Biotech Firms' Convergence to Human Models and AI

Announcement

The drug developers are rapidly adopting artificial intelligence (AI) technologies in their settings, mainly for safety and discovery testing, targeting reducing cost and time, aligning with the US Food and Drug Administration’s FDA drive to diminish reliance on animal testing. The industrial experts from the contract research organizations, brokerages, and biotechnology firms stated that in the next three to five years, the merged use of reduced animal testing and AI will somehow balance costs and timelines. Currently, it might take 15 years and above $2 billion to introduce a new drug to the market.

Drug Developers' Continuous Efforts to Adopt Technology in a Suitable Setting

Certara, the drug development software specialist, together with biotech firms like Recursion and Schrodinger Pharmaceuticals, is already using AI to model, working on proving the experimental drugs' eligibility to be distributed and absorbed easily, also to predict toxic side effects. Recursion claims that their AI-powered platform was capable of advancing a cancer drug candidate into clinical testing within 18 months, significantly quicker than the company's average of 42 months.

The Jefferies and TD Cowen, the leading analysts, have high hopes of these AI-based approaches to instantly shorten development cycles and diminish costs. In the US, the FDA has focused on the vision in which technologies like human cell-based systems and computational modelling, and AI can raise standards for toxicity assessments and pre-clinical safety through animal testing applicable to a few cases in the next three to five years.

In one of the April month’s statements, the agency advised of this method that will directly lessen the drug prices, specifically in the area of monoclonal antibody development. As per FDA requirements company will continue with organizing an animal study to test for potential adverse effects. The studies will approximately take six months, consisting of an average of 144 non-human primates, with a cost of $50,000 per animal.

Charles River Laboratories, one of the known research contractors, is among the smart players investing more in new approach methodologies (NAMs). These methods use machine learning, human-derived systems, and computer-based modeling, including organs-on-chip, to enact the behavioral (movement) of an organ. The small companies are also heading ahead in this field, for instance, Swiss firm insphero is testing drug efficacy and testing in 3D liver models with the help of lab-boost microtissues to reflect organ function. Also, New York-based Schrodinger is merging physics-based simulations with AI to forecast toxicological outcomes.