PCI High Potent Manufacturing
LB Bohle – 10.06.2025
Temax_Krautz

Current Edition

Current Edition

Subsection - CDMO

Examining how innovative technologies, integrated manufacturing approaches and AI are shaping manufacturing.

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Subsection - Injectables

Exploring advances in injectable drug delivery and sterile manufacturing, designed to improve patient-centric delivery.

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Subsection - Neurodegenerative Diseases

Exploring emerging approaches to neurodegenerative disease research and treatment.

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Subsection - Nasal & Pulmonary

Highlighting how advances in nasal and pulmonary drug delivery, formulation, devices and analytics are enabling more complex therapies.

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CPHI 2027
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Lifecore Biomedical

Overcoming AI Anxiety in Medical Affairs: Strategies for Successful Adoption

Artificial intelligence (AI) is becoming increasingly integrated across the pharmaceutical industry and promises to revolutionise many aspects of medical affairs. From enhancing drug development and clinical trial design to streamlining real-world evidence generation and optimising patient engagement strategies, AI’s potential benefits are undeniable.

Despite this growing enthusiasm, AI anxiety and apprehension over implementing technologies have swept through the medical affairs community. A lack of understanding about AI technologies, data privacy and security concerns and ethical considerations have all contributed to a hesitancy towards embracing AI fully.

In this article, Alice DI Giulio, AI Frontier PR lead at Envision Pharma Group, explores the causes of AI anxiety in the pharmaceutical industry and medical affairs. She addresses the primary sources of concern, debunks common misconceptions and provides strategic solutions for successful AI adoption.

Demonstrating value:

Establishing a return on investment (ROI) and demonstrating the tangible benefits of AI helps to justify investments. Medical affairs teams can demonstrate value by showcasing how AI projects translate into measurable outcomes that align with organisational goals.

Deployment and scaling:

Deploying and scaling AI technologies is a complex process. By investing in technical infrastructure and operational experience organisations can overcome challenges and fully integrate AI into existing systems.

Trust in AI models:

Trust in AI can be fostered with transparency and explainability of models. This involves ensuring accuracy and reliability using rigorous validation processes.

Ethics, fairness and bias:

As biases can arise in AI models, ensuring the ethical use of data and maintaining trust and compliance with regulations helps with implementing AI fairly.

AI integration:

Integrating AI systems with existing technologies and workflows, while also managing organisational change, leads to successful AI integration.

Perceived vs. actual benefits:

The gap between expected and realised benefits can be bridged by setting realistic expectations and focusing on achievable outcomes. Employee education and training are key to establishing realistic expectations and maximising AI benefits.

As well as the barriers that the pharmaceutical industry faces, medical affairs professionals face additional challenges when dealing with AI-generated insights, which can lead to increased AI anxiety.

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