<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/f8724d060625449586c3285bca6cbbba&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/f8724d060625449586c3285bca6cbbba-5238906f1ee1f204.gif</thumbnail_url><duration>391.789</duration><title>Antibody Target Predictor</title><description>In this Loom, I walk you through PatSnap Life Science AI&apos;s Antibody Target Predictor and how it helps screen antibody target relationships fast. I used the example prompt to find the optimal antibody for the tau target. The agent evaluates 2155 tau antibodies and compiles evidence including affinity characteristics, binding kinetics, and epitope information. The report includes links to recent patent publications and top ranked antibodies with heavy and light chain sequences, plus KD and EC50 performance data and selection rationale. I did not ask for any specific action from you.</description></oembed>