Management Support Crucial to AI in Pharma

Research studies suggest that artificial intelligence (AI) is becoming more widely used within the pharmaceutical industry, and that senior executive support will be crucial to piloting and implementing AI-based approaches to improve R & D efficiency.

Industry interviews and an https://www.ncbi.nlm.nih.gov/pubmed/31248680" target="_blank">extensive survey by the Tufts Center for the Study of Drug Development (TCSDD), the Drug Information Association (DIA), and eight bio/pharmaceutical manufacturers has found that pharmaceutical and biopharmaceutical companies are adopting AI to help improve functions ranging from discovery and development to risk assessment, safety monitoring, and manufacturing.

The research involved interviews with AI experts within the industry, as well as a survey of 402 professionals at pharmaceutical and biopharmaceutical organizations, to assess the current state of AI use and implications for the future.

Survey results found that 70% of respondents use AI in some form, with planning and piloting efforts focused mainly on clinical trials (i.e., patient selection and clinical study recruitment) and identification of data gathering for medicinal products.

Research found that staff skills (55%), data structure (52%), and budgets (49%) are currently the greatest obstacles to increased use of AI in pharma. Nearly 60% of survey respondents said that their companies plan to increase staffing over the next two years, to support AI use or implementation.

In addition, TSDD reports, the survey found that:

The clinical operations function makes the highest use of AI (61%), followed by pharmacovigilance/safety/risk management (57%), and information technology (IT) (55%).

42% of respondents reported that AI implementation is not centrally managed at their companies, while 20% indicated that it is managed by R & D and 12% said that it is overseen by the chief information officer.

59% of respondents plan to expand AI staff through 2020, with the largest staffing increases slated for data scientists, computer scientists, IT specialists, and AI architects.

"Pharmaceutical and biotechnology companies as well as service providers now rely on AI technologies across all therapeutic areas, [particularly] for oncology, central nervous system, cardiovascular, immunology, rare diseases, and metabolic/endocrine diseases," said Mary Jo Lamberti, research assistant professor and associate director of sponsored research at Tufts CSDD, who led the analysis.  She expects precision medicine and demand for new rare disease treatments to drive potentially exponential growth in the industry’s use of AI as regulators and industries develop standard policies and regulations to address ethical use, bias, and validation.

Deep Knowledge Analytics also released a report examining AI, which examined practices at 50 pharmaceutical companies to identify leaders who are most actively driving the use of AI in their organizations.

Importance of senior management

The goal of this research is to benchmark the impact of management support on the use of AI and overall efforts to increase R & D efficiency, according to Margaretta Colangelo, managing partner at Deep Knowledge Ventures. She expects future research to find a correlation between level of commitment to AI and market capitalization growth.

Sources: Tufts, http://analytics.dkv.global/data/pdf/AI-for-DD-Q4/Top-100-AI-Leaders.pdf" target="_blank">Top AI executives