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DNAPrint genomics is a young e-biotech company based in southwest Florida. We are developing an informatics platform system that will provide dynamic solutions for disease gene discovery, genetic predisposition and genetic analysis testing. Our work has real-life application to the germinating field of Personalized Medicine and will help lay the foundation for a brand-new area of medical research called Phenomics.
The PhenomeSM platform system that we are developing will help identify an individual predisposed to develop cancer before the onset of illness so that lifestyles can be altered and/or preventative measures taken. It will be used to identify individuals who are incompatible with certain drug treatments before the drugs are prescribed and damage is done. It will be used to tease out important genetic determinants associated with complex genetic diseases, so that drugs can be developed to target these genes.
Our aim is ambitious. By partnering our platform with biotech/pharma, we will participate in the downstream profits generated from pharmaceutical products our platform has enabled. By marketing our platform directly to the public, we intend to make comprehensive genotype screening solutions accessible to people all over the world via the internet. Our system will enable a more holistic approach to using genomics information to improve peoples lives.
The patient of the future will have more information and power than ever imagined. The human genome project, the internet and recent technological advancements all contribute to make this possible, and we intend to take advantage of these synergies to become the primary conduit for the generation and distribution of personalized genetic information.
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Our Aim
We intend to enable the application of human genomics to help prevent, define and diagnose disease. We will do this by developing a new high throughput informatics platform by which SNPs and complex sets of SNPs can be holistically and comprehensively associated with complex diseases and physical traits.
Our model is to license/partner our platform to generate 21st century medicines, and enable personalized medical analysis. We will do this through a combination of license/partnerships, hardware and software placement and application service provider (ASP) based models.
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Founders
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Tony Frudakis
Tony Frudakis, Ph.D.(tfrudakis@dnaprint.com)
Chief Executive Officer, President and Laboratory Director. Dr. Tony Frudakis is a Phi Beta Kappa, Magna Cumme Laude graduate of the University of California system. He received his doctorate degree in molecular and cell biology from the University of California Berkeley and has 14 total years of experience as a molecular biologist. Dr. Frudakis' technical experience encompass a range of areas within biology, including the molecular biology of eukaryotic transcriptional regulation, the creation and study of transgenic animals, the development of novel nucleic acid isolation techniques and gene discovery protocols, bioinformatics processing and anatomical gene expression profiling. At Corixa Corporation in Seattle, WA he developed several new techniques for RNA fingerprinting, managed and executed high-throughput gene discovery programs for various cancers and was instrumental in the companies early success in attracting R and D partners. Founding GAFF biologic in 1998, Dr. Frudakis established a good reputation for high quality DNA sequencing and library construction/screening services, until its evolution into the DNAPrint Genomics that exists today. In all, his work has resulted in a patent portfolio for over 350 unique genes and 2 products
George Frudakis
George Frudakis(gfrudakis@dnaprint.com)
Vice President of Business Affairs. George Frudakis has vast experience with start-up company development. He started and developed a successful multi-component company called GAFF group, which today enjoys over 15 million dollars annually in revenue. During his life’s work as an entrepreneur and businessman, George has learned how to run and successfully manage the financial and operational aspects of both small and large companies alike. He is a graduate from the California State University at Long Beach in California.
Myung Ho Kim, Ph.D. Mathematics
Myung Ho Kim, Ph.D. Mathematics(mkim@dnaprint.com)
Director of Informatics and Lead Mathemetician. Myung recieved his Ph.D. in Mathematics from the University of Michigan in Ann Arbor in 1988 and M.S. in Mathematics from The Ohio State University in Columbus Ohio. Most recently, Myung worked on the Ant World Server project supported by DARPA (Defense Advanced Research Progect Agency) and implemented Kolmogorov-Smirnov tests, linear/nonlinear regression, nonparametric analysis and modeling to a TREC 6 (Text Retrieval Conference) project using SAS, C/C++ and Perl languages. Prior to this, Myung simulated mathematical modeling for breast tumors and implemented/developed various image processing algorithms. He has served as an Honorary research Fellow in the Department of Mathematics and Information Science at the University of Auckland, New Zealand and a Visiting Research Scholor in the Department of Mathematics at the University of California at Santa Cruz in California. Prior to coming to the United States, Myung held the position of Assistant Professor in the Department of Mathematics at Sungkyunkwan University in Soel Korea.
Venkateswarlu Kondragunta, Ph.D.
Venkateswarlu Kondragunta, Ph.D. (vkondragunta@dnaprint.com)
Director of Biostatistics. Dr. Kondragunta obtained his Ph.D. in Statistics from the University of Madras, Madras, India. He most recently served as a Postdoctoral Fellow at the School of Public Health, University of Texas, Houston, TX under the tutelage of Dr. Ranajit Chakraborty, one of the most famous and accomplished genetic mathematicians in the world. His research interests include variance components, linear regression models, general linear models, design and analysis, discriminant analysis, principal component analysis and statistical genetics. He has taught courses in Variance Components, Design and Analysis of Experiments and Linear Regression Models and Probability Theory at Concordia University in Montreal, Canada. Dr. Kondragunta is an accomplished programmer and has amassed considerable experience with implementing statistical genetic ideas into C++, S-plus, FORTRAN (7 years experience) and JAVA code. His most recent work used the REG, ANOVA, GLM, VARCOMP, CANDISC, CLUSTER, DISCRIM, FACTOR, PRINCOMP and LOGISTIC tools in the SAS computing environment on real and simulated data sets.
A partial list of publications for Dr. Kondragunta include:
Chaubey, Y.P. and K.Venkateswarlu. A numerical study of some robust estimators of variance components in one-way model. International Indian Statistical Association Conference proceedings, October 10-11, 1998, McMaster University, Hamilton, Canada.
Venkateswarlu, K. K.N.Ponnuswamy, and M.R.Srinivasan. Estimation of variance components based on diallel model. Mathematical Biosciences, V-150, 105-112.
Venkateswarlu, K, and K.N.Ponnuswamy. Estimation of variance components based on bio-model of diallel crosses (balanced). Communications in Statistics (Theory & Methods), Vol-27, 139-152.
Venkateswarlu, K. Estimation of variance components based on diallel model involving maternal and maternal interaction effects. Biometrical Journal, Vol-39, 287-295.
Phenomics
Over the past several years, scientists all over the world have been working to assemble genome databases for a variety of organisms including humans. These studies, called genome projects, aim to produce catalogues of genes for each organism. However, simply having genome information is not the same as knowing how to read or understand it, because this data contains little information about the construction or behavior of integrated cellular genetic processes. If we are to take advantage of the wealth of genome data in our databases, we need to learn how to translate static genome information into dynamic functional information.
Phenomics is a field of study borne from the completion of the human genome project to effect just this end. Simply put, it is study of genomics information to better understand the complex relationship between genotype and phenotype. This relationship is frequently non-linear in nature, which poses a problem for traditional means of genetic study. These traditional methods are not well suited to accommodate the effect of quantitative trait loci or multi-dimensional genetic interactions at work in the determination of most human phenotypes. Through the use of heuristic algorithms and empirical data sets, we aspire to apply raw genomics data to real life study, by considering the multi-dimensional contribution that genes have in determining complex phenotypes through a genetic architecture.
Recent scientific papers relevant to the field of Phenomics
As the genome era winds down, the field of phenomics is ramping up. Several recent scientific papers , and quotes from within, allude to the promise that the massive amount of human genome information has in store for us all.
The Scientific Challenge
Most study on the genetic basis for disease focuses on single-defect – single disease relationships. By their nature, such diseases are exceedingly rare in the population. For example, an allele of the “breast cancer gene” BRCA1, has received considerable press and funding over the past couple of years, yet accounts for less than 1% of all breast cancers world-wide. The evidence shows that most human diseases are not as simple to dissect as one-gene-one-disease.
Virtually every human trait or disease is the result of complex interactions between genetic factors and the environment. Interactions between and within genetic pathways radiate through an environmental lens to project unique images of individuality. They create biological effects whose magnitude cannot be predicted by having an understanding of the interacting components on their own. In other words, to understand how genetic information contributes to disease, it is necessary to recognize that the whole (the disease or phenotype) is often times greater than the sum of its parts (the genes). The study of human genetics therefore is gradually drifting from a study of simple genetic mutations or alleles, toward a study of genetic non-linearity, where gene-disease relationships are considered as a function of a complex three-dimensional “Genetic Architecture”. The term “Genetic Architecture” is intended to signify the full range of genetic and environmental factors that go into creating a phenotype.
From the U.S. Governments National Institute of Health (NIH) guide: Genetic Architecture of complex phenotypes: "(Complex) phenotypes may have relatively simple underlying genetics, but their transmission appears complex because of its context, including interactions with other loci and with the environment. Alternatively, complex phenotypes may have multiple genetic and environmental causes. Most chronic, common diseases are complex by this definition. Complex phenotypes may be continuous in distribution, like height or blood pressure, or they may be dichotomous, like affected and not affected. The complexity arises from the fact that many genetic and environmental factors may interact with each other in unpredictable ways, such that the association between the phenotype and any single factor taken by itself may be imperceptible. Nonlinear interactions, including epistatsis and genotype by environment interactions, mean that the expression of the phenotype may not accurately be predicted from knowledge of the individual effects of each of the component factors considered alone, no matter how well understood the separate components may be."
Technology limitations in the past have translated into a disproportionately weighted understanding of rare human disease with simple genetic causes. These problems have simply been more tractable to study; they require the construction of familial pedigrees and using them to create genetic maps through linkage analysis. More comprehensive approaches require the consideration of massive amounts of data, and until recently, the technology simply has not existed by which to do this. As a result, we currently know little about the genetic components of an alarming number of diseases and traits. Even the genetic pathways that determine simple eye color are largely unknown.
The solution
A more comprehensive approach is needed to understand the relationship between the human genome information that is now available and human disease. Our solution is to determine whether a gene or set of genes can be associated with a phenotype (i.e. a disease) using a systematic and comprehensive approach. We apply heuristic analysis to empirical data sets in order to construct complex multi-genic linkage disequilibrium (LD) maps. This requires an analysis of huge amounts of data from a population of unrelated but characteristically similar (i.e. afflicted) individuals. Until recently, the equipment and genetic data necessary for these types of studies has been unavailable. However, over the past few years, over 3 billion dollars of government money has been spent to produce the first ever map of the entire human genetic code (over 90% of this exists in the public domain). Further, several years of government and private research has recently produced machinery capable of cost-effective, high-throughput DNA polymorphism analysis (i.e. the application of mass spectrometry to SNP analysis). We intend to use our technology with these advancements to accomplish a high-throughput application of our approach and be one of the first companies in human history to practice human genetics on a truly comprehensive scale.
Personalized Medicine and Pharmacogenomics
Science
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Genes, and DNA
The complexities of human genetic variation
Heuristic analysis
Polymorphism, trait inheritance and individuality
Doctors and pharmacists have long known that individuals respond differently to the same drug. The reason for this is the underlying genetic variability between individuals. Pharmacogenomics is the study of drug interactivity against the backdrop of genetic variability and most properly involves a consideration of complex genetics (a good analogy to this system is the flux-balance model in E. Coli- Schilling et al.,1999). Whereas one person may effectively and safely metabolize a certain drug, another may metabolize the same drug into a dangerous toxin. By evaluating drug response against genotype, it will be possible to define genetic profiles which are compatible with certain treatment regimens and those which are not. In this way, a patient’s response to a drug can be accurately predicted before the drug is prescribed. The idea of using a patient’s genotype as a factor in deciding on treatment options is commonly referred to as Personalized Medicine. Though today’s drugs are approved and developed based on their performance in a large population of people, medicine of the future will be evaluated and prescribed as tailor made solutions for a particular patient’s needs.
Services
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DNAPrint Genomics performs three contract DNA services:
SNiPdocTM- high-throughput SNP profiling service.
DNAPrintTMSTaR - STR typing service.
SeaQuickTM - internet based DNA sequencing service.
SNiPdocTM
High-throughput SNP profiling-To help us with our bottom line, we provide contract SNP profiling services to the drug development community. We call this service our SNiPdocTM service, and it is targeted towards pharmaceutical companies. Many pharmaceutical companies are seeking to enter into the field of Pharmacogenomics. This new field of study could have a dramatic impact on overall health care costs in the future. Furthermore, by having access to pharmacogenomics data, pharmaceutical companies can focus their clinical trials on segments of the population that are genetically receptive to the treatment. Experimental drugs can be targeted to individuals of a particular genotype, and genetic variations shown to underlie a poor-response to a trial drug could be used as a basis for eliminating the non-responding segment of the trial population from the study. In this way, pharmaceutical companies can reduce drug trial failures and the costs associated with them. Contracting this work out to service providers is a viable option for many smaller pharmaceutical companies who do not have the volume of work necessary to justify the price of the equipment and expertise. At DNAPrint Genomics, we offer multiple patient – multiple SNP sampling matricies designed on a custom, semi-custom or predefined basis. We can use our proprietary PhenomixM databases of medically relevant SNPs (numbering in the thousands of SNPs at present), or design chips for your application de-novo. We will work with your scientists to develop the experiments from beginning to end, that suit your needs, and we can handle your project from blood/tissue or DNA starting points. Data handling will be customized for each client; data can be deposited in our secure SNP relational databases system offering you the option of accessing your data over the internet. Alternatively, we can burn and hand-delivered CDs to you. As we develop our data mining algorithms, you will have access to some of the most revolutionary SNP pattern finding tools available anywhere. Using smart PhenomixSM could help you identify overlapping sets of genotypes associated with various phenotypes and/or phenotypic responses, which you might otherwise miss if you conducted your studies on your own or through another less-specialized facility.
DNAPrintTMSTaR
STR typing - (so-called DNA testing) for the public and forensic community, including paternity and maternity testing. STR typing differs from SNP profiling in that it looks at only a few inter-genic regions of DNA. Therefore, it is useful only for individual identification and pedigree analysis, and tells nothing about an individuals phenotype. This kind of testing is commonly referred to as DNA testing and is the basis for forensic DNA science used by local and federal law enforcement. We use 7 or 13-locus tests to offer up to 1 in 2 billion resolution power. All tests are performed on PE Applied Biosystems 310 genetic analyzer using PE Profiler and Profiler Plus AMPlFSTRTM kits.
SeaQuickTM
DNA sequencing - There are an abundance of contract DNA sequencing services in operation today. Ours is unique because we offer the customer a seamless web-based interface for submitting, retrieving, manipulating and storing their data files. To date, no other service of this kind exists because it is difficult to design software that is compatible with the complicated DNA sequencing files (called a chromatogram - a series of colored peaks with the corresponding nucleotide sequence identity above each peak). We operate our service through a unique web-capable relational database management system (RDMS), which will be available by early April. Our system is used to collect sequencing requests from customers though a web-based interface, use the requests to build sample sheets for sequencing and organize chromatogram files by customer, project and library. The customer will use the system, through web-pages, to make their orders and retrieve their data from remote locations or their home laboratory. All chromatogram files are processed through the phred basecalling algorithm to give reads and quality values. The resulting reads are then compared to a set of vector sequences (UniVec from NCBI) and the E. coli genome. Customers can retrieve chromatogram files and sequences as quality trimmed, vector masked or unedited files. E. coli sequences can be excluded.
Advantages
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As one of the first practitioners in the new field of Phenomics, we hold distinct advantages.
Our advantages are:
We have developed and patented a proprietary biochemical reagent (TruSeqTM) for high-throughput genetic analysis using a DNA chip based or electrophoresis based platform technology.
We are forming strategic alliances with other genomics and pharmacogenomics companies, for access to raw materials and intellectual property, lowering our R and D basis.
We are assembling a proprietary collection of LIMS (FEMSTM) and heuristic software tools for a revolutionary data mining process specially suited for Phenomics applications.
We are compiling unique SNP databases for target phenotypes and diseases. Our proprietary data mining routines capitalize on the newness of high-throughput genotyping technology and the recent completion of the human genome project.
Technology
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For high-throughput SNP analysis, we use Genetic Bit Analysis (GBA). Using proprietary analytical and software tools with this equipment, we can produce the massive data quantity and quality necessary for comprehensive genetic analysis. We process genetic profiles in DNA chip based format, at a rate of 1-5 per second. We will analyze over 500,000 genotypes during the coming year.
For standard DNA testing we use PE Applied Biosystems Genetic Analyzer machines. This machine is a capillary electrophoresis machine which uses a robotic liquid handling system to process reactions with a minimal of user intervention.
We employ our innovative and proprietary products with both pieces of equipment.
Investor Relations
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The Market
The Opportunity
Recent Press Releases
Intellectual Property
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PhenomixTMSNiP databases
TruSeqTM
TruSpinTM
FEMS
Home DNA specimen Collection Kit
Careers
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We offer bright and motivated individuals an opportunity to work with a young and energetic company on a truly cutting-edge science for the betterment of mankind. It is commonly said that "Nothing worthwhile comes easy". This applies to nothing if it does not apply to what we do here. As innovators in the new field of Phenomics, we are blending genomic information with real biology and we solve problems as challenging as there are in the world of science today. We are a group of individuals with the courage to be innovative and the fortitude to accomplish our goals. We are all, every one of us, entrepreneurs. At DNAPrint Genomics, we are not content to simply pile data onto old and banal data sets - we strive to revolutionize science and develop ways of thinking and products few people even contemplate today. Being a young company, it is important to us to publish early and often. Unlike many companies who hold their cards close to their chest, we rely on peer-reviewed publications to validate our ideas and progress.
DNAPrint Genomics employees come from all over the country, span various academic and professional fields and share a certain core set of characteristics. More than seeking employees, we are seeking partners; in addition to offering excellent salary and benefit packages, we provide equity participation benefits unequaled in the industry. If you have the courage to strike out into the frontiers of science as a partner in a young start-up company, and find a position listed below that matches your skills, we would love to talk with you about joining us. Please send dated electronic or hard copy of your curriculum vitae or resume to:
DNAPrint Genomics
Human Resources
1748 Independence Blvd.
Suite D1
Sarasota, FL 34234
(941) 351-4543
hresources@dnaprint.com
We have openings in the following areas (updated 2/2000):
Software Engineering
Scientists
Information Technology Professionals
Population Geneticist/Biostatistician |
