The FDA has identified the development of new biomarkers as one of the key opportunities to increase efficiency, predictability, and productivity in drug development. I provide below a description of the presentation, discussion and workshop activity for the session on Biomarker Discovery & Applications in Drug Development which will take place on Thursday 19th October ’06 at the InnovationWell meeting at Bryn Mawr.
The session on the application of biomarkers in drug development will explore new advances and challenges in this area and will include a keynote from Keith Elliston, CEO (Genstruct), with Zentam Tsuchihashi (BMS) discussing Biomarker Roles in Tumor Immunotherapy, Darius Dziuda (CCSU) will cover the topic of Multivariate BioMarkers, Michael Jones (Novartis) will discuss Proteomics applications whereas Bernd Bonnekoh (Otto-von-Guericke University) and Ansgar J. Pommer (SkinSysTec) will provide perspectives for Multi Epitope Ligand Kartography (MELK) and skin disease applications. This latter work is being published in Nature Biotechnlogy and is featured on its mid-October cover.
Full abstracts are provided below.
Barry Hardy
(continued…)
Biomarker Discovery & Applications in Drug Development
http://innovationwell.net/COMTY_biomarkers/
InterAction Meeting Session, Bryn Mawr, Philadelphia, USA,
Thursday, 19 October 2006
chaired by Zentam Tsuchihashi (Bristol-MyersSquibb)
KEYNOTE: Harnessing the Power of Systems Biology – Delivering Mechanism-of-Action and Biomarkers in Drug Development
Keith Elliston, Genstruct
Dexter Pratt, Bill Ladd, Toby Segaran, Justin Sun, Charlie Lieu and Keith Elliston. Genstruct Inc. Cambridge, MA, 02140
Systems biology offers new conceptual and computational tools for integrative analyses of complex clinical data sets. These tools allow researchers to break through cognitive barriers caused by the magnitude of molecular profiling information, and help us systematically elucidate and represent new biological insights. Using a systems biology approach, we have developed an integrated technology platform and methodologies that enable the investigation and identification of disease mechanisms, compound efficacies and toxicities. Panomics analyses of biological responses over time are used to map the trajectory of activated molecular pathways, and computable models are created to define molecular mechanisms.
We will present the methods and technology used to model scientific knowledge, generate specific mechanistic hypotheses through automated reasoning, and build computable Causal System Models. These models define the mechanisms underlying diseases, compound efficacies and toxic effects, and provide a map of the biological system to enable the identification of candidate biomarkers. Biomarkers can then be evaluated for their performance in noninvasive monitoring of the progression of disease, the mechanism of compound efficacy as well as the onset and reversal of toxicity.
Many layers of biomarker roles in tumor immunotherapy
Zenta Tsuchihashi, Bristol-MyersSquibb
Based on the “Critical Path” document that appeared in 2004, FDA recently released two follow up documents, “Critical Path Opportunities List” and “Critical Path Opportunities Report”. In these documents, FDA identified the development of new biomarkers as one of the key opportunities to increase efficiency, predictability, and productivity in drug development. In parallel, there is a recognition on the industry side that the identification of novel biomarkers and the actual utilization of them needs to be a key ingredient of the drug development. I will discuss the key considerations in the study of clinical biomarkers especially for the development of anti-cancer immunotherapy. For the treatment to be effective, enough quantity of the drug has to be present at the site of the action for enough time (pharmacokinetics), and then that needs to generate a sufficient amount of action (pharmacodynamics). And the latter, the pharmacodynamic process itself consists of multiple steps. First, there is a binding of the drug to the target, followed by a stimulation of the immune system. This leads to an anti-tumor attack by the host immune system, then ultimately there should be a destruction of the tumor cells. Different biomarkers can potentially monitor each of these steps, and they give us a more precise picture of how the drug is acting, complementing the clinical observations. This additional information from biomarker analyses provides us a critical tool for the key decisions in the development of this drug. However, despite the technological advances especially in the genomics area that can now create a flood of biomarker candidates, developing and ‘qualifying’ these candidate markers to generate a utility is still not a straightforward process, and it requires a careful thinking and well-planned clinical studies.
Multivariate Biomarkers Discovery
Darius M. Dziuda, Central Connecticut State University
Life sciences are rapidly changing from disciplines that were dealing with relatively small data sets to research areas ‘bombarded’ with large and huge data sets. As a result of research sparked by the Human Genome Project, we have now growing library of organisms with already sequenced genome. Data sets generated by current microarray technologies consist of tens of thousands of gene expression variables. When protein chip technology matures, we may even see data sets with more than a million variables. Traditional “one-gene-at-a-time”, or univariate approach, which has dominated life sciences for a very long time, is no longer sufficient. Different approaches are necessary and multivariate analysis should become a standard one. There is nothing wrong with using the univariate analysis, but if the research stops there (and this, unfortunately, is still the case in many studies), the huge amount of generated data may be heavily underused, and potentially important biomedical knowledge contained therein not extracted.
Biomarker discovery means selection of an optimal subset of variables, which together – as a set – can significantly differentiate the phenotypic classes of interest. Due to large numbers of variables, p, exhaustive search that would guarantee finding the best subset cannot be implemented, as the order of the search space is O(2p). Generally, many problems related to feature selection have been shown to be NP-hard. Because of these difficulties, many studies reported in the literature pretty much neglect this step and apply more or less arbitrary selection of features used then to build classification models. Usual approach is to find an ordered list of features (using simple univariate methods like ANOVA) and then use some number of the features from the top of the list. Such a univariate approach not only neglects correlations between variables but also usually results in removing from consideration important discriminatory information.
The presentation will outline and discuss current issues in biomarker discovery, especially multivariate approach to identification of genomic, proteomic or metabolomic biomarkers for medical diagnosis, prognosis, individualized medicine, and drug discovery.
Keywords: Biomarkers, Multivariate Analysis, Data Mining, Bioinformatics, Genomics, Proteomics, Metabolomics, Differential Diagnosis, Drug Discovery, Individualized Medicine, Classification and Prediction Systems.
Application of Proteomics to Biomarker Discovery
Michael Jones, Novartis
The search for biomarkers has been intensified in recent years as the need for more accurate and less invasive methods for detecting disease progression, assessing drug efficacy and performing pharmacogenomic analysis has increased. In an attempt to discover surrogate molecular biomarkers in the background of complex disease states and population heterogeneity high throughput methods have been utilized. One popular high throughput biomarker discovery method is microarray analysis which requires obtaining patient tissue biopsies to extract the mRNA needed for profiling. Validation of discovered biomarkers is later done through more sensitive and quantitative methods in more easily obtained sources such as serum. Using tissue biopsies is problematic, since acquiring biopsies requires invasive techniques, and since the tissues may not be representative of the clinical method used for measuring molecular biomarkers. Biomarker discovery through proteomics has arisen as an alternative. Proteomics technologies have the potential to determine protein identity and quantity directly from body fluids. Potentially, with proteomics, the same tissue source could be used for biomarker discovery, validation and clinical use.
Several methods in proteomics have been developed for high throughput molecular biomarker discovery. We will discuss Mass Spectrometry (MS) related profiling technologies. Two commonly used techniques are the use of LC-MS/MS or LC-MS analysis of complex peptide mixtures. A third approach involves the direct measurement of complex mixture of undigested proteins. Each of these methods has advantages and deficiencies in the ability to produce quantitative profiles.
These methods will be assessed in terms of their advantages and disadvantages in the areas of quantitation, identification and sample preparation. We will finally discuss the technical hurdles that need to be overcome to make proteomic profiling competitive with microarray analysis for biomarker discovery.
Perspectives for Multi Epitope Ligand Kartography (MELK) for Detection of Diagnostic and Therapeutic Biomarkers in Skin diseases, Allergology and Beyond
Bernd Bonnekoh, Clinic for Dermatology, Otto-von-Guericke-University
Bernd Bonnekoh (1), Ansgar J. Pommer (2), Lars Philipsen (3), Raik Böckelmann (1), Harald Gollnick (1)
(1) Clinic for Dermatology, Otto-von-Guericke-University, (2) SkinSysTec GmbH, (3) MelTec GmbH & Co. KG, Magdeburg - Germany
We present a novel bioanalytical methodology called Multi Epitope Ligand Kartography (MELK) robot technology which basically represents an extension of multiplex immunophenotyping. The patented rationale of MELK consists in a repetitive three-step cycling process including 1) an initial incubation of a tissue section or cell preparation with a fluorophore-labeled tag (e.g. antibody), 2) a subsequent imaging of the fluorescence signal, and 3) a final soft bleaching. This process can be repeated up to at least 100 times with divergent tags. Resulting fluorescence images may be binarized with regard to internal and external positive and negative standards and overlaid by computational visualistic tools. This allows in an unprecedented manner to analyze the colocation of defined epitopes in microtopographic units defined by the pixel matrix of the CCD camera of the microscope. E.g. using a 20x objective magnification, such a microtopographic unit (i.e. a pixel) will correspond to a 450 nm2 area of the biologic specimen.
Given these basics of MELK robot technology, we have developed a special platform for analyzing in-situ-proteomics (i.e. toponomics) in skin tissue or blood specimens in the context of dermatological research. This was achieved by a close partnership as an university institution (Clinic for Dermatology, Otto-von-Guericke-University) and an industrial biotech company (SkinSysTec GmbH).
Until now we have initiated various projects aiming at the better understanding of the pathophysiology of common chronic, partly allergic skin diseases such as psoriasis and atopic dermatitis in order to find new treatment targets. A special aspect of our work is the creation of a new biological drug binding biochip assay which integrates a candidate biological drug after fluorophore-labeling into a MELK tag library for the purpose of a refined analysis of the drug´s binding sites. Another application field is diagnostics of skin cancer.
As a major future perspective our high-dimensional technology offers powerful additional options to conventional strategies of drug target identification and characterization.
WORKSHOP
Analyzing in-situ-proteomics by Multi Epitope Ligand Kartography (MELK) in skin research and beyond
Ansgar J. Pommer, SkinSysTec
Ansgar J. Pommer (1), Bernd Bonnekoh (2), Lars Philipsen (3), Raik Böckelmann (2), Harald Gollnick (2)
(1) SkinSysTec GmbH, (2) Clinic for Dermatology, Otto-von-Guericke-University, (3) MelTec GmbH & Co. KG, Magdeburg - Germany
We present our skin research-related platform of MELK robot technology. This break-through methodology allows to decipher the colocation of at least up to one hundred defined molecules (e.g. proteins) in subcellular spaces of biological specimens such as skin tissue sections or blood cell preparations. This opens new avenues for research and development in the fields of diagnostics, drug development and cosmetics.
MELK robot technology represents a highly advanced fluorescence microscopy. In principle it relies upon a sequel of i) incubation of a specimen with a fluorophore-labeled tag/antibody, ii) fluorescence imaging and iii) soft bleaching, allowing subsequent repeats of this cycling process. The point-precise overlay of the fluorescence images enables a mapping of the subcellular colocation of chosen molecular markers. Thus, a magnitude of molecular markers can be detected in a single specimen with a preserved histoarchitecture. This means a major advantage as compared to 1) conventional immunohistology (dealing rarely with more than 2 markers) or 2) cell- and tissue-disintegrating techniques alike conventional proteomics or array analyses.
Established applications of MELK robot technology are: a) the identification of pathophysiologic targets in inflammatory skin diseases, b) the monitoring of clinical treatments, c) the unprecedented in-situ-identification of rare cell types such as keratinocyte stem cells or d) the tracing of biological drugs (such candidates) for their tissue binding characteristics under the conditions of an ex vivo MELK biochip assay.
In front of this background the hardware and software components of our skin research platform of MELK robot technology and related service products will be presented. The workshop will be held in a questions & answers atmosphere and is addressing all interested representatives from research and industry in the fields of biotechnology, pharmaceutics, cosmetics and medicine.
InnovationWell Press Release (2 October 2006): http://www.prweb.com/releases/2006/10/prweb444155.htm
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Posted by: kadam | February 14, 2007 at 08:25 AM