‘AI usage in Indian pharma still at a nascent stage’: Ganesh Ramachandran

‘AI usage in Indian pharma still at a nascent stage’: Ganesh Ramachandran
4 Jan, 2022

The pharmaceutical industry has witnessed myriad changes over the last couple of years, be it in demand variation, input pricing pressure or the need to accelerate new product pipelines. However, Ganesh Ramachandran, Global Chief Information Officer (CIO), Alkem Laboratories, said the industry is still at a nascent stage when it comes to implementing advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT) and blockchain. In an interview, Ramachandran discussed the role of emerging tech in the pharma sector, and the way forward in terms of collecting the right data while allaying privacy concerns. Edited excerpts:

What kind of emerging technologies are being deployed in the pharmaceutical industry today? 

If we refer to the pharmaceutical industry, one sees many newer age technologies being adopted across the value chain globally, with research and development (R&D) at one end and front office at the other, though Indian pharma majors are rapidly looking to scale adoption. A lot of tracking on the whole R&D pipeline is ensuing to reduce the product launch time. Technology is also being leveraged to ensure there are fewer rejections and give the right kind of requirements from an entire project management perspective across different stages of filing.

Which are the places where tech such as AI, blockchain or IoT are implemented?

Multinationals overseas use a substantial amount of AI, while in the Indian context it is still at a nascent stage. In the global context, they are in a phase of discovering use cases in various business operations, in various current manual processes to eradicate manual intervention and make the processes more accurate. 

In India, a lot of focus has gone on developing the right data models and ensuring data quality over the last few years, which is a key requirement to drive the usage of AI. Cost-sensitivity needs to be assessed as well, with labour costs not being as high as what one sees overseas. Having said that, one is beginning to see business teams looking to leverage the power of AI and machine learning (ML), though these are more in a proof of concept (PoC) stage currently.

Quality is an area where immense tech is being used. While blockchain is being used for transparent data sharing between contractors or supply manufacturers, the adoption is just gaining momentum in India. I see blockchain use cases emerging between pharma majors and contract manufacturers to ensure that the quality levels are fine from inputs through to the finished product.

We have seen some major pharmaceutical companies being breached lately, how is the security issue addressed?

Although we talk about the IoT as one of the main pillars of industry 4.0, to link the information technology (IT) and operational technology (OT) is being seen as a potential area for a security breach. Some of these concerns are holding back organizations from going full swing on IoT implementation. One thing can be the IoT implementation for local areas, but again, it does not justify the kind of investments required. Thus, many organizations which had started out the implementation of industry 4.0 prior to the lockdowns have slowed down due to concerns around security, especially during the pandemic. Many of the organizations have looked at strengthening their cyber security posture, we are seeing zero trust, AI/ML coming into play, along with analytics for automated responses to threats.

What do you think is the way forward for pharma companies?

Unlike in consumer-packaged goods (CPG), where manufacturers have a good idea of the demand generated at retail, movement of stock at the stockists and consumer behaviour, pharmaceutical manufacturers in India have a limited view of the stockists, chemists, doctors and patients’ needs and behaviours. To add to this a pharmaceutical organization typically has multiple divisions within an organization, with each division addressing a particular therapy. 

The challenge comes when multiple divisions address the same doctor, leading to the doctor being duplicated at an organization level. This makes it challenging to get accurate details of the doctor in the customer relationship management (CRM) platform, and to ensure that organizations can personalize communication that would be relevant for doctors.

Pharma manufacturers are also looking to gain insights from doctors on whether the product is solving the requirements that doctors have or how products are faring against competitors, or which are the products that are not moving, to ensure availability of the right stocks at the right place at the right time. This is a classical big data problem where you have a bundle of data coming from all sources.

The way forward is to start by collecting the right data, keeping in mind privacy concerns and pooling in the different data sources.


Moumita Deb Choudhury