# Develop and Commercialize the Bayesian Dose-Response Modeling System and Services

> **NIH NIH R42** · KS AND ASSOCIATES, LLC · 2020 · $972,476

## Abstract

PROJECT SUMMARY
Chemical risk assessment is widely applied in industries and regulatory agencies as an important tool to
evaluate chemical toxicity in support of chemical registration, safety evaluation, and exposure limitation
development. One of the most notable improvements in dose-response assessment - a required quantitative
step in risk assessment - is the development of benchmark dose (BMD) methodology to better utilize
toxicological information to facilitate toxicity evaluation of chemicals. Although the BMD method has been
advocated by the US Environmental Protection Agency (EPA) and European Food Safety Authority (EFSA) for
its scientific advantages (such as less dependency on the design of experiments and more plausible
interpretation on uncertainty) for years, the employment of the method in practical risk assessment has been
significantly hindered by a few important limitations, one of which is the lack of a reliable modeling system to
support consistent practice of BMD modeling across different sectors. Therefore, based on the Bayesian
benchmark dose modeling system (BBMD) prototype successfully built in Phase I of the STTR project, the
objective of Phase II is to further the development of the BBMD system to meet more diverse needs in dose-
response assessment and to enlarge the user base of the system as an essential component for
commercialization. The rational is that, given relatively limited practical implementation of BMD modeling for
dose-response assessment in industry and some government agencies, demonstrating and improving the
utility of the BMD method rather than sophisticating the methodology are more appropriate at the current stage
to enhance the acceptance of BMD method and then create business opportunities for the company. To
accomplish this objective, three specific aims will be pursued: (1) develop a Bayesian BMD modeling approach
with software for typical epidemiological dose-response data; (2) develop a Bayesian BMD modeling approach
with software for high-throughput dose-response data; (3) upgrade the BBMD to a data computation and
management system to perform, store, and distribute BMD analyses approved by a panel of experts. The
success of the project will fill multiple gaps that hamper the large-scale adoption of BMD methodology in
industry and government. Meanwhile, Dream Tech will increase the influence of the BBMD system and build
up user base through an array of channels to commercialize the dose-response modeling platform and
services in support of chemical risk assessment.

## Key facts

- **NIH application ID:** 10081313
- **Project number:** 9R42ES032642-02
- **Recipient organization:** KS AND ASSOCIATES, LLC
- **Principal Investigator:** Kan Shao
- **Activity code:** R42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $972,476
- **Award type:** 9
- **Project period:** 2018-08-15 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10081313

## Citation

> US National Institutes of Health, RePORTER application 10081313, Develop and Commercialize the Bayesian Dose-Response Modeling System and Services (9R42ES032642-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10081313. Licensed CC0.

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