![]() It aims to spur a discussion with interested parties in the medical products development community, such as pharmaceutical companies, ethicists, academia, patients and patient groups, and global counterpart regulatory and other authorities, on using AI/ML in drug and biologic development, and the development of medical devices to use with these treatments. The discussion paper was developed as a collaboration between the FDA’s Center for Drug Evaluation and Research (CDER), the Center for Biologics Evaluation and Research, and the Center for Devices and Radiological Health, including its Digital Health Center of Excellence. The first paper, “ Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products,” addresses these concerns as well as challenges related to algorithms that have a degree of opacity, or algorithms that may have internal operations that are not visible to users or other interested parties, which can lead to amplification of errors or preexisting biases in the data. However, significant ethical and security challenges remain. Digital or computerized ‘twins’ of patients can be used to model a medical intervention and provide biofeedback before patients receive the intervention.” Conversational agents or chatbots, which are based on ‘generative’ AI, have the potential to answer people’s questions about participating in clinical trials or reporting adverse events. ![]() “For example, AI/ML could be used to scan the medical literature for relevant findings and predict which individuals may respond better to treatments and which are more at risk for side effects. ![]() “Ultimately, AI/ML can help bring safe, effective, and high-quality treatments to patients faster,” she wrote. In a statement introducing the papers, Patrizia Cavazzoni, M.D., Director of the FDA Center for Drug Evaluation and Research, highlighted the potential of AI/ML to transform how stakeholders develop, manufacture, use, and evaluate therapies. Information on business management and marketing is provided to help existing processors expand their business and to help farmers and entrepreneurs start a successful value-added dairy foods business.On May 10, the FDA released two discussion papers on the use of artificial intelligence and machine learning (AI/ML) in drug development and manufacturing. In this section of the Extension website, you will find resources to help you navigate the world of dairy foods processing starting with milk production on the farm to processing different products, and the regulations, sanitation and food safety practices needed to make safe, high quality dairy products. ![]() Processing dairy products in not difficult, but it is not necessarily straightforward, taking into account the many aspects of quality, safety, and understanding which regulations apply to all processors and which apply only to processors of a certain size or who are making a specific type of dairy product. Pennsylvania has over 300 dairy food processors that use milk from cows, goats, and sheep to produce fluid milk products, cheese, yogurt and other cultured dairy products, ice cream and frozen desserts, butter, and concentrated and dried dairy products.ĭairy food processors in Pennsylvania range in size from operations with less than 5 employees processing less than 2,000 pounds of milk per week to more than 150 employees processing more than 500,000 pounds of milk per week. The dairy industry supports 52,000 jobs and contributes $14.7 billion to the state's economy. Pennsylvania is one of the top states in the nation for milk production. The Dairy Food Processing Industry in Pennsylvania Use Penn State’s resources on milk production at the farm, manufacturing different types of dairy foods, regulations, food safety and sanitation, and business and marketing to help make your dairy foods business successful. Making high quality, safe dairy foods involves many steps from farm to the finished product.
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