# A Multiscale Toolkit for Predicting Clinical Pharmacological Response of Antibody Therapeutics

> **NIH FDA R43** · CFD RESEARCH CORPORATION · 2020 · $168,085

## Abstract

Response to National Institutes of Health Small Business Innovation Research (SBIR)
 NIH SBIR: PHS 2019-2 Omnibus Solicitation for SBIR/STTR Grant Applications
Re : Submission of R43/44 SBIR Phase I Proposal
FOA :
PHS 2019-2 Omnibus Solicitation of the NIH, CDC, FDS and ACF for
Small Business Innovation Research Grant Applications (Parent SBIR
[R43/R44])
Institute/Division/Topic :
National Institute of General Medical Sciences (NIGMS)
Topic B- Pharmacological and Physiological Sciences
Proposal Title :
A Multiscale Toolkit for Predicting Clinical Pharmacological Response of
Antibody Therapeutics
ABSTRACT
Antibody therapeutics (Abs) account for 80% of the best-selling drugs in the market. Their success in areas of
neuroscience, oncology and autoimmune disorders infectious diseases, immuno-oncology, autoimmune
diseases and rare diseases has augmented their commercial potential. Over the last three decades since the
first mAb was approved by the FDA, about 60 mAbs have been marketed in the United States, and with ~350
new entities in active clinical development, the commercial potential for these therapeutic antibodies is projected
to reach ~$300B by 2025. Furthermore, with two bispecific Abs (bsAbs) in the market already and approximately
85 additional bsAbs in clinical development, sales by 2023 are projected to be $4.4B. In response to this trend,
a robust simulation tool, which can aid in model-based drug development for the prediction of safe and efficacious
clinical dose will be valuable to the pharma industry for accelerating development regulatory approval.
The overall objective is to develop a multiscale modeling/simulation toolkit for predicting the clinical
pharmacology of antibody therapeutics (in collaboration with Prof. Laird Forrest at University of Kansas School
of Pharmacy). During Phase I, we will develop a mechanistic physiology-based pharmacokinetic and
pharmacodynamic model (PBPK/PD) of mAbs and Triomab bispecifics (bsmAbs), which are delivered
intravenously or subcutaneously. We will adapt the existing human PBPK model, which was developed by the
PI and team for small molecule pharmacology under prior and ongoing NIH/FDA/DoD projects. Detailed models
of target organs to adequately resolve the concentrations at tissue sites, ligand types (soluble vs. membrane-
bound), pH-dependent neonatal Fc receptor recycling (FcRn), binding, affinity and target suppression to better
elucidate the local PK/PD interactions will be incorporated.
Using the model, we will conduct predictive clinical trial simulations and validate the outcomes with available
clinical data. For proof-of-concept demonstration, we will rely on clinical PK data for FDA-approved mAbs (e.g.,
Adalimumab, Tocilizumab, Trastuzumab, Tefibazumab and Infliximab), and Triomabs (e.g., Catumaxomab;
Ertumaxomab). We believe that the predictive model developed under this project can be extended for predicting
First-in-Human (FiH) doses, characterize the initial exposure-response re...

## Key facts

- **NIH application ID:** 10139975
- **Project number:** 1R43FD006979-01
- **Recipient organization:** CFD RESEARCH CORPORATION
- **Principal Investigator:** Harsha Teja Garimella
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2020
- **Award amount:** $168,085
- **Award type:** 1
- **Project period:** 2020-09-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10139975

## Citation

> US National Institutes of Health, RePORTER application 10139975, A Multiscale Toolkit for Predicting Clinical Pharmacological Response of Antibody Therapeutics (1R43FD006979-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10139975. Licensed CC0.

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