yassa_bio is an open-source Python toolkit for bioanalytical assay data, starting with ELISA and other ligand-binding assays (LBA), with a roadmap toward universal support for plate-based and chromatographic assays.
It is built for scientific rigor, automation, and regulatory alignment—targeting labs that need reliable, explainable, and auditable pipelines, from academic cores to pharma and CROs.
- ✅ Curve fitting and back-calculation: Supports 4PL, 5PL, and linear models with transform, weighting, and outlier handling
- ✅ ICH M10 / FDA BMV 2018 / USP ⟨1225⟩-based acceptance criteria
- ✅ Automated evaluation of:
- Calibration fit
- QC accuracy/precision
- ✅ Flexible schema for analytical runs using
pydanticmodels - ✅ Extensible plug-in registry: Add new evaluators or transform logic via decorators
- ✅ Rerun-aware pipeline engine: Smart re-evaluation when calibration levels fail and are dropped
- ✅ Readable outputs: Results returned as dicts
This library is:
- Schema-first: All input/output structures are formalized via
pydantic, enabling structured config, validation, and API wrapping - Composable: Pipelines consist of atomic steps with a typed shared
Context, rerunnable after refitting - Domain-aligned: Acceptance steps follow bioanalytical validation standards like ICH M10, FDA BMV 2018, and USP ⟨1225⟩
- Deployable: Enterprise modules (auth, signoff workflows, dashboards) could wrap this open core
from yassa_bio.evaluation.run import run
from yassa_bio.schema.layout.batch import BatchData
from yassa_bio.schema.analysis.config import LBAAnalysisConfig
from yassa_bio.schema.acceptance.analytical.spec import LBAAnalyticalAcceptanceCriteria
ctx = run(
batch_data=BatchData(...),
analysis_config=LBAAnalysisConfig(),
acceptance_criteria=LBAAnalyticalAcceptanceCriteria(),
)
print(ctx.acceptance_results)See PlateData and WellTemplate for how to define input formats.
git clone https://github.com/your-username/yassa_bio.git
cd yassa_bio
pipx install poetry # or: brew install poetry
poetry install # install dependencies
poetry run pre-commit install
poetry run pytest # run testsyassa_bio/
├── schema/ ← Pydantic models: layout, acceptance, config
├── evaluation/ ← Step logic for acceptance criteria
├── core/ ← Curve fitting, transforms, QC utilities
├── io/ ← Raw data loaders (CSV, Excel)
└── run.py ← Main entrypoint to run the pipeline
This is an open science tool. If you're in pharma, biotech, or academia and would like to collaborate, file an issue or email the maintainer. You can also:
- Fork the repo and open a PR
- Request features or improvements
- Share example plate formats or data
Apache 2.0 – free for academic, commercial, and clinical use.
Contact [ruba.andrew@gmail.com] or open a GitHub Issue.