of this ongoing transformation, biometrics and data science leaders must reimagine their talent acquisition, training, and external partnerships to enable the necessary shift in roles, skills, and culture.

In this blog we explore some of the key considerations in building teams and talent in the context of this rapid change:

Talent attraction and retention

As the demand for specialized skills and experience increases, leaders should be strategic and focused with their recruitment efforts to succeed in a highly competitive, candidate-led market. Alongside specialist recruitment channels, biometrics services providers can also be instrumental in allowing sponsors to access hard-to-hire expertise through tailored FSP (Functional Service Provider) outsourcing models.

With new roles and responsibilities emerging, many biometrics leaders are also reassessing their hiring criteria and job descriptions to attract candidates with the desired skill sets. For example, as the demand for data science, advanced analytics and machine learning expertise increases, organizations may need to broaden their scope to include candidates with broader quantitative backgrounds. Alongside these considerations, soft skills and the ability to leverage technology are becoming more highly emphasized and sought-after characteristics. This strategic approach to talent acquisition and investing in building a diverse and skilled workforce will position organizations well to navigate the rapidly evolving clinical data landscape.

Training

Clinical data science skills span technical, technology and soft skills, so developing a strong team requires targeted and customized training programs that focus on the specific requirements of the evolving roles. For example, statistical programmers will increasingly draw on programming languages beyond SAS, such as R and Python, alongside the development of new capabilities in machine learning (ML) and artificial intelligence (AI). Clinical data managers will be routinely using AI and ML tools and risk-based approaches as part of their toolkit. Additionally, project management, communication, and influencing are increasingly important competencies in a modern biometrics environment which relies on collaboration between multiple internal and external stakeholders.

Building a culture of innovation and collaboration

With the fast pace of change, it’s important to be intentional about creating a culture of innovation to drive progress and support the adoption of new technologies.

Opportunities for professional development and training, cross-functional collaboration, and transparent communication all contribute to a more forward-thinking, receptive environment where new, better ways of doing things can thrive.

Leveraging external partnerships and collaborations for specialized expertise

External partnerships and collaborations are essential to help leaders to better optimize their biometrics infrastructure and successfully navigate the complexities of digital and complex clinical trials. There are also promising opportunities for organizations to build efficiencies by leveraging the technology stack and knowledge of outsourced partners. As SCDM points out in its Position Paper, “too many transformation initiatives focus on “People, Process and Technology” and forget to consider the internal and external Partnership dimension which is crucial as no one can succeed alone.”

As the clinical data landscape continues to rapidly evolve, empowered, skilled, and motivated people will pave the way for innovation and redefine the horizons of possibility.

By investing in talent attraction, skills development, innovation-led culture, and specialized partnerships, biometrics teams will be well placed to confidently navigate the challenges and opportunities which lie ahead.

To learn more about the people, process and technology transformations shaping a new clinical biometrics blueprint, download our latest ebook.