Artificial Intelligence in Drug Discovery – Could help Reduce Significant Capital and Time Required

Drug discovery is a complex process which involves significant utilization of time and resources. As per several sources, on an average, the entire drug development process (from initial proof-of-concept to commercial launch) takes around 10-15 years and capital investments worth USD 4-10 billion to develop a drug from concept to commercial launch. The early stages including target discovery and lead molecule identification, play an important role in the success of the drug in both preclinical and clinical studies. However, despite the advances in technology and improved understanding of biological systems, the drug discovery process is still considered to be inefficient. In order to optimize the ongoing and future drug development projects, stakeholders are exploring advanced technology solutions (such as artificial intelligence in drug discovery) in order to facilitate better decision making during the various stages of drug discovery and development. Several industry stalwarts, namely Pfizer, Sanofi and Genentech, are already using different AI-enabled platforms for internal drug discovery efforts; given how this field is evolving, medical R&D is likely to become more structured in the foreseen future.

Services Providers Offering AI-based Drug Discovery Platforms and Services

Given the huge market potential of Artificial Intelligence in drug discovery sector, we at Roots Analysis conducted a detailed analysis of the companies that are involved in this domain. Over 170 companies offer AI-based services and platforms for discovery of small molecules and biologics. These companies claim to have expertise across various stages of drug discovery. The market is dominated by stakeholders that have established presence across various regions of the globe. In North America region, the US emerged as the most prominent hub, featuring the presence of 56% players. Presently, Europe has the second highest number of stakeholders (34%), with the UK being the base of operations for most of the companies, engaged in this segment, located in this region.

Potential Cost Savings Associated with the Implementation of Artificial Intelligence In Drug Discovery Purposes

AI platforms allow integration of available data with workflow management algorithms, across several processes, to increase productivity, as well as reduce the cost and time required for the overall process. The adoption of AI-enabled tools and operational approaches, across different stages of drug discovery, is likely to have an impact on the R&D expenditure, enabling significant cost savings worldwide. Based on Roots Analysis proprietary analysis criterion, AI-enabled technologies have the potential to reduce 15% of the overall expenditure associated with the drug discovery, across the world.

Revenue Generating Potential of Companies Offering AI-based Drug Discovery Services

To estimate the overall market opportunity associated with this domain, Roots Analysis conducted a detailed market forecast analysis. The market has been estimated across various segments instance geography, drug discovery steps, therapeutic area and end users. To account for the uncertainties associated with this industry and to add robustness to our model, we have provided three forecast scenarios, portraying the conservative, base and optimistic tracks of the market’s evolution.

To get detailed insights about this market, check out the report here

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