Barbara Latulippe, Chief Data Officer of Takeda Pharmaceutical Company Limited, speaks with Tracy Gusher, AI, Data and Automation Leader of EY in a video interview about her role, AI preparation data, the three pillars that drive Ai-Faries, and what it means to relate to responsible AI.
Takada is a value-based, R&D-driven global biopharmaceutical company.
Latulippe shares her role as a CDO as exciting as she leads her role as a platform as a service, data management as a service, AI, and senior generations as a service. This role includes everything from intake to data markets and data products. The emergence of Generator AI (Genai) adds a new dimension to this role.
When asked what it means to have AI preparation data, Latulippe states that AI cannot exist without data, and it all starts with a powerful data foundation. To be genai-enabled, having robust data governance is important, and Takada expanded its focus to include analytical governance, she adds.
Furthermore, data quality is paramount and it is necessary to ensure that the right data is available for the right purpose. This includes maintaining contextual and high quality data and implementing processes such as data authentication, whether registered, validated or certified. This supports self-service for business partners and allows you to access the right data at the right time through your organization's data marketplace.
According to Latulippe, being AI ready is a great fundamental to data management. These include understanding of data sources and data collection, particularly optimizing purchases and incoming data with growing unstructured data.
In detail, she says Takada has set up a new division under a team focused on data collection. She says that prioritizing data quality doesn't mean that not all data hold the same value. Adding more, according to Latulippe, Takeda's data quality is aligned by domain, with a total of 21 domains, and the strategy is driven by three strategic pillars.
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Accountability – Ensuring excellent data quality, defining KPIs, maintaining contextual data, authentication, and controlling access.
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Large scale – This is agile and leads to assess whether platform and governance practices can be expanded. The company has introduced new requirements to this pillar, particularly focusing on legal, ethical and compliance considerations for responsible AI.
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Genai for everything – Built on the foundations of good data management practices. Domain accountability allows business leaders to be closely assigned to partners with their data, digital and technology teams. This collaboration ensures that business voice drives domain use.
Of the 21 domains, 5-6 are mastered through a Master Data Management (MDM) environment, while the rest is managed through data quality rules, says Latulippe. Takeda is also developing a large data stewardship matrix, working at regional, local levels and digital teams to identify the data needed for effective governance and related Genai use cases.
Shedding light on what Takeda is doing, Latulippe says the organization is committed to being a leading science-driven, digital and data-focused pharmaceutical company. To place patients at all the cores it does, domain strategies focus on healthcare providers, patients, suppliers, products and brands to ensure engagement in a regulated environment.
Takada's goal is to provide more rapid life-saving therapy to patients and target patients more effectively during clinical trials. One of the organization's biggest challenges is identifying and registering suitable patients for these trials and monitoring them throughout the patient pathway. Accurate data combined with Genai accelerates this process, allowing the company to reach patients faster and provide the critical care they need.
Emphasizing the connection between data and responsible AI, Latulippe is the first to share about achieving great success with a responsible AI framework that is widely accessible across Takeda. This approach includes a robust data governance structure led by the Global Data Council, which oversees all aspects of data.
To complement this, Takada established the AI and Genai steering committee, consisting of representatives from the entire organization. The committee will serve as the governing body of AI and Genai initiatives, with executive-level decisions being made to ensure the responsible implementation of AI and Genai.
Latulippe mentions treating Genai and treating them as an extension of traditional AI and machine learning rather than separating them. The expansion of governance is important as it has brought many new dimensions, such as ethical use and ensuring equitable data sets. She also mentions the development of a data market that serves as a central repository for the Genai and Analytics models, including expanding the capabilities of the Vector Market, API Marketplace, and Agents and Prompts.
Integrating traditional data with Genai governance enhances the data lineage that has the right metadata and monitors it through a responsible AI framework. She mentions ongoing ML and LLMOPS programs for continuous monitoring and requires sign-off from the relevant groups to ensure that the algorithm is responsible.
Many current algorithms focus on improving internal productivity, and Takeda has developed a classification system that determines the appropriate level of governance required for models before they enter production.
Additionally, Latulippe mentions launching an internal collaboration platform called Takeda.ai, featuring direct access to agents and prompt libraries, learning pathways and responsible AI frameworks. She adds that a complementary platform, Takeda.Data, is being developed for the data community.
Additionally, Latulippe says that as businesses focus on AI optimization, it is important to establish AI governance early in the process and build a robust data foundation. She says that this approach had a major impact on Takeda's efforts and allowed collaboration across the company. Increased data and AI flow is an important aspect of this journey.
In conclusion, Latulippe shares that the company has started with a user group of 1,000 people and is currently deploying its entire company. The initiative also highlights its genai use cases, promoting self-service discovery.
CDO Magazine is grateful to Barbara Latulippe for sharing her insights with our global community.
