Artificial intelligence (AI) has shifted from experimental projects to a valuable pharmaceutical research and development (R&D) asset. While the pace of adoption varies across the industry, AI is enabling organizations to address inefficiencies, reduce timelines, and improve decision-making at critical drug development stages.
Building on the insights from part 1, which highlighted how companies are adopting AI and rethinking their R&D operational and portfolio strategies, this installment explores how AI is unlocking operational efficiency, addressing persistent challenges, and paving the way for future innovation.
As the industry pushes to accelerate timelines and reduce costs, AI is proving to be a valuable tool for optimizing complex workflows. According to Norstella’s State of the Industry AI Survey, 2024, 57% of respondents identified operational efficiency as a primary benefit of AI adoption, underscoring its impact on streamlining processes and improving decision-making.
One notable improvement identified in the survey is AI’s ability to automate data handling, which increases the “accuracy and speed of access to real-time clinical trials”. By enabling organizations to surface insights derived from high-quality data coming into the Sponsors faster than ever they make timely adjustments to protocols, site strategies, and recruitment efforts, this capability ensures trials remain on track, delivering better outcomes across the R&D pipeline.
“With AI, pharmaceutical companies can automate data handling to increase accuracy and speed of access to real-time clinical trials.”
AI’s influence also extends to safety assessments, with 27% of organizations leveraging it to predict and mitigate risks earlier in the development cycle, according to the survey. By identifying potential safety concerns earlier — such as through evaluating trends and data on products with similar mechanisms of action — organizations can proactively address issues, reducing the risk of delays or failures in later phases. These advancements help streamline the R&D process by enabling better resource allocation and ensuring higher efficiency throughout the pipeline.
Achieving operational efficiency, however, requires more than just technology.
Collaboration between clinical subject matter experts, data science, and regulatory teams is critical to ensuring that AI-driven insights are trusted, actionable, and aligned with organizational goals. When cross-functional teams integrate AI effectively, they create a feedback loop between technology and expertise, amplifying AI’s value and driving meaningful outcomes throughout the R&D pipeline.
While AI’s potential to streamline operations is clear, many organizations face significant hurdles in fully realizing its benefits. 42% of survey respondents cited data integration as the most pressing challenge. Harmonizing disparate datasets – from clinical trials to real-world evidence (RWE) – remains a critical yet complex step in ensuring AI models produce reliable and actionable insights.
Without a solid data foundation, even the most advanced AI systems can fall short of their potential.
Another key challenge is algorithm bias, which can arise from incomplete or unrepresentative datasets. Bias can skew predictions and hinder decision-making, particularly in patient recruitment and protocol design. To address this, companies should prioritize using inclusive datasets and focus on ethical AI frameworks to ensure fairness and transparency. In turn, this will engender equality and trust in the outputs and recommendations.
However, overcoming bias requires more than better data and technical fixes – it requires strategic collaboration across teams and aligning expertise in clinical, regulatory and data science functions. These challenges, while complex, can be addressed through informed strategies and tools that build cohesion across functions – a theme central to Norstella’s work in fostering actionable AI insights.
Future applications of AI are expected to focus on personalized medicine, real-time patient monitoring, and post-market surveillance – all key areas identified in Norstella’s AI survey as transformative opportunities in the coming years.
As discussed in part 1, larger pharmaceutical companies are investing heavily in sophisticated in-house AI capabilities, leveraging their resources to address these complex R&D challenges. Meanwhile, smaller biotech firms are focusing on strategic partnerships, enabling them to access cutting-edge tools without requiring significant infrastructure investments. This dual approach continues to shape the trajectory of AI adoption across the pharmaceutical industry.
The future of AI adoption in pharmaceutical R&D is expected to accelerate. 47% of survey respondents anticipate AI integration in select development programs, while 26% predict full-scale adoption across all programs in the next five years.
Our survey also suggested that AI adoption will demand significant changes in workforce expertise, with 85% of respondents anticipating it will influence workplace requirements.
As AI becomes more embedded in pharmaceutical R&D, its success will depend on organizations’ ability to overcome hurdles like data integration, transparency, and trust, while aligning technology with strategic goals. Achieving seamless AI adoption requires more than just implementing new technologies; it calls for the right strategies, tools, and cross-functional collaboration to drive meaningful transformation across the R&D landscape.
Norstella’s suite of solutions supports this transition by offering access to integrated datasets, actionable analytics, and market intelligence tailored to the complexities of pharmaceutical R&D. By addressing critical issues such as data harmonization and aligning insights across teams, Norstella provides the resources organizations need to optimize workflows and make informed decisions at every stage of the R&D process.
Didn’t catch part 1 of this series? Explore how companies are embracing AI, from building internal capabilities to forging strategic partnerships and laying the groundwork for innovation.
For those seeking further insights into AI strategies and partnerships, platforms like NorstellaLinQ provide a wealth of resources to stay informed about the latest trends and practical approaches to maximizing AI’s potential.
To learn more, download Norstella’s State of the Industry AI survey, 2024 infographic and discover key insights shaping the future of AI adoption.
Managing Editor, Custom Content | Norstella
General Manager, Clinical & Regulatory | Citeline
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