The Next Industrial Revolution: Human Manufacturing
It’s time. It’s time for us to finally start putting humans on the conveyor belt. We finally won our ticket to the assembly line and now we are approaching an era where we are finally going to start seeing the beginning of human manufacturing.
Not quite literally, yet, but with 2019, we are going to start seeing the convergence of technologies in improved genetic analysis and modification techniques like CRISPR, pumped into an eco-system of rapidly evolving machine learning for experimentation & prototyping and finally meticulously put through the modern smart drug delivery techniques to be able to control the genetic code of our species. By 2021, Frost & Sullivan expects that artificial intelligence (AI) systems will generate $6.7 billion in revenue from healthcare globally. Furthermore, the precision medicine market is forecast to grow at a CAGR of 10.5% over the period of 2016–2023, hitting USD 87.7 billion by 2023.
Are we the instrument or product?
In 1913, Henry Ford put humans behind the conveyor belt to make machines. Now, finally, those machines will sit behind watching us on the conveyor belt. Surprised? I am too, but, if you are a programmer you will understand exactly what I mean.
Humans are simply the genomic code that is naturally programmed by the process of natural selection, mutation and evolution. Like agile software development, we were designed, implemented, tested and constantly iterated on. Our diseases are our bugs, but, what we lacked was the ability to perform a root cause analysis (RCA) on our defects and go fix them. We tried; we experimented with pharmaceuticals but what we are going to see now is less about reverse engineering. We may finally be able to look at our code, read our genes and translate genomics into a language we better understand.
Genomic Revolution
Machine Learning enables us to identify patterns within genetic data sets and computer models can make predictions about an individual’s odds of developing a disease or responding to interventions. Google’s tool DeepVariant uses the latest AI techniques to turn high-throughput sequencing (HTS) into a more accurate picture of a full genome. The Canadian start-up Deep Genomics uses its AI platform to decode the meaning of the genome to determine the best drug therapies for an individual based on the DNA of the cell. In China, as of November 2018, the first HIV free genome-edited babies, created using the CRISPR gave birth. This marks a milestone in human history. Early, yet the latest and ever-growing advances in the CRISPR techniques will change human history.
The growth of both, our understanding of our genomic structure as well as gene editing technologies with advanced machine learning & AI technologies will soon enable us to produce the correct prescriptive medicine to our diseases.
Drug Delivery
The next challenge posed to us has been how we target the delivery of these medicines to the human body. Nanoparticle structures and microchip technology has made it possible to think beyond current medicine. We can biologically control cell targeting and technologically control timing and release of medicine. This enables us to deploy our solution right where we identified the defect in our code. With the prescriptive designs for our cures at hand, pharmaceuticals will now be able to manufacture precise medicines and minimize the side effects caused my probabilistic and generic medicines.
What we are really going to see is an end-to-end pipeline where very specific diseases can be targeted and iterated via means never seen before. We are going to be able to literally “edit” ourselves into being. Not by curing the symptoms but adhering to the root cause. This extends our ability to surgically “fix” the shortfalls in our body. And furthermore, possibly do this even before we come into being; the ability to genetically control the structure of our babies.
Summary
In a nutshell, the process by which we are able to obtain, analyze, identify and enact upon genetic information will be in its formative years in 2019 due to the rapid convergence of technologies for each of these stages. CRISPR and machine learning contribute to the first while chip technology to the latter. The integration of these technologies will change the way humans look at diseases, our make, and our future. We are headed towards the perfect being — that in itself will surface a new set of problems. But for now, let’s embrace the beginning of our journey where we will productize ourselves…
