“For us geeks, this is the trailer. This isn’t the movie,” John Stanford told BioWorld as he reacted to the prices the U.S. Centers for Medicare & Medicaid Services announced Aug. 15 for the 10 drugs selected for the first round of negotiations under the Inflation Reduction Act. While the prices are generally in line with what was expected, Stanford said they raise more questions than answers. The rationale for those prices, which must be released by March 1, will be part 1 of the movie as it should provide some insight into the price setting, said Stanford, the executive director of Incubate, a coalition of investors in the early stage life sciences sector.
In Pumpkinseed Technologies Inc.’s first public patenting, the company’s co-founders describe their development of new proteomics platform that merges nanotechnology, biochemistry, silicon photonics and machine learning for high-resolution phenotyping to deliver new biological insights.
Chinese artificial intelligence (AI)-driven drug discovery firm Quantumpharm Inc., also known as Xtalpi, began trading on the Hong Kong stock exchange June 13, listing under a new special technology listing track that lured it away from an IPO in the U.S.
Chinese artificial intelligence (AI)-driven drug discovery firm Quantumpharm Inc., also known as Xtalpi, began trading on the Hong Kong stock exchange June 13, listing under a new special technology listing track that lured it away from an IPO in the U.S.
As the average cost of new drug R&D continues to skyrocket, the perception around using artificial intelligence (AI) as a tool to boost drug discovery is changing. “Developing new AI-based drugs is a difficult task, not only for Korea but also for countries with leading AI technology,” Hyeyun Jung, principal researcher of Korea Health Industry Development Institute’s Center for Health Industry Policy, told the audience at the Bio Korea meeting on May 9. “But there is a change in perception; [namely that] applying AI to new drug development is not an option but a necessity.”
As the average cost of new drug R&D continues to skyrocket, the perception around using artificial intelligence (AI) as a tool to boost drug discovery is changing. “Developing new AI-based drugs is a difficult task, not only for Korea but also for countries with leading AI technology,” Hyeyun Jung, principal researcher of Korea Health Industry Development Institute’s Center for Health Industry Policy, told the audience at the Bio Korea meeting on May 9. “But there is a change in perception; [namely that] applying AI to new drug development is not an option but a necessity.”
Anvisa launched a pilot program to help Brazilian biopharma startups navigate the regulatory path from the initial phases of product development. In addition to providing regulatory support, the goal of the program is to accelerate the process of drug innovation in the country.
As part of its required series of guidances on using real-world evidence, the U.S. FDA released a draft guidance in response to sponsors’ growing interest in the potential use of observational studies to contribute to a demonstration of the effectiveness or safety of a drug or biologic.
In a first, the U.S. FDA accepted an artificial intelligence (AI)/machine learning-model into its Innovative Science and Technology Approaches for New Drugs (ISTAND) pilot program for drug development. The program will support use of Deliberate AI Inc.’s anxiety and depression assessment tool, called the AI-generated Clinical Outcome Assessment, as a qualified drug development tool.
In a first, the U.S. FDA accepted an artificial intelligence (AI)/machine learning-model into its Innovative Science and Technology Approaches for New Drugs (ISTAND) pilot program for drug development. The program will support use of Deliberate AI Inc.’s anxiety and depression assessment tool, called the AI-generated Clinical Outcome Assessment (AI-COA), as a qualified drug development tool.
