Key points are not available for this paper at this time.
The pharmaceutical industry is a cornerstone in the global healthcare system, renowned for its pioneering discoveries and unwavering commitment to addressing complex health challenges. Over decades, it has proven its resilience in ensuring the availability of life-saving treatments. However, this stalwart industry is not without its challenges, from high costs and intricate regulations to the complexities of intellectual property protection, drug pricing, and the ever-looming spectre of emerging health threats, (as witnessed in recent pandemics). Amidst these diverse challenges, technological advancements in Artificial Intelligence (AI) emerge as a beacon of hope, positioned to transform the industry. This article explores the transformative role of AI within the pharmaceutical industry, unravelling its multifaceted impact across crucial domains. From revolutionizing drug discovery and development to optimizing clinical trials, enabling personalized medicine, enhancing manufacturing and quality control, ensuring pharmacovigilance, streamlining supply chain management, and even influencing drug marketing and sales, AI’s influence is pervasive. The integration of AIs into the pharmaceutical industry signifies a transformative moment in the course of healthcare evolution. In summary, as we navigate this era of unprecedented technological advancement, the pharmaceutical landscape is poised for a profound and drastic change, signalling a leap toward enhanced patient outcomes and a more resilient healthcare ecosystem. The integration of AI offers numerous benefits, including faster and more cost-effective drug discovery, enhanced precision in personalized medicine, improved clinical trials through better data analysis etc. However, AI also faces limitations such as the need for high-quality, unbiased datasets, regulatory and ethical concerns regarding transparency and data privacy, and the inherent complexity of biological systems that can sometimes outstrip AI’s current capabilities. In light of these opportunities and challenges, the future of AI in pharmaceuticals hinges on careful implementation, continuous innovation, ethical considerations and a collaborative approach to addresses these challenges.
Suri et al. (Thu,) studied this question.