Clarkston’s team of life sciences consultants have highlighted the top life sciences industry trends that businesses should consider. See an excerpt of the trends report below, and read all five trends for 2025 by downloading the full report here.

2025 Life Sciences Industry Trends

As geopolitical instability and economic uncertainties continue to shape the global landscape, life sciences companies have a unique opportunity to leverage sophisticated growth strategies and emerging technologies to thrive in 2025. With the integration of AI and ML, along with a surge in M&A activity, innovation is set to drive industry growth. At the same time, the increasing complexities of supply chains, dynamic geopolitical environment, and growing concerns about data integrity will require organizations to prioritize agility in order to remain competitive. In this trends report, we outline the key opportunities that will define the life sciences industry in the coming year, offering insights to help organizations stay agile and well-positioned for sustained growth. 

Trend #1: Revolutionizing R&D with Artificial Intelligence (AI) & Machine Learning (ML)  

Artificial Intelligence (AI) and Machine Learning (ML) present significant opportunities to enhance efficiency in drug discovery, manufacturing, and clinical research; expand data analysis capabilities; and reduce operational costs for life sciences companies in 2025. While beneficial in R&D and data processing, scaling these technologies to meet cGXP standards remains a complex challenge for many organizations. In 2025, it will be essential for companies to begin integrating AI and ML throughout business units to stay competitive.  

AI and ML have already started to revolutionize the R&D realm. With capabilities such as target identification, predictive protein folding, and candidate filtering, AI tools can act as virtual assistants, accelerating the drug discovery process. Predictive protein folding models can help identify patterns and drug candidates faster than ever, saving years of manual labor in the lab. The integration of AI and ML models has also led to the development of the “Lab in a Loop” concept. By training AI systems with data generated from laboratory and clinical studies, models like this can predict disease targets and therapeutics, which are then tested in the physical lab. The integration of complex AI algorithms with wet lab execution allows for more informed decision-making throughout the R&D process.  

AI also has robust data management capabilities. Validation 4.0 leverages digitization and automation to link data with quality systems in real time, providing an integrated data validation approach. With AI and ML, traditional big data validation has shifted from document-centric to data-centric, creating a more holistic and efficient process. However, this model requires a strong foundation of data to be effective. Organizations must assess their data creation, usage, and access to have an accurate understanding of their current data landscape. Building an “AI-ready” data core through scalable, resilient pipelines and integration tools will provide the foundation for AI adoption.  

Integrating these advanced technologies can be highly rewarding, though the process can be daunting. Companies are encouraged to take a risk-based approach when implementing automation systems in 2025. Establishing AI literacy programs in tandem will establish an effective hybrid workforce of human and technology that can drive innovation. While the process may never be flawless, starting with small use cases that deliver tangible value is key. As data is cleansed and becomes more accessible, additional use cases can be gradually added in. For instance, begin by implementing your AI model in a single business unit, site, or process to identify successes and areas for improvement. From there, the model can be scaled with confidence, knowing that core business operations remain unaffected.  

Trend #2: Increased Complexities in Manufacturing and Supply Chain  

The recent rise of novel therapeutic areas is highlighting pharmaceutical supply chain complexities more than ever. Emerging therapeutic areas such as cell and gene therapies, radiopharmaceuticals, regenerative medicine, and mRNA therapies are shaping the regulatory landscape in 2025 and beyond.  

In response to the expansion of innovative therapeutic areas, CBER has introduced the Office of Therapeutic Products (OTP). With this introduction comes increased guidance on manufacturing and comparability studies for change management within the companies. As a result, there’s an increased need for harmonization, standardization, and visibility throughout the supply chain. To prepare for the adoption of complex supply chain features, companies will now need to stress test their manufacturing process more than ever. Advanced technology tools, like a digital twin, can replicate real-world scenarios, simulate potential changes, and predict outcomes to increase crisis preparedness. Implementing automation systems in manufacturing will also improve accuracy and reduce human error to ensure precise and timely production. 

New regulations surrounding the pharmaceutical supply chain are also expected to have a significant impact on processes in 2025. The BIOSECURE Act, passed by the House of Representatives in September 2024, prohibits life sciences companies from doing business with biotechnology companies of concern. In combination with proposed tariffs, these regulations will have wide-spread effects across the supply chain. Deadlines for compliance with the Drug Supply Chain Security Act (DSCSA) have also been extended into 2025, allowing manufacturers, repackages, wholesalers, and dispensers to implement changes in phases through the end of 2026. Given these evolving guidelines, it’s essential for businesses to prepare their supply chains for the uncertainties ahead in 2025 and beyond. We anticipate organizations will reassess their internal capabilities, with many pulling strategic functions back in-house to leverage efficiencies, reduce risks, and maintain collaboration with external partners throughout the supply chain.  

Despite these regulatory changes, cell and gene therapies (CGT) are rapidly gaining commercialization momentum, and this market is expected to grow by $111 billion from 2025-2033. CGT provides groundbreaking technology to treat a range of diseases; however, it also comes with additional supply chain complexities. For the therapy to be effective, patient chain of custody must be maintained across the entire process—from development to manufacturing and delivery. CGT developers must address logistics during the early stages of product development to prepare for scaling up.  

CGT isn’t the only complex therapy on the rise. Radiopharmaceuticals, mRNA therapies, and regenerative medicine each present unique manufacturing and supply chain challenges. Radiopharmaceuticals require a precise “just-in-time” supply chain due to the short half-life of the radioactive isotopes they contain. Similarity, quality raw materials with short lead times are essential to mRNA therapies and regenerative medicine, as these processes are highly dependent on the stability of materials.  

With the continuous advancements of therapeutics and the changing environment, risks to the supply chain have never been more real. Companies must remain flexible to quickly assess impacts, evaluate risks, and mitigate immediate threats. Continue reading by downloading the full report below.

Download the Full 2025 Life Sciences Industry Trends Report Here

Read last year’s Life Sciences Industry Trends Report here.

Contributions from Riley Welch