MilliporeSigma Launches AI Solution for Integrating Drug Discovery and Molecule Synthesis
MilliporeSigma’s new platform combines generative AI, machine learning, and computer-aided drug-design aimed at increasing the success rate of new drugs and therapies.
On Dec. 5, 2023, MilliporeSigma, the US and Canada Life Science business of Merck KGaA, Darmstadt Germany, launched AIDDISON, a drug discovery software touted as the first software-as-a-service platform. The platform aims to bridge the gap between virtual molecule design and real-world manufacturability using Synthia retrosynthesis software application programing interface (API) integration.
The platform combines generative artificial intelligence (AI), machine learning, and computer-aided drug-design designed to speed up drug development. The AIDDISON software is trained on more than two decades of experimentally validated datasets from pharmaceutical R&D, and, as a result, it can identify compounds from more than 60 billion possibilities having the key properties of a successful drug: non-toxicity, solubility, and stability in the body, according to a company press release. Upon identification, the platform then proposes ways to best synthesize these drugs.
According to MilliporeSigma, AI and machine learning models such as its AIDDISON software can extract hidden insights from large datasets. In doing so, these models can increase the success rate of delivering new therapies to patients. “AI has the potential to offer more than $70 billion in savings for the drug discovery process by 2028, and to save up to 70% time and costs for drug discovery in pharmaceutical companies,” the company stated in its press release.
“With millions of people waiting for the approval of new medicines, bringing a drug to market still takes, on average, more than 10 years and costs over $2 billion,” said Karen Madden, chief technology officer, Life Science business sector of Merck, in the press release. “Our platform enables any laboratory to count on generative AI to identify the most suitable drug-like candidates in a vast chemical space. This helps ensure the optimal chemical synthesis route for development of a target molecule in the most sustainable way possible.”
Source: MilliporeSigma
