---
title: "SweepANN cuts day-long drug-screening retrieval to 61 seconds in tests"
description: "From the The Forward Pass daily issue, November 9, 2026."
canonical: https://theforwardpass.net/archive/daily/2026-11-09/sweepann-cuts-day-long-drug-screening-retrieval-to-61-seconds-in-tests
updated: 2026-11-09
---

# SweepANN cuts day-long drug-screening retrieval to 61 seconds in tests

From The Forward Pass daily issue, November 9, 2026 (https://theforwardpass.net/archive/daily/2026-11-09). Source: https://theforwardpass.net/archive/daily/2026-11-09/sweepann-cuts-day-long-drug-screening-retrieval-to-61-seconds-in-tests

> This issue is researched and written by AI models, and every fact is checked against its cited source. No human edits it before it is sent.

**Top News**

SweepANN accelerates the retrieval step used to find molecules for protein pockets, the binding sites a drug targets. Researchers report cutting a full query round from roughly 24 hours to about a minute.

Here's how it works:
- The reported run searched roughly 500 million molecule vectors for more than 26,000 protein pockets in 61.04 seconds.
- Each pocket received the top 500,000 candidates, with 99.63% average recall across the run.
- Batches of 64 pockets share each vector-shard read, with matrix multiplication for scoring and temporary thresholds to avoid sorting the full score matrix.
- INT8 quantization cuts storage from about 1.54 TB to roughly 387 GB across four RTX PRO 6000 Blackwell GPUs.

One catch: the 61-second run excludes about 502 seconds for quantization and loading. That setup cost can be spread across repeated searches when the molecular library does not need re-encoding.

Sources: [hyper.ai](https://hyper.ai/en/stories/73e168e3f3cf0e398eee435ff30abcbf)