Accelerate Innovation | Reduce Costs | Optimize Performance

AI-Powered Enzyme Engineering for Biotech Startups

Biotech startups face high R&D costs, lengthy development cycles, and unpredictable enzyme performance. Our AI-powered enzyme engineering service provides a smarter, faster, and more cost-effective approach to optimizing and discovering new enzymes for your applications.

  • 50% Faster Development – AI reduces enzyme discovery time from years to months
  • 30% Cost Savings – AI-driven optimization minimizes lab experiments & production costs
  • 2x Improved Enzyme Performance – Enhanced stability, activity, and specificity tailored to your needs
enzyme engineering biotech startups

What is Machine Learning in Enzyme Engineering?


Machine learning has transformed enzyme engineering by using large datasets and predictive models to simulate enzyme behavior, optimize functionality, and streamline discovery. Traditional trial-and-error methods can be time-consuming and costly, but AI-driven approaches unlock faster, more precise results.

  • Predictive Algorithms: AI models predict how enzyme mutations affect performance, stability, and activity.
  • Data-Driven Engineering: Machine learning analyzes molecular and biological data to design highly effective enzymes for specific tasks.
  • Rapid Screening: With AI, we can simulate and evaluate millions of enzyme variants in silico, reducing experimental load and time.

Our AI-Powered Enzyme Engineering Services:

  • Custom Enzyme Design
    AI-based design tools create custom enzymes optimized for your specific industrial applications.
  • High-Throughput Screening with ML
    Machine learning accelerates enzyme screening by predicting the performance of enzyme libraries, focusing on the most promising candidates.
  • Optimization of Existing Enzymes
    Improve existing enzyme efficiency, stability, and activity using AI to simulate modifications and enhance enzyme properties.
  • Enzyme Data Modeling
    Utilize machine learning models to predict enzyme-substrate interactions, guiding the design of more effective enzymes.

Applications for Biotech Startups:

Pharmaceuticals
Biotechnology
Biofuels
Food production

Why Choose Our AI-Enzyme Engineering

Significant time and cost savings in R&D
Custom-tailored enzyme properties for specific needs
Increased enzyme efficiency and stability
Accelerated path to commercialization
Optimization of cellulase variants Neoncorte Bio AI/ML protein enzyme engineering company
Optimization of cellulase variants
Frequently Asked Questions (FAQs)

Transform your biotech R&D with AI-powered enzyme engineering

Let’s collaborate to make protein & enzyme R&D faster, cheaper, and more effective

Neoncorte Bio

Where AI Meets Biotechnology
Neoncorte Bio is at the forefront of the convergence between artificial intelligence and enzyme engineering. Our team comprises experts in computational biology, bioinformatics, and machine learning, all driven by a mission to accelerate innovation in enzyme design. By leveraging our advanced AI models, we provide unparalleled solutions that enhance efficiency, reduce costs, and push the boundaries of what's possible in enzyme engineering

Publications

Scientific Publication of Neoncorte Bio Team
  • 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:
  • 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