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Genetic medicines such as cell and gene therapies and mRNA vaccines offer extraordinary promise for treating a variety of diseases, including genetic disorders, cancer, and autoimmune diseases. These therapies are made possible by the growing field of synthetic biology, which applies design principles and machine learning advancements to reengineer biological systems by manipulating the code of life, DNA, to encode a certain biological function. Each piece of DNA can be long and complex, and to achieve the desired function, they must be accurate. The potential for breakthroughs is immense— but despite the excitement, challenges remain that must be addressed to fully unlock the potential of these next-generation therapies.
The Complexity of Therapeutic Development
Synthetic biologists have embraced the design-test-build-learn (DTBL) approach from software engineering to build the prerequisite understanding of intricate biological systems to reengineer biology. This approach has led to remarkable advancements in simpler systems like bacterial and yeast models where organism function can be accurately predicted based on DNA sequence manipulation. For example, scientists have altered the function of corn to grow faster and in new climates, produced heme to make plant-based meats, and caused a mosquito colony to collapse using genetic engineering. The possibilities across synthetic biology are immense; however, translating these findings into more complex organisms that are used in therapeutic development (ranging from immortalized cell lines to animal models and, eventually humans) poses unique challenges. The scientific community doesn’t lack innovative ideas; the current limitation is the scientific tools to reliably build at scale better predicted clinical outcomes from early discovery data.
DNA Write: Limits of Traditional DNA Synthesis
Technologies to sequence (read) DNA have greatly outpaced our ability to synthesize (write) DNA, causing a bottleneck in our ability to convert genomic findings to functional outcomes. For the past 40 years, phosphoramidite or chemical synthesis has enabled scientists to write custom short DNA sequences. These short DNA sequences or oligonucleotides are the foundation of molecular biology, enabling the PCR and NGS revolutions which have deepened our understanding of biological systems.
Built on these core technologies, scientists have been assembling these short oligos together to build larger genetic constructs. While gene synthesis technology has greatly enabled our ability to manipulate the code to life, it isn’t without its challenges. Chemical synthesis damages DNA as it is synthesized, causing limitations in length and the specific patterns of A/C/G/T that can be produced. Sequence patterns like extreme GC content, long repetitive sequences, or homopolymers are extremely difficult or impossible to make with short pieces.
The types of genetic constructs scientists struggle to build are not only long, but also contain highly complex elements. Inverted terminal repeats (ITRs) are critical to transcription in AAVs; extremely repetitive sequences are common to CRISPR arrays, and fixed-length poly A tails and structured untranslated regions (UTRs) in mRNAs to name a few examples. Sourcing these sequences can be impossible or take months of development time, slowing the DTBL cycle and lengthening time-to-market for therapies.
Fully Enzymatic Synthesis: Unlocking the Future of Genetic Medicines
To overcome these challenges, Molecular Assemblies has developed a Fully Enzymatic Synthesis™ (FES™) technology powered by a template-independent polymerase to build DNA from the ground up with best-in-class oligonucleotide building blocks. Consider the difference in efficiency required to assemble a jigsaw puzzle broken up into thousands of identical small pieces vs. several large distinguishable ones. Unlike traditional chemical synthesis, FES can build long and accurate sequences regardless of complexity, enabling the reliable construction of the most difficult sequences. With these advancements, scientists can move faster, iterate more effectively, and bring transformative therapies to life, accelerating the path from discovery to real-world impact.
What can FES enable in your research?
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