# Machine Learning for Drug Response Prediction

> **NIH NIH R35** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $407,965

## Abstract

Abstract
 Modeling cell type-specific responses to drugs is an important yet challenging topic in drug
development and personalized medicine. Our research program has developed a suite of algorithms for
predicting cell-line level drug responses, and seeks to address the next-step questions in improving the
transferability of predicting cell type-specific and combinatorial drug responses. Our goal over the next five
years is to tackle the following three major challenges that hinder the transferability of drug response
models. The first challenge is delivering drug response models across datasets generated by different
platforms and labs. The second challenge is transferring drug response predictions from in vitro systems
to humans. The third challenge is the heterogeneity of the samples, which can hinder the effectiveness of
targeted therapy due to the acquisition of mutations and the evolution of tumors to evade the immune
system. To address these challenges, we will focus on improving the robustness of models across
datasets by establishing coherence networks of drugs. We will leverage and fine-tune large language
models to refine our collection of literature-based drug information and extract new features for drugs. We
will also explore the possibility of using the heterogeneity of the samples to improve the accuracy and
robustness of drug response models. Overall, we envision that our research program will contribute to
personalized medicine and expedite the drug development process.

## Key facts

- **NIH application ID:** 10836685
- **Project number:** 2R35GM133346-06
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Yuanfang Guan
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $407,965
- **Award type:** 2
- **Project period:** 2019-09-01 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10836685

## Citation

> US National Institutes of Health, RePORTER application 10836685, Machine Learning for Drug Response Prediction (2R35GM133346-06). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10836685. Licensed CC0.

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