Decoding Genomics


Genomics is the key to decipher the puzzle of our evolution, a pre-requisite to personalised treatments. Let us examine how innovations in the digital era are aiding genomics

A few decades ago genomics was considered to be a far-fetched notion, but defying the belief, it soon emerged as a revolutionary science. The first human genomes were determined in 2001, marking the millennium with innovations and since then it has been exploring new avenues and solving mysteries. The intricate mystery of evolution can be explained with only a few set of theories and genomics plays a significant part in untangling those  threads. To unravel our history, to understand the nuances of our functioning, the elements that affect us and to devise a way to personalised ailments, the requirement to innovate genomics arose.

Since its advent, genomics has been proving its worth with numerous applications in the healthcare segment. Though the task of completing the entire DNA sequence of the human genome seemed monumental then, exciting advances have already emerged in the field now. Worldover, powerful technologies are being deployed to churn out extensive genetic information, while robust analytical methods help make sense of a massive collection of data.

Digital technologies

A World Economic Forum’s report on emerging technologies of 2015 states that digital technologies in genomics such as Digital Genome, Artificial Intelligence and Genetic Engineering Techniques are a game-changer. Many others including Next Generation Sequencing (NGS), Big Data Analytics, Internet of Things, Cloud Computing have cropped up to support the building of a grand database which could be significant in reducing the disease burden. Clustered regularly interspaced short palindromic repeats (CRISPR) genome editing technology is yet another innovation which is advancing treatment options for some of the toughest medical conditions faced today, including chronic illnesses and cancers for which there are limited or no treatment options available currently. The applications of CRISPR are far ranging—from identifying genes associated with cancer to reversing mutations that cause blindness.

Aparna Dhar, Medical Geneticist and Genetic Counselor, Core Diagnostics, in regards to upcoming digital technologies opines, “Genomic sequencing technologies are undergoing regular upheavals at unprecedented speeds. The fastest technologies can now sequence an entire genome, three billion bases, in hours and the corresponding costs have dropped within a year.”

Let us now look at how these technologies are helping to transform Indian genomic industry.

Integration in Indian market

Though Indian genomic market is a nascent one and so are the technologies adopted by the industry, there have been significant measures taken up by the government along with various initiatives by genomic players to boost the sector.

Government intervention: The Union Budget, 2017-18 allocates Rs 1250.58 crore to Biotechnology Research & Development which includes research for the various technologies that are likely to generate multiple genomics solutions. A Central sectoral scheme, Bengaluru-Boston Biotech Gateway to India has been formed. Through this initiative, a range of institutes in Boston (Harvard/ MIT) and Bengaluru will be able to connect to share ideas and mentor the entrepreneurs, especially in the field of Genomics. Another one is the National Laboratories Scheme, which will aid the development of low-cost technologies in big data in health genome biology. These schemes are bound to promote further innovations.

The contribution of genomic players: Genomic players are rigorously putting in their time and efforts in devising new technologies as the scope in the genomic industry is enormous. Companies are investing a larger chunk of their resources into research and development of NextGen and Machine Learning platforms to aid the transformation of the healthcare sector. Sam Santosh, Chairman, Medgenome, claims, “We generate almost 1 PB of data every year through diagnostics and research projects. Most of this data is heterogeneous and complex in nature consisting of raw DNA sequencing and other genomics data, clinical and phenotypic data, demographics, medication and family history, variants/ mutations associated with an individual, and knowledge curation about a specific disease from literature”.

Analysing this data requires sophisticated algorithms as well as the domain knowledge to quickly sift through the mounds of complex data to identify the variations or mutations that explain the disease and can be the potential targets of novel drugs. Various genomic players offer customised tests which use digital technologies to suit the needs of their patients. For instance, Core offers geneCORE Predict which is used as a predictive tool. By sequencing and analysing the genome of an individual they claim to predict the risk, genetic carrier status of 22 types of cancers and the likelihood of passing it on to the next generation, liquiCORE Detect, which enables to obtain information through DNA sequencing, thus assisting the patient to decide the drugs and medical approaches suitable and amnioCORE which is a non-invasive prenatal test (NIPT) detecting the most common foetal genetic disorders during a woman’s pregnancy.

Mithua Ghosh, Director- R&D, Triesta Sciences informs, “Our centre incorporates latest technologies like NGS technology using Illumina sequencers and Digital droplet PCR for Liquid Biopsies in our day-to-day operations. The laboratory is equipped with instruments from companies like Illumina, Agilent, and Bio-Rad which are considered as world standard and trusted in terms of quality.  We collaborate with Strand Life sciences for bioinformatics, who are considered as the best in clinical informatics and analysis platform in terms of accuracy, precision and speed of NGS data analysis.


Being the second most populous country and with a rising burden of infectious and chronic diseases, India is an upcoming market for integrating innovative and cost-effective models. Genomics focuses on prediction and prevention which could eventually lead to the transformation of the healthcare system in the country. Given that the capabilities of genomic sequencing continue to expand, integrating it fully into clinical settings may reduce overall healthcare expenditures. This will further open path to personalised medicine and tailor treatments to individuals not only based on disease symptoms but also based on the genetic make-up.

Santosh elaborates, “These technologies are central to the business because they allow us to generate and analyse the data in a reasonable time and cost, thereby directly benefiting patients by uncovering the underlying cause of the disease faster and accurately. Diagnostic tests based on these advancements offer one of the continuously increasing revenue sources for the company. Services and genomic solutions built using the data across disease areas offer another revenue source. The future revenue source is expected to come from our commitment to developing value from rich clinical and genomics data to better understand the diseases, their progression and molecular underpinnings and helping pharma for novel target discovery and conducting effective clinical trials.”

Pranav Anam, Founder, The Gene Box adds, “Digital Technologies are helping mainly in terms of automating our structure which helps in fast-tracking the process and reducing the chances of error in operations. Thus, saving time and losses due to human errors.”

Though the cost benefits can not be directly interpreted, there is cost saving as due to preventive measures along with personalised medicines will decrease the overall expenditure of the patients.”


Digital technologies are undoubtedly advancing but quite a few hurdles are yet to be overcome. Santosh elaborates that awareness, adoption, affordability and overall reach of these technologies to make the field of medicine and healthcare a truly personalised one is still in the initial stages. He adds that setting up a high-throughput genomics lab not only requires a significant capital investment but also deep technical know-how and trained professionals to optimise the lab workflows and run it efficiently. There is a need to have the domain knowledge to interpret the results of algorithms in a meaningful context. This requires highly qualified professionals with deep expertise in different disease areas to really translate the raw results into the clinical setting which is useful to patients and physicians.

Ghosh elaborates, “Human genetics is evolving so rapidly both in terms of discovery and innovative technologies that costly machines can become obsolete in a very short time.” Anam throws light on the challenges faced due to the issue of quality control.

A few challenges would be faced by the healthcare providers if digital technologies are fully incorporated in genomics. With digital technologies being adopted at a fast pace in many parts of the world, there may arise concerns in regards to human intervention. It is likely that machine learning and other digital technologies may displace some, if not all, healthcare providers. Dr Saleem highlights that just like the West  would be taken over by automated cars replacing the drivers, the healthcare segment will eventually be transfigured. As the medical sector is lacking precision along with comprehensive analytics which machine learning has a knack for, it may soon be required to provide validation for human intervention.

The way forward

On the contrary, Santosh expresses, “Human interventions play a very crucial role to validate the results using independent lines of evidences and translate the results of the algorithms in a context usable by patients and physicians. We strive to build computer systems that can help the domain scientists to pose the right questions, collect evidences from all the necessary databases, literature information – structured or unstructured, validate and visualise the results to eventually generate the report. Despite these advances, given the complex nature of the problem and potential impact on the outcome on patients, these systems are not advanced enough yet to eliminate the human intervention.”

If not immediately, increasing government investments to boost research will eventually be advanced enough to take over the genomics sector supplementing human intervention with precision and machine learning. Thus, the healthcare providers along with the genomic players need to constantly upgrade themselves so as to stay in the game.

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