
AI-POWERED
DNA ENGINEERING
The Software Engine for Scalable Protein Production
MNDL BIO ENABLES SCALABLE PROTEIN PRODUCTION BY OPTIMIZING DNA
Technology Features
Physics-Guided AI
Fusing biophysical modeling with advanced machine learning to navigate DNA sequence space and optimize expression beyond simple codon usage.
Whole-Construct Design
Engineering the entire genetic system, tuning mRNA folding and ribosomal traffic, to drive consistent, high-yield production in any host.
Proven Scalability
Validated across dozens of organisms and high-value verticals, including antibodies, industrial enzymes, and AgTech, with documented yield improvements.
Selected Case Studies
Solving Expression Bottlenecks with Smart Genetic Design
FGF expressed in
P. pastoris

Challenges in the expression and downstream processing of growth factors represent a significant hurdle for the biotechnology and next-generation food sectors. Efficient expression of these proteins is essential for the economic feasibility and scalability of modern biomanufacturing. To address these limitations, MNDL Bio collaborated with a multidisciplinary academic team to investigate new pathways for maximizing the production of a critical growth factor. The project focused on Pichia pastoris, a highly desirable host due to its robust ability to secrete post-translationally modified proteins. The primary objective was to engineer genetic variants that could surpass current expression benchmarks. MNDL Bio applied its proprietary biophysical and generative AI models to both the coding (CDS) and non-coding sequences of the target protein. By analyzing the interplay between sequence structure and host-specific translation dynamics, we engineered 12 genetic variants specifically designed for maximal expression in P. pastoris. The results demonstrated the transformative power of AI-driven design. Notably: - Expression Boost: One engineered variant achieved a 2.5x greater median expression level compared to the wild-type sequence. - Sequence Integrity: Optimized yields were achieved while strictly preserving the integrity and functionality of the target protein. Our methods transcend traditional "simple" optimization protocols by integrating biophysical constraints that influence the entire translation lifecycle.
mAb expression in CHO cells

A biotechnology partner developing RNA-targeted therapies for non-small cell lung cancer (NSCLC) faced a significant technical bottleneck. They required high-titer production of a specific monoclonal antibody (mAb) in Chinese Hamster Ovary (CHO) cells. The antibody's coding sequence had already been processed by standard optimization platforms. The expression had reached a plateau, where traditional codon-based methods could no longer provide incremental gains. To progress, the partner needed a breakthrough that surpassed the industry-standard benchmark. MNDL Bio was recruited to apply its deep, data-driven expertise to resolve this stagnation. The project focused on moving beyond the coding sequence (CDS) alone to unlock hidden expression potential within the genetic architecture. Unlike traditional tools that focus strictly on codon usage bias, MNDL Bio’s proprietary algorithms analyze the interplay between the coding and non-coding regions. We modeled the biophysical constraints of the entire transcript to improve mRNA stability and translation efficiency. The design was specifically tuned to the metabolic and regulatory environment of the CHO host. The optimization was performed while maintaining 100% amino acid sequence fidelity, ensuring the resulting antibody's functionality and binding affinity remained unchanged. The MNDL Bio-optimized sequence was benchmarked in a head-to-head trial against both the wild-type and a competitor-optimized version. Analytical testing confirmed that the increased yield did not compromise protein folding, solubility, or therapeutic activity.
15 kDa Protein in a Bacterial System

In a project for a commercial client operating in a highly cost-sensitive sector, MNDL Bio was tasked with enabling scalable expression of a ~15 kDa recombinant protein using an E. coli-based cell-free expression system. The native (wild-type) sequence yielded negligible protein levels, making it unsuitable for production-scale workflows. To address this, MNDL deployed a suite of its proprietary optimization algorithms — combining machine learning, deep learning, and biophysical models — to generate and test multiple synthetic variants of the gene. The results were striking: several of MNDL’s designed sequences achieved a ~9.5- to 15-fold increase in protein expression compared to the original sequence. This dramatic improvement underscores the platform’s ability to overcome fundamental expression challenges in cell-free systems — an increasingly attractive alternative to live-cell expression for rapid prototyping, diagnostics, and precision biomanufacturing. In industries where protein cost directly affects product viability, such expression gains can meaningfully shift the economics of production. MNDL’s ability to deliver such performance without compromising sequence fidelity or function demonstrates its critical value in accelerating the development of high-efficiency bioproducts in next-generation manufacturing systems.
Leadership
Dedication. Expertise. Passion.
Our team unites leading expertise in AI and biophysical modeling with proven business and R&D leadership. Together, we are productizing breakthrough AI to redefine the limits of gene expression and protein production.
Research Powering Our Solutions
Read about our peer-reviewed publications, science and magic.
Our Sectors
MNDL can assist with medical, agriculture, pharmaceutical, clothing, etc.
Medical
MNDL can assist with medical, agriculture, pharmaceutical, clothing, etc.
Pharmaceutical
MNDL can assist with medical, agriculture, pharmaceutical, clothing, etc.
Agriculture
MNDL can assist with medical, agriculture, pharmaceutical, clothing, etc.
Clothing
MNDL can assist with medical, agriculture, pharmaceutical, clothing, etc.
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