Global Biochips Market size and forecast By 2020

Bio-microsystem is a group of miniaturized and integrated devices for biological or biochemical reactions in diagnostics, monitoring, therapy, and research and development. Some of the advantages of bio-microsystems are parallelism, integrated intelligence, low cost, speed, complexity and redundancy. Biochip is one of the examples of technical development of bio-microsystem. Biochip is a collection of microarrays arranged on a solid substrate which allows hundreds or thousands of complex biochemical reactions such as decoding genes in few seconds. Biochips are used in variety of applications such as research application in biotechnology such as genomics and proteomics, drug screening and development and molecular diagnostics. It also offers other diagnostic applications such as microfluidic technologies, microarray and biosensors. Biochip is also used to analyze organic molecules associated with living organisms. Biochip helps in identifying gene sequences, airborne toxins, environmental pollutants and other biochemical constituents. There are various types of biochips such as DNA chips, lab-on-a-chip and protein chips. Chip based analysis is mainly used in on-site diagnostics.

North America dominates the global market for biochips due to large number of aging population and broad technical applications of biochips. Asia followed by the Europe are expected to show high growth rates in the next five years in global biochips market. China and India are expected to be the fastest growing biochips markets in Asia-Pacific region. Some of the key driving forces for biochip market in emerging countries are increasing R&D investment, large pool of patients and rising government funding.

In recent times there is increased use of biochips due to increasing cancer treatment and diagnostics. Rise in personalized medicine, drug discovery and life science research, need for high speed diagnostics and increased government funding are some of the key factors driving the growth for global biochips market. In addition, increasing healthcare awareness is also fuelling the growth of global biochips market. However, limited technical knowledge related to biochips, low acceptance due to high cost and availability of alternative technologies are some of the major factors restraining the growth for global biochip market.

Increasing R&D investment and outsourcing of pharmaceutical companies would lead to growth in biochips market in Asia. In addition, broaden application of biochips products would develop opportunity for global biochip market. However, high cost involved in manufacturing of biochips could lead a challenge for global biochips market. Some of the trends for global biochips market are outsourcing of biochips technology, which would help in reducing labor cost and capital requirement. Some of the major companies operating in the global biochips market are Affymetric Inc, Illumina Inc, GE Healthcare Ltd, Agilent Technologies Inc. Roche NimbleGen, Life Technologies Corporation, EMD Millipore., Bio-Rad Laboratories Inc, Abbott Laboratories and Fluidigm Corporation.

( Source: Persistence Market Research)

How Will Genomics Enter Day-to-day Medicine?

Summary:  A quiet transformation has been brewing in medicine, as large-scale DNA results become increasingly available to patients and healthcare providers. Amid a cascade of data, physicians, counselors and families are sorting out how to better understand and use this information in making health care decisions.


National experts who have gathered in Clinical Genetics Think Tank meetings at two large pediatric hospitals recently issued their first recommendations for integrating genomics into clinical practice.

The recommendations appeared online May 12, 2016 in Genetics in Medicine, co-led by Ian D. Krantz, M.D., director of the Individualized Medical Genetics Center at The Children’s Hospital of Philadelphia (CHOP), and Ronald D. Cohn, M.D., co-director of the Centre for Genetic Medicine at the Hospital for Sick Kids in Toronto.

“As genetic testing has become more complex, it’s being applied across many more medical specialties and into primary care,” said Krantz, a clinical geneticist. “These tests will move toward broad use in screening healthy populations, and our recommendations aim to help people better integrate testing results into clinical practice.”

Krantz and co-author Sarah Bowdin, M.D., of the Centre for Genetic Medicine at the Hospital for Sick Kids in Toronto, spearheaded the two Clinical Genetics Think Tanks, hosted at their respective hospitals in 2014 and 2015.

Co-authors of the recommendations are other Think Tank participants: clinical geneticists, genetic counselors, and laboratory professionals and bioinformatics experts. “Our co-authors represent the main stakeholders in this field,” said Krantz. “We also included patients and parents in the Think Tanks, to incorporate their experiences in dealing with these concerns on an everyday basis.”

Krantz added that he and Bowdin launched the Think Tanks after hearing from colleagues struggling with many similar issues as other institutions established clinical genomic and exome sequencing programs. Among those challenges were how to best interpret DNA findings, how to report to patients and clinicians about gene variants of uncertain significance, how to report secondary findings unrelated to the primary reason for the testing, and how to share findings with other centers. “As each institution independently developed its own procedures, we thought that exchanging experiences across our field could improve overall practice.”

The recommendations address the pretesting process (including selecting patients and obtaining insurance coverage), patient and clinician education, interpreting sequence data, and posttest patient care (including how to return test findings and offer reevaluation of data). Another broad area, added Krantz, is phenotyping–establishing consistent terminology for patients’ clinical characteristics, so that clinicians can better interpret the significance of DNA results, share data across centers, and ultimately standardize care for patients.

Krantz compared these new challenges to a more straightforward clinical situation–obtaining a targeted genetic test for fragile X syndrome–in which a test reveals whether a patient has a specific DNA change that causes fragile X symptoms. In contrast, current clinical genome and exome sequencing produces many unknowns: for each individual, test results yield many variants of uncertain significance, as well as secondary findings, which are genetic variants unrelated to the primary condition for which a patient is tested.

Facing a flood of DNA data, families told other Think Tank participants that they often preferred two posttest sessions to discuss test findings–one to learn the principal diagnostic results, and a second session to discuss secondary findings that are medically actionable.

Crucially, Krantz added, the data from genomic testing are dynamic–as new scientific knowledge accumulates, the significance of data changes: some findings of uncertain significance will become clearer, and will become medically actionable in the future, so that healthcare providers will need to devise ways to systematically offer future reevaluation of a patient’s genome. “We need to make these data longitudinal, not static,” he said.

One emerging issue raised in the Think Tanks is how to best integrate genomic results into each patient’s electronic health record. This becomes all the more important, said Krantz, as clinical sequencing moves toward general screening of healthy patient populations, including newborns, as part of the progression toward precision medicine.

One conversation with a family, added Krantz, helped to drive home that issue. He was explaining results of genomic testing in a child with multiple medical issues. After learning the unexpected secondary finding that their child carried a cancer predisposition gene, the parents asked about performing the test for their healthy child too.

“We have framed this document not as a set of overt guidelines, but as recommendations, which we expect to change as our field evolves,” said Krantz. He added that future Think Tanks may meet to address new challenges.

(Source: The above post is reprinted from materials provided by Children’s Hospital of Philadelphia. CHOP News)

Global Genomics Market Outlook: 2015-2020

Genomics is a discipline which analyzes the function and structure of genomes. It uses various sampling, sequencing, and data analysis and interpretation techniques to decode, assemble, and analyze genomes. The knowledge of complete set of DNA helps to identify certain genetic diseases, develop best course of treatment, and contribute to precision medicine.

With the significant decrease in the sequencing costs and rising investments in the pharmaceutical industry, the global genomics market is forecast to grow at a CAGR of 15.1% to be worth $19,938.6 million by 2020.

This growth is further driven by the technological innovations in bioinformatics, increasing clinical capabilities, and more clinically relevant sequencing timescales. However, need of significant clinical investment, lack of funding in the emerging markets, rising consolidation mainly in the instruments market, and ethical and legal challenges will act as a constraint to industry growth during the forecast period.

The global genomics market is segmented by methods, technology, instruments, consumables, services, and geography. The genomics industry is still at a nascent stage with many untapped markets present across the globe. However, the sequencing method is relatively at a mature stage, especially, in the developed markets. As, the scale of genomes data grows, the data analysis and interpretation market is expected to grow at a significant rate in the near future. Next-generation DNA sequencing (NGS) technology has transformed biomedical research, making genome and RNA sequencing an affordable and commonly used tool for a wide variety of research applications. As a result, the market has been stressed to manage the enormous data output from this process. Therefore, the complexity and sheer amount of data generated by NGS has led to a need for genomic centers to form bioinformatics teams in order to analyze the output data.

North America is the major market in the global genomics market and is expected to dominate this market during the forecast period, with the U.S. contributing a major share, followed by Europe, and Asia-Pacific. On the other hand, the Asian market, especially India and China, is expected to witness a boost in demand for genomics market during the forecast period, as a result of their economic development, increasing genetic research and development activities, drastically reduced mass scale genetic testing costs, and the growing focus of the major players in this region.

The key players in the global genomics market are Affymetrix, Inc., Agilent Technologies, BGI (Beijing Genomics Institute), Illumina, Inc., Thermo Fisher Scientific, Inc., Bio-Rad Laboratories, Inc., Cepheid, GE Healthcare, Qiagen N.V, Roche Holding AG, Pacific Biosciences of California, Inc., Oxford Nanopore Technologies Ltd., Beckman Coulter Genomics, Inc., Perkin Elmer, Inc., DNASTAR, Inc, Genomatix Software Gmbh, and GenoLogics Life Sciences Software, Inc.,

The global genomics market is segmented by methods, technology, instruments, consumables, services, and geography:

Genomics Methods/Stages

– Sampling,

– Sequencing,

– Analysis,

– Interpretation

– Application

Genomics Technology


– Sequencing

– Microarray

– Nucleic acid Extraction & Purification

Genomics Instruments


– NGS Platforms

– DNA Microarrays

– Nucleic acid Extraction and Purification Systems

– DNA Sequencers

– Others

NGS Platforms

– Illumina

– Thermo

– Roche

– Pacific Biosciences

Genomics Consumables


– DNA Sequencing

– Nucleic acid extraction and purification systems

– Genechips

– Microarrays

– Others

Genomics Services

– Laboratory Services

– Software

Genomics Market, By Geography

North America

o U.S.

o Canada


o U.K.

o Germany

o France

o Italy

o Spain

o Rest of Europe


o Japan

o China

o India

o Rest of Asia-Pacific

– Rest of the World

o Latin America

o Middle East and Africa

(Source: PRNewswire)

Using deep learning to analyze genetic mutations

Full article written by David Beyer can be found here: Deep learning meets genome biology

  • The application of deep learning to genomic medicine is off to a promising start; it could impact diagnostics, intensive care, pharmaceuticals and insurance.
  • The “genotype-phenotype divide”—our inability to connect genetics to disease phenotypes—is preventing genomics from advancing medicine to its potential.
  • Deep learning can bridge the genotype-phenotype divide, by incorporating an exponentially growing amount of data, and accounting for the multiple layers of complex biological processes that relate the genotype to the phenotype.
  • Deep learning has been successful in applications where humans are naturally adept, such as image, text, and speech understanding. The human mind, however, isn’t intrinsically designed to understand the genome. This gap necessitates the application of “super-human intelligence” to the problem.
  • Efforts in this space must account for underlying biological mechanisms; overly simplistic, “black box” approaches will drive only limited value.

(Source: Deep Genomics)


CRISPR gene editing: A commercial timeline

In just three years, CRISPR gene editing has hurtled to the forefront of biological science – with vast potential in agribusiness, human health, and industrial biotechnology. And unlike many nascent biotechs, which take years to attract significant funding, CRISPR has already attracted a lot of commercial interest. 2015 was a banner year for the technology. One could wager that once this patent nonsense is behind us, CRISPR will accelerate forward at breakneck pace.

The Broad Institute has a comprehensive timeline of CRISPR’s scientific development. Scientific American just published a story that details CRISPR’s commercial timeline. Here it is, sequentially:

January 2015

  • Novartis signs two deals with Intellia Therapeutics and Caribou Biosciences to engineer immune cells and blood stem cells, meant for drug discovery research.
  • AstraZeneca signs four deals with the Wellcome Trust Sanger Institute, the Innovative Genomics Initiative, the Broad and Whitehead Institutes in Massachusetts, and Thermo Fisher Scientific. It’s meant for preclinical validation of new drug targets.

May 2015

  • Juno Therapeutics and Editas Medicine collaborate on next-gen CAR-T and TCR Cell therapies.

August 2015

October 2015

  • Vertex Pharmaceuticals and CRISPR Therapeutics sign a deal worth up to $2.6 billion.

December 2015

  • Bayer and CRISPR Therapeutics team up in a $335 million gene editing pact to develop new therapies for blood disorders, blindness and congenital heart disease.

January 2016

(Source: MedCityNews)

CRISPR Timeline

The discovery of the CRISPR-Cas microbial adaptive immune system and its ongoing development into a genome editing tool represents the work of many scientists from around the world. This timeline presents a concise history of the seminal contributions and the scientists who pushed this field forward, from the initial discovery to the first demonstrations of CRISPR-mediated genome editing.

For a narrative perspective of the history of CRISPR research, read “The Heroes of CRISPR,” by Eric S. Lander, in the January 14, 2016 edition of Cell.

Discovery of CRISPR and its function

1993 – 2005 – – Francisco Mojica, University of Alicante, Spain

Francisco Mojica was the first researcher to characterize what is now called a CRISPR locus, reported in 1993. He worked on them throughout the 1990s, and in 2000, he recognized that what had been reported as disparate repeat sequences actually shared a common set of features, now known to be hallmarks of CRISPR sequences (he coined the term CRISPR through correspondence with Ruud Jansen, who first used the term in print in 2002). In 2005 he reported that these sequences matched snippets from the genomes of bacteriophage (Mojica et al., 2005). This finding led him to hypothesize, correctly, that CRISPR is an adaptive immune system. Another group, working independently, published similar findings around this same time (Pourcel et al., 2005)

Discovery of Cas9 and PAM

May, 2005 — Alexander Bolotin, French National Institute for Agricultural Research (INRA)

Bolotin was studying the bacteria Streptococcus thermophilus, which had just been sequenced, revealing an unusual CRISPR locus (Bolotin et al., 2005). Although the CRISPR array was similar to previously reported systems, it lacked some of the known cas genes and instead contained novel cas genes, including one encoding a large protein they predicted to have nuclease activity, which is now known as Cas9. Furthermore, they noted that the spacers, which have homology to viral genes, all share a common sequence at one end. This sequence, the protospacer adjacent motif (PAM), is required for target recognition.

Hypothetical scheme of adaptive immunity

March, 2006 — Eugene Koonin, US National Center for Biotechnology Information, NIH

Koonin was studying clusters of orthologous groups of proteins by computational analysis and proposed a hypothetical scheme for CRISPR cascades as bacterial immune system based on inserts homologous to phage DNA in the natural spacer array, abandoning previous hypothesis that the Cas proteins might comprise a novel DNA repair system.

Experimental demonstration of adaptive immunity

March, 2007 — Philippe Horvath, Danisco France SAS

S. thermophilus is widely used in the dairy industry to make yogurt and cheese, and scientists at Danisco wanted to explore how it responds to phage attack, a common problem in industrial yogurt making. Horvath and colleagues showed experimentally that CRISPR systems are indeed an adaptive immune system: they integrate new phage DNA into the CRISPR array, which allows them to fight off the next wave of attacking phage (Barrangou et al., 2007). Furthermore, they showed that Cas9 is likely the only protein required for interference, the process by which the CRISPR system inactivates invading phage, details of which were not yet known.

Spacer sequences are transcribed into guide RNAs

August, 2008 — John van der Oost, University of Wageningen, Netherlands

Scientists soon began to fill in some of the details on exactly how CRISPR-Cas systems “interfere” with invading phage. The first piece of critical information came from John van der Oost and colleagues who showed that in E-scherichia coli, spacer sequences, which are derived from phage, are transcribed into small RNAs, termed CRISPR RNAs (crRNAs), that guide Cas proteins to the target DNA (Brouns et al., 2008).

CRISPR acts on DNA targets

December, 2008 — Luciano Marraffini and Erik Sontheimer, Northwestern University, Illinois

The next key piece in understanding the mechanism of interference came from Marraffini and Sontheimer, who elegantly demonstrated that the target molecule is DNA, not RNA (Marraffini and Sontheimer, 2008). This was somewhat surprising, as many people had considered CRISPR to be a parallel to eukaryotic RNAi silencing mechanisms, which target RNA. Marraffini and Sontheimer explicitly noted in their paper that this system could be a powerful tool if it could be transferred to non-bacterial systems. (It should be noted, however, that a different type of CRISPR system can target RNA (Hale et al., 2009)).

Cas9 cleaves target DNA

December, 2010 — Sylvain Moineau, University of Laval, Quebec City, Canada

Moineau and colleagues demonstrated that CRISPR-Cas9 creates double-stranded breaks in target DNA at precise positions, 3 nucleotides upstream of the PAM (Garneau et al., 2010). They also confirmed that Cas9 is the only protein required for cleavage in the CRISPR-Cas9 system. This is a distinguishing feature of Type II CRISPR systems, in which interference is mediated by a single large protein (here Cas9) in conjunction with crRNAs.

Discovery of tracrRNA for Cas9 system

March, 2011 — Emmanuelle Charpentier, Umea University, Sweden and University of Vienna, Austria

The final piece to the puzzle in the mechanism of natural CRISPR-Cas9-guided interference came from the group of Emmanuelle Charpentier. They performed small RNA sequencing on Streptococcus pyogenes, which has a Cas9-containing CRISPR-Cas system. They discovered that in addition to the crRNA, a second small RNA exists, which they called trans-activating CRISPR RNA (tracrRNA) (Deltcheva et al., 2011).  They showed that tracrRNA forms a duplex with crRNA, and that it is this duplex that guides Cas9 to its targets.

CRISPR systems can function heterologously in other species

July, 2011 — Virginijus Siksnys, Vilnius University, Lithuania

Siksnys and colleagues cloned the entire CRISPR-Cas locus from S. thermophilus (a Type II system) and expressed it in E. coli (which does not contain a Type II system), where they demonstrated that it was capable of providing plasmid resistance (Sapranauskas et al., 2011). This suggested that CRISPR systems are self-contained units and verified that all of the required components of the Type II system were known.

Biochemical characterization of Cas9-mediated cleavage

September, 2012 — Virginijus Siksnys, Vilnius University, Lithuania

Taking advantage of their heterologous system, Siksnys and his team purified Cas9 in complex with crRNA from the E. coli strain engineered to carry the S. thermophilus CRISPR locus and undertook a series of biochemical experiments to mechanistically characterize Cas9’s mode of action (Gasiunas et al., 2012).They verified the cleavage site and the requirement for the PAM, and using point mutations, they showed that the RuvC domain cleaves the non-complementary strand while the HNH domain cleaves the complementary site. They also noted that the crRNA could be trimmed down to a 20-nt stretch sufficient for efficient cleavage. Most impressively, they showed that they could reprogram Cas9 to a target a site of their choosing by changing the sequence of the crRNA.

June, 2012 — Charpentier and Jennifer Doudna, University of California, Berkeley

Similar findings as those in Gasiunas et al. were reported at almost the same time by Emmanuelle Charpentier in collaboration with Jennifer Doudna at the University of California, Berkeley (Jinek et al., 2012). Charpentier and Doudna also reported that the crRNA and the tracrRNA could be fused together to create a single, synthetic guide, further simplifying the system. (Although published in June 2012, this paper was submitted after Gasiunas et al.)

CRISPR-Cas9 harnessed for genome editing

January, 2013 — Feng Zhang, Broad Institute of MIT and Harvard, McGovern Institute for Brain Research at MIT, Massachusetts

Zhang, who had previously worked on other genome editing systems such as TALENs, was first to successfully adapt CRISPR-Cas9 for genome editing in eukaryotic cells (Cong et al., 2013). Zhang and his team engineered two different Cas9 orthologs (from S. thermophilus and S. pyogenes) and demonstrated targeted genome cleavage in human and mouse cells. They also showed that the system (i) could be programmed to target multiple genomic loci, and (ii) could drive homology-directed repair. Researchers from George Church’s lab at Harvard University reported similar findings in the same issue of Science (Mali et al., 2013).

( Source: Broad Institute of MIT and Harvard)

DNA Sequencing

Since the completion of the Human Genome Project, technological improvements and automation have increased speed and lowered costs to the point where individual genes can be sequenced routinely, and some labs can sequence well over 100,000 billion bases per year, and an entire genome can be sequenced for just a few thousand dollars.

Many of these new technologies were developed with support from the National Human Genome Research Institute (NHGRI) Genome Technology Program and its Advanced DNA Sequencing Technology awards. One of NHGRI’s goals is to promote new technologies that could eventually reduce the cost of sequencing a human genome of even higher quality than is possible today and for less than $1,000.

Researchers now are able to compare large stretches of DNA – 1 million bases or more – from different individuals quickly and cheaply. Such comparisons can yield an enormous amount of information about the role of inheritance in susceptibility to disease and in response to environmental influences. In addition, the ability to sequence the genome more rapidly and cost-effectively creates vast potential for diagnostics and therapies.

Although routine DNA sequencing in the doctor’s office is still many years away, some large medical centers have begun to use sequencing to detect and treat some diseases. In cancer, for example, physicians are increasingly able to use sequence data to identify the particular type of cancer a patient has. This enables the physician to make better choices for treatments.

Researchers in the NHGRI-supported Undiagnosed Diseases Program use DNA sequencing to try to identify the genetic causes of rare diseases. Other researchers are studying its use in screening newborns for disease and disease risk.

Moreover, The Cancer Genome Atlas project, which is supported by NHGRI and the National Cancer Institute, is using DNA sequencing to unravel the genomic details of some 30 cancer types.  Another National Institutes of Health program examines how gene activity is controlled in different tissues and the role of gene regulation in disease. Ongoing and planned large-scale projects use DNA sequencing to examine the development of common and complex diseases, such as heart disease and diabetes, and in inherited diseases that cause physical malformations, developmental delay and metabolic diseases.

(Resource: National Human Genome Research Institute)