Google Cloud’s life sciences leader believes Gen AI will transform in these four ways by 2025

The field of life sciences is vast and accounts for billions of dollars in research, development and innovation spent annually around the world. Over the past decades, this thriving field has provided humanity with some of the most groundbreaking developments – from new developments in pharmaceuticals and biotechnology to medical devices and various tools to deliver more personalized patient care.

Generative AI (Gen AI) has played an incredibly crucial role in this area. Innovators have developed a strong interest in the potential of this technology – especially when it comes to transforming workloads, making processes more efficient and even aiding drug discovery and development.

Shweta Maniar, Global Director of Healthcare and Life Sciences at Google Cloud, is optimistic about Gen AI, explaining that there are numerous opportunities for the technology to have a positive impact on the life sciences, including in drug discovery, patient personalization and the regulatory arena. In fact, Maniar predicts that 2025 will be a formative year for the intersection of Gen AI and life sciences, primarily in the following four ways:

1. AI will become increasingly multimodal and provide new solutions to data limitations. Models will increasingly be able to query and process data from different sources. This advancement solves an incredibly challenging problem; data is often spread across numerous formats, and research and development often takes place within the confines of the limited data available. Maniar describes how Bayer, one of the largest pharmaceutical companies in the world, is using Gen AI to overcome the very specific challenge of working with limited data sets; the company uses synthetic images generated from histological data to extend the limitations of existing training data to gain insights.
2. There will be growth in the use of AI agents, especially to improve workflows, increase efficiency and deliver greater value to enterprises and end users. Examples of this are already evident across the industry, ranging from customer-facing chatbots to many companies (even outside life sciences and healthcare) deploying AI agents internally to assist employees on a daily basis.
3. Search capabilities will continue to evolve rapidly, especially with the introduction of more intuitive and natural ways to do so. In life sciences, traditionally tedious tasks such as searching regulatory documents, conducting literature searches, and developing clinical trial processes have incredible potential to be transformed with this technology. For example, AI-based search can quickly process large amounts of information and generate coherent answers that can quickly expand workflows. Especially with the introduction of natural language processing (NLP), people can interact with these systems in significantly easier ways.
4. Gen AI will transform patient engagement and the customer experience. Patient communication is one of the most important aspects of life science work. Whether it’s counseling a patient about the complexities of a drug, or delving into the nuances of a clinical trial with enrolled individuals, Gen AI can help simplify communication and, most importantly, make the experience more enjoyable. Additionally, Gen AI’s ability to work in different languages ​​and cultural contexts can help life science companies further leverage the technology to meet the needs of diverse patient groups.

However, Maniar approaches all these innovations with caution. She talks about how, despite all this incredible momentum and investment in improving Gen AI, the focus for 2025 and for the future in general should also be on establishing trust by developing the technology in a sophisticated and ethical way : “realizing it [the] full potential [of Gen AI] will require the industry to continue its strong focus on ethics, data privacy and cross-industry collaboration.” Without this focus on trust, she explains, the field can only progress so far.

Google Cloud is undoubtedly one of the pioneers in generative AI work. Especially regarding life sciencesthe company has made significant progress in the industry. More broadly, the field of generative AI has grown remarkably in recent years and competition among tech titans is fierce. The latest in this area is that of Amazon news last week that it will invest another $4 billion in Anthropic, widely known as OpenAI’s biggest competitor. Amazon itself has become a leader in generative AI with its Bedrock platform, and has also made numerous strides in healthcare and life sciences spaces. Congruently, organizations are also increasingly willing to focus on technology. I recently wrote about Tenet Health and its groundbreaking partnership with Commure to deploy its ambient AI platform across Tenet’s organization. While not specific to the life sciences, the deal highlights the general trend of companies trying to leverage AI to improve workflows.

Ultimately, while the above four concepts have been labeled as predictions for the coming year, the reality is that the work behind each of these projects is already unfolding at a breakneck pace. As businesses grow, workflows become more complex, and workforce challenges continue to increase, technology will ultimately be called upon to provide solutions. As the field of Gen AI continues to evolve, the value and return on investment behind these innovations will undoubtedly and increasingly become self-evident.