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Exclusive interviews revealed that digital transformation, data integrity protocols, and a regionalized supply chain are crucial strategies for optimizing drug development and manufacturing efficiency.
CPHI Frankfurt 2025 highlighted a pharmaceutical industry in flux, navigating the rapid acceleration of artificial intelligence (AI) integration, profound shifts in global supply chain management, and the imperative for sustained innovation in both formulation and manufacturing processes.
Pharmaceutical Technology® Group spoke with more than a dozen key opinion leaders as part of its coverage of the three-day annual conference. Here are the top 10 questions we asked—or perhaps more accurately, the top 10 responses we received.
Toni Manzano, PhD, co-founder and chief scientific officer at Aizon, said the main barrier is the availability of high-quality data, as effective AI models require robust digital systems capable of collecting and creating a consistent data foundation.
Eva-Maria Hempe, head of Healthcare & Life Sciences, NVIDIA, said adoption is primarily hampered by organizational issues like silos, legacy information technology systems, and fragmented AI strategies, compounded by resource scarcity such as insufficient graphics processing unit computing resources.
According to J.D. Mowery, president of Bora Pharmaceuticals, organizations are pivoting toward localized supply chains to mitigate geopolitical risks and operational constraints, often executing clinical trials and manufacturing within the region of operation.
Significant barriers persist for implementation, said Nigel Langley, global technical director of Life Sciences at gChem, despite the need for novel excipients to match complex drug modalities, requiring closer collaboration between pharmaceutical companies and excipient suppliers.
Manzano feels that organizations must ensure data quality by establishing specific roles, such as a chief data officer, and embed technical staff savvy in digital solutions to raise the overall skill set of the organization.
Again, Manzano cautioned that regulatory guidance is emerging quickly, centered on a risk assessment approach that evaluates how the AI model impacts the final patient based on drug quality, safety, and efficiency.
Hempe said the largest opportunities lie in establishing the "lab in the loop" by automating wet lab processes to generate high-quality data that feed models, accelerating the R&D process by predicting the next optimal experiments.
As Marina Cañellas, PhD, COO of Zymvol Biomodeling, explained, enzymes serve as highly selective and eco-friendly natural catalysts, enabling chemical reactions to be executed effectively and sustainably compared with traditional chemical catalysis.
Viktoria Enkmann, co-founder and CEO of RNAnalytics, said that current quality control processes, built for high-volume batch manufacturing, fail personalized medicines, which require miniature testing platforms and robust quality checks to ensure safety and effectiveness with precious samples.
The shift is fundamentally driven by patient compliance, Frank Romanski, PhD, vice-president of Strategic Growth & Revenue Management and head of Global Pharma Solutions at Lonza Capsugel, said, as a large percentage of the population dislikes or avoids injectable biologics, spurring technology development to solve formulation challenges for sensitive small peptides and glucagon-like peptide-1 drugs.
Click here for all of our CPHI Frankfurt 2025 coverage.