For Biology to eat the world, software will have to eat Biology
Towards the beginning of this century, Human Genome Project created a map of DNA code that makes up human genome. The first genome cost one billion dollars and over a decade of research effort. Two decades later, it can now be sequenced at less than $1000, one-millionth of the original cost, and this cost is expected to soon go down to below $100.
We designed a vaccine for COVID within 2 days using the mRNA technology that had been in the works for more than three decades. From $330k for a burger made with lab-grown meat at the time of its first public tasting in 2013, we are expecting the price tag to come down to 1/10,000th within a decade from the date.
We can not only read, but also edit genes using CRISPR, and even trick it into exhibiting different behavior using Synthetic Biology, and are creating different biological compounds than what organisms are naturally designed to create. We are creating human organs, flavors, edible proteins, among others. This is set to change how we live, what we consume, how we diagnose and treat diseases, how and what we produce. In a nutshell, it will change the understanding of what is hitherto known to humans as natural order.
If we step back and look at the development cycle of these technologies that are harbingers of an era of Biology, we will find that the unit of time still remains as decades. Biological innovations continue to be driven by serendipity and specialized skill, as against the data-driven, automated, learnt decision making era that software has ushered us to.
The true power and impact of Biological innovations will be realized when the cost and time-to-market for these technologies will be driven down faster than Moore’s law will allow. And that can happen only by leveraging the power of software and algorithms.
Computational biology has a potential to bring future innovations to us 10x faster than what traditional microprocessor based systems can. The power of computing can also be harnessed to simulate biological systems that bridge the gap between biology and computing.
So far, the focus of software has largely remained to be medical records, insurance, hospital data, and other such health related data. We are seeing software focusing on areas where data is more amenable for data processing, like drug discovery. We need new software innovations to study, quantify and analyze biology beyond health data including biomaterials, food, drugs, proteins, DNA/RNA and diseases for us to have an outsized impact on human wellness.
We are living in times where world population is set to approach 10 Billion by 2050, with demand for resources doubling every 10–12 years. Human health is facing steep challenges even without a pandemic where nearly 30% of young people under age 20 are obese, 31% of deaths are from cardiovascular disease, and cancer cases are growing at a rate twice as fast as the population. The technological innovations we need to solve these challenges are going to be found at the intersection of Biology and Software. And the time to build those technologies is NOW.
References:
