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TECHNOLOGY PLATFORM
Millennium has developed what we believe to be the industry's leading set of integrated capabilities for genomics-driven drug discovery and development. This claim is supported by the list of major companies that have been willing to pay for access to our capabilities, either indirectly through major R&D alliances, or directly through technology transfer alliances.
Our goal for our technology platform has always been very clear: it must maximize our ability to develop breakthrough treatments based on a sophisticated understanding of the underlying mechanisms of disease. More specifically, it must enable us to:
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Perform cutting-edge research into the molecular pathways that lead to disease;
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Identify the best targets in these pathways to intervene for therapeutic benefit;
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Develop the right drugs that have an appropriate effect on these targets; and
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Identify the patients most likely to be able to respond to these drugs.
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All of the above must be done in a highly productive manner to reduce the time and the enormous cost typically associated with the development of new drugs.
To achieve all of this, we have integrated a diverse array of advanced technologies and capabilities into a series of coherent processes for drug discovery and development. Because many of these are automated, high-throughput processes generating large amounts of complex information, we have also developed sophisticated capabilities in information technology and knowledge management. By helping us to make timely decisions based on highly relevant information, these capabilities contribute significantly to our drive for high productivity.
Representative technologies in the platform include:
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Imaging: Anatomical and molecular imaging technologies, such as MRI, PET, and CT, designed for preclinical discovery research to advance disease modeling and drug efficacy testing as well as provide a bridge to clinical development.
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Transcriptional profiling: Microarray-based procedures for determining and comparing the expression levels of tens, hundreds or even thousands of genes in parallel, which can be applied, for example, when looking for small differences between normal and diseased tissues, or between patients who respond to a drug and others who do not.
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SNP detection: Cost-effective methods for detecting SNPs (single nucleotide polymorphisms), which are small genetic differences between people that can serve as markers for the inheritance of genes associated with a disease, or with degree of responsiveness to a drug.
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Proteomics: A range of technologies to identify and characterize the proteins present in particular cells or tissues, using technologies such as LC/MS (liquid chromatography linked to high-powered mass spectrometry) and biosensors.
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Bioinformatics: Computer programs that process large amounts of data and enable important inferences to be made, such as the likely functions of novel proteins, or the existence of gene expression patterns that correlate with disease states.
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High-throughput screening: Highly automated procedures for testing large numbers of compounds or antibodies for their ability to interact with a potential drug target.
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Synthetic chemistry: Procedures for making large libraries of compounds with drug-like properties for testing against drug targets, and for iterative synthesis (repeated tests and variations) of improved versions of compounds that show promise as drugs.
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Chemi-informatics: Computer programs that pull together large amounts of information relating to chemical structures and their biological activities in a way that facilitates the design and synthesis of improved compounds for testing.
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Predictive ADMET: Techniques that apply specialized computational analyses to data generated in biological testing systems in order to predict crucially important properties of drug candidates, namely, their Absorption, Distribution, Metabolism, Excretion and Toxicity.
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Clinical trial simulation: Computational methods for optimizing the design of clinical trials, using data collected from previous testing of the candidate drug to simulate the likely outcomes with different clinical trial designs.
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