Jitendra Mishra, SVP, VP-CIO, Akums Drugs, and Pharmaceuticals Ltd
Jitendra Mishra, SVP, VP-CIO, Akums Drugs, and Pharmaceuticals Ltd, in an exclusive interview with CIOtechOutlook, shares his views on the challenges the pharma industry overcome to fully leverage smart manufacturing, strategies pharmaceutical companies adopt to upskill their workforce, how smart manufacturing help pharma companies mitigate supply chain disruptions, impactful technologies to ensure the quality of drugs and more. He is a visionary leader with over twenty-five years of diversified experience across the Pharmaceuticals and Clinical Research industry verticals in providing strategic direction to the management on technology and more.
Considering the current context from a couple of years, especially after COVID, we see a lot of digital adoption and buy-in from the management. Digital adoption makes a lot of contributions, from a pharmaceutical context to novel drug discovery to the go-to-customer market. The go-to customer market means that we are going to shorten the lifecycle of medicines to reach the market for patients.
When it comes to personal health care, digital is moving at a very fast pace. There are certain proven use cases in which personalized digital healthcare is vital to the patient's needs. If we look into that, the doctor and patient connect over virtual calls, and the information is exactly required from the patient's perspective on the medicine. There has been a significant change in the overall supply chain, from drug discovery to reaching the patient at the country's last leg and global reach.
We see that digital has played a vital role in this, not only in drug discovery but also in ensuring in-time medicine availability across the value chain. So, that is the power of digital. The authenticity of the medicines that the government and most innovative pharma have already started doing to ensure that safe medicine reaches the patients.
The adoption of smart manufacturing demands a shift in workforce skills towards data analytics and digital proficiency. What strategies should pharmaceutical companies adopt to upskill their workforce for a smart manufacturing future?
In any organization, successful digital transformation requires diligent planning combined with a solid strategy and agility to implement. To develop digital competency and digital literacy across the organization, they want to take advantage of the digital transformation in a complete value chain which is a strategic call. It cannot go on a nut bolt strategy where you digitize some portion and the remaining portion is still maintained on a legacy or a manual way. Digital transformation is a strategic call that ensures right from the inception of any solution to the result and the output. There is a handle, clear-cut plan, strategical plan, and then maturity and change management which is equally important.
So, this is what we call any digital manufacturing in terms of any initiative, for digital manufacturing there has to be a very clear cut very well-signed-off plan where the leadership is equally involved. There's plenty of opportunity to avoid the bind results as we follow the incremental changes. The successful implementation leads to the customer experience. So, customer involvement, the digital experience, and taking the team in confidence are equally important for such large initiatives. If we see that in more depth in this direction, the companies with strong synergies and IT business relationships, must be very much grounded to begin any such digital transformation journey.
Being an IT department so close to the business is very important for any digital success. As information technology has to play a very vital role in that, In that sense, there has to be skill development, which is the theme without skill development, because all such initiatives may not lead to success. Concerning digital manufacturing, a lot of new innovative solutions we see that in the current context, like generative AI, and machine learning, which have become proven use cases, and many organizations are getting the benefit. Currently, there are relevant use cases available, and many organizations are harnessing the benefits of this digital transformation and emerging technology. So, skill development is one of the most important—secondly, change management. Thirdly, the overall C-level engagement on any such digital initiative and the participation from the CXO level to the last person on a shop floor is equally important as they also need to be part of this change because they also need to be participants in their day-to-day activities.
Supply chain is one of the vital areas where firms perform the predictive analysis based on the benchmarking ensuring the just-in-time concept, whereas the medicines or the availability of all the raw material, and packing material in time, is available because a lot of dependencies on third party or global supplier. We have to ensure that all the availability of required medicines that send raw material, packing material, and the transportation system, everything needs to be synced in a way where we can have a very robust and resilient system, not only that perspective, but also looking into that the global economic perspective.
In a current challenging context, if we look into the global perspective, supply chain resiliency is one of the very vital where we have a dependency on global partners. We have to ensure that the proper inventory levels, looking to that the current context of the situation, how we can ensure seamless supplies, not only from the partner level, but also ensuring the proper stock availability to manufacture in time, just-in-time, not having the cost burden and complete supply chain plays a very vital role to ensure delivery to the right time to the right mission. Also, predictive analysis is very important to ensure seamless supplies.
This is very important as how digital initiatives ensure the quality of the product. So, there are a couple of solutions that are running as a proof of concept, ensuring the quality of each batch. So, there are standards that have been predefined. Firms perform Root cause analysis based on the benchmarking of every medicine ensuring with the RPA systems, which has been predefined against the standard and what are the anomalies we are getting in each batch, which is again subject to the measure.
The companies focus on this emerging technology usage for ensuring their product quality, whether it is a laboratory information system, which is connected to the batch manufacturing batches again subject to the RPA systems which analyze against the benchmark and alert wherever wrong. Hence, this is a predictive analysis in terms of using the RPA technology, where analyzing every batch, ensures that all the compliances and good quality are being met against the standard that we defined.
Taking into account the pharmaceutical from the novel drug discovery perspective, the clinical trial which is the highest life cycle, and companies are spending most of the time on that for around 10 to 12 years. So, that's the biggest cycle in any pharmaceutical, and the core focus is how to shorten and go-to-market strategy in terms of reducing the overall life cycle of the novel drug discovery. Machine learning and artificial intelligence play a very vital role and there are very proven use cases where we see that these two technologies are rapidly being developed to reduce the time cycle for any drug discovery and go-to-market strategy.
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