Artificial intelligence and drug development: Accelerating the discovery of life-saving medications

The discovery of life-saving medications has always been portrayed as the heart of pharmaceuticals. It substantially revolutionized public health outcomes, in relation to the prevention, treatment, and even curing of a vast range of initial terminal ailments. Nevertheless, significant shortcomings have become apparent regarding the traditional methods for developing life-saving medications in an increasingly fast-paced society. The demand for an ever-growing pipeline of innovative pharmaceutical products could often exceed the pace of R&D leading to the delay in granting patient access to them, often even after it had been proved by robust clinical data that the benefits outweigh the risks. Here, the timely access to life-saving medications is declared as one of the main challenges for healthcare and society. There is much hope and belief that both academia and industry players should shift towards unparalleled innovation in order to foster critical advancements in the pharmaceutical sector. The commercial opportunities are considered as vast, in an attempt to address a global market deficit.

In this context, the goal of this report is to investigate and discuss the potential impact of artificial intelligence technologies on pharmaceutical innovation with a focus on their potential to significantly accelerate the discovery of life-saving medications. The essay deliberates on recent and future contributions and analyses AI-driven technologies with broader implications shaping the future landscape of drug development and pharmaceutical delivery. It focuses on the drug discovery phase, discussing how advancements in AI technologies have led to innovation of sophisticated algorithms. These advancements are progressively employed and embedded in the current drug development workflow. The report is structured as follows. It begins with a general overview of modern healthcare challenges, underscoring the necessity by demonstrating the manifest difficulties of the processes in the light of the most significant pathways and targets. Following this interpreted foundation, the essence of the applied AI technologies is deliberated with a more profound and focused analysis on the employed methodologies. The report then extends this discussion on to the integration of different AI technologies to converge on platforms currently utilized in an environment where the old paradigm is being overtaken by the new. It finishes with a contemplation encompassing possible future trends, together with remarks and conclusions ensuring a vastly taken perspective for its importance.