Last week at the end of the 2020 'Feeding or Fooling the World?" debate in Norwich, 2 women farmers from Andhra Pradesh approached the man from Monsanto and told him they wished his company never to come to India again. Biobiz fever, however, is biting deep into India's political, business and science elites.
According to an article from an Indian financial paper ("AP Plans Sops To Boost Biotech Ventures" ) reproduced on Monsanto's 'biotechknowledge.com' site :
"Aimed at luring major private sector investments into the State in the field of biotechnology ahead of some of the competing States, the Andhra Pradesh Government is currently drafting an attractive incentive package for biotech ventures as a part of its biotechnology policy to be announced shortly." http://www.biotechknowledge.com/showlib.php3?uid=5002&country=india
In the Times of India we read:
"We've got immense opportunities right here in India: We have inbred tribes, inbred communities. In a very simple way useful data can be mined... It is an opportunity for international companies to come in and I think Indian companies should collaborate with them. We can share IPRs. If we don't do this, we'll be isolating ourselves and lose out on all that information. Through shared IPRs, a lot of licensing money will become available: We can't take it to the market, but they can."
This comes, of course, against a background of growing realisation of how biotech research has failed to live up to expectations. The heading of the article? 'Boom Time for Biotech'.
---
Boom Time for Biotech
Times of India (www.timesofindia.com)
Wednesday 25 April 2001
BANGALORE: With the unravelling of the human genome, it seems that biotechnology will soon overtake IT as the most promising new industry. ``Although everyone's talking about BT, not many know much beyond cloning and the fears of BT cotton cultivation'', complains `BT crusader' Kiran Mazumdar-Shaw. As Karnataka's Biotech Vision Group chairperson and CMD of India's biggest BT company Biocon India Limited, Shaw has been leading the BT revolution from the forefront. She spoke to Sowmya Aji Mehu:
What is the biggest challenge to the development of bio-informatics as the next revolution in IT? What is the real opportunity, the real business of bio-informatics?
It is not possible for every software company to get into bio-informatics. And biotech companies too realise that they can't very easily get into bio-informatics. It is a synergy of the two skills that we are talking about: The domain skills in the area of experimental biology and bio-science and the domain skills in software development.
How does one marry these skills?
That is the challenge of bio-informatics.
How much of the hype has actually helped?
Though a lot of the hype has died down, the VCs are now at least aware of what these opportunities are. Hype has played havoc in the IT sector. There was unrealistic valuation of just ideas - revenues did not matter; they said, as long as you have smart ideas and sticky eyeballs, that's all that matters. In the end, this simply didn't work. Similarly, the mapping of the human genome generated great enthusiasm and interest in genomics. But VCs need to be cautious and not go after things they don't understand.
Because it is what your revenue model is, in terms of what you're doing with that new-found space in genomic sciences, that will determine the success of companies, as is happening in the US. Celera Genomics and other biotech companies got over-rated on the eve of the human genome map's completion. Stock prices shot up. But as soon as people realised that genome draft by itself meant nothing and it is what you do with it is what will get the big bucks, suddenly, stocks crashed.
Now Celera is looking to add value to the genome map: What causes disease; what are the genetic markers which will help evolve new products and new therapies, for instance. How can software make a difference in this process of value-addition? It depends on what kind of software it is, who is developing it and what knowledge they are developing it with.
When we started our bio-informatics initiative, we could perceive that we have very high skills in biology knowledge at the molecular, genetic, chemical level. But we soon realised we didn't have the kind of mathematical, computational and algorithmic skills with which to mine this knowledge.
The partnership that we have with Strandgenomics is addressing this need. We know what is required of the knowledge, but we don't have the skill. Strandgenomics has the skill but absolutely no domain knowledge. This I call the symbiosis, where both sectors need to add value to each other. Even if you have a good algorithm to search out gene sequences, since you have no knowledge of what these sequences are about, only when we tell you that these are relevant can you mine them for us.
What can we achieve with this kind of research?
Our objective is to find genetic aberrations: We're trying to find out, what is it that the gene is reading wrong - and that's where we need this kind of information deciphered. We've been trying to use computer technology for a long time to try and handle large volumes of data that are being generated by research findings. Is this information just a database, or, is there something valuable in there that can be mined?
For instance, we've got a bio-diverse collection of fungi and we are developing C-DNA libraries of each fungus. Now we're saying we want to look at genes which are expressing certain proteins. We could, working together with, say, Strandgenomics, digitise this information and search these specific genetic sequences. Having done that, we could go further into much more focused research. You can actually start mining useful information as opposed to random information.
This you can apply to other projects like drug discovery. Suppose you're trying to mine an anti-infective fungus which can be used for producing an antibiotic. You look at all the antibiotics in the marketplace today, relate it to genes which are expressing these antibiotics; maybe there's some commonality in those genes. Then you start looking at newer organisms; you can do some rational drug design: If I had a gene sequence that also had this other component, maybe I can get a newer antibiotic? Then I start searching my genetic databases - is there such a sequence in my collection?
Here the power of computational technology is useful. Instead of looking for a needle in a haystack, maybe you can look for a pitchfork. Relating this to human genetic databases, you can do more powerful things, looking at genetic aberrations through familial histories and their genetic makeup and saying, this is the thing that is causing the problem.
How much of this kind of research is India, and in particular, Karnataka, equipped for?
It's important to do original research and it's not easy. A lot depends on how accurately you document and interpret information. Opportunities, IT, high computational power are needed - you're dealing with three billion base-pairs of information which is what the human genome is all about - you are mining huge volumes of data, most of which is junk. We are hoping CDC-Digital will be able to develop an affordable computer specially designed for this sector.
Such computers cost billions of dollars. We can't afford it. So we'll have to look at specific segments only and get a lot of intellectual property rights (IPR) out of it.
We've got immense opportunities right here in India: We have inbred tribes, inbred communities. In a very simple way useful data can be mined. One can, in fact, focus on a particular tribe that has a high incidence of some disease. There is so much of public domain information available; this can be applied to these small niches to gain some medical wisdom. It is an opportunity for international companies to come in and I think Indian companies should collaborate with them. We can share IPRs. If we don't do this, we'll be isolating ourselves and lose out on all that information. Through shared IPRs, a lot of licensing money will become available: We can't take it to the market, but they can. Slowly we can also evolve and become confident enough to do our own research.