What is future of Biotechnology ? by Rahul Kharade

In order to answer this, one need only look at the technologies that are presently treated as theoretically possible but difficult to implement.
Regenerative Medicine

A lot of research is moving this to fruition. Every few months, some stem cell derived organ has been grown, shown to work or implanted for the first time; lungs, livers, kidneys, tracheae are a few of a very long list.

When this has fully matured, organ farms will be able to grow or even print any fully functional organ and have it ready for implantation in weeks. This will dramatically increase life expectancy and quality. Thousands of people die every year waiting for an organ donor. Even those who get the organ they need live a perilous, uncomfortable life on immunosuppressant drugs. Regenerative medicine will end this death and suffering.

Synthetic Biology

We have woken on this planet and found ourselves surrounded by intractably complex, ancient machines all buzzing away to fulfill some ancient programming. What if we could unravel their nightmarishly unreadable code so to write new algorithms for them or dictate entirely new forms for them? What if we could even reverse engineer them in order to compile a whole new language to work with?

This is already being done in a variety of industries. We genetically engineer plants to carry vitamins or be pest resistant, so we don't need to use pesticide. Since the 1970s, the insulin we give diabetics has come from genetically modified yeast. What if we could engineer bacteria to scrub the air of our pollutants and turn them into fuel or plastics?

When this is mature, we'll do more than just swapping pre-existent genes between organisms for neat combinatorial affects; we'll be working from scratch. If we come to solve the protein folding problem, we'll be able to design and mass produce novel enzymes not otherwise found in nature for any conceivable effect. We may see problems that cannot be easily solved with conventional biology and design whole new genetic languages with new base pairs and amino acids custom built to the problems of tomorrow.

Population Genomics and Gene Therapy

The cost of full genome sequencing has been falling exponentially (outpacing even Moore's law) since the 1990s. With this becoming affordable, we will be able to aggregate databases of millions of genomes and correlate them to specific disease risks.

This will let people who've had their genome sequenced see where they stand in relation to statistical outcomes -- based on their lifestyle and genes, what are the odds of developing specific conditions. Even better, with sufficient data, we will even be able to use correlations in the data to recommend meal plans and drug treatments.

It gets better. Massive data sets like this will let us find genes in the whole of humanity that help lower the occurrence of obesity, cancer, heart disease, and dementia and help raise attributes like intelligence, athleticism, even aesthetics. These are the genes we'll want to put into the rest of us.

We should expect to see genetically engineered babies long before in vivo gene therapy, as that has proven more challenging to do to an acceptable standard of safety and efficacy. There is no reason to suspect that it will not eventually be perfected, however, utilizing genetically modified viral vectors.

Iterated Embryo Selection (IES)

Imagine if you could run a successful, regimented eugenics program for 300 years, selecting who breeds with whom and ignoring any ethical objections. It's an untenable effort, but this new technique would allow it to be done in months with few of the ethical qualms. The idea is genius.

Take stem cells from as many volunteers as you like and cause them to differentiate into as many sperm and egg as you will. Fertilize the eggs with the sperm to form zygotes. Sequence the DNA of the zygotes and identify which candidate zygotes possess as much of some trait that you want to select for -- intelligence, for example.

In in vitro fertilization (IVF), this would be where you implanted the selected zygote(s) into a prospective mother -- not in IES. Instead, take stem cells from the best zygotes and stimulate those stem cells to differentiate into sperm and egg. Fertilize the eggs with the sperm and repeat the process to your satisfaction and then implant the final zygote at the end of the iterative process into a prospective mother.

This technique will let us perform evolution in vitro by skipping the 20 years that it naturally takes for generational turnover. The effects of this can be profound. If we could correctly identify the genetic corollaries of intelligence and selected for those, we might be able to achieve gains higher than 300 IQ points in a single generation.

This may be the single most impactful technique in biotech since the polymerase chain reaction.

Biological Computing

At its core, biological systems are information systems. They store information, transmit it, code, decode, and scramble it. They behave according to a complex array of logic gates, so is it any surprise that we could conceivably
Manipulate biomolecules and even whole organisms into computers?

DNA has been engineered into a high density, super low error data storage device. Living cells can be rigged into behaving like transistors, fulfilling algorithmic routines normally only seen in computer code (IF, AND, OR statements). We can do the same thing using enzymes or even DNA itself.

This approach to computing has drawbacks but also benefits. Chemical pathways tend to be slow compared to silicon computing, not producing results for minutes or hours. However, biological computers have the capacity to be massively parallel, which lends itself to certain categories of computing problems. Also, cells and enzymes have their own actuators; not only can they compute a result, they can then physically move things around based on that result. We eventually want molecular scale nanobots that can assemble things for us, monitor and maintain our health, but the hardware for these poses enormous engineering hurdles. Living cells provide premade hardware; we only need to give them the right software.

Obsolescence

In biotech, we are haphazardly cobbling together an ancient technology that was never built for us. It is not designed for our ease of use or for the particular problems we face. Therefore, it will never be as efficient as something we could design ourselves if we had the means.

As we acquire that means, biology will become irrelevant as we optimize solutions that are less inspired by nature and moreso tailor made to our needs. Robots measured in micrometers will replace the synthetic cell. Super advanced robotics will replace regenerative medicine. Artificially intelligent systems will replace neurologically intelligent systems.

No technology ever disappears (in 2015, we still use oil candles and horse drawn carriages), but technologies do become marginalized and subservient to newer, superior tools. The trappings of biotech will be no different.