Immunology to neuroscience: Data science across disease areas at J&J

From models that predict disease progression in oncology to breakthroughs in neuroscience, immunology and clinical operations, discover how data scientist Francisco Talamas, Ph.D., is taking on complex healthcare challenges with the potential to positively impact the lives of patients around the globe.

Intersectional data science: Implications for immunology and neuroscience

New approaches to patient identification for diseases. Research into risk factors in disease development. Data-driven insights to help get essential medicines to the patients who need them faster. Francisco is pretty busy these days.

Indeed, to get a sense of the scope of Francisco’s impact, consider that his two priority disease areas—immunology and neuroscience—are usually thought of a two distinct fields, each with its own dedicated journals and bodies of research. 

But that's part of the promise of data science—or more precisely, what it makes possible, as Francisco explained. 

"We're trying to harness this huge amount of data to answer some very narrow, very specific questions, but those answers can often be applied across any number of therapeutic areas or indications. Data science is what allows our teams to aggregate and analyze unprecedented volumes of data. We're using data science to answer questions that would have been unanswerable in the past."

For example, Francisco, in collaboration with clinical operations teams at J&J, recently helped develop an algorithm that predicts the performance of different clinical sites, with the goal of answering an all-important question: Which site or sites will help us enroll the most patients—and complete the trial—the fastest?

It's a question with massively important implications for our patients—and perhaps one of the reasons Francisco feels data science is uniquely positioned to positively impact people's lives in the context of healthcare.

Solve one complex problem, then move on to another

Another example might help drive that point home: Right now, Francisco is also working on data science applications that can be used to evaluate the effectiveness in clinical trials of "comparators"—or placebo groups whose outcomes are compared against those of the treated group. By leveraging statistical methods and real-world data, he aims to create similar groups to those that received the placebo, which in turn can enhance and help confirm the results observed in clinical trials.

"We can mimic the inclusion and exclusion criteria based on the protocol created for the clinical trial, and measure the outcomes of those patients by using real-world data and applying data science," Fransisco explained. 

Meanwhile, he's also working on what he calls “a novel approach in the context of neuroscience.” The idea, in a nutshell, is to use natural language processing to parse data extracted from the electronic health records of participants in clinical trials. Doing so would enable his team to create much more complete profiles of patients, therefore understand the health outcomes of participants in those trials in a more nuanced way.

Novelty aside, Francisco thinks such an approach could help us get more clinical trials across the goal line going forward—and he knows that would make a world of difference in the lives of patients everywhere.

Francisco's path to J&J's data science community

Born in Mexico, Francisco received his Ph.D. in chemistry from the University of Alberta in Canada, went on to do post-doctoral work in organic chemistry at Harvard University and launched a successful career in the pharmaceutical industry before coming to Johnson & Johnson. What ultimately prompted the move?

Six years into his tenure, Francisco has a pretty clear idea.

"I was really impressed by the opportunities to make an impact here," he said. "From everything that I have seen, this company is unique in the amount of attention we pay to our patients, our customers and our communities. All of that ties back to Our Credo."

Also unique, in Francisco's view, is the way that his team at Janssen approaches the drug development process.

"We allow people to try out new things and experiment with their ideas," he said. "We never put in constraints that limit options or opportunities. There's no one 'right' way of doing things with data science at Johnson & Johnson—and I think that reflects the diversity of Johnson & Johnson as a whole."

Francisco added, "We're using data science to answer questions that would have been unanswerable in the past."

Join our community of data scientists

Ready to collaborate with the best and the brightest in your field? To bring to life bold healthcare breakthroughs? To take on complex challenges while being challenged to grow?

If so, check out all of the data science roles we're hiring for across Johnson & Johnson. Plus, sign up for our Global Talent Hub. It's a great way to stay in touch, learn more about our data science community and get updates about jobs that might interest you in the future.