AI
There is “a lot of flexibility” in the European Medicines Agency’s reflection paper on the use of artificial intelligence during drug development, which is principles-driven rather than setting rigid recommendations, says the agency’s Florian Lasch.
The FDA is developing several structures and a broad group of experts across disciplines to help craft artificial intelligence policy. But the proliferation of AI-related initiatives raises the question of who, ultimately, will make decisions about when novel applications of AI are acceptable.
Many of the comments were very helpful in improving the document in relation to both form and content, the European Medicines Agency said of its newly published reflection paper on the use of artificial intelligence during the drug development, marketing authorization and post-authorization phases.
The five-year roadmap aims to expand support for AI research and development in essential health care and new drug development, as well as advance medical data usage systems and enable its safe use.
Medicines regulators in the EU have “much to gain” from using AI models in their processes, but this technology must be used in a “safe and responsible” way, says the European Medicines Agency.
A recurring question about using artificial intelligence in drug development is whether the US Food and Drug Administration can accept a model that operates as a black box, meaning that developers cannot explain exactly how the model does what it does.
Pink Sheet reporter and editors discuss new developments in the FDA’s plans to regulate artificial intelligence and drugs associated with it, including a new AI Council within CDER, as well as some of the unanswered questions about AI in drug development.
AI modeling can predict which animal tests are useful and necessary, saving money for companies and meeting objectives set by regulators in the US and EU, VeriSIM Life’s CEO and founder Jo Varshney tells the Pink Sheet.
The Artificial Intelligence Council takes over work that three different entities in the US FDA’s drugs center had been performing. The new, centralized entity will develop and promote consistency in AI-related activities and advance innovative uses.
Regulatory uncertainty and the biopharma industry’s longstanding aversion to risk are hindering adoption of artificial intelligence and machine learning in drug and biologic development, panelists said at a recent US FDA/CTTI workshop.
AI has the potential to save vast amounts of time and money by optimizing pharma supply chain processes, but companies must think about legal risk and liability from all angles, Ewan Townsend, partner at law firm Arnold & Porter, tells the Pink Sheet.
Pharmaceutical companies should only use AI in evidence generation and reporting where there is “demonstrable value from doing so,” according to England’s health technology assessment body, NICE.
Shanghai issues a new set of policies and financial incentives designed to support and speed up regulatory and commercial activities in the biopharma sector, in a comprehensive stimulus package for companies based in the major Chinese city.
From the US FDA’s ISTAND Program to EU’s Melloddy Initiative, and from the global challenges of real-world data to the opportunities in India, Parexel’s EVP for Clinical Data and Digital Services, chief strategy officer and India head speak on a range of topics in this interview with the Pink Sheet.
As well as planning action to improve the EU’s competitiveness in the life science sector, the European Commission has confirmed that it will propose new legislation to reduce the bloc’s reliance on overseas suppliers of medicines as a way of tackling drug shortages.
Europe’s Innovative Health Initiative, a public-private funding partnership, has put out a call for a research project that could help analyze the use of regulatory sandboxes in health care innovation in addition to three others.
Pink Sheet reporter and editors discuss what the FDA included in its long-awaited guidance on clinical trial diversity action plans, along with what was left out, as well as an upcoming guidance on the use of artificial intelligence in regulatory decision-making.
The Center for Drug Evaluation and Research’s medical policy chief says artificial intelligence can aid patient recruitment and increase trial diversity, but warned of “unique” potential pitfalls for sponsors.
Draft guidance will offer a risk-based framework for accessing the credibility of AI and help ensure that AI models used to answer regulatory questions are sufficiently credible for a particular ‘context of use,’ CDER’s Tala Fakhouri says.
FDA leadership weighs in on limitations of AI as part of rollout of new technology meeting program that looks to give industry and other stakeholders a chance to inform future regulation.