Pioneering next-generation anti-angiogenesis strategies with AI-powered aptamer discovery
AI-Driven In Silico Design of Novel VEGF-Binding Aptamers
Welcome to Neoncorte Bio, a pioneering AI aptamer discovery company transforming the field of aptamer discovery and development. By integrating advanced artificial intelligence with extensive expertise in molecular biology, our team accelerates the design, selection, and optimization of aptamers customized for diagnostics, therapeutics, and biosensor applications. With deep experience in both AI and biotechnology, we provide innovative, data-driven aptamer solutions tailored to meet the specific requirements of your research or industry projects, enabling faster, more efficient outcomes in key areas such as academic research, drug discovery, and clinical diagnostics.
Problem & Need
VEGF (Vascular Endothelial Growth Factor) is a critical driver of tumor angiogenesis and pathological neovascularization in diseases such as:
- Solid tumors (colon, breast, lung, ovarian)
- Age-related macular degeneration (AMD)
- Diabetic retinopathy and retinal vein occlusion
Antibody-based VEGF inhibitors (e.g., bevacizumab, ranibizumab) have improved treatment outcomes, but key challenges remain:
- High treatment and manufacturing costs
- Limited patient response due to resistance
- Repeated injections required in ocular diseases
- Complex production and cold-chain requirements
Researchers, CROs, and biopharma developers seek novel VEGF-binding aptamers as cost-effective, specific, and stable alternatives for oncology and ophthalmology applications.
- AI-Driven Sequence Prediction and Optimization
- Custom High-Affinity Aptamers for Specific Targets
- Fast Turnaround Time with Minimal Experimental Data
Our Solution
At Neoncorte Bio, we apply AI-driven in silico design pipelines to accelerate VEGF-binding aptamer discovery:
Predictive binding affinity models
rapid screening of candidates
3D structural modeling & docking
ensures strong and stable VEGF binding
Virtual optimization cycles
test thousands of variants in silico, reducing failed experiments
Integration with lab validation
reduced SELEX rounds, lowering cost and time
Applications of VEGF-Binding Aptamers
Our VEGF aptamers can power innovation across:
Cancer immunotherapy
aptamer-based immune checkpoint inhibitors as cost-effective antibody alternatives
Companion diagnostics
aptamer-based assays to stratify patients for checkpoint inhibitor therapies
Biosensors
portable and sensitive PD-L1 detection for tumor profiling and liquid biopsy
Drug delivery
aptamer-guided delivery platforms for precision oncology treatments
Why Choose Neoncorte Bio?
Why Choose Neoncorte Bio’s AI-Driven In Silico Design of Novel VEGF-Binding Aptamers?
Rapid Discovery
Reduce discovery timelines from months to weeks
Cost Efficiency
Minimized lab work = lower R&D spend
Innovation
Proprietary platform built for aptamer design
Precision
High binding specificity for VEGF and reduced off-target effects
How Our AI-Powered Platform Works
How Does Our AI Aptamer Discovery Platform Work?
- Data CollectionWe begin by gathering data on your protein target and functional requirements.
- AI Model TrainingOur machine learning models simulate interactions between aptamer candidates and your target.
- Candidate SelectionHigh-confidence candidates are selected based on binding affinity, stability, and specificity.
- Lab ValidationValidated aptamers are fine-tuned and optimized based on experimental feedback.
Frequently Asked Questions (FAQs)
Our software leverages advanced artificial intelligence and machine learning algorithms to design and optimize aptamers—short, single-stranded DNA or RNA molecules that bind to specific targets. The tool streamlines the discovery process, reduces experimental iterations, and delivers high-affinity, specific aptamer candidates for therapeutic, diagnostic, or research applications.
Our solution is ideal for biotechnology and pharmaceutical companies, academic research labs, diagnostic developers, and any organization involved in molecular recognition and bioassay development. Whether you’re working on biomarker discovery, drug delivery, or point-of-care diagnostics, our tool can accelerate your aptamer design process.
The process begins by inputting your target molecule’s structure and desired binding characteristics. Our platform then uses deep learning models and molecular simulations to generate a library of potential aptamer sequences. These sequences are evaluated and ranked based on predicted binding affinity, specificity, and stability. You receive a prioritized list of candidates for further experimental validation.
Typically, you will need structural data of the target (e.g., protein 3D structure, sequence information) and information on desired binding properties. Our team can help guide you through the data requirements during an initial consultation.
Absolutely! Our platform is highly customizable. We work with you to tailor the AI algorithms and parameters according to your target molecule, assay requirements, and experimental constraints. Custom integration with your existing R&D workflows is also available.
Our software features API integration and standard data export options (e.g., CSV, JSON) to seamlessly integrate with your Laboratory Information Management Systems (LIMS) and data analysis pipelines. We also offer training sessions to ensure your team can easily adopt the platform.
Our AI models are trained on extensive datasets of known aptamer-target interactions and validated through iterative cycles of experimental feedback. This ensures high predictive accuracy. However, while our software provides a strong starting point, experimental validation is recommended to confirm performance in your specific application.
Yes, we provide PoC trials and collaborative validation support. We work closely with your team to validate the top aptamer candidates in your wet lab, ensuring that the predictions translate into practical, high-performance molecules.
Our pricing is tailored based on your project scope, required customization, and integration needs. We offer subscription-based models as well as project-based pricing. Please contact us for a detailed quote and consultation.
We offer comprehensive customer support that includes onboarding training, technical support via email and phone, and regular software updates. Our dedicated customer success team is available to assist you at every stage of your aptamer design journey.
Partner with us to accelerate your VEGF-targeted programs
Neoncorte Bio
Where AI Meets Biotechnology
Neoncorte Bio leads the way in integrating artificial intelligence with aptamer discovery. Our team of experts in computational biology, bioinformatics, and machine learning is committed to advancing innovation in aptamer discovery. By leveraging cutting-edge AI-driven models, we offer highly efficient, cost-effective solutions that push the boundaries of aptamer design. Our approach accelerates the identification and optimization of aptamers, allowing for rapid and precise targeting of molecular structures, whether for therapeutic, diagnostic, or research purposes. With Neoncorte Bio, in silico aptamer design reaches new heights of performance and innovation.
Publications
Explore our contributions to the forefront of biotechnology and artificial intelligence. From AI-driven enzyme engineering to deep learning applications in data analysis, our publications highlight innovative solutions to complex challenges in molecular biology and computational science.
- Modification of natural enzymes to introduce new properties and enhance existing ones is a central challenge in bioengineering. This study is focused on the development of Taq polymerase mutants that show enhanced reverse transcriptase (RTase) activity while retaining other desirable properties such as fidelity, 5′-3′ exonuclease activity, effective deoxyuracil incorporation, and tolerance to locked nucleic acid (LNA)-containing substrates.
- The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be addressed via the style transfer approach. Either technical factors or any biological details about the samples which we would like to control (gender, biological state, treatment, etc.) can be used as style components.
- List of all Neoncorte Bio publications dedicated to Molecular Biology, Biotechnology, Artificial Intelligence and Artificial Neural Networks, published mostly by Nikolay Russkikh, CEO of Neoncorte Bio
Our Expertise in Action
With extensive experience in AI applications and software engineering tailored to the life sciences, we specialize in solving complex challenges and delivering innovative solutions for our customers. Our work demonstrates a deep understanding of cutting-edge technologies and their application in the real world.
Here are examples of the types of projects we have successfully delivered:
Here are examples of the types of projects we have successfully delivered:
- Automated NGS Data Analysis:Designed a production-grade solution for the automated processing, annotation, and analysis of Next-Generation Sequencing (NGS) data.
- Single-Cell Data Integration:Built state-of-the-art tools for integrating multimodal single-cell data, achieving recognition for technical excellence.
- Metagenomic Classification Algorithms:Developed advanced methods for classifying sequencing reads in metagenomics research.
- High-Throughput Image Processing Pipelines:Engineered an efficient pipeline to process millions of sequencing images with exceptional accuracy.
- Cell Counting via AI:Created a computer vision solution for precise cell counting in microphotography images, streamlining data analysis.
Get in touch with our team
Phone: +1-503-754-3958
Email: contact@neoncorte.com
Email: contact@neoncorte.com
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contact@neoncorte.com
contact@neoncorte.com