Clinical and Translational Science Institute
Advancing today’s discoveries to improve health for all.

Pharmacology Knowledge Base

Doctor looking at pill boxes

Pharmacology Knowledge Base

  • MPRINT-KP Silver

    The Maternal and Pediatric Precision in Therapeutics (MPRINT) knowledge base is a crucial maternal and pediatric research informatics infrastructure. The silver version of the MPRINT knowledge base aims to assist researchers in discovering published maternal and pediatric research easily and quickly. The deep-learning model was trained using a comprehensive maternal and pediatric study corpus. Subsequently, PubMed abstracts were thoroughly screened using the established deep learning model to predict the publication study types and relevant populations. Users can retrieve studies based on the drugs, diseases, specific populations, and study types. 

    Reference: PMID: 36625779, https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2835

    Contact: Lang Li

  • MPRINT-KP Gold

    The Maternal and Pediatric Precision in Therapeutics (MPRINT) knowledge base is a crucial maternal and pediatric research informatics infrastructure. The gold version of the MPRINT knowledge base aims to provide expert-curated knowledge from published maternal and pediatric studies. It primarily provides drug pharmacokinetic parameters and epidemiological evidence. Each piece of knowledge is well-annotated with relevant information, including demographic information, therapeutics, and other risk factors.

    Reference: PMID: 36625779, https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2835

    Contact: Lang Li

  • DrugCombo

    DrugCombo is a comprehensive knowledge base that integrates drug toxicity and pharmacokinetic data for single drugs and drug combinations from the United States Food and Drug Administration Adverse Event Report System (FAERS), drug labeling from the National Library of Medicine’s DailyMed website, published study results in PubMed, and the DrugBank database. DrugCombo is the first database to contain crucial data, such as the maximum tolerable dose (MTD), dose-limiting toxicity (DLT), and dose range, for Phase I clinical trial design.  It also provides pharmacokinetic evidence of drug interactions between cancer drugs and other relevant knowledge. DrugCombo currently integrates 8577 drug/target interactions and 8797 drug interactions from DrugBank, 3995 severe adverse drug events (ADEs), 95,535 common ADEs from drug labels, 1,816,030 ADEs from FAERS, and MTD and DLTs from 2592 Phase I trials.

    Reference: https://doi.org/10.1158/1538-7445.AM2023-6573 , https://doi.org/10.1200/JCO.2023.41.16_suppl.1571 

    Contact: Lang Li

  • SLKB

    Synthetic lethality knowledge base (SLKB) is dedicated to curating CRISPR double knockout experiments (CDKO) aiming to identify synthetic lethal (SL) interactions between two genes. SL identification is highly context dependent, differing across pathways, gene targets, cell lines, and CDKO libraries. SLKB analysis pipeline, additionally distributed as a python package, allows SL score calculation for CDKO studies. Via SLKB, users can analyze their own CDKO data and browse their results.

    Reference: PMID: 37889037

    Contact: Lang Li

  • CTKG

    CTKG is a knowledge graph integrating a wide variety of information from clinical trials (e.g., interventions, drug side effects, disease symptoms). Together with computational tools to learn from knowledge graphs, CTKG faciliates knowledge discovery from clinical trials, and many relevant tasks such as information retrieval, drug repurposing, etc. 

    Reference: PMID: 35304504

    Contact: Xia Ning, Access Ning Lab

  • DRKG

    DRKG is a very large and comprehensive knowledge graph integrating a wide variety of entities, including drugs, diseases, symptoms, genes, proteins, etc. Together with computational tools to learn from knowledge graphs, DRKG facilitates drug repurposing, among other tasks such as information retrieval, etc. 

    Reference: https://github.com/gnn4dr/DRKG/blob/master/DRKG%20Drug%20Repurposing%20Knowledge%20Graph.pdf 

    Contact: Xia Ning

Natural Language Processing

Person displaying data

Natural Language Processing (NLP)

  • BioBERT

    BioBERT is Bidirectional Encoder Representations from Transformers for Biomedical Text Mining. It is a domain-specific language representation model pre-trained on large-scale biomedical corpora. BioBERT significantly outperforms many text mining methods on the following three representative biomedical text mining tasks: biomedical named entity recognition, biomedical relation extraction and biomedical question answering.

    Reference: PMID: 31501885

    Contact: Lang Li

  • BERT

    BERT is a transformer-based model that employs bidirectional training of Transformer encoders to achieve state-of-the-art performance in numerous natural language processing tasks at the time of its introduction. The development of BERT laid the groundwork for current generations of large language models, serving as a proof of concept for bidirectional transformer architectures. BERT is built upon the attention mechanism but deviates from the original encoder-decoder structure by focusing solely on the encoder. Its architecture consists of multiple layers of bidirectional self-attention and is pre-trained on a large corpus of text, including the entire Wikipedia and BookCorpus. BERT's key innovation is its ability to capture context from both directions, allowing for a deeper understanding of language semantics.

    Reference: https://arxiv.org/abs/1810.04805

    Contact: Lang Li

  • PubBERT

    PubBERT is a variant of BERT specifically fine-tuned on a corpus of biomedical literature, such as PubMed articles, to enhance its performance in biomedical text processing tasks. This adaptation allows PubBERT to better understand and generate language pertinent to the biomedical field, improving upon the general BERT model for domain-specific applications.

    Contact: Lang Li

  • Llama 2

    Llama 2 is a series of large language models by Meta AI, designed for various NLP tasks, available in three sizes: 7 billion, 13 billion and 70 billion parameters.

    Reference: https://arxiv.org/abs/2207.06947

    Contact: Ping Zhang

  • Mistral

    Mistral is an advanced language model designed for various natural language processing tasks, available in two sizes: 7 billion and 8x7 billion parameters.

    Reference: https://arxiv.org/abs/2307.02022

    Contact: Steve Rust

  • Mixtral

    Mixtral combines multiple 7 billion parameter models to enhance performance across various NLP tasks.

    Reference: https://arxiv.org/abs/2307.02022

    Contact: Steve Rust

  • Phi 2

    Phi 2 is a powerful language model designed for natural language understanding and generation.

    Reference: https://arxiv.org/abs/2306.11692

    Contact: Steve Rust

  • Flan-T5

    Flan-T5 is a fine-tuned language model from Google, optimized for various NLP tasks, available in sizes Lg 780M and XXL 11B.

    Reference: https://arxiv.org/abs/2210.11416

    Contact: Steve Rust

  • Falcon

    Falcon is a high-performance language model optimized for speed and efficiency, available in sizes 7 billion and 40 billion parameters.

    Reference: https://arxiv.org/abs/2208.13269

    Contact: Steve Rust

  • GatorTron

    GatorTron is a biomedical language model developed by the University of Florida, available in sizes S 345M, Medium 3.9B, and Large 9B.

    Reference: https://arxiv.org/abs/2207.07177

    Contact: Steve Rust

  • RoBERTa

    RoBERTa (Robustly optimized BERT approach) is a transformer-based model that improves on BERT by training with larger mini-batches and more data.

    Reference: https://arxiv.org/abs/1907.11692

    Contact: Steve Rust

  • Phi 3

    Phi 3 is the latest iteration of the Phi series, designed for advanced natural language processing and understanding.

    Reference: https://arxiv.org/abs/2308.11239

    Contact: Steve Rust

  • MPT

    MPT is a versatile transformer model available in sizes 7 billion and 30 billion parameters, designed for a wide range of NLP tasks.

    Reference: https://arxiv.org/abs/2307.11590

    Contact: Steve Rust

  • OPT

    OPT (Open Pre-trained Transformer) is a series of transformer models designed for various NLP tasks, available in multiple sizes.

    Reference: https://arxiv.org/abs/2205.01068

    Contact: Steve Rust

Clinical and Translational Science Pilot Program Ideation Session 2

Clinical and Translational Science Pilot Program Ideation Session 1

AI Informatics Tools

computer chip displaying artificial intelligence

AI Informatics Tools

These tools enable researchers to store, analyze and use data to improve healthcare by enhancing efficiency, maintaining accuracy and collaborating effectively throughout their projects. 

Doctor holding graphic of AI
AI for Drug Development
Data being organized
Bioinformatics Data Analysis Pipeline
Person putting data in the cloud
Cloud Infrastructure Development
Person using mobile health application
Dashboard and Mobile Health Application
Doctor using electronic health record
Electronic Health Record (EHR) Predictive Analytical Models
Person using AI assistant
Generative AI
People looking at charts
Image Data Analytics
Person displaying data
Natural Language Processing (NLP)
Doctor looking at pill boxes
Pharmacology Knowledge Base

Need Data Support?

The Ohio State University offers numerous data sources for researchers, but effectively navigating these resources can be daunting. To assist faculty and staff in this process our Data Navigator acts as the first point of contact. The Data Navigator provides a high-level explanation of regulatory and institutional processes regarding these databases, identifies potential collaborators and addresses initial data-related questions. The navigator helps clarify requests, coordinates efforts and links investigators with domain experts for different data sources.

Contact the Data Navigator

T32 Postdoctoral

T32 Predoctoral

Grant Writing Programs

People studying at Thompson Library

Grant Writing Programs

The CTSI offers a variety of grant writing programs to help researchers at all career stages develop competitive proposals and secure funding for their translational science projects. Whether you are a junior investigator seeking your first grant, a mid-career researcher looking to expand your skills and network or a senior faculty member willing to mentor the next generation of translational scientists, we have a program that suits your needs. 

person working at computer

Grant Writing Office Hours

Do you need expert advice on an aspect of a grant you are writing? You can find it at the CTSI Grant Writing Office hours. Drop-in on Zoom or In-Person at the appointed time, and an experienced and well-funded investigator will discuss your questions with you.

Two women working together

Launch to K

A specialized program that focuses on the specific requirements and expectations of NIH K awards, which support career development and mentored research of clinician-scientists.

Two people working on a computer

Launch to R

A comprehensive program that provides individualized coaching, peer feedback and expert guidance to junior faculty who are preparing their first R grant application.

 

New Name for Translational Science Center

This change reflects our commitment to serve the entire clinical and translational research community across Ohio State and at Nationwide Children’s Hospital. As the CTSI, our commitment to delivering resources, fostering collaborations, supporting the careers of clinical and translational scientists, particularly those who are early in their career, and helping identify efficiencies to accelerate clinical and translational science remains steadfast. 

This new name designation underscores our dedication to more comprehensively support the full spectrum of clinical and translational research within our community and aligns with many peer CTSA hubs nationwide. We are excited about the work and milestones achieved since the CCTS was established in 2006 and anticipate even greater accomplishments under the banner of CTSI.

“For the past two decades, the institute has been an impactful resource to the scientific and research community at Ohio State,” said Julie Johnson, PharmD, Clinical and Translational Science Institute director, associate dean for clinical and translational research in The Ohio State University College of Medicine and associate vice president of research for The Ohio State University. “Our aim moving forward is to more fully serve the entire clinical and translational research community on campus and at Nationwide Children’s Hospital and to facilitate and streamline research discoveries that improve health for all.”

Julie Johnson, PharmD, is the Director and Principal Investigator at The Ohio State University Clinical and Translational Science Institute. 

K12 Mentored Career Development Grant

Two researchers in a lab

K12 Mentored Career Development Grant

The CTSI K12 Mentored Career Development Grant funds early career investigators to conduct clinical or translational research and develop their research skills as they progress to be independently funded researchers.

K12 Important Dates

Release Date

September 10, 2025

Download the K12 RFA

Letter of Intent Due

October 26, 2025, 11:59 p.m.

Full Application Due

December 16, 2025, 11:59 p.m.

Submit an Application

Study Section

February 2026

Notice of Award Date

March 2026

​​The CTSI K12 supports the career development of investigators committed to clinical and translational research.

The K12 program is designed to develop a cadre of well-trained early-stage faculty investigators from across the health and biomedical sciences through individualized training to engage fully, succeed and lead in translational research and science. The training programs and educational infrastructure will foster a pipeline of early career clinician scientists with training that promotes scientific curiosity and discovery. We will sustain and enhance a culture in which translational scientists can collaborate to accomplish trans-disciplinary research that results in improved clinical outcomes.

The K12 program is open to any assistant professor engaged in clinical or translational research or science, who has less than three years of service in that role at the time of appointment. The K12 Award is available for a period of three years (contingent on satisfactory progress), with two years of CTSI funding and a third from the scholar’s home college/department.

The Ohio State CTSI seeks proposals that address scientific questions consistent with our mission to fund research across the Translational Spectrum: the biological basis of health and disease, interventions that improve the health of individuals and the public, and health outcomes research.

K12 Mentored Career Development Grant

Letter of Intent is Due October 26, 2025
Download the K12 RFA
Two men walking outside

K Workgroup Leaders

K. Luan Phan, MD

luan.phan@osumc.edu

K. Luan Phan headshot

Cynthia Carnes, PharmD, PhD

carnes.4@osu.edu

Cynthia Carnes headshot

Loren Wold, MD

loren.wold@osumc.edu

Loren Wold headshot
Subscribe to