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Predicting and Reducing Immunogenicity

  PREDICTING AND REDUCING IMMUNOGENICITY As discussed the mechanisms leading to antibody induction by therapeutic proteins are still not completely understood. As a consequence it is impossible based on our current knowledge to fully predict the immunogenicity of a new product in patients. For nonhuman proteins which induce the classical immune response, the level of nonself is a relative predictor of an immune response. However, it is not an absolute predictor. Sometimes a single amino acid change is sufficient to make a self protein highly immunogenic. With other proteins substantial diver-gence from the natural sequence has no effect. For foreign proteins a number of in vitro stimulation and binding tests and computational models are adver-tised as predictors of immunogenicity. However, all these tests have their limitations. T-cell proliferation assays, for example, have the drawback that many antibodies are capable of inducing some level of T-cell activation or inhibit cell prolif
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Genomics, “Omics” Technologies, Personalized Medicine

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  Genomics, Other “Omics” Technologies,Personalized Medicine, and Additional  Biotechnology-Related Techniques INTRODUCTION Pharmaceutical biotechnology and the products result-ing for biotechnologies continue to grow at an exponential rate. Note that 2005 was a record setting year with the U.S. Food and Drug Administration (FDA) approval of 21 biopharmaceutical products. There were 15 FDA approvals in 2004, 20 in 2003, and 13 in 2002 since the last edition of this textbook (Rader 2006; Staff, 2006). Early 2006 saw approvals of several unique new biopharmaceutical entities including a recombinant vaccine widely hailed as the first vaccine for the prevention of an oncogenic virus-associated cancer. However, until recently, the techniques made available by advances in molecular biology and biotechnology that have provided currently approved therapeutic agents generally fell into two broad areas: recombinant DNA (rDNA) technology and hybridoma techniques (to produce monoclonal antibodies)
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An Introduction to “Omics” Technologies

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  AN INTRODUCTION TO “OMICS” TECHNOLOGIES Since the discovery of DNA’s overall structure in 1953, the world’s scientific community has continued to gain a better understanding of the genetic information encoded by DNA and the genetic information carried by a cell or organism. In the 1980s and 1990s,biotechnology techniques produced novel therapeutics and a wealth of information about the mechanisms of various diseases such as cancer. Yet the etiology of many other diseases, including obesity and heart disease, remained unknown at the genetic and the molecular level, presenting no obvious target to attack with a small molecule drug or biotechnology-produced therapeutic agent. The answers were hidden in what was unknown about the human genome. Despite the increasing knowledge of DNA structure and function in the 1990s, the genome, the entire collection of genes and all other functional and non-functional DNA sequences in the nucleus of an organism, had yet to be sequenced. DNA may well b
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Genomics - An Introduction to “Omics” Technologies

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  Genomics   Sequencing the human genome and the genomes of other organisms has lead to an enhanced under-standing of human biology and disease. Many industry analysts predicted a tripling of pharmaceutical R&D productivity due to the sequencing of the human genome (Williams, 2007). Success to date has been limited and there is significant debate as to the impact of genomics on successful drug discovery and development (Nirmala, 2006; Caldwell et al., 2007). Validation of viable drug targets identified by genomics has been challenging (Bagowski, 2005). An interesting concept is that of the “druggable” genome (Hopkins and Groom, 2002). This is an estimate at 600 to 1,500 valid molecular targets for drug discovery, as assessed as the intersection of the number of human genes identified linked to disease with the subset of the human genome products that could be modulated by small-molecule targets. However, the genomics revolution has been the foundation for an explosion in “omics” te
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“Omics” Enabling Technology: Bioinformatics

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  “Omics” Enabling Technology: Bioinformatics Structural genomics, functional genomics, proteomics, and other “omic” technologies have generated an enormous volume of genetic and biochemical data to store. The entire encoded human DNA sequence alone requires computer storage of approximately 10 9  bits of information: the equivalent of a thousand 500-page books! GenBank (managed by the National Center for Biotechnology Information, NCBI, of the National Institutes of Health), the European Molecular Biology Laboratory (EMBL), and the DNA Data Bank of Japan (DDBJ) are three of the many centers worldwide that collaborate on collecting DNA sequences. These databanks, (both public and private) store tens of millions of sequences (Martin et al., 2007). Metabolic databases and other collections of biochemical and bioactivity data add to the complexity and wealth of information (Olah and Oprea, 2007). Once stored, analyzing the volumes of data, (i.e., comparing and relating information from va
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Transcriptomics - An Introduction to “Omics” Technologies

  Transcriptomics This technology examines the complexity of messen-ger RNA transcripts of an organism (i.e., transcrip-tome), under a variety of internal and external conditions reflecting the genes that are being actively expressed at any given time (with the exception of mRNA degradation phenomena such as transcrip-tional attenuation) (Subramanian et al., 2005). Therefore, the transcriptome can vary with external environmental conditions while the genome is roughly fixed for a given cell line (excluding  mutations). The transcriptomes of stem cells and cancer cells are of particular interest to better under-stand the processes of cellular differentiation and carcinogenesis. High-throughput techniques based on microarray technology are used to examine the expression level of mRNAs in a given cell population.
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Proteomics, Structural Proteomics, and Functional Proteomics - “Omics” Technologies

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  Proteomics, Structural Proteomics, and Functional Proteomics Functional genomics research will provide an unprece-dented information resource for the study of biochemical pathways at the molecular level. Certainly a large number of the  ~ 25,000 genes identified in sequencing the human genome will be shown to be functionally important in various disease states (see druggable genome discussion above). This will result in the identification of a vast array of proteins implicated as playing pivotal roles in disease processes (Evans, 2003). These key identified proteins will serve as potential new sites for therapeutic intervention (Fig. 1). The research area called proteomics seeks to define the function and correlate that with expression profiles of all proteins encoded within an organism’s genome or “proteome” (Edwards et al., 2000; Kreider, 2001; Voshol et al., 2007). The  ~ 25,000 human genes can produce 100,000 proteins. The number, type and concentration may vary depending on cell
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