24/7 BIOPHARMA - issue 1 / October 2024

LOGICA

The future in a nutshell

hypotheses, to test the boundaries of current knowledge, and to accelerate the pace at which new treatments can be developed and brought to market. Looking to the future, the promise of AI in drug discovery is boundless. With each advance in AI technology and each new dataset generated from experimental research, we edge closer to a world where drug discovery is more predictive, personalised and potent. The collaborative efforts of researchers, leveraging AI and experimental science, are crucial as we navigate this uncharted territory, blending the art and practice of science with the precision of advanced algorithms to forge new paths in healthcare. As we embrace the AI revolution, we do so with the knowledge that we are not just witnessing a change in how we discover drugs, but are participating in a historic moment that will define the future of medicine. 1. Fleming, N. How artificial intelligence is changing drug discovery. Nature. 2018;S55. 2. Ayers, M., et al. Adopting AI in Drug Discovery. Boston Consulting Group. March 29, 2022. Accessed April 8, 2024. 3. Blanco-Gonzalez, A., et al. The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies. Pharmaceuticals. 2023;16(6):891. 4. Barzilay, R., et al. The race for a cure. Royal Society of Chemistry. June 3, 2020. Accessed April 8, 2024. 5 Jiménez-Luna, J., et al. Artificial intelligence in drug discovery: recent advances and future perspectives. Expert Opinion on Drug Discovery. 2021;16(9):949-959. 6. Khatami, S.G., et al. Using predictive machine learning models for drug response simulation by calibrating patient-specific pathway signatures. npj Systems Biology and Applications. 2021;7(1):40. 7. Regalado, A. An AI-driven ‘factory of drugs’ claims to have hit a big milestone. MIT Technology Review. March 20, 2024. Accessed April 8, 2024. References

The horizon for AI in drug discovery is expansive, promising to streamline the discovery of new therapies and usher in an era of personalised, effective and accessible treatments. As AI and experimental science fuse, the drug discovery landscape will be transformed, with a focus on leading the charge toward this exciting future. This shift is expected to accelerate innovation, diversify the pipeline of drug candidates and potentially reduce the overall cost of bringing new treatments to market, marking a significant step forward in making advanced drug discovery tools accessible to a broader range of researchers and companies. As we stand on the brink of a new era in drug discovery, the integration of AI with experimental data heralds a transformative shift in how we approach the creation of new medicines. This revolution, characterised by a seamless blend of computational power and biological insight, is not merely about enhancing the efficiency of drug discovery processes; it’s about fundamentally redefining what is possible in the quest to treat and cure diseases. The burgeoning field of digital biology, powered by AI, is poised to turn biology into an engineering discipline, opening unprecedented opportunities for drug discovery [ 7] . Furthermore, the rapid advancement of AI designed drugs through both the discovery and preclinical stages, as demonstrated by recent clinical trials, underscores AI’s potential to significantly accelerate the drug development process. This acceleration is not confined to a single entity; rather, it is a testament to the collaborative efforts across the scientific community, driving forward with innovations that promise to reshape the landscape of pharmaceutical research and development. Embracing drug discovery The journey of AI in drug discovery, from its nascent integration to becoming an indispensable tool, illustrates a path filled with challenges, learning and, ultimately, immense rewards. The ability of AI to sift through and make sense of vast datasets, to predict outcomes with increasing accuracy and to uncover insights that elude human cognition, is a testament to the power of this technology. Yet, it is the marriage of AI with the rich, nuanced data from experimental research that truly unlocks its potential. This partnership does not replace the human element, but rather enhances it, allowing scientists to explore new

EMILIO CORDOVA Executive Director Logica

38 TWENTYFOURSEVENBIOPHARMA Issue 1 / October 2024