BioTech 3.0 On It's Way

Today innovation in biology is not as easy as writing a phone app. A phone app can be written in a weekend whereas innovation in biology can still require years. There are some exceptions though. We witnessed the rapid development of the COVID-19 vaccine by the Moderna RNA vaccine team, within 2 days of receiving the genome sequence of the virus. Vaccine design today has already become comparable to writing a phone app - though the clinical trials and regulatory approvals processes remain long and hard. Biotech 3.0 will give us platforms to write living machines as apps, with the same ease with which we today write phone apps.

The VC firm Andreessen Horowitz has predicted that Bio will eat the world. Mayfield, the respected VC firm that funded the original Biotech startups like Amgen and Genentech, has predicted that Bio is going to revolutionise multiple trillion-dollar industries. The bio-focused startup accelerator IndieBio has sized the Bio opportunity as $100 trillion over 25 years. The last time there was so much excitement over an emerging technology was over the birth of the internet. What is happening to cause this kind of excitement among people who are on record only a few years earlier saying they would never invest in Bio? Before talking about this, let’s first take a fresh look at Bio from the lens of technology.

The recipe for life

Tokyo is the most populous city in the world, with a population of around 38 million. A living cell is more populous with around 42 million proteins according to our best analyses, to say nothing of nucleic acids and innumerable small molecules. We use the word 'protein' in everyday language to refer to nutritional requirements. However to a molecular biologist the word brings to mind a Transformers-like nanorobot. Some of these nanorobots are molecular scissors, some run border security for the cell, some run the transportation system of the cell, and most are 'knowledge workers' helping to integrate complexity from one layer and presenting it to another layer in the biochemical networks inside the cell.

There are around 20,000 different guilds of these nanorobots in the cell, with around 10 to 5000 members in each guild. The precise map of this micron-scale city is still not known. The interaction patterns between individual proteins remain mostly mysterious at a systems level. Even the train lines of this city are barely sketched out. Despite much progress, the behaviour of the cell remains one of the yet-to-be-explored frontiers of human knowledge. Making sense of the cell is like trying to understand the workings of a Tokyo-sized city within an alien civilization millions of miles away which you cannot visit and about which all the information you have are the location traces of a few thousand residents.

A cell is a remarkable model of governance. There is no leviathan central authority running things, each individual 'resident' molecule is completely free. And yet, there is remarkable coordination and self-organisation, allowing cells to carry out all the miracles of life. It is a perfect example of Searle’s Chinese Room - an intelligent agent capable of life, survival and reproduction emerging from spontaneous chemical interactions. Biology emerges from Chemistry at the level of the cell.

Let’s try a thought experiment to understand this better. Imagine sorting all the molecules in a cell and binning all molecules of the same type together. In fact, you can do a version of this experiment in any molecular biology lab by taking cells, breaking them open and filtering them to sort different molecules. You would get back the same collection of molecules in a sorted order. The vitality of life is lost and we are left with mere Chemistry.

So the magic of the cell is not merely in the molecules. If that were the case, we would not have lost the vital spark simply by sorting molecules. Just like a society emerges from the interactions of its various constituents, the vitality of the cell emerges from the information processing performed by the network of molecular interactions. Biology is sophisticated behaviour which emerges when Chemistry performs Algorithms. The focus shifts from the individual nanorobot to the algorithms executed by networks of nanorobots. Can we create life if we run this thought experiment in reverse, by taking molecules and arranging them into an information-processing network? The recipe for life would then read as 'Chemistry with a pinch of Programming.'

Domesticating the cell

Biotechnology is the journey of domesticating the cell. Human beings have been domesticating cells before they knew of their existence. This happened through the serendipitous discovery of fermentation processes which improve the taste and nutritional profile of food. Fermentation has been a key technology in every human civilisation, giving us yogurt, cheese, kefir, bread, beer, idli, sauerkraut, kombucha and many other flavourful and nutritious foods.

Biotech 1.0

The conscious effort to domesticate the cell and harness its powers to human ends signalled the start of Biotech1.0. Built on the bedrock of the discoveries of molecular biology over the second half of the 20th century, the focus was on inducing cells to make the proteins that we wanted them to make. Biotech1.0 married the processes of chemical engineering with the new-found tools of molecular biology. The bioreactor was the major advance of Biotech 1.0, allowing the harnessing of cells for industrial production of proteins of interest. The initial proteins of interest were molecules like Insulin which had immediate healthcare uses or genetically-modified foods which could express proteins that might confer pest-resistance. More recently, there has been interest in getting cells to generate and organise proteins for various industries outside life sciences, including textiles, construction, chemical, etc. This playing out of Biotech1.0 outside life sciences has been referred to as 'Build With Bio'.

Biotech 2.0 

Biotech 2.0 is the x-omics revolution driven by efforts to sequence the human genome, which required the convergence of chemistry, hardware, and software. The fields of bioinformatics and microfluidics have emerged as specialisations supporting Biotech 2.0. The platforms emerging from Biotech 2.0 have transformed the ease and speed with which humanity can read and write molecules, specially nucleic acids. This in turn has enabled the development of ever-more-precise analysis and synthesis of nucleic acids, bringing about a new era in agriculture, personalised medicine and drug discovery. Biotech 2.0 is starting to play outside the life sciences, with a new era of DNA Memory companies that are using this tech stack to support archival memory use cases for the cloud.

Biotech 3.0 

Biotech 3.0 is the effort to program sophisticated behaviour into molecules by making information-processing networks out of them. When this effort is pursued inside cells, it is called Synthetic Biology. When it is pursued with cell extracts, it is called Cell-Free Transcription-Translation. When this effort is pursued with purified molecules of nucleic acid and protein, it is called Molecular Computing. Biotech 3.0 is the first time humanity will write programs in chemistry to perform algorithms. Such smart chemistry is going to be fairly modest to begin with, perhaps having simple applications in better molecular testing. But as the size of these networks increases, the capacity to perform more sophisticated algorithms will emerge and these systems will start exhibiting more and more of the attributes of living cells. In this sense, Biotech3.0 is truly about programming biology.

Progress in Biotech1.0 was measured by how many types of proteins you can make and in what quantities and purities. Progress in Biotech 2.0 is measured in terms of cost-accuracy-bandwidth tradeoffs. Progress in Biotech 3.0 will be measured by the size of the networks, the amount of computation we can perform with them and the ease of programming them. 

Biotech 3.0 is going to be about computation. Computation requires precision and precision requires modelling and quantitation of error. Biotech 3.0 is going to require making biology into a quantitative engineering discipline. This is virtually impossible to do within the cell because of our profound ignorance concerning its workings. This is why I believe synthetic biology efforts will hit a wall, and Biotech 3.0 will emerge by borrowing from the cell, but reconstituting these circuits outside the cell.

Today innovation in biology is not as easy as writing a phone app. A phone app can be written in a weekend whereas innovation in biology can still require years. There are some exceptions though. We witnessed the rapid development of the COVID-19 vaccine by the Moderna RNA vaccine team, within 2 days of receiving the genome sequence of the virus. Vaccine design today has already become comparable to writing a phone app - though the clinical trials and regulatory approvals processes remain long and hard. Biotech 3.0 will give us platforms to write living machines as apps, with the same ease with which we today write phone apps. Biotech 3.0 is software eating biology so biology can eat the world.


Biology as technology is going to put the power of creating living machines in each one of our hands. This will happen by integrating algorithms and biologics into one platform. This technology will reinvent healthcare, food and pharma, but it won't stop there. It will also reinvent chemicals, textiles, energy and climate.

This is not going to be a disruption, it is going to be a reinvention of civilisation. The new world that we will remake will be a world where our material needs like food, clothing, etc. can be printed in fishtank-sized devices sitting in our homes. Healthcare won't be something that happens once a year, but will become a continuous monitoring of inputs going into the body, state of the body and outputs from the body. Ageing will be attacked like a disease, cancer will be detected in Stage I, food will be grown in vats in factories without needing plants or animals. Carbon sequestration, plastic rapid decomposition and ocean deacidification efforts will happen on a planetary scale. Our precise control over molecules will enable better batteries, nuclear fusion, quantum computers and terra forming of inhospitable terrains, launching a new wave of innovation on top of this one.

A lot of investment, research and development is going to be needed to actualise the promise of Biotech 3.0 and deliver truly transformational returns. The timing for injection of investment seems to be right, as witnessed by a pickup in Venture Capital funding from a mere 18 billion USD in 2016 to more than 65 billion USD in 2021. Putting together multidisciplinary teams is not a problem, but the rare individuals with skills transcending bio and tech are going to be valued very highly. Many software engineers re-educating in biology, along with biologists training in data science, are expected to come. 

A strong foundation in basic science is going to be indispensable as well. Essentially Biotech 3.0 is higher on technical risk and lower on market risk than the tech revolution, meaning that founders will be those who are best able to analyse and reduce technical risk, suggesting we will see more founders with deep science and deep tech qualifications. Since the dawn of the industrial revolution, knowledge and wealth have emerge from the spinning of the science to product to data to science flywheel, a spinning which has gone through multiple institutions including academia to produce its impact over a span of decades. We are now seeing that flywheel spinning tighter than ever before. The entire cycle can now complete within one individual early-stage startup. 

For millennia, humanity has been awed by nature’s providence and bounty. We have worshipped it in various symbolisms like the mother goddess, or the horn of cornucopia or kamadhenu or the tree of life. While mystery still shrouds the workings of the cell and we remain as much in awe of the miracle of life, we should not belittle the hard-fought ground we have gained. None of our ancestors could answer as precisely as we can today questions like 'where is the tree within the seed?' Though we are far from having all the answers, we are surely beginning to ask the right questions. 

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