Could you introduce us to SAP's operations in the life sciences sector?
At SAP, I lead the Life Sciences and Healthcare Industry Business Unit, focusing on solution management. My role involves understanding customers’ needs collaborating with product development teams to create next-generation products that meet those needs. These products are then introduced to the market through our regional sales channels. Our goal is to keep pace with the dynamically changing business models in the regulated life sciences industry. In this consumer sector, our customers range from BioPharma and medical device manufacturers, hospital providers, end consumers like patients to wholesalers, retail pharmacies, and healthcare professionals. We prioritize delivering solutions that meet the needs of both customers and suppliers, including contract manufacturers and contract research organizations (CxO) companies.
How is AI impacting the life sciences industry?
AI's role in the life sciences industry, a heavily regulated field, is multifaceted. It is increasingly used in drug discovery, quality control, and regulatory submissions, enhancing outcomes by managing both structured and unstructured data. AI helps in understanding large volumes of data models and responding to complex queries, thus improving the user experience with simplified input. For instance, AI is critical in managing real-world evidence, medical imaging data, and supporting big data from structured and unstructured sources relevant for regulatory filings. In process management, AI plays a pivotal role in ERP systems, assisting in supply chain, procurement, manufacturing and quality control. A prime example is how AI aids in demand forecasting in biopharma, integrating various data points like time series forecasting inputs, buffer stock, historic consumption, dropout and enrollment rates to optimize supply chains. However, given the regulated nature of the industry, issues like data privacy and cybersecurity are paramount. SAP Business AI is built into our core business process, but we do continue to work with partners to explore new AI applications, involving external algorithms from different sources. This collaboration is driving innovation in the life sciences.
What are SAP's strategies for dealing with AI challenges in the life sciences?
SAP's approach to AI in the life sciences industry involves adhering to an ethical AI framework and capturing relevant data to improve business processes. We constantly evolve our analytics and architecture through strategic acquisitions. Our flagship product, S/4HANA, and our industry cloud offer innovative solutions for clinical supplies, cell and gene therapies, and batch release in the quality assurance area. We engage with customers through events like roundtables and workgroups, allowing them to help us prioritize investment. This collaborative process ensures that our development aligns with customer needs. SAP publicly shares these developments, demonstrating our commitment to transparency and customer collaboration in advancing AI applications in life sciences.
How important is collaboration between technology companies and the life sciences sector in saving lives?
Collaboration between technology companies and the life sciences sector is a crucial element in saving lives, as evidenced during the COVID-19 pandemic. SAP played a significant role in vaccine distribution, providing visibility and process support to manufacturers.
We facilitated sourcing of vaccine ingredients and planned manufacturing and distribution to meet government orders. Through partnerships with companies like Qualtrics, we also gathered real-world data on customer experience and satisfaction. Our tools helped manage inventory and track and trace individual vaccine vials, ensuring efficient delivery to pharmacies and healthcare facilities. This collaboration exemplifies how technology can support life sciences, not just in commercial supply chain and clinical trials, but in essential infrastructure and operations, contributing to saving lives globally.
Could you give an overview of SAP's role in the life sciences sector and highlight any significant changes in the past year?
In the life sciences industry at SAP, we have traditionally focused on supply chain management, encompassing planning, procurement, and manufacturing. However, recent trends, particularly in biologics, are shifting this focus. Unlike small molecule pharmaceuticals, biologics demand a more personalized and lean supply chain, often tailored to individual patients. This necessitates a shift from a 'make-to-stock' to a 'make-to-order' model. Our tools are now designed to cater to this complexity, ensuring precise monitoring of individual batches in the supply chain. Another emerging challenge is the integration of development operations with commercial manufacturing, a critical part of product lifecycle management. Addressing these changes requires SAP to provide technology tools with our partner ecosystem that are ahead of the curve.
What potential challenges do you foresee for SAP in the life sciences sector in the next 5-10 years, particularly regarding technology integration?
One of the primary challenges lies in managing patient data as personalized medicine becomes more prevalent. This extends beyond pharmaceuticals to include areas like health and wellness, demanding a deep understanding of patient and consumer data. Personalization in treatment necessitates integrating patient-specific information, such as weight or cell count, into manufacturing systems. However, this is complicated by varying regulations across countries. Integration between hospital information systems and manufacturers' systems is essential for a smoother data exchange to reduce cycle time and cost. Another aspect is sustainability, where parameters like carbon footprint and resource consumption need to be meticulously tracked and reported. SAP's role is to facilitate these processes, working closely with wholesalers, retail pharmacies, and hospital systems to ensure real-time data availability, thereby improving efficiency and outcomes. This complex landscape requires SAP to constantly evolve, addressing new challenges and breaking boundaries in the industry to address changing business models.
