Sample Submission Guidelines
What Is Drug Repurposing?
Drug repurposing, sometimes called drug repositioning, is a smart way to develop new therapies using existing compounds. Instead of starting from scratch, this approach identifies new disease areas where a known drug may be effective.
Because these drugs already have safety, toxicity, and pharmacokinetic data available, researchers can skip much of the early-stage development. That means faster timelines, lower costs, and fewer risks—especially when tackling urgent areas like rare diseases, cancer, or emerging infections.
Some of the biggest advantages of drug repurposing include:
- Shortening the path from lab to clinic by years
- Lowering R&D costs by up to 60% compared to traditional discovery
- Reinvigorating shelved assets or extending the lifecycle of existing drugs
- In an era of rising development costs, drug repurposing offers a practical, data-driven route to innovation.
Our Drug Repurposing Solution
A flexible strategy, built around your drug's potential.
At CD Genomics, we recognize that no two repurposing projects are alike. That's why we offer a full suite of tailored drug repositioning strategies—each designed to uncover new therapeutic value from your existing assets. Whether you're working with small molecules, biologics, or shelved compounds, we help you find faster, more cost-effective routes to market.
Our approach goes beyond static pipelines. We combine biological insight, AI-powered analytics, and pathway-driven modeling to identify high-confidence repurposing candidates aligned with your research goals and therapeutic areas of interest.
Here's how we support your drug repurposing project from multiple angles:
Drug-Centric Repurposing
Match known compounds to alternative targets or disease pathways based on mechanism of action or molecular profile.
Disease-Centric Repurposing
Identify drugs that may affect disease networks similar to your indication of interest—ideal for rare, or emerging diseases.
Target-Centric Repurposing
Focus on a biological target of interest and uncover previously approved drugs that interact with it.
Therapeutic-Centric Repurposing
Extend your product portfolio by identifying related therapeutic classes where your compound can be effective.
Large Molecule-Based Repurposing
Explore new applications for biologics, monoclonal antibodies, or peptides using omics-driven pathway analysis.
High-Throughput Indication Scanning
Use AI and data mining to rapidly evaluate your compound across hundreds of disease indications.
Veterinary Drug Repurposing
Translate human drug data into actionable insights for animal health applications.
Reformulation & Drug Combination Strategies
Enhance efficacy or reduce toxicity by exploring new dosage forms or synergistic combinations.
Drug Lifecycle Management Strategies
Maximize ROI by identifying new markets, extending exclusivity, or repositioning aging assets for unmet needs.
Our Bioinformatics Approach
Bringing data, biology, and AI together to power in silico drug repurposing.
At the core of our drug repurposing services is a robust computational bioinformatics pipeline—purpose-built to reveal novel drug-disease relationships through integrated omics analysis, machine learning, and network modeling.
We don't rely on a single data source or algorithm. Instead, we merge multiple layers of biological evidence—gene expression, structure, interaction, and phenotype—into a unified framework that guides confident repositioning decisions. Whether you're screening hundreds of compounds or validating a single asset, our approach gives you the clarity to move forward.
Here's how we do it:
Transcriptomic Signature Matching: Identify compounds with gene expression profiles similar to those known to be effective for the target indication.
Gene Expression Profiling & Pathway Enrichment: Reveal relevant biological pathways and disease mechanisms influenced by your candidate compound.
Structural and Molecular Similarity Modeling: Compare your compound's structure to known drugs to infer likely activity or off-target effects.
Drug-Target-Disease Network Mapping: Visualize and analyze connections between chemical entities, molecular targets, and disease phenotypes using graph-based models.
Curated Drug Repurposing Databases: Integrate proprietary and public datasets to support data-rich prioritization strategies.
Machine Learning for Prediction & Prioritization: Leverage AI models to forecast which compounds are most likely to succeed based on historical and experimental data.
Literature and Public Database Mining: Mine scientific publications, clinical trials, and pharmacovigilance sources to extract actionable insights.
Our Workflow
A flexible pipeline tailored to your data, goals, and timelines.
- Consultation & Data Intake
We align on your goals, target indications, and available data (in-house or public).
- Data Preprocessing
Raw datasets are cleaned and normalised to ensure analysis quality and consistency.
- Signature & Similarity Analysis
We extract transcriptomic and molecular signatures, then match them to known disease profiles.
- Mechanism of Action Prediction
Pathways and biological targets influenced by the compound are mapped and interpreted.
- Candidate Prioritisation
Using AI models, we score and rank repurposing opportunities based on biological relevance and novelty.
- Report Delivery
Results are provided in a secure, interactive HTML report—ready to guide your next research step.
Key Advantages
Why researchers and developers choose CD Genomics
🔹 Rapid, AI-Driven Analysis
Automated algorithms accelerate candidate discovery and indication mapping.
🔹 Reduced Cost & Risk
Lower R&D investment compared to de novo drug development paths.
🔹 Mechanism-Based Predictions
Insights grounded in biological pathways and molecular targets.
🔹 Flexible Data Inputs
Supports raw or pre-processed data from internal or external sources.
🔹 Fully Documented & Reproducible
Every result includes method traceability and versioned pipelines.
🔹 Scalable for Any Project Size
Customizable for startups, academia, and large pharma workflows.
🔹 Research-Use Only
No clinical claims or regulatory hurdles—ideal for early-phase exploration.
Deliverables
Clear, actionable outputs to guide your next move.
Interactive HTML Report
A secure, password-protected report hosted on our server. Fully clickable, searchable, and structured for easy navigation—no specialized software required.
Ranked List of Repurposing Candidates
Each candidate is scored by biological relevance, transcriptomic similarity, structural fit, and machine learning–based repurposing potential.
Mechanism of Action Summary
MoA hypotheses for each candidate, supported by pathway analysis, known targets, and literature references.
Visualizations & Network Maps
Pathway enrichment diagrams, drug–target–disease interaction networks, and clustering heatmaps—ready for presentation or publication.
Full Methodology Documentation
A clear record of tools, parameters, databases, and scoring models used—ensuring full reproducibility and regulatory transparency.
Optional Add-ons
Custom formatting (e.g. Excel export), downstream analysis recommendations, or consultative review sessions can be included on request.
Why CD Genomics?
A partner built for data-driven drug discovery.
- 15+ years of expertise in omics and computational biology
- Customizable workflows tailored to your compound and indication
- Secure, confidential, and research-use-only service model
- Interactive, publication-ready deliverables backed by biological rationale
- Trusted by global pharma, biotech, and academic institutions
Whether you're rescuing shelved compounds, exploring new markets, or supporting IP filings, CD Genomics delivers the insight—and flexibility—you need to move forward with confidence.
Frequently Asked Questions
Q1: What kind of data do I need to provide?
We accept a wide range of input formats, including raw gene expression data (e.g., FASTQ, CEL), preprocessed expression matrices, or compound information such as SMILES structures. If no in-house data is available, we can help you source relevant public datasets.
Q2: Can you work with shelved or underperforming compounds?
Yes. Our platform is specifically designed to identify new indications for existing compounds—including shelved, off-patent, or low-priority assets—by leveraging transcriptomic signatures, structural similarity, and AI scoring models.
Q3: Is this a clinical service?
No. All of our drug repurposing services are for research use only. We do not offer clinical validation, regulatory submission, or diagnostic applications.
Q4: Do I need bioinformatics expertise to use your service?
Not at all. We handle all computational work—from data cleaning to advanced analysis—and provide user-friendly, fully documented reports that are ready for internal or external presentation. Our team is available to walk you through the results.
Q5: What makes CD Genomics different from other providers?
We combine advanced bioinformatics with a highly customizable workflow. Unlike generic platforms, we tailor every project to your data and therapeutic goals—backed by deep biological interpretation, reproducibility, and responsive technical support.
Q6: Do you support follow-up analysis or ongoing projects?
Yes. We offer optional consulting sessions, add-on analyses, and support for integrating our results into your ongoing research or licensing strategies.
Q7: I don't have a complete dataset—can I still use your service?
Yes. We can work with partial datasets, historical data, or even begin from compound structures alone. If needed, we help identify and retrieve relevant public transcriptomic or structural data to support your project.
Q8: How actionable are the results? Can I use them to justify internal decisions or funding applications?
Absolutely. Our deliverables include fully traceable evidence, pathway-backed hypotheses, and prioritised candidates with scoring rationale. They are widely used in internal R&D reviews, grant proposals, and early-stage asset positioning.
Q9: How much input is required from my team during the project?
Minimal. After our initial consultation, we take care of the bioinformatics pipeline. You'll be updated at key milestones, and we provide a final interactive report with optional review sessions if needed.
Q10: Can I choose specific diseases or targets to focus on?
Yes. You can define disease areas of interest, target classes, or biological mechanisms you'd like us to prioritise during analysis. Our strategy is highly customizable to your R&D roadmap.
Q11: Will I be able to understand and present the findings to non-bioinformatics stakeholders?
Yes. Our reports are designed for multidisciplinary teams. Visuals, scoring breakdowns, and plain-language summaries make it easy to present findings to management, collaborators, or investors.
Q12: Is there a risk of data sharing or IP exposure?
No. All client data is handled under strict confidentiality. We operate under NDAs, use secure servers, and do not share or reuse your data in any form.
Q13: Can your service support patent strategy or licensing efforts?
Yes. Many clients use our insights to identify new IP claims (e.g., for new indications or combinations), support 505(b)(2) pathways, or strengthen out-licensing packages with validated repurposing logic.
References:
- Pushpakom S, Iorio F, Eyers PA et al. "Drug repurposing: progress, challenges and recommendations." Nature Reviews Drug Discovery 18, 41–58 (2019).
- Ashburn TT & Thor KB. "Drug repositioning: identifying and developing new uses for existing drugs." Nature Reviews Drug Discovery 3(8), 673–683 (2004).
- Pan X, Lin X, Cao D et al. "Deep learning for drug repurposing: methods, databases, and applications." arXiv:2202.05145 (2022).
