Shiva Padmanabhan, Managing Director of AstraZeneca India Pvt Ltd. Ltd. (AZIPL), runs the bio-pharmaceutical company’s Global Capability Center (GCC), which was rebranded this April as the Global Innovation and Technology Center (GITC). In an interview, Padmanabhan shared the progress made by the unit which has a workforce of around 3,000; How this has helped AstraZeneca develop capabilities to handle vaccine development manifold and how AzipL works with the Clinical Data and Insights (CDI) team to develop enterprise data products. Edited excerpt:
How has your GCC entity role evolved over the years?
Prior to 2014, we (AstraZeneca) relied heavily on external partners to meet our IT commitments, and there was an emerging need to step up the quality of service for the business. It was then that the importance of insourcing our IT capability became very clear. Technology has now become an integral part of the way we work as a company. After successful IT insourcing in 2014, the unit was soon expanded by bringing in additional service lines such as Global Business Services in 2017, R&D (research and development) services in 2018, and now, we are engaged in core services such as clinical data. areas as well. Management which was established at the end of last year. Today, India is one of the more than 100 markets we serve as GCC for AstraZeneca.
How did your unit help in the development of the COVID-19 vaccine?
We are proud of the role we have been able to play in the development of this vaccine (Oxford-AstraZeneca COVID-19 Vaccine). A typical vaccine development timeline is 5-6 years but it was developed within a year. It tackled a number of technical challenges such as ensuring the scalability of the systems used to manage every element of the value chain – from clinical testing, procurement, supply chain management and commercial operations. GITC has integrated dozens of additional supply chain partners, installing electronic connectivity, stress testing and revising our adverse event (e.g., allergy) reporting systems to handle increasingly high volumes, new technology-enabled processes for expiration dates. Played a very important role in designing and implementing the Management, etc. The co-location of global commercial operations and global IT and R&D services in India enabled rapid acceleration of the project.
Given that you are a pharma and life sciences company, how are you using visualization tools and techniques such as augmented reality (AR) and virtual reality (VR)?
We use many technologies such as Extended Reality (XR), which includes AR and VR. These have immense potential to transform the entire life science industry. We are seeing many applications. For example, visualizing how a particular drug interacts inside the body, and how it targets certain cell types, etc. In addition, patients attending clinical trials can get a virtual experience of what to expect at the trial site. By wearing a pair of VR glasses, they can see what each step of participating in a trial looks like such as the test site set-up, the tests to be performed, the actual administration of the drug as well as the ongoing check-in. This makes it easier for them to participate in the trial and it is really a patient-centred way of using this technology.
In manufacturing, we are seeing huge applications in the way we train our operators – with VR and even with haptic gloves. So, before operating the machine, they can imagine as well as feel everything. Physicians can now visualize how the drug works inside the body and get an idea of the symptoms and side effects. So, instead of a medical representative just handing out flyers, you can actually give physicians a full experience of how this product works inside the human body and what the potential side effects might look like.
How does AZIPL work with your CDI division?
That team (CDI) is extremely skilled. He has vast experience in the domain using artificial intelligence (AI) and machine learning to extract actionable insights from different data sources.
We combine this with the deep technology expertise and data engineering capability we have built up. On the IT side, today we are very fast at building data products. Earlier, when we encountered a problem, we would try to solve it by going into the data input requirement and building a data warehouse or data lake. But today, we have enterprise data products that exist as building blocks, and we are able to bring them together using application programming interfaces (APIs) to solve a specific business question or problem.
We’re also working on data mesh technologies, which basically bring all of these data products together, allowing us to run data science experiments quickly—modeling and asking questions and the right types of questions for those questions. Trying to gain insight.
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