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The House Goes Long On Drones

Client Alert | 1 min read | 09.20.22

Last week, the House passed the Drone Infrastructure Inspection Grant Act, which establishes programs within the Department of Transportation (DOT) to support the use of small unmanned aircraft systems (sUAS) when inspecting, repairing, or constructing a variety of types of infrastructure, including roads, electric grids, water, and other critical infrastructure. 

Specifically, the legislation authorizes DOT to award up to $100 million over two years in grants to state, tribal and local governments to support their purchase and use of sUAS to increase efficiency, reduce costs, improve worker safety, and reduce carbon emissions when carrying out infrastructure inspections, repairs, and construction.  In addition to the customary flowdown requirements that accompany grant funding, the infrastructure inspection grants will include mandatory country of origin provisions, requiring grant recipients to use U.S.-manufactured sUAS made by companies not subject to Chinese influence or control. 

The legislation also authorizes a separate $100 million pool of funding for DOT to use for grants to educational institutions to support student training and education in the use of drones and related technologies.

The bill, which passed the House by a 308-110 vote, now proceeds to the Senate. A companion bill was introduced in the Senate on August 8 and has been referred to the Committee on Commerce, Science, and Transportation for consideration.  Both bills have significant support from industry leaders and local government groups.

  

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Client Alert | 7 min read | 09.14.26

AI in Life Sciences: Ten Legal Considerations and Risks of AI Use in Drug Discovery and Development

Over the past several years, the biopharmaceutical industry has embraced artificial intelligence and machine learning (AI/ML) in near lockstep with the pace of AI/ML innovations. Today, industry leaders are using AI/ML to, among other things: discover and assess biological pathways, target chemical structures and sequences; design proteins; model pre-clinical and clinical trials; recruit and screen potential patient populations; evaluate clinical trial results and biomarker data; prepare regulatory filings; and manage supply chains. Deployment of new AI/ML models promises extraordinary advances in pharmaceutical development. However, as with any technological and scientific advances, the use of AI/ML also poses substantial legal risks that life sciences companies need to consider and proactively manage. ...