As Vice President and Global Head of the Clinical Data and Insights (CDI) unit at AstraZeneca, Natalie Fishburne’s role is an integrated approach to clinical data, analysis, insights and risk management across the pharma company’s clinical trials portfolio. is to promote. In an interview at the AstraZeneca India head office in Bengaluru, Fishburne explained how she does it; how data analytics can help develop drugs and bring them to market faster; Importance of CDI Division in India; And how data analytics is helping to improve the efficacy of clinical trials. Edited excerpt:
How big is the CDI globally? And how important is India’s contribution?
We have approximately 500 employees, and an additional 900 through our functional service provider partners. At CDI India (6th global site), we have crossed 100 within a year. India worked in collaboration with Oxford (the Covid vaccine is sold under the brand names Covishield and Vaxjeveria) on several trials.
And we did a lot of data related activities — cleanup, regular data preparation to be presented to regulators. This has enabled us to deliver over 3 billion doses worldwide in 180 countries. We will make further investments in India based on AstraZeneca’s business needs.
What is the strength of CDI India team?
Our India CDI has a strong programming group. It supports us, especially in how we handle data. Also, when I was talking about integration of data management, this group (CDI India) supports us in terms of setting up the database, editing probes and custom tasks so that we have our database set up for production. Yes, and we can start collecting data faster. Thus, we get patient data quickly.
How many women are there in your team?
I am proud to say that we have 42% of the workforce which is women in India. The skill set mirrors that of other employees—programmers, data scientists, data managers, risk-based quality managers, and standard developers. We believe that diversity is our future. And we have people from 22 different states.
At AstraZeneca, you talked about bridging the gap between science and patients. Can you tell us more about this?
In terms of data, I can talk specifically about how we’re doing this in our centralized monitoring space. When we design a study, we look at the risks involved in that study. And we identify any critical data that needs monitoring to ensure its quality. In each study, we will develop a suite of tailored analytics and dashboards that will monitor those critical data points throughout the study. There are predefined flags or triggers if we reach the quality tolerance limit. Over the past eight years of working in this model, we have really developed and honed our analytical abilities, and as a result the quality of our studies has improved. Although some studies will still fail because the drug is not efficacious, they should not fail because your data lacks quality. How is data being used to help develop drugs and bring them to market faster?
Data is the lifeblood of the organization. Our people are hearts. Data is vitally important in any drug you develop, because if you don’t have good data, you don’t have a product. In recent years, we have focused on making our trials more patient-focused and collecting data directly from patients using technology such as digital tools, in a less intrusive manner. Digital presents various opportunities for us at the backend as the amount of data created is exponential when compared to the volume we have collected in the past. This is where the impact of AI (artificial intelligence) is already beginning to affect our daily activities.
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