---
title: Humatch on the platform
description: >-
  Score antibody humanness against the human germline repertoire with a
  deep-learning classifier, per V-gene and per position.
tags:
  - humatch
  - antibodies
---

A therapeutic antibody has to look human to the immune system, or it risks provoking an anti-drug response. "How human is this sequence?" is therefore one of the first questions you ask of a candidate — and you want the answer per position, so you know exactly where to intervene. Humatch scores humanness with a deep-learning classifier trained on the human germline repertoire, flags the least-human positions, and names the closest human germline V gene. It is the fast humanness gauge in the [antibody engineering](/docs/antibodies) cluster.

## Try it

**Try this prompt** — [open in a guest chat](/chat/new?guest=true&prompt=Run%20IgBLAST%20on%20the%20adalimumab%20heavy%20chain%20to%20identify%20V%2FD%2FJ%20germline%20genes%20and%20CDR%20boundaries%2C%20then%20score%20joint%20VH%2FVL%20humanness%20with%20Humatch%20%E2%80%94%20does%20the%20fully%20human%20antibody%20score%20above%20therapeutic%20threshold%2C%20and%20recommend%20whether%20the%20V-gene%20assignment%20suggests%20a%20manufacturer-specific%20humanization%20liability%20for%20a%20biosimilar%20program%3F).

> Run IgBLAST on the adalimumab heavy chain to identify V/D/J germline genes and CDR boundaries, then score joint VH/VL humanness with Humatch — does the fully human antibody score above therapeutic threshold, and recommend whether the V-gene assignment suggests a manufacturer-specific humanization liability for a biosimilar program?

_Annotate with IgBLAST, then score humanness with Humatch — a common characterization pair._

## What Humatch does

Humatch takes antibody variable-region sequences and scores how closely each resembles the human germline repertoire. Under the hood it aligns each sequence and runs a CNN classifier that predicts V-gene family membership, producing an overall humanness score, per-V-gene scores, per-position scores, and a list of the positions that drag the humanness down. It names the closest human germline V gene and classifies each sequence as human or not against your threshold.

## Citations

> Chinery L, Jeliazkov JR, Deane CM. Humatch - fast, gene-specific joint humanisation of antibody heavy and light chains. *mAbs*. 2024;16(1):2434121. doi: [10.1080/19420862.2024.2434121](https://doi.org/10.1080/19420862.2024.2434121)

## When to reach for it

- **Fast humanness scoring** — you want a quick, per-position humanness read on one or many sequences.
- **Paired-chain evaluation** — you want VH and VL each scored against their matching germline model (one call per chain).
- **Humanization quality check** — you want to confirm a humanized candidate clears a threshold before lead nomination.

Reach for [BioPhi](/docs/biophi) instead when you want the OASis humanness metric *and* an actual humanization (Sapiens or CDR grafting) in the same step — Humatch scores but does not rewrite the sequence. The two are complementary and are often run together. Humatch chains forward into [ADMET-AI](/docs/admet-ai) prediction and [DiffDock](/docs/diffdock) docking.

## How it fits the workflow

Humatch is a scoring step. A common arc is IgBLAST annotation → Humatch scoring, or OAS search → Humatch scoring: annotate or mine first, then score humanness. Its per-position and flagged-position output tells you *where* to humanize, which you then act on with [BioPhi](/docs/biophi).

## How it runs

Humatch runs as an asynchronous CPU job on Modal compute. You submit one or more sequences, the platform tracks and polls the job, and a result card lands on the canvas when it finishes — typically within two to three minutes.

## Read next