“The current drug discovery market is not responding sufficiently to health care needs where it is not adequately lucrative to do so. Unfortunately, there are a number of important yet non-lucrative fields of research in domains including pandemic prevention and antimicrobial resistance, with major current and future costs for society. In these domains, where high-risk public health needs are being met with low R&D investment, government intervention is critical. To maximize the efficiency of the government’s involvement, it is recommended that the government couple its work catalyzing R&D with the creation of a drug development ecosystem that is more conducive to the use of high-impact artificial intelligence (AI) technologies. The scientific and political communities have been ringing alarm-bells over the threat of bacterial resistance to our current antibiotics arsenal and, more generally, the evolving resistance of microbes to existing drugs. Yet, a combination of technical capacity issues and economic barriers has led to an almost complete halt of R&D into treatments that would otherwise address this threat. When a gap arises between what the market is incentivized to produce and the healthcare needs of society, governments must step in. The COVID-19 pandemic illustrates the importance of bridging that gap to ensure we are protected from future threats that would result in similarly devastating consequences. Artificial intelligence (AI) capabilities have contributed to watershed moments across a variety of industries already. The transformative power of AI is showing early signs of success in the drug discovery industry as well. Should AI for drug discovery reach its full potential, it offers the ability to discover new categories of effective drugs, enable intelligent, targeted design of novel therapies, vastly improve the speed and cost of running clinical trials, and further our understanding about the basic science underlying drug and disease mechanics. However, the current drug discovery ecosystem is suboptimal for AI research, and this threatens to limit the positive impact of AI. The field requires a shift towards open data and open science in order to feed the most powerful, data-hungry AI algorithms. This shift will catalyze research in areas of high social impact, such as addressing neglected diseases and developing new antibiotic solutions to incoming drug-resistant threats. Yet, while open science and AI promise successes on producing new compounds, they cannot address the challenges associated with market-failure for certain drug categories. Government interventions to stimulate AI-driven pharmaceutical innovation for these drug categories must therefore target the entire drug development and deployment lifecycle to ensure that the benefits of AI technology, as applied to the pharmaceutical industry, result in strong value added to improve healthcare outcomes for the public….
This document puts forward a set of recommendations that, taken together, task governments with the responsibility to promote: 1. Research and development in fields of drug discovery that are valuable to society and necessary to public health, but for which investments are currently insufficient because of market considerations. 2. Uptake of AI throughout the entire drug discovery and development pipeline. 3. A shift in culture and capabilities towards more open-data among stakeholders in academia and industry when undertaking research on drug discovery and development….”