SandboxAQ Launches AQPotency, Bringing Ultrafast Virtual Screening to Drug Discovery Without a Solved Protein Structure

{
  "signal_id": "196ef2ce-71c6-ff3d-ed1b-44e0b8580422",
  "signal_type": "news",
  "signal_subtype": "launches",
  "detected_at": "2026-08-19T15:53:00+00:00",
  "company": {
    "name": "SandboxAQ",
    "domain": "sandboxaq.com"
  },
  "data": {
    "url": "https://www.prnewswire.com/news-releases/sandboxaq-launches-aqpotency-bringing-ultrafast-virtual-screening-to-drug-discovery-without-a-solved-protein-structure-302855441.html",
    "title": "SandboxAQ Launches AQPotency, Bringing Ultrafast Virtual Screening to Drug Discovery Without a Solved Protein Structure",
    "excerpt": "PALO ALTO, Calif. , Aug. 19, 2026 /PRNewswire/ -- SandboxAQ today announced the general availability of AQPotency , 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. 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. 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...",
    "product": "AQPotency",
    "summary": "SandboxAQ announced the general availability of AQPotency, its Large Quantitative Model (LQM) for predicting drug efficacy, now available on Claude via Model Context Protocol (MCP).",
    "location": "Palo Alto, California, USA",
    "planning": false,
    "image_url": "https://mmx.prnewswire.com/media/MS1542217/SandboxAQ-Logo-Accent-Color-Black-TM-Logo.jpg?id=OA2897769&p=facebook",
    "confidence": 0.95,
    "product_data": {
      "name": "AQPotency",
      "full_text": "AQPotency , its Large Quantitative Model (LQM) for predicting how well a potential drug will work",
      "fuzzy_match": false
    },
    "product_tags": [
      "future_tech",
      "general_technology",
      "medical"
    ],
    "published_at": "2026-08-19T15:53:00Z",
    "location_data": [
      {
        "city": "Palo Alto",
        "state": "California",
        "region": "Northern America",
        "country": "United States",
        "continent": "Americas",
        "fuzzy_match": false
      }
    ],
    "effective_date": "2026-08-19",
    "article_sentence": "SandboxAQ today announced the general availability of AQPotency , its Large Quantitative Model (LQM) for predicting how well a potential drug will work, now available on Claude via Model Context Protocol (MCP)."
  }
}

curl https://signals.autobound.ai/v1/signals/196ef2ce-71c6-ff3d-ed1b-44e0b8580422 \
  -H "X-API-KEY: $AUTOBOUND_API_KEY"

curl -X POST https://signals.autobound.ai/v1/companies/enrich \
  -H "X-API-KEY: $AUTOBOUND_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"sandboxaq.com","limit":20}'