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Tech Industry

When matter becomes code

With molecular lab science becoming information science--designed on a computer instead of a lab bench--Steve Jurvetson analyzes how start-ups are approaching the brave new world of nanotech.

    As we think about the start-up opportunities in nanotechnology, an uncertain financial environment underscores the importance of market timing and revenue opportunities over the next five years. Considering the various paths to nanotech, which are 20-year quests in search of a government grant, and which are market-driven businesses that will attract venture capital?

    As a thought experiment, imagine that I could hand you today any nanotech marvel of your design--a molecular machine as advanced as you would like. What would it be? A supercomputer? A bloodstream submarine? A matter compiler capable of producing diamond rods or arbitrary physical objects? Pick something.

    Now, imagine some of the complexities: Did it blow off my hand as I offered it to you? Can it autonomously move to its intended destination? What is its energy source? How do you communicate with it? If you can manipulate atoms, where would you start?

    These questions draw the "interface problem" into sharp focus: Does your design require an entire nanotech industry to support, power and "interface" to your molecular machine? As an analogy, imagine that you have designed a fancy new chip with the latest sub-micron geometries. You then need to "wire-bond" the chip to a larger lead frame that connects to a larger printed circuit board, fed by a bulky power supply that connects to the electrical power grid. Each of these successive layers relies on the larger-scale precursors from above, and the entire hierarchy is needed to access the potential of the microchip.

    For molecular nanotech, where is the scaling hierarchy? Today, the infrastructure lies in biology--in DNA, proteins and cells. Biological systems are replicating machines that parse molecular code (DNA) and a variety of feedback to grow macro-scale beings. These highly evolved systems can be hijacked and reprogrammed to great effect.

    A future alternative is to grow a massively complex system from scratch. For a non-biological molecular machine to produce macro-scale material, it must first replicate itself into trillions of copies before performing useful work, like extruding a diamond beam. Moving one atom at a time goes nowhere fast; replication is the bottom-up solution to the scaling problem (early progress will come from biology--by reprogramming bacterial DNA).

    Another way to connect to the molecular world today is light. When a molecular design is at the scale of the wavelength of light, interesting quantum behaviors emerge (for example, quantum dot lasers that emit light and bandgap crystals that switch light). We have funded a company in Chicago that is commercializing a breakthrough in nano-material manipulation. Arryx generates 10,000 independently controllable laser tweezers that can manipulate molecular objects in 3D (move, rotate, cut, place), all from one laser source passing through an adaptive hologram. With thousands of robot arms, they can sort cells and proteins as well as manipulate the organelles and DNA inside a living cell.

    Honey, I shrunk the chips
    A separate path to nanotech is the gradual shrinking of semiconductor manufacturing technology from the micro-electro-mechanical systems (MEMS) of today into the nanometer domain of NEMS. MEMS have already revolutionized medical and automotive sensors and photonic switches. Cahners In-Stat predicts that the $4 billion MEMS industry will grow to $11 billion by 2005. But progress is constrained by the pace (and cost) of the semiconductor equipment industry, and by the long turnaround time for fab runs.

    MEMGen in Torrance, Calif., is seeking to overcome these limitations to expand the market for MEMS. Instead of a semiconductor clean-room fab that produces flat silicon, they have a single, inexpensive tool that rapidly creates 3D micromachines from a variety of materials. Designers can rapidly prototype and manufacture diverse devices, without the funny bunny suits.

    Crossing the "interface" chasm
    Today's business-driven paths to nanotech diverge into two strategies to cross the "interface" chasm.

    On one hand, the non-biological MEMS developers are addressing current markets in the micro-world while pursuing an ever-shrinking spiral of miniaturization that builds the relevant infrastructure tiers as it goes. Not surprisingly, this is very similar to the path that has been followed in the semiconductor industry.

    On the other hand, biological manipulation presents myriad opportunities to effect great change in the near-term. Drug development, tissue engineering and genetic engineering are all powerfully impacted by the molecular manipulation capabilities available to us today. The limiting factor is our understanding of these complex systems. We will learn more about molecular biology and the origins of disease in the next 20 years than we have in the past 2000 years.

    The sequencing of the human genome presents an archaeological document of the computer equivalent of low-level machine code--code that becomes massively more complex as it directs the creation of highly-interactive proteins--code that we now need to reverse-engineer and decipher.

    How compact and descriptively powerful is the biological code? If we took your entire genome and burned it onto a CD, it would be much smaller than Microsoft Office. (For more detail, see The Convergence of Infotech, Biotech and Nanotech).

    Compared to crude computer code, much of the power in bio-info-processing comes from the leverage of feedback in the electrical, physical (pressure, temperature) and chemical domains. Early work in tissue engineering converted skeletal muscle to cardiac muscle under the electrical stimulation of a pacemaker. Bone marrow in one's knee can be converted to replacement fibrocartilage under special physical stimulation. When the force of gravity is removed, the kidneys go through a profound change in gene expression, which explains astronauts' lack of essential protein production. Most recently, the Bio-X program at Stanford distilled adipose stem cells from a standard liposuction and converted them into one billion neurons. Fat to neuron conversion at the bedside--imagine the marketing.

    The brain is also the product of massive amounts of feedback. With a staggering 100 trillion synaptic connections, it is not "installed" from your DNA like Microsoft Office. It is grown along chemical gradients, and through widespread synaptic connectivity sprouting from "static storms" of positive electro-chemical feedback. In early childhood, 90 percent of the underused connections are pruned through continuous usage-based feedback.

    The coding efficiency of DNA extends beyond the leverage of numerous feedback loops to the complex signaling loops in which many human genes produce proteins that regulate the activity of previously produced proteins and other genes.

    The result is a complex mesh of direct and indirect controls, which implies that genetic re-engineering can be a very tricky endeavor if we have partial system-wide knowledge about the side effects of tweaking any single gene. For example, rats with genetically enhanced memory suffer from increased sensitivity to pain.

    Like the Web, our genetic code is a dense network of nested hyperlinks. It is also the muse for computer programmers seeking to grow complex systems. Beyond indirect pointers and recursive loops, biological systems have inspired research in evolutionary programming, neural networks and artificial life.

    We are entering an era of exponential growth in our capabilities in biotech, molecular engineering and computing. The cross-fertilization of these formerly discrete domains compounds our rate of learning and our engineering capabilities across the spectrum.

    Lab science, from biotech to nanotech, is becoming information science--designed on a computer, not at a lab bench.

    With replicating molecular machines, physical production itself migrates to the rapid innovation cycle of information technology. Matter becomes code.