Training the next-generation of biomedical scientists through artificial intelligence-driven education and research in pharmacology and pharmaceutical sciences.

Abstract

Artificial intelligence (AI)-driven graduate education and research in pharmacology and pharmaceutical sciences (AIPPS) aims to address the rapidly-growing role of AI and machine learning (ML) applications in biomedical sciences. This review provides perspectives on why and how the next-generation of biomedical scientists equip themselves with skills necessary to integrate AI and ML tools into their current fields of study, particularly pharmacology and pharmaceutical sciences. The AI-enabled approaches discussed in this article highlight opportunities for improving competitiveness in an evolving scientific landscape, that includes academia, pharmaceutical and biotech industries and regulatory science. Furthermore, this review discusses how graduate education and research can be enhanced through training in AI-driven disease prediction, molecular target identification drug design and discovery, drug repurposing and pharmacometric modelling. The knowledge outlined here may help graduate students and early career researchers navigate the challenges associated with applying AI-based methodologies in fundamental research, product and process development, service delivery, and regulatory policy and ethics. Overall, the insights provided in the review aim to support the development of skilled forward-thinking biomedical and pharmaceutical scientists capable of leveraging AI technologies in modern research environments.