I (Alpana Saha) am presenting a part of an interactive intellectual discussion with Professor Pawan Kumar Dhar.  Professor Dhar is the Dean, School of Biotechnology in Jawaharlal Nehru University. His team has developed a disruptive novel drug discovery platform from the dark matter of the genome. Currently, he is working on the application of AI in speeding up the drug discovery pipeline.   

Why does biotechnology need AI ?

In Science reproducibility of results is an absolute must. The time and costs involved in performing experiments and confirming the observations with repeat experiments are enormous. In 2016, a Nature survey reported that 70% of researchers had tried and failed to reproduce results of their peers. Worse, over 50% of researchers had failed to reproduce their own results. These figures do not indicate a deliberate intent of misrepresenting the data but highlight a much deeper issue that has largely remained unaddressed i.e., lab-to-lab variation in obtaining the results from experiments performed manually. 

It is not that automation will fix this problem once for all.  The automation will take away manual errors, give real time feedback at various quantitative steps and help develop a standard protocol based on the cells, strains and culture conditions. 

Furthermore, experiments are increasingly getting miniaturised.  A case in point is large scale screening where one uses thousands of combinations of small volumes to get the right hit. For example if one needs to accurately dispense 0.5 microliters of a DNA solution in 10,000 wells within few minutes then robotic-technologies are certainly the answer.  

Another serious issue is the human-induced contamination while performing cell culture.  A scientist may be using a small number of culture flasks but extremely valuable biopsy from patient for diagnostic / prognostic purposes. In such situations, one cannot afford to lose the material to microbial contamination. 

Thus, the need of the hour is to move the material handling (chemicals to liquids) from humans to robots.

Are there any specific examples where Robotics have be used in Biotechnology?

Biotechnology includes applications in agriculture, services, industrial and pharmaceutical sectors. One needs to explore the use of AI across all these sectors. However, some of the companies have taken a quick step in adopting the AI technology. One would hope to see more AI players to come on board.  


The US company OpenTrons (https://opentrons.com) has launched an OT series of robots to automate hundreds of protocols and workflows for dispensing small liquid quantities into multi well plates. 

Likewise, the UK based Synthace (https://synthace.com) is harnessing the power of digital world to engineer biology and transform lab productivity. Their proprietary Antha algorithm that automates experimental workflows, allows easy, rapid and accurate design of experiments.  The company claims a significant reduction in the time for optimal experimental designs from several weeks to a few hours leading to appropriate utilisation of resources and a several fold increase in the productivity. 

Desktop Genetics (https://www.deskgen.com) has created a AI platform to design gene editing constructs. Their proprietary AI approach allows rapid and accurate construction of CRISPR libraries customised to the targets. 
 
Companies are also using AI to analyse images of diseased cells to understand the effect of therapeutic molecules and process biopsy samples to speed up diagnostic outcomes. 

Which hazardous and mundane process of Biotechnology can be automated for Human safety and security?

Areas where automation is urgently needed to address human safety and security needs are: handling of corrosive liquids, pathogenic microbes and toxic substances, especially if chemicals are volatile. Currently, standard biosafety protocols and guidelines do exist. However, the replacement of the human element by the machines can greatly reduce (maybe eliminate) the chances of accidents and outbreaks. 


What is the funding scenario of AI in Biotechnology ?

Reports indicate that the US Government has invested more than 5 billion dollars in AI research while Chinese have invested more than 12 billion dollars. It is expected that both government and private funding will  increase many times over in the coming years. Likewise Europe is gearing up its labs with significant funding for AI research. 
 
Recently, with an introductory USD half a billion funding, Government of India (DST) announced setting up 20 centres for research in future technologies that include Artificial Intelligence, Machine Learning, Internet of Things and Quantum Computing. 
 

The race to embrace AI is heating up.  According to recent studies, China, India, and Singapore have highest possibility  of delivering AI based technologies in the near future.  Also, it seems healthcare and energy will see maximum investment. 

 

What are your suggestions to upgrade biology labs in India?

I agree that biology labs need a significant upgrade especially in rural areas. However, in my view we need to upgrade the network more than work. Even if one undertakes large scale upgradation drive of biology labs, where do you place the students with the right skills ? There is a need to revise the existing national policy and look at the issue end-to-end. It is important to bring private sector on board, revive the biotech sector that has seen little attention by the industry sector.


India is having a good number of demographic dividends in the form of youth? How can we bring balance in using Human Resource and Robots in various sectors?

Robots have been the source of both anxiety and aspiration. Studies indicate that robots may take away half of the jobs in the US.

Automation is bound to replace human jobs that are repetitive in nature.  However, at this moment, humans are more creative than robots. We must make use of this narrow time window and create policies and opportunities.  

Calls for regulation have been frequently sounded. A graded integration of robotics in the society is needed. In my view, jobs that are dangerous and difficult may be considered for robots. However, the adoption of robots as competitors for employment must come with an exclusion criteria. Ultimately, it depends a lot on the government, people, economy, environment and so on.  We must make a national policy on the phase wise integration of robots and identify sectors that will be managed only by humans. 

On a lighter note, the grand human inner exploration to find the existential core will never any face competition from robots. Will Yoga turn out to be the highest employment generation sector for humans in future? We do not know. 

Thanks for your time and showering extensive light on the interdisciplinary problems of bio science lab and robotic implementations in those labs

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