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Pharma Function Highlights: Data Science & Christel Chehoud, PhD

The Data Science function works with healthcare data to generate impactful evidence and insights. Christel Chehoud is featured.

In this series, we highlight specific functions or departments within typical pharmaceutical company organizations. We also feature the perspectives of women working in these different functions and their career journeys.

About the Data Science function

The Data Science function is typically responsible for working with data to generate impactful evidence and insights. These data describe the pharmaceutical company’s therapeutic products and patients. Such work can support the entire life cycle of a drug, from early stage development to post-market commitments. The overarching goal of the work may be to advance scientific and medical knowledge and enable data-driven patient care and access. 

Data Science in pharma utilizes advanced analytics tools to generate impactful evidence and insights from healthcare data.

Many pharmaceutical companies are currently striving to leverage the plethora of health data generated from patients. They are utilizing advancing technologies to make sense of all that data for the benefit of the business. Thus, the Data Science function may be a relatively new addition to the company. Alternatively, the function may also be the result of the evolution of predecessor functions that previously housed scientists with relevant skillsets. 

There are various types of data that Data Scientists might help generate, process, and analyze. These include real world data such as electronic health records and registry data, radiographic images, genome sequences, and clinical trial data, etc. Data Scientists may apply broad-ranging skills, such as epidemiologic methodology for designing studies. In addition, they may apply advanced analytics, such as machine learning or natural language processing tools. 

To be successful, Data Scientists need to be well-versed in drug development and the current healthcare environment. They may need to collaborate with a diverse team of clinical subject matter experts, statisticians, and various other functions, depending on the business needs or deliverables. The work of Data Scientists can inform internal decision making or be publicized as scientific publications. Their work may include contributions to documents submitted to regulatory or health authorities and health technology assessment or payer organizations.

Data Scientist generates, processes, and analyzes a variety of different types of healthcare data.

Data Science departments may also be called some of the following names:

  • Real World Data Science
  • Personalized Healthcare Data Science

Some of the people working in these functions may hold position titles such as:

  • Data Scientist or Data Analyst
  • Real World Data Scientist or Analyst

The education of people in the Data Science function may include degrees in:

  • Genetics
  • Molecular Biology
  • Epidemiology
  • Biostatistics
  • Computer Science
  • Bioinformatics

Function Feature:

Christel Chehoud, PhD

Principal Data Scientist, The Janssen Pharmaceutical Companies of Johnson & Johnson

Photo of Christel Chehoud, Principal Data Scientist

1. Briefly describe your educational and professional background up to your current role.

While an undergraduate at Princeton University, I participated in an innovative curriculum that combined biology, chemistry, physics, and computer science. We approached scientific problems holistically by bridging the various disciplines to find solutions. This focus on interdisciplinary thinking has been fundamental to my career development. 

Also while still an undergraduate, I spent two summers conducting research at the Broad Institute. It was there that I broadened my experience using statistics and computer science to solve real-world scientific problems. I focused on microbiome research projects and continued to do so for the next decade.

After graduating from Princeton, I worked at Second Genome, a microbiome-based company, and then completed my PhD at the University of Pennsylvania. At UPenn, I worked at the intersection of infectious disease, genomics, computational biology, and statistics to understand human microbial community compositions and their function in healthy and diseased states. 

2. Briefly describe your current role (responsibilities, day-to-day tasks, etc.).

I am currently a Principal Scientist within the Data Science team at Janssen R&D. I lead a team of data scientists to design, develop, and field impactful data science solutions spanning the entire R&D value chain from discovery to late development. We utilize a plethora of advanced analytic tools, including machine learning, deep learning, and natural language processing, to predict disease progression, increase clinical trial efficiencies, identify biomarkers, etc. My role involves providing technical guidance to conceive and implement Data Science solutions to business questions, interfacing with scientific domain experts to ensure alignment, and leading and advising on collaborations with external Data Science companies. Prior to this role, I worked on Data Science projects that supported clinical trial site selection, patient journey analytics, and quality audit monitoring.

3. What skills/attributes are needed for a candidate to excel in your function?

We look for team players who are passionate about leveraging data and technology to solve challenging questions. Our goal is to drive healthcare innovation. Accordingly, we are building a diverse team with expertise in different areas, including advanced algorithms, signal processing, statistical modeling, disease biology, and natural language processing. To truly excel in this field, one must be able to effectively communicate technical work to a broad audience and demonstrate a strong ability to bridge technical and scientific concepts to drive projects forward.

4. What do you find most challenging about your current role?

Data is inherently messy; it is without a doubt the most cumbersome part of a data scientist’s job. 

5. What do you know now that you wish you knew earlier in your career journey?

That our passions can and should infuse our careers. Instead of focusing on a job title or a salary, my advice to others is to reach for positions that will challenge you to learn and to grow. Being passionate about your work leads to higher productivity and longevity which, in turn, lead to job fulfillment and greater success

Want to have your function featured? Would you like to be featured to share your career advice? Please contact us!