The Mobile World Congress (MWC) 2025 has once again showcased the transformative impact of Artificial Intelligence (AI) across multiple industries. Among the most disruptive areas, AI’s application in research and development (R&D) for the chemical industry is redefining how companies create more sustainable and efficient products.
In this context, our CEO had the opportunity to participate in a Fireside Chat with Elisabeth Roma, R&D Director at AC Marca Home Care, where we explored how digitalization and AI are accelerating innovation in the chemical sector.
The Role of AI in Chemical Innovation
One of the key topics at MWC 2025 has been how AI is revolutionizing traditional sectors. In chemistry, the combination of molecular modeling and AI enables R&D teams to reduce physical experimentation, optimize formulations, and predict the performance of new products before they are synthesized in the lab.
According to Elisabeth Roma, European regulations are pushing the adoption of more sustainable chemistry. The pressure to comply with the Green Deal and other environmental policies forces companies to find alternatives to certain compounds in a short period of time, driving the use of advanced digital tools.
One of the most powerful concepts that emerged from our conversation was the digital continuity of data. Elisabeth Roma emphasized the importance of having well-digitized and structured R&D data that can be leveraged in several stages of product development. Proper data management not only facilitates access but also allows the application of AI and machine learning models to optimize formulations and accelerate product development.
Traditionally, the chemical industry has relied on knowledge accumulated through experience and physical experimentation. However, digital data allow:
- Simulation and performance prediction of formulations: Molecular modeling calculates physico-chemical properties of ingredients and formulations. High-throughput calculations generate large and consistent synthetic data that can be optimally leveraged in data-driven approaches. Machine learning enables predictions of how new ingredients will behave without extensive physical testing.
- Integration with regulations: Structured data makes it easier to comply with regulations by cross-referencing substance classification and restriction information.
- Greater efficiency and agility in development: Companies that invest in digitalization today will be able to formulate products much faster and more efficiently in the coming years.
Challenges and the Future of Digital R&D in Chemistry
Despite the clear benefits, digitalizing chemical R&D still faces challenges:
1. The need for data: AI algorithms can only generate accurate predictions if fed with high-quality and large enough datasets, requiring an effort in data generation, collection and curation.
2. Mindset shift in R&D teams: Transitioning to digital tools requires scientists to adopt a new approach to formulating and validating hypotheses.
3. Investment in digital skills and talent: Companies must train teams capable of managing AI and molecular simulation tools.
Conclusion: Molecular Modeling and AI, the New Era of Chemical R&D
MWC 2025 has reaffirmed that digitalization is no longer optional but essential in the chemical industry. The combination of molecular modeling and AI accelerates the development of sustainable products, reducing time and costs.
Companies that adopt these technologies will lead the sector’s transformation in the coming years. At Nextmol, we are committed to this change, offering solutions like NEXTMOL Lab, which allow R&D teams to experiment virtually and characterize formulations before physical synthesis.
Read this article also in Linkedin: https://www.linkedin.com/pulse/conversation-rd-leader-what-i-learned-mwc-2025-monica-de-mier-9ja6f/