{"id":4331,"date":"2026-08-19T20:28:11","date_gmt":"2026-08-19T20:28:11","guid":{"rendered":"https:\/\/smartinvestingschronicle.com\/index.php\/2026\/08\/19\/sandboxaq-launches-aqpotency-for-drug-target-screening\/"},"modified":"2026-08-19T20:28:11","modified_gmt":"2026-08-19T20:28:11","slug":"sandboxaq-launches-aqpotency-for-drug-target-screening","status":"publish","type":"post","link":"https:\/\/smartinvestingschronicle.com\/index.php\/2026\/08\/19\/sandboxaq-launches-aqpotency-for-drug-target-screening\/","title":{"rendered":"SandboxAQ Launches AQPotency for Drug-Target Screening"},"content":{"rendered":"<div data-id=\"9a4764\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"theme-post-content.default\">\n<p class=\"wp-block-paragraph\"><strong>Insider Brief<\/strong><\/p>\n<ul class=\"wp-block-list\">\n<li>SandboxAQ has made AQPotency generally available as a Large Quantitative Model for predicting drug-target activity and prioritizing candidate molecules. <\/li>\n<li>The model can rank molecule-target pairs without requiring a solved 3D structure of the target and provides confidence information alongside its predictions. <\/li>\n<li>AQPotency is available through Claude via Model Context Protocol and SandboxAQ\u2019s website, with the company saying the model has been used in eight customer programs with experimentally validated results.<\/li>\n<\/ul>\n<p class=\"wp-block-paragraph\">Press release \u2013 SandboxAQ\u00a0today announced the general availability of\u00a0AQPotency, its Large Quantitative Model (LQM) for predicting how well a potential drug will work, now available on Claude via Model Context Protocol (MCP). For any disease target, AQPotency scores how strongly candidate molecules are likely to act on it, and it does this without the expensive, time-consuming lab work that older methods depend on. Drug discovery teams can now rank enormous libraries of molecules by computer in seconds, then spend their limited lab budgets only on the candidates most likely to succeed.<\/p>\n<p class=\"wp-block-paragraph\">Early drug discovery is a high-stakes guessing game. Teams have to decide which molecules to test in the lab, and a wrong call can cost months of work and significant expense. The established computer methods for narrowing the field are slow and costly to run, and they only work when scientists already have a detailed structural map of the disease target. Many of the most valuable targets have no such map, so those methods never reach them, and promising programs stall before they start.<\/p>\n<p class=\"wp-block-paragraph\">AQPotency clears that roadblock. It runs on ordinary computing hardware, ranks pairs of molecules and targets in seconds, and costs as little as $1 per 1,000 comparisons. For every prediction, it also reports how confident it is and whether the target falls within the range where the model performs reliably. Older tools give scientists a single score with no sense of its reliability. AQPotency tells them not only what it predicts, but when they can trust it, which makes the results something teams can act on.<\/p>\n<p class=\"wp-block-paragraph\">AQPotency also works in the other direction. Starting with a single promising molecule, it scans a broad panel of proteins across the body and returns a ranked list of the ones it is most likely to act on. When a molecule shows a useful effect but no one yet knows why, this gives research teams a focused set of leads to test.<\/p>\n<p class=\"wp-block-paragraph\">\u201cSandboxAQ\u2019s models have been very impactful for our work as we develop new treatments for Parkinson\u2019s,\u201d said Professor Dario R. Alessi, OBE, FMedSci, FRS, Director of the MRC Protein Phosphorylation Unit at the University of Dundee. \u201cThese models enable us to explore a much larger biochemical space in a short timeframe and improve both activity and selectivity. SandboxAQ\u2019s unique datasets and models stand out in the industry for their impact.\u201d<\/p>\n<p class=\"wp-block-paragraph\">\u201cThis collaboration with SandboxAQ highlights the power of combining advanced AI-enabled discovery with rigorous experimental validation to unlock novel opportunities against historically difficult membrane targets. By identifying selective SV2C binders from a broad commercial library, the work establishes a compelling foundation for the development of first-in-class small-molecule tools and future therapeutics aimed at Parkinson\u2019s disease and other disorders of dopaminergic signaling,\u201d said Dr. Gary W. Miller the Adrienne Block Professor of Environmental Health Sciences and the Vice Dean for Research Strategy and Innovation at the Columbia University Mailman School of Public Health.<\/p>\n<p class=\"wp-block-paragraph\">Andrea Bortolato, Vice President of Drug Discovery, at SandboxAQ, said: \u201cAQPotency has given us and our customers a faster, scalable and reliable way to prioritize compounds in the workflows we already run, without needing a 3D crystal structure of the target. This opens up programs that structure-based methods simply couldn\u2019t reach. The confidence intervals make the output actionable for biopharma companies, and the model has already been successfully used in eight customer programs with experimentally validated impact.\u201d<\/p>\n<p class=\"wp-block-paragraph\">\u201cWhat\u2019s compelling about AQPotency is that it makes high-value discovery decisions faster and more practical,\u201d said Robin Roehm, CEO and Co-Founder at Apheris, which offers federated data and AI networks for life science companies. \u201cResearchers can prioritize the most promising compounds with greater confidence, focus experimental resources where they matter most, and expand discovery efforts to targets that have traditionally been harder to pursue.\u201d<\/p>\n<p class=\"wp-block-paragraph\">AQPotency is generally available today through Claude via MCP and SandboxAQ\u2019s website, with availability on Google Cloud\u2019s Marketplace to follow. Its general availability is paired with the GA on Claude and Claude Science of a second LQM, AQCat Adsorption Spin, for catalyst discovery.<\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Insider Brief SandboxAQ has made AQPotency generally available as a Large Quantitative Model for predicting drug-target activity and prioritizing candidate molecules. The model can rank molecule-target pairs without requiring a solved 3D structure of the target and provides confidence information alongside its predictions. AQPotency is available through Claude via Model Context Protocol and SandboxAQ\u2019s website, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":4332,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-4331","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech-news"],"_links":{"self":[{"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/posts\/4331","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/comments?post=4331"}],"version-history":[{"count":0,"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/posts\/4331\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/media\/4332"}],"wp:attachment":[{"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/media?parent=4331"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/categories?post=4331"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/smartinvestingschronicle.com\/index.php\/wp-json\/wp\/v2\/tags?post=4331"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}