Rationale Design of new Drugs Using Azure

Subscribers:
344,000
Published on ● Video Link: https://www.youtube.com/watch?v=4XYlVCNPVqI



Duration: 47:45
135 views
0


Using computers instead of conventional wet chemical synthesis and biological assay of molecular drug candidate saves both time and money in the long (~10 years) and expensive (~$1 billion) process of new drug development. TeraDiscoveries leverages the power of Azure to develop and deploy scientific software for the analysis, modeling and simulation of quantitatively intense life sciences and drug discovery computing problems. The hallmark of TeraDiscoveries' drug discovery platform is the Inverse Design system, our successful research through Duke University in chemo-informatics. We have combined the best of breed algorithms that resulted from this research with Azure to provide a blazingly fast, highly accurate drug discovery platform. Beginning with the X-ray structure of a target, the Inverse Design platform can identify novel leads, peptides or biologics as a virtual screening step, and the first step in drug discovery after target validation. Further, Inverse design can optimize an existing lead to produce a better binding lead, or a proprietary new lead.




Other Videos By Microsoft Research


2016-07-28Approximating the Expansion Profile and Almost Optimal Local Graph Clustering
2016-07-28Stochastic Dual Coordinate Ascent and its Proximal Extension for Regularized Loss Minimization
2016-07-28A Practical Approach to Reduce the Power Consumption of LCD Displays
2016-07-28CryptDB: Processing Queries on an Encrypted Database
2016-07-28Performing Time, Space and Light
2016-07-28Probabilistic Methods for Efficient Search & Statistical Learning in Extremely HighDimensional Data
2016-07-28Quantum Computation for Quantum Chemistry: Status, Challenges, and Prospects - Session 4
2016-07-28Quantum Computation for Quantum Chemistry: Status, Challenges, and Prospects - Session 2
2016-07-28Quantum Computation for Quantum Chemistry: Status, Challenges, and Prospects - Session 1
2016-07-28Bug Finding Techniques for Programs with Infinitely Many States
2016-07-28Rationale Design of new Drugs Using Azure
2016-07-28Verifying the integrity of peripherals' firmware
2016-07-28Privacy, Audit and Accountability
2016-07-28One Mouse per Child
2016-07-28The Benefits Of Being Out Of Focus: Making the Most of Lens PSF
2016-07-28Algorithms for bipartite matching problems with connections to sparsification and streaming
2016-07-28MIMD on GPU
2016-07-28The Case for Continuous Time
2016-07-28Starfish: A MADDER and Self-tuning System for Big Data Analytics
2016-07-28Spatial Coding for Large-scale Partial-duplicate Image Search
2016-07-28Testing Atomicity of Composed Concurrent Operations & Automatic Fine-Grain Locking



Tags:
microsoft research