2024 was yet another landmark year in artificial intelligencia (AI), data, life sciences and the powerful combination of all three. From the first AI-discovered and AI-generated drug to enter clinical trials for idiopathic pulmonary fibrosis to AI advancements receiving two Nobel Prizes that will shape the future of medicine, as well as the surge of growth in GLP-1 drugs for treating an even wider group of medical conditions, this year has been nothing short of revolutionary when it comes to the intersection of science, healthcare data and AI.
This is the time of year when predictions (and resolutions) are made. Here’s what our bench of interdisciplinary experts expects to see as they share their 2025 pharma predictions.
Top Pharma Predictions for 2025 from Industry Experts
Dimitrios Skaltsas, Co-Founder and CEO
Here are my three 2025 pharma predictions.
1. The adoption of artificial intelligence (AI) in standard operations in clinical development is currently just shy of 20% (another 30% is with pilots). Standard operations adoption will double in 2025.
2. More pharmaceutical companies will turn to reliable external data to help train internal data science models, including large language models (LLMs). This will become a rapidly growing market (‘garbage in, garbage out’).
3. ‘Expert AI,’ for example, highly AI applications to address highly complex topics, such as the probability of technical and regulatory success (PTRS), will gain more prominence, as the pharmaceutical industry will face challenges in gaining trust in generic generative AI models.
Panos Karelis, Director of Insights Excellence
In 2025, the life sciences industry will increasingly rely on large language models (LLMs) to transform strategic decision-making. These models have the potential to provide seamless access to insights across previously siloed datasets—combining trial data, real-world data (RWD), and competitive intelligence to inform portfolio prioritization and market strategies. AI will shift from merely supporting tactical decisions to driving boardroom discussions by enabling stakeholders to interrogate data in natural language, explore scenarios, and assess risks in real-time. This will also democratize data access within organizations, empowering non-technical teams to make evidence-backed decisions faster. Ultimately, AI will transform decision-making into a dynamic, proactive process, helping life sciences companies navigate complexity and uncertainty more effectively.
Gerry Liaropoulos, Director of Data Science and Bioinformatics
Increasingly, I expect the pharmaceutical industry to use LLMs to retrieve information regarding a particular landscape or indication. Big pharmaceutical companies will also leverage generative AI w to produce reports that will be used to make essential decisions internally in the big pharmaceuticals. The use of LLMs to create reports in the pharma industry will explode.
Alex Ferraro, Associate Director of Marketing
For the future of pharma in 2025, two big predictions top my list (and, of course, one is related to brand and marketing).
- Snackable AI With Measurable and Real Impact: It’s overwhelming and near impossible to go all in on AI (or any newer and less understood tech) all at once, especially in an industry where precision and accuracy matter as people’s lives are impacted. There will be a more digestible implementation of AI that builds and is rolled out over time thoughtfully without trying to boil the ocean and temper expectations on what it can (and can’t do). For example, I see smaller subsets of teams onboarding new AI solution providers and data annotation solutions and having to prove the value before it’s adopted more broadly in the organization. It will come in bite-sized chunks with corresponding metrics at the end of pilots to demonstrate the value-add. This Pharma Executive article noted, “real-time insights generated by AI daily are equivalent to 60,000 people analyzing 14 million spreadsheets over an entire year.” We will see more and more of these data points and even more focus on particular areas within drug development to prove the value of driving financial, operational, and clinical decisions while continuing to recalibrate AI-forward initiatives.
- Influencing Patient Engagement With Creative Pop Culture Icons and a Hint of Nostalgia: Using celebrity icons tied to drugs in the market is nothing new (e.g., Nick Joans for type 1 diabetes awareness or Lady Gaga for migraine medication), but I see more surprising and less expected spokespeople and elements of buzzy creativity to capture the general public’s attention. The recent Lil Jon “get low” campaign from Exact Science focuses attention on the need for colon cancer screenings, which is the second largest cancer killer in the U.S. We will see more investment of mainstream influencers tapping into nostalgia vibes to positively (and creatively) influence patients proactively putting their health first. Let’s see if colon cancer screenings increase in 2025 (along with Lil Jon tunes playing in outpatient centers).
Andreas Dimakakos, Director of Scientific Insights
I have three thoughts about AI trends in drug development in 2025.
- Multiple new AI-focused startups will enter the market, and the competitive landscape for solution providers will shift.
- The industry will focus even more on small pharma, those with valuations below $250M acquisitions. We’ll also see an increase in licensing opportunities.
- Metabolic has already been generating strong traction, and similar trends in the cardiovascular space will also be seen.
Agamemnon Krasoulis, Senior Data Scientist, Bioinformatician
I foresee at least two AI-generated drugs having positive readouts from phase II clinical trials and an AI-generated drug entering a phase III clinical trial. As some of my colleagues have already mentioned, there is and will continue to be a shift from scaling up large language models (LLMs) towards more efficient architectures that can attain the same level of performance but with less training data and/or smaller models.
Angeliki Lykoudi, Business Development Associate
Skepticism about AI will decrease, and more people will appreciate it as a powerful tool. We live in a world filled with data, and machine learning and AI-driven analytics serve as the key to unlocking the potential of that data. AI enables us to uncover insights, minimize risks, and make more informed decisions – all imperative in clinical development.
Additionally, preclinical research will increasingly focus on computational models. I foresee more new drug entities and new drug candidates suggested by AI models advancing to clinical research. This approach shortens timelines and reduces preclinical research costs, such as those associated with experimental models.
Eva Digalaki, Technical Expert
2024 has been a year of increased awareness and acceptance of how AI influences our ever-changing world. With generative AI reaching the public and new data centers being built, more sectors are eager to integrate AI and the robustness of data-driven approaches into their operations. In 2025, we will likely see more industry participants establishing data operations teams within their organizations or collaborating with external providers. These efforts will focus on shorter-term data applications rather than larger, long-term projects, as leaders in the field aim to validate data-driven approaches before fully adopting them.
In the bio-health sector, several pressing questions remain unresolved: the mental health crisis, infections with the potential for global impact, drug-resistant microorganisms, rare cancer indications, and diseases for which no disease-modifying therapies are available. 2025 might mark the beginning of first-in-class drug clinical research in some of these areas, paving the way for new and innovative treatments to become available within 5-10 years. A few such treatments are already in advanced stages of development, such as Gepotidacin for urinary tract infections (UTI) and Suzetrigine for pain. I am eager to see what breakthroughs come next!
Marina Anastasiou, Senior Scientific Associate
I predict we’ll see two core AI applications come to life in 2025.
- Smarter Drug Combos: AI will be leveraged to crack the combo therapy codes and find the best drug combinations for challenging diseases like cancer and Alzheimer’s.
- Synthetic Data Revolution: Think mock data or fake data with REAL impact! Synthetic data will be the go-to for training AI in healthcare and finance. Although this will help privacy issues and easily fill data gaps, AI will be trained on fake data to affect real people in pivotal areas such as healthcare.
Névine Zariffa, Scientific Advisory Board Chair
Beyond what we can expect regarding the progression of data and AI in the application of healthcare, one of the main uncertainties is in the public health arena. Worldwide conflicts impact health and well-being in obvious ways. They threaten vaccination programs, and in the U.S., the new administration may also have a direct impact. Scientific knowledge and communication with the general public will be key in the coming years.
Tina Baumgartner, Senior AI and Life Science Content Writer
The buzz in 2024 was all about generative AI and retrieval augmented generation (RAG). We will see this interest continue into 2025. However, the next big new thing is already out there and ready to take the spotlight: agentic AI. Agentic AI is a type of artificial intelligence that can perform complex tasks independently, uses sophisticated reasoning, learns from experience, and adapts to changing conditions with limited or even entirely without human intervention. While genAI excels at creating content, agentic AI enables autonomous systems to take action. 2025 will be the early days of adoption by a few technology enthusiasts, but there will be lots of interest and hype and rapid technological advances.
Andriana Aktypi, Scientific Associate
When it comes to the future of pharma in 2025, I predict that we will see an increase in:
- AI-driven drug discovery and therapy development.
- AI-powered clinical trial design and recruitment.
- Real-time patient monitoring and trial optimization.
- Growth of personalized medicine with AI and synthetic data.
Mairi Moniaki, People Operations Manager
From a people operations perspective, it’s clear that Intelligencia AI—and companies in general—will need to address some critical challenges moving forward.
- Bridging Generational Gaps: For the first time in history, four distinct generations, from Boomers to Gen Z, are coexisting in the workplace. The main challenge is bridging the gaps between these generations, notably when their values, communication styles, and work preferences often differ significantly. Companies that fail to take this task seriously risk falling behind. Building strategies to foster understanding, inclusivity, and collaboration across generations is no longer optional; it’s a necessity for sustainable growth.
- The Balancing Act of Artificial and Human Intelligence: While the focus on AI grows, are we neglecting human intelligence? In the talent space, finding individuals who are skilled but also coachable, collaborative and capable of engaging in difficult conversations within a business context is becoming increasingly rare. These qualities will be critical as we navigate the complexities of the modern workplace. Teams must prioritize these attributes to ensure a well-rounded and adaptable workforce.
- Recognizing People as the Core of Success Will Become Paramount: Behind every successful product, service, or company are the people driving its impact. As people operations leaders, we must protect and nurture this foundation against the rising tide of individualism and ego. Creating a culture that values collective success, emotional intelligence, and humility will set companies apart in a competitive landscape.
Only time – and perhaps some AI-generated predictions–will tell what 2025 brings to the intersection of tech, AI, data and the pharmaceutical industry. Let’s see how our predictions hold up in the year ahead. What’s on the top of your 2025 healthcare prediction list?