AI Enables Smart Drug Discovery Solutions

Life-sciences companies are making strides in the fields of gene and cell therapies, omics technologies (genomics, transcriptomics, proteomics and metabolomics, etc.), and smart molecules approaches, creating an urgent need for advanced, cost- and time-effective technologies that can parse large databases of information to help develop novel therapies, according to a report published by Frost & Sullivan, a research and consulting firm.

The report, Artificial Intelligence Revolutionizing the Pharmaceutical Industry, presents the technology roadmap, trends, capabilities, and applications driven by artificial intelligence (AI) in the pharmaceutical industry. It includes stakeholders' activities as well as industry initiatives and analyzes the investment environment, regional, and global regulation landscape, and standardization approaches for tackling challenges.

"Pharmaceutical companies are increasingly recognizing the value of deploying AI-based platforms that can leverage data regarding gene mutations, protein targets, signaling pathways, disease events, and clinical trials to find hidden drug-disease correlations," said Cecilia Van Cauwenberghe, associate fellow and TechVision senior industry analyst at Frost & Sullivan, in a Dec. 17, 2018 press release. "This technology will enable scientists to derive structured and unstructured data from multiple sources as never before. Strategic collaborations with AI-driven companies can help large pharmaceutical companies establish a robust, AI-based pipeline as part of their portfolios and address new therapeutic areas."

AI-driven tools are encouraging companies to develop therapies for underserved areas and are also paving the way for precision medicine through a stratified therapeutics discovery and development approach. Frost & Sullivanpredicts that collaborations among database holders, AI developers, and drug manufacturers will facilitate the early development of multiple therapeutics, even those focused on treating rare and chronic diseases.

AI-based technology companies can also make the most of scientific results and learning systems synergy to ensure a successful clinical translation of therapeutic, diagnostic, and theranostic developments. Some of the key applications of AI technologies in pharmaceuticals outlined in the report include:

• Drug development-aids in disease modeling, drug design and development, lead identification, and drug repurposing

• Candidates' validation-helps design and run pre-clinical trials, in silico/in vitro/in vivostudies, and investigational new drug process

• Clinical trials-supports all processes, from designing the trial to patient identification through data collection, analysis, and report generation

• Regulatory approval-facilitates the approval of application and process, labeling, and safety updates

• Precision medicine-accelerates the development of preventive and personalized care, treatment surveillance, and omics adaptive models.

"Overall, there is a profound and growing scientific understanding of many metabolic and signaling pathways, especially at molecular and genomic levels, which encourages the use of sophisticated technologies to develop groundbreaking therapies," noted Van Cauwenberghe in the release. "As the underlying causes of many diseases remain vague and imprecise, AI-based approaches have emerged as the ideal mechanisms for finding novel treatments."

Source: Frost & Sullivan