SOT Component Groups (Regional Chapters, Special Interest Groups, and Specialty Sections) and Committees host webinars throughout the year. Webinars are an effective distance-learning method intended to impart scientific knowledge to members of each group as well as the SOT membership at large. These webinars are just one of the many benefits of SOT membership.
Information on upcoming Component Group and Committee webinars, the SOT FDA Colloquium, and SOT Virtual Meeting webinars is provided here.
US FDA’s Safety Evaluation of Foods from Genetically Engineered Plants
Host: American Association of Chinese in Toxicology Special Interest Group (AACT)
Date and Time: Thursday, April 16, 2020, 3:00 PM– 4:00 PM (ET)
The US Food and Drug Administration regulates foods derived from plants, including those that have been developed using genetic engineering or genome-editing techniques, commonly referred as “GMOs” or as “bioengineered.” Our Biotechnology Consultation Program is voluntary but helps developers ensure that their foods from genetically engineered crops meet mandatory safety and regulatory requirements. During this webinar, I will go over details about our evaluation process and the data and information we look for in a submission. Our program has reviewed submissions on more than 150 events. Most of those events are from corn, soybeans, cotton, potato, and canola, and the most frequent traits are insect resistance and herbicide tolerance. In the recent years, we have seen more new crops and traits, such as non-browning apples, pink pineapple, and high oleic acid soybean oil. We are currently working on guidance for foods derived from plants produced using genome editing.
Jamie Zhu, PhD
US FDA, Staff fellow/Consumer Safety Officer
From Science to Regulation: How Research Priorities Are Used to Inform the Center for Tobacco Products Regulatory Activities at the US FDA
Host: Hispanic Organization of Toxicologists Special Interest Group (HOT)
Date and Time: Wednesday, April 22, 2020, 11:00 AM–12:00 Noon (ET)
The US Food and Drug Administration Center for Tobacco Products (US FDA/CTP), established in 2009 by the Family Smoking Prevention and Tobacco Control Act (Tobacco Control Act), has the broad authority to regulate the manufacturing, distribution, and marketing of tobacco products, with the ultimate goal of reducing harm caused by tobacco use. Under the Tobacco Control Act, US FDA regulates cigarettes, roll-your-own tobacco, and smokeless tobacco. In 2016, US FDA finalized a rule extending the US FDA authority to regulate electronic nicotine delivery systems (ENDS), cigars, hookah tobacco, pipe tobacco, and nicotine gels. Toxicologists support the Office of Science at CTP by providing sound scientific evidence for implementation of the Tobacco Control Act. This webinar will briefly present how toxicological information from multiple data streams is used to understand the mechanism of tobacco-related disease, specifically toward ENDS, and how the scientific evaluation is used in the regulatory activities to support research projects aimed to inform our regulatory decision-making at US FDA/CTP.
SOT FDA Colloquia on Emerging Toxicological Science: Challenges in Food and Ingredient Safety
Artificial Intelligence Applications in Food and Cosmetic Safety
This event is offered as part of the SOT FDA Colloquia on Emerging Toxicological Science: Challenges in Food and Ingredient Safety series and is being offered exclusively via webcast.
Hosts: SOT and the US Food and Drug Administration Center for Food Safety and Applied Nutrition
Date and Time: Wednesday, April 29, 2020, 8:00 AM–12:50 PM (ET)
Artificial intelligence (AI) is defined as the science and engineering of making intelligent machines. Machine learning is a subset of AI in which analytical model building is automated and not explicitly programmed. It is based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention. As more data are generated in various scientific disciplines, AI promises to provide an analytical tool with more precision than existing standard methods. Advances in computational toxicology have benefited public health by reducing reliance on animal studies and reducing the cost of performing such experiments. Machine-learning methods can extend the capacity of computational toxicology methods such as read across, QSAR, and kinetic models. In fact, natural language processing and deep learning methods are being used to develop predictive toxicology models to outperform the traditional QSAR and read across models.
These developments in science and technology show great potential in further advancing the safety of our food and cosmetic production. In the broader food production and food safety space, AI technologies are being developed to enhance the growth of foods by monitoring and modifying growth parameters, managing supply chains, cleaning processing equipment, identifying plant diseases, developing new products, and enforcing employee personal hygiene procedures during food processing. In the cosmetic space, AI technologies are being used to augment data from in vitro studies and predict dermal absorption and toxicity in the absence of animal tests. As these technologies mature, we must start thinking about how to standardize procedures for safety assessments derived from AI-generated data and how to best leverage these technologies to advance food and cosmetic safety.
SOT Virtual Meeting Webinars
Live webinar presentations featuring content from the Annual Meeting will continue through June 2020. Both Scientific Sessions and Continuing Education courses will be presented as live webinars. Most Scientific Sessions are being presented on Tuesdays and Thursdays between 12:00 noon and 4:00 pm (ET), while Continuing Education courses are being presented on Fridays between 12:00 noon and 3:30 pm (ET). The full list of scheduled sessions and courses is available on the “Virtual Meeting Program” web page, which is being regularly updated as activities are finalized.