A very important aspect of gene editing is to avoid off target effects. Established biopharma companies have the volume and resources to exhaustively test CRISPR guide RNAs using whole genome sequencing. Ideally using patient's cells, as everyone's genome is unique and thus offers unique opportunities for off-target effects.
Bio-engineering offers fascinating possibilities, but also deep ethical pitfalls. A further problem, the legal environment is often not defined, or at least official interpretation of local laws are still pending. If pharma companies want to follow this path, they need a strong Ethics & Compliance department.
Gene mutations are a part of normal biology. It has now been developed into a tool, and as with all tools, it can be used well or badly, to a benefit or to harm. (The use and misuse of nuclear power might be a relevant parallel here.)
The main issue is that science does not understand well enough what each gene does and even less how functions of various genes overlap. Consequently, gene manipulations are at present a game of a “blind leading the blind”, and is likely to remain this way for some time. As to the actual outcome of gene modification in humans, it is a game of roulette; will your number come up?
Pharma industry might be well advised to consider gene editing as a part of the overall concept of precision / personalized medicine.
As we learn more about the impact of CRISPR technology on healthcare delivery and outcomes, it is likely that large drug companies will want to be in the business of offering highly individualized treatments for specific ailments, especially as the technology overtakes the need for medications where they currently make their profits.
CRISPR technology has at it's heart the promise of a robust shared database of trials and results for any conceivable disease. If ould reduce surgeries, impact short and long term treatment plans, and holds the promise of reducing healthcare costs significantly. Stay tuned and watch emerging developments impact our future.
It may be too early to consider applications of AI to technologies such as CRISPR shaping future healthcare delivery infrastructure and insurance business. However, AI could and should be used to resolve technical issues such as off-target effects of CRISPR and subsequent serious side effects, efficacy of homology-directed repair, viability of edited cells, immunogenicity of therapeutic components, and also in vivo efficiency etc. when translated from animal models to clinical studies.