To say the world of gene therapy has come on leaps and bounds in the last couple of decades would be a gross understatement. The early approaches to gene addition were fairly rudimentary, consisting of thrusting healthy copies of a gene into a cell in the hope that the cell would produce enough functioning protein to compensate for the mutated ones. A sort of hit-and-hope tactic that never actually dealt with the root cause mutation.
Through the evolution of targeted gene cutting and gene editing, and with the serendipitous discovery of CRISPR/Cas9, we have today reached the stage of precision genome-wide editing. With this drastic optimisation of protocol and technology comes the inevitable boom of capitalist ventures looking to profit from it. However, there are still problems to be solved.
Companies in the field are currently working on solving these in a number of ways. The further development of viral vectors, non-viral vectors and taking advantage of delivery outside the body (ex-vivo) are helping improve transport of the genes to their target, tackling delivery issues.
Once inside the cell, the current batch of gene editing tools have relatively high rates of off-target effects, potentially triggering immunogenicity and low conversion of treatment to desired outcome. Protein engineering allows the alteration of the nuclease, an enzyme that acts as the pair of biological scissors to cleave the DNA target site during the CRISPR process, increasing the efficiency of the technique and creating the next generation of CRISPR technologies, CRISPR 2.0.
Utilising artificial intelligence and data mining will facilitate the creation of new algorithms and software tools to optimise the design of new gene editing components such as guide RNA, and machine learning programmes will help predict the interaction of these new tools with the biology of the target cells. There is also a hope that computational meta-genomic analysis will throw up biological tools even more useful than CRISPR, after all if we know what we are looking for this time, who knows what we may uncover.
The bottlenecks in this field often occur in the manufacturing stage, which is why innovation in this area is of paramount importance. The automation of the workforce will allow the use of high through-put systems, and along with supply chain innovation should expedite the pipeline from research to clinical practice.
As the economics, technology and infrastructure of these incredible treatments continue to develop, a future where the latest in gene editing tools are employed across the globe to help battle the most devastating diseases is coming ever closer.
Engineering the Genome: Challenges and Opportunities in the Next Wave of Medicine: https://a16z.com/2019/10/05/engineering-the-genome-challenges-and-opportunities-in-the-next-wave-of-medicine/