Hello everyone. Welcome to my session on today's presentation. I'm gonna be talking about API architecture, and the goal of this presentation is to show you how API driven integration architecture, help pharmaceutical operations. My name is ard. I have a nine years of experience leading enterprise integration initiative, currently working as a principal integration engineer. At Moderna. I work into life science, pharmaceuticals, manufacturing, and supply chain industries. Before we deep dive into the technical architecture, let's first understand how mRNA vaccines are getting developed. It all starts by identifying the virus and decoding. Its RNA. Think of it as a long instruction manual made up of four letters, A, CGT. It is adenine, uracil, ging, n cytosine. Once they identify the virus sequence. The next step is the mRNA design scientist creates mRNA instruction that teach our body, which can fight through the virus so that we get immunized after that vaccine goes into the clinical trial. This clinical trial vaccine get tested with diver population and once the vaccine is proven and safe and effective, they start manufacturing production scales up quickly and agencies like FDA checks everything before approving it. And the last and important steps is supply chain and distributions. Special cold storage and transportation systems are required to deliver vaccines safely to hospital clinics and around the world. So this is just a high level overview, but in general, vaccine development goes through many phases across the enterprise, and it is very important for pharmaceutical industry to stay connected across enterprise, to track the progress and move forward into the process. So now let's take a look at the digital transformation journey we had gone through to support the vaccine development and the distribution. The problem is pharmaceutical industries uses so many different software and tool across their different department to perform their job because there is no one software available, which does everything. Also pharmaceutical industries has a old systems manual processes and lots of disconnected data. They slow down everything to fix it. We develop API integration with over 300 and integration to connect 110 plus systems across the enterprise, internally and externally. By developing those API, it helped us broke down silos and build a connected digital setup across the enterprise. This led us to acceleration Information becomes available across all the systems, reducing delays, and helping team move faster. Finally, we focus on the continuous improvement using the real time data. We keep adjusting, improving how we work, staying flexible and ready for future need. This wasn't just a small upgrade, it's completely changed how operations work, making everything faster and more connected. So when it. When it comes to the connecting different system, there is no one size fits all solution. Different situation needs different API pattern. So first is rest, API, rest API is a simple, secure way for such systems to share information in real time. Then we have a pub sub model. Pops up is a event driven updates, send information as soon as something happens. This pattern generally helps in a real time data integration, especially manufacturing use cases. The E and third one is E-T-L-E-T-L is extract, transfer and load this. Pattern of the integration used for the batch processing. Whenever the huge data load is required and required to sync two different systems, it generally goes through ETL processes such as use case like financial and clinical data. Processing that requires ETL processes. And finally, the hybrid approach, which is API plus file based integration. So this approach requires when, or we use this this approach when the partner can't fully use their API or they are not capable of integrating with API. We combine. With the file transfer integration, which is a very traditional way of doing Integra integrations, each method help create a strong and flexible digital system. So how it help, so integration layer is a enabler. Think of it as a enabler of the business and across the enterprise. It goes through different. Saxons and integration helps as a enabler to perform all those actions. API integration layer becomes enabler into each of our vaccine manufacturing and distribution journey. Because of integration, we had unified data connectivity across enterprise. Connected data from research, manufacturing supply chain so that information can flow smoothly. This helps collaborate with teams, partners, and regulators. It allowed them to work together in real time, making better decision and faster decision. It allow automated audit and easier to meet regulations. And lastly, innovative workflow automation. With AI and smart processes, we boost productivity and speed up innovations. The integration layer isn't just about the connection. It's help. It's about helping companies move faster, adapt easier, and innovate better. So now let's talk about the manufacturing transformation we had gone through when we implemented this API integration architecture across the enterprise. In previous and legacy setup, manufacturing was manual and it was disconnected. Data entries between system were causing lots of delays and it also having a human errors because it was manually entering into different system it was difficult to track anything because each systems are not integrated or are not in a sync with each other. So it is hard to scale operation when demand grows. So now with the digital manufacturing excellence, how we imple after the implementation of the API architecture, now it is very, all the systems are fully integrated and connected with each other. It eliminate all the paper based workflows as well in. Event driven architecture also helps us decision making and compliance build right into the system, making audit tracking and validation much easier. This upgrade isn't just about moving faster. It is about building stronger, smarter, and future proof manufacturing. So whenever they can require to scale, they can scale with this architecture, or they can scale down with this architecture. Because we develop API integration talk with each other systems. So it reduce the human effort to to enter any kind of data manually into systems. Another use case we have seen where we got a lot of boost using this API architecture is clinical trial. So think of it clinical trial happen across the globe. Other different horizons and CROs perform generally this kind of clinical trial. So it is very important to integrate with the CROs systems on a real time basis. Otherwise we don't get the data on a real time and then it. Cause lots of additional delays with having this architecture implementation with directly with CROs externally and to our internal system. It cut delays by 30 to 40%. It also help. Make decision faster so that scientists can look at the data of whatever the clinical trial data comes from, the CROs system. They can make the decision whether this vaccine is working effectively, or what are, what kind of doses required to do, or what kind of diverse population required to get into clinical trials. So those kind of decision they can make faster. And it also help reduce 14 days under four days and be because of this all integration architecture. It maintain the GXP compliance. Together, this change make clinical trial faster, cheaper, and safer. Because all it's going is through the same integration architecture. So with all these patterns and integration, we have seen very huge work over saving because all the manual process are gone First. It was required to do manual data entry, which was eliminated, and we have seen 90,000 hours a year cutting a year of saving and it reduced error by 78%. Then automated workflow with 24 smart automation, which we save an extra 35 minute on every protocol which get executed. And this led to strategic relocation. So with saving of 90,000 hours of manual work hour, scientists can now focus on the research and new ideas instead of paperwork. In the end, enhanced productivity means researchers now spend 40% more time doing important scientific work. Saving our isn't just about being faster. It's about letting people focus on what really matters. This API architecture we develop on the cloud native. Everything is AWS We scale up using molecule cluster. We set up all the molecule cluster and EC2 instance to support GXP and enterprise workload. We use mod modular architecture with reusable component building API and template that speed up deployment by file times faster. And we made sure that even with the all the securities founds found essence are strong separating GXP and non GXP and SOX related workflows separately validating compliance with 21. CFR part 11 and securing everything through Okta 2.0. Sorry, OO 2.0, Okta and web application firewall. So security we take consider as a important part of our architecture because. To stay compliant. And in the regulated industry, it is very important to stay compliant and secure. This setup helped us stay fast, secure, and compliant as we scale operation globally. So with this final takeaways are speed and efficiency. API helpless. Cut time to market by 60% and reduce clinical trial by 38%. Reduce clinical trials cycle by 38%. Quality and safety. Automated validation, improved accuracy by 99% and cut compliance issues by 94%. Patient-centric innovation, AI power systems and automation feed up over 90,000 hours a year for research breakthrough. And the next steps is build secure modular cloud native systems to drive innovation and transform pharmaceutical operations. At the end of the day, it's not just about better systems, it's about building a faster, safer, and more patient centric. Systems for the future of healthcare. Thank you everyone for listening to me, and if you have any questions related to this architecture, API pattern or anything, please feel free to reach out to me on a LinkedIn. You can find me by typing my name. And, one second. Thank you very much. I looking forward to hear back from you. Thank you.