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Insights from Pharma 2025: Harnessing AI: Revolutionizing drug discovery and early disease detection

At the Pharma 2025 conference in Barcelona, global industry leaders, innovators, and changemakers gathered to explore the evolving landscape of pharmaceuticals and healthcare. Through a series of in-depth interviews with experts from across the sector, Cencora uncovered valuable perspectives on the challenges and opportunities shaping the future, from accelerating access to innovation and enhancing patient-centricity, to harnessing the power of data and digital transformation.

 

These conversations reflect the pulse of an industry in motion, committed to driving smarter, more sustainable healthcare solutions in an increasingly complex world. Whether focused on regulatory evolution, market access, technological breakthroughs, or cross-sector collaboration, each expert offered a unique lens on how pharma is adapting to meet the needs of tomorrow.

Here, we share the key highlights from the conversation between Jörg Schüttrumpf, Chief Scientific Innovation Officer at Grifols, and Poka Cui, Director at Vintura, part of Cencora, on the transformative role of artificial intelligence (AI) in pharmaceuticals.

Understanding the power of AI in Research and Development (R&D)

The integration of AI into the pharmaceutical sector signifies a paradigm shift, particularly in R&D. AI applications now extend across all phases of drug development–from early discovery to market launch. “AI has the potential to accelerate innovation,” Schüttrumpf stated, emphasizing its capacity to uncover insights that were previously unattainable. This capability not only boosts the efficiency of drug discovery but also fosters precision medicine, ensuring that patients receive the most appropriate treatments tailored to their specific needs.

Key applications of AI

  1. Real-world data utilization: Grifols has harnessed an extensive database of over 100 million samples collected from 5 million plasma donors over 10 to 15 years. By integrating this data with real-world evidence, Grifols can identify disease patterns and predict health outcomes. Schüttrumpf shared a notable example ofcollaboration with the Michael J. Fox Foundation, where they are using AI to explore biomarkers that can indicate Parkinson’s disease years before diagnosis.1
  2. Precision medicine: AI empowers researchers to detect disease markers at earlier stages, shifting the focus from treatment to prevention. Schüttrumpf noted that understanding these biomarkers facilitates the development of targeted therapies capable of altering disease trajectories, ultimately improving patient outcomes. “If you can detect so early, you can really change the course of the disease over the lifetime,” he explained, highlighting a critical advancement in the pursuit of precision medicine.
  3. Optimizing clinical trials: The integration of AI in clinical trials aids in identifying the right patient populations and optimizing trial designs. Schüttrumpf explained how real-world data can inform inclusion and exclusion criteria, ensuring that clinical trials are more effective and aligned with patient needs.

Challenges and considerations

Despite the promising applications of AI, several challenges persist in its implementation:

  1. Data privacy and integration: The need for robust data governance is paramount. Schüttrumpf pointed out the importance of anonymizing patient data while ensuring that the integration of various data sources does not compromise privacy. He noted that navigating data privacy remains a significant challenge for the industry as a whole.
  2. Understanding AI algorithms: The complexity of AI technology can make it a "black box" for many organizations. Schüttrumpf emphasized the need for transparency in AI algorithms to avoid biases and ensure accurate outcomes.
  3. Collaboration across the ecosystem: Schüttrumpf underscored the necessity for collaboration among pharmaceutical companies, regulatory bodies, and other stakeholders to fully leverage AI's capabilities. “It’s crucial that we reach out, partner with private and public organizations”, he added, highlighting the importance of collective effort.

Future directions in AI and pharma

Looking ahead, both speakers conveyed optimism regarding AI’s potential to transform drug discovery and enhance patient care. Schüttrumpf highlighted the ability to derive deep insights from large datasets, stating, “That’s really a new superpower.” As companies like Grifols continue to integrate AI into their strategies, the focus will be on building the infrastructure necessary to support the ongoing evolution of R&D processes.

The pharmaceutical landscape is rapidly being reshaped by AI, offering vast opportunities for improving drug discovery and disease detection. By embracing AI technologies and fostering collaboration across the industry, stakeholders can drive innovation and significantly enhance patient outcomes. This discussion underscored a collective commitment to leveraging AI in the pursuit of smarter, more effective healthcare solutions.

Watch the full conversation

Watch the insightful discussion between Jörg Schüttrumpf and Poka Cui to gain a deeper understanding of how AI is transforming the pharmaceutical industry and what it means for the future of healthcare. Discover the opportunities and challenges that lie ahead as we navigate this exciting landscape.

 

The contents of this piece contain marketing statements and do not include legal advice.

Source:
1: https://www.grifols.com/en/view-news/-/news/grifols-pioneers-high-tech-analysis-of-plasma-bank-to-detect-early-signs-of-parkinson-s-disease

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