Code to Cure: Crafting the Future of Life Sciences With AI Use Cases

Use Cases & Projects, Scaling AI Marie Merveilleux du Vignaux

The landscape of life sciences is rapidly evolving, driven by technological shifts and the digitalization wave. At the forefront of this transformation is the integration of advanced analytics and AI. This blog features insights from the Dataiku Life Sciences Use Case Library to help life sciences organizations understand how to harness the power of these technologies with the help of Dataiku.

Accelerating the Transformation of Life Sciences With Data

Technology shifts tied with digitalization in recent years are driving unparalleled transformation in the life sciences industry. More than any other industry, we are seeing leaders in biotech and pharma investing in AI, including Generative AI, to improve strategic business objective outcomes. Moreover, we see these transformations not only refining their key business objectives but redefining new business models, such as investments in digital health. 

And there is more to it than just AI. There is collective ambition and imperative to adopt streamlined data-driven approaches that include broad data democratization to enable self-service analytics, particularly in established global organizations that often carry burdens of legacy systems, redundancy and historical silos in people, processes, and data.  

→ Read the Full Use Case Library Here 

A Use Case Library: A Glimpse Into the Future

In this library, you will find a representative sample of use cases, bound to expand and grow as novel solutions to common problems in the industry are found. From optimal reach and engagement strategies with healthcare professionals and patients, to speeding discovery and development of new therapeutics, there are dozens of ways that companies can harness AI, data, and analytics to drive value at scale — all while maximizing corporate efficiency and patient care. 

Continue reading for a sneak peak of some of the solutions and applications that have helped life sciences companies get ahead in their data game, from transversal and corporate data strategies to data visibility, accessibility, reuse, and more.

Accelerating Discovery and Development: Drug Repurposing Knowledge Graph

The decline in R&D returns has driven the biopharmaceutical industry to explore novel approaches, such as drug repurposing. Dataiku’s drug repurposing knowledge graph solution automates the ingestion of key public data sources, cleans and prepares input data, and facilitates deep dives into complex relationships between drugs using graph analytics. This accelerates development times, reduces costs, and taps into new revenue sources.

Optimizing Clinical Research and Operations: Predict Clinical Site Risks and Impacts With NLP

A leading biopharmaceutical company utilized Dataiku to predict risks to its global operations by creating custom risk identification models with NLP. By analyzing global news cycles and other data sources, the Global Security Operation Center could issue early alerts, mitigating potential disruptions in the supply chain and clinical operations.

doctors pointing to a computer screen

Digital Manufacturing and Resilient Supply Chains: Predictive Process Modeling

In pharmaceutical manufacturing, inefficiencies in batch processes cost billions annually. Dataiku's batch performance optimization solution empowers data teams to dissect vast volumes of production process data, providing actionable insights for technicians and engineers. The solution enhances overall equipment effectiveness and accelerates the move from reaction to anticipation in batch manufacturing.

Improving Data Collation Processes: Inventory Visibility

Effective inventory management is crucial in healthcare, influencing costs and patient care. Dataiku helps address the challenge of manual efforts in sending manufacturing quality control reports by automating the reporting process. This not only saves time but also enhances the ability to access, format, and visualize data.

Self-Healing Supply Chains: AI-Driven Drug Stocking and Transportation

By leveraging historical drug usage data, patient visit data, and transportation route data, life sciences companies can optimize drug inventory management. Dataiku's AI models provide accurate inventory and transportation predictions, centralization through a dashboard, automated alerts before drug expiration, and optimal route identification for transportation.

Transforming Life Sciences with Dataiku

As we navigate the intricate landscape of life sciences, the integration of AI and advanced data analytics stands as a beacon of innovation. Dataiku's modern orchestration platform acts as a catalyst, breaking down silos and providing a central, governed hub for data collaboration. From drug discovery to supply chain optimization, this life sciences use case library illustrates how organizations trust Dataiku to tackle the industry's hardest challenges, ultimately speeding up the delivery of life-saving or life-changing therapies to the world.

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