The Genomics Story... The Gene Logic Story
The term genomics was first used in 1986 to describe the field that aimed to map and sequence the human genome. The field of genomics takes advantage of the common biological language represented by DNA and RNA and combines high throughput sequencing strategies, microchip arrays, digital technology, and computationally intensive analysis to understand the structure, function, and evolution of diverse organisms. The short but exciting history of genomics can be broadly segregated into the early emergence of genomic tools and technologies, newer trends in gene expression analysis and its ultimate impact on biomarker discovery and the emergence of systems biology.
The '90s saw the emergence of new technologies, particularly Gene Expression Technology that came up in a big way. Some of the examples shown above say a lot about the ability of these new technologies to change the face of research. The changing face of genomics propelled us to be the earliest industry adopters of genomics technologies, knowledge databases, discovery platforms and technology driven solutions to cater to the growing needs of global pharmaceutical and biotechnology drug discovery efforts that were beginning to embrace genomics in their in-house research.
Some of the tools that were developed internally by us were READS™ Technology that could disclose the expression of genes not yet represented in the public gene sequence databases, Flow-thru Chip™ technology, a biomolecular analysis platform with performance advantages over traditional substrates for biological sensing applications, Molecular Topography™ tool that could show the changes in gene expression patterns as a disease develops and progresses in a specific cell or tissue type and MuST™ Technology that helped characterize the characterizes the gene regulatory elements responsible for the regulation of the disease-associated genes. The cumulative effort resulted in the creation of the world's largest commercial gene expression facility. We have now managed to process over 40,000 biological samples from more than 200 tissue types on over 200,000 microarrays. We have also identified 2,513 genes associated with heart failure, renal disease, infertility, and other disorders and 1,794 genes associated with mammalian toxicity and agricultural crop characteristics and completed the world's first comprehensive survey of human gene expression across the 40 major normal tissue types.
Gene Logic from 1996 to 1999
Gene expression signatures or patterns capable of distinguishing biological samples belonging to different classes or conditions serve as potential biomarkers. Over the past decade or so, there have been numerous scientific and technological advances that have greatly contributed to a dramatic increase in the number of new chemical entities. An impressive number of these demonstrate good efficacy data in animal disease models. However, only a disappointingly small number of these compounds prove to be effective in clinical studies. Thus, a major challenge in the pharmaceutical industry continues to be reducing the number of projects terminated either because of the lack of efficacy or increased adverse effects in humans. In this scenario, Biomarkers have proved to be of immense value in drug discoveries. Biomarkers can play an important role in drug development even if they are used for internal decision-making purposes prior to an expensive clinical trial with a clinical end-point.
There is a need for new biomarkers to enable faster detection of adverse events due to drugs and disease processes. One would prefer biomarkers that are useful in multiple species (i.e., translational or bridging biomarkers) so that it would be possible to directly link responses between species and follow such injury in both preclinical and clinical settings.
Biomarker discovery has been the focus of our research to address this latent need. Internally developed programs such as ToxExpress™ has identified gene markers associated with toxicity and pathology using gene expression for animal models. These predictive models enable screening of potential toxicity and prioritization of lead compounds earlier in the drug development process. The Program has initiated development of additional predictive capabilities based on other organ models and cell types, including kidney, heart and bone marrow. The program has been used to find biomarkers that predict susceptibility to Parkinson's disease and to identify gene expression patterns in white blood cells (WBC) that are statistically associated with multiple sclerosis (MS) in association with Mayo Clinic and Accelerated Cure Project for Multiple Sclerosis (ACP).
Today, the search for a gene of interest often starts with expressed sequence tags (ESTs), genomic sequence, and protein sequence. A major step in making sequence information publicly available for large-scale analysis that happened in 1982 was the formation of GenBank and its counterpart, the European Molecular Biology Laboratory data library. Efficient algorithms for searching large databases have also been key to making sequence information useful to biologists. Reference databases consisting of large sample numbers and high-dimensional microarray data are now available for the investigation of adverse events in animal model systems such as the rat. This large volume of data, accompanied by appropriate study designs, compound and dose selection procedure, and minimization of technical and biological confounding effects, can yield successful predictive models for a variety of hypotheses. The process of training, validating, and implementing predictive models is cyclical and complex.
The need for such databases prompted us to develop custom gene expression databases targeted to specific therapeutic areas of customer interest, including heart failure, kidney disease, osteoporosis, psychiatric disorders, asthma, allergies, diabetes, and other major disease indications. These databases are being continually developed to make them highly intuitive, visual and usage of convenient tools.
Gene Logic from 2000 to 2007
Some of these functional databases, genomic and toxicogenomic informational databases based on gene expression are rEST™ (rare EST) database containing sequences for rarely-expressed genes that are not available through public sources, TAG™ (The Annotated Genome) database that assigns human genes to functional pathways based on their patterns of expression and regulation, BioExpress™ database that contains a broad survey of both normal and diseased human tissue samples for target discovery and validation, ToxExpress™ database that contains a survey of human and experimental animal tissue samples treated with known toxic compounds for predictive toxicology assessment and ASCENTA® database that is an intuitive, highly visual gene expression reference system provides summarized, high quality microarray expression data from difficult-to-obtain, well-annotated, diseased and normal tissue samples organized into sample sets defined by relevant clinical parameters.
It will be fair to say that the whole Gene Logic story ran parallel to the genomic story and we will continue to do so in the years to come. Your needs have always defined our priorities.
Emergence of functional genomic tools and Gene Expression as a technology
- Researchers from Harvard University reported that gene expression in the brain can differ significantly among members of a species with different life histories...
- Although cancer classification had improved over the past 30 years, there was no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction) till scientists from MIT changed this using gene expression as an approach in 1999...
- In 2000, L Iversen from University of Oxford, suggested that all drugs require a period of several weeks before they become fully effective suggesting that they modify gene expression in the brain and that the resulting altered biochemical state takes a long time to become stabilised...
The '90s saw the emergence of new technologies, particularly Gene Expression Technology that came up in a big way. Some of the examples shown above say a lot about the ability of these new technologies to change the face of research. The changing face of genomics propelled us to be the earliest industry adopters of genomics technologies, knowledge databases, discovery platforms and technology driven solutions to cater to the growing needs of global pharmaceutical and biotechnology drug discovery efforts that were beginning to embrace genomics in their in-house research.
Some of the tools that were developed internally by us were READS™ Technology that could disclose the expression of genes not yet represented in the public gene sequence databases, Flow-thru Chip™ technology, a biomolecular analysis platform with performance advantages over traditional substrates for biological sensing applications, Molecular Topography™ tool that could show the changes in gene expression patterns as a disease develops and progresses in a specific cell or tissue type and MuST™ Technology that helped characterize the characterizes the gene regulatory elements responsible for the regulation of the disease-associated genes. The cumulative effort resulted in the creation of the world's largest commercial gene expression facility. We have now managed to process over 40,000 biological samples from more than 200 tissue types on over 200,000 microarrays. We have also identified 2,513 genes associated with heart failure, renal disease, infertility, and other disorders and 1,794 genes associated with mammalian toxicity and agricultural crop characteristics and completed the world's first comprehensive survey of human gene expression across the 40 major normal tissue types.
Gene Logic from 1996 to 1999
Trends in Gene Expression analysis and repurcussions in Biomarker discovery
Gene expression signatures or patterns capable of distinguishing biological samples belonging to different classes or conditions serve as potential biomarkers. Over the past decade or so, there have been numerous scientific and technological advances that have greatly contributed to a dramatic increase in the number of new chemical entities. An impressive number of these demonstrate good efficacy data in animal disease models. However, only a disappointingly small number of these compounds prove to be effective in clinical studies. Thus, a major challenge in the pharmaceutical industry continues to be reducing the number of projects terminated either because of the lack of efficacy or increased adverse effects in humans. In this scenario, Biomarkers have proved to be of immense value in drug discoveries. Biomarkers can play an important role in drug development even if they are used for internal decision-making purposes prior to an expensive clinical trial with a clinical end-point.
There is a need for new biomarkers to enable faster detection of adverse events due to drugs and disease processes. One would prefer biomarkers that are useful in multiple species (i.e., translational or bridging biomarkers) so that it would be possible to directly link responses between species and follow such injury in both preclinical and clinical settings.
Biomarker discovery has been the focus of our research to address this latent need. Internally developed programs such as ToxExpress™ has identified gene markers associated with toxicity and pathology using gene expression for animal models. These predictive models enable screening of potential toxicity and prioritization of lead compounds earlier in the drug development process. The Program has initiated development of additional predictive capabilities based on other organ models and cell types, including kidney, heart and bone marrow. The program has been used to find biomarkers that predict susceptibility to Parkinson's disease and to identify gene expression patterns in white blood cells (WBC) that are statistically associated with multiple sclerosis (MS) in association with Mayo Clinic and Accelerated Cure Project for Multiple Sclerosis (ACP).
The era of data management tools and functional databases- the emergence of Systems Biology
Today, the search for a gene of interest often starts with expressed sequence tags (ESTs), genomic sequence, and protein sequence. A major step in making sequence information publicly available for large-scale analysis that happened in 1982 was the formation of GenBank and its counterpart, the European Molecular Biology Laboratory data library. Efficient algorithms for searching large databases have also been key to making sequence information useful to biologists. Reference databases consisting of large sample numbers and high-dimensional microarray data are now available for the investigation of adverse events in animal model systems such as the rat. This large volume of data, accompanied by appropriate study designs, compound and dose selection procedure, and minimization of technical and biological confounding effects, can yield successful predictive models for a variety of hypotheses. The process of training, validating, and implementing predictive models is cyclical and complex.
The need for such databases prompted us to develop custom gene expression databases targeted to specific therapeutic areas of customer interest, including heart failure, kidney disease, osteoporosis, psychiatric disorders, asthma, allergies, diabetes, and other major disease indications. These databases are being continually developed to make them highly intuitive, visual and usage of convenient tools.
Gene Logic from 2000 to 2007
Some of these functional databases, genomic and toxicogenomic informational databases based on gene expression are rEST™ (rare EST) database containing sequences for rarely-expressed genes that are not available through public sources, TAG™ (The Annotated Genome) database that assigns human genes to functional pathways based on their patterns of expression and regulation, BioExpress™ database that contains a broad survey of both normal and diseased human tissue samples for target discovery and validation, ToxExpress™ database that contains a survey of human and experimental animal tissue samples treated with known toxic compounds for predictive toxicology assessment and ASCENTA® database that is an intuitive, highly visual gene expression reference system provides summarized, high quality microarray expression data from difficult-to-obtain, well-annotated, diseased and normal tissue samples organized into sample sets defined by relevant clinical parameters.
It will be fair to say that the whole Gene Logic story ran parallel to the genomic story and we will continue to do so in the years to come. Your needs have always defined our priorities.
