# Better bioassays via designs for robots analyses with improved model selection and similarity bounds that limit potency bias

> **NIH NIH R43** · PRECISION BIOASSAY, INC · 2021 · $251,991

## Abstract

Project Summary
Biological assays (bioassays) provide critical measurements of the activity of complex biological drug products
(proteins, vaccines, cell therapy, and gene therapy products) particularly during product development and
production quality control. These assays use living systems for measurement and have special designs and
analyses to accommodate the large variation and confounding factors involved. Common lab bioassays
impose complex statistical structures that, if not designed and analyzed properly, lead to poor precision for
estimates of potency and limited capabilities to monitor assays for developing problems. These problems
contribute to lot release failures for manufacturers and slow down or block the development of
biopharmaceutical products for consumers.
Precision Bioassay provides statistical services for bioassays, helping organizations that develop, use,
perform, validate, monitor, and regulate bioassays use modern methods to get better information and
performance, ultimately improving the quality and accelerating the discovery of biopharmaceutical drug
products. The proposed research will lead to three new tools that will improve bioassay design, analyses and
monitoring, each will become a new product (a combination of software and consulting support). New bioassay
designs that exploit the capabilities of modern robots will, in combination with good analyses, separate
important sources of variation that are confounded with current designs and analyses; this improved
information will accelerate bioassay development and enhance monitoring of bioassays. Improved methods for
selection of which sources of variation to include in bioassay analysis models (equivalence-based random
effects model selection) will improve estimation of important sources of variation that are often ignored with
current analysis methods; this will substantially improve bioassay monitoring. Limiting bias of potency is
essential to ensuring that a bioassay is fit for its intended use: a new approach to setting bounds for
equivalence tests of similarity of test samples to standards will limit bias of potency associated with allowed
non-similarity to pre-specified levels, ensure that most samples that are similar will pass similarity, and
estimate the assay size required to achieve this performance target.
In Phase II we will extend the proof-of-concept results from this research using prototype software able to
address practical cases. The products from this research will become additional packages in our existing
software and consulting services that will accelerate the development of biopharmaceutical products.

## Key facts

- **NIH application ID:** 10155988
- **Project number:** 1R43GM140743-01
- **Recipient organization:** PRECISION BIOASSAY, INC
- **Principal Investigator:** David Matthew Lansky
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $251,991
- **Award type:** 1
- **Project period:** 2021-03-01 → 2023-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10155988

## Citation

> US National Institutes of Health, RePORTER application 10155988, Better bioassays via designs for robots analyses with improved model selection and similarity bounds that limit potency bias (1R43GM140743-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10155988. Licensed CC0.

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