Researchers affiliated with UTHealth Houston competed as Novamab AI in the international AIntibody Challenge, a blinded, prospective benchmark published in Nature Biotechnology. The team placed among the top five groups in the competition, demonstrating that AI-guided antibody design can produce candidates that perform well under laboratory test conditions rather than relying on in silico metrics. The result strengthens the case for using AI systems to accelerate early antibody discovery, while keeping an emphasis on experimental validation in pre-specified evaluation frameworks. For biotech sponsors, the benchmark format is especially relevant because it tests generalization against fixed experimental criteria, which can better predict whether AI-designed candidates translate into real lab performance.