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Tuesday, June 10

7:30 am - 6:00 pm Registration Open 

7:30 am Breakfast Workshop (Sponsorships Available) or Morning Coffee

8:15 Chairperson’s Remarks

8:20 The Myth and Reality in Drug Discovery and Development
Ting-Chao Chou, Ph.D., Director, Preclinical Pharmacology Core, Molecular Pharmacology & Chemistry Program, Memorial Sloan-Kettering Cancer Center
I have used a very different approach for my biomedical research and drug discovery by applying the median-effect equation of the mass-action law, which is based on and derived from the biophysical, biomedical, and mathematical. This approach integrated the information into a whole body of pharmacological dynamic systems. My experience tells me that the molecular biology and cell biology, which is based on systems biology has little to do with drug discovery. Those basic research are for “knowledge” which is very remote from actual practices. Drug discovery is practical mission-oriented, emphasizing the end-results. I can use my own stories as examples to prove my points for the efficient and effective way of drug discoveries.

8:50 Using a Systems Approach to Drug R&D
Ulrik Nielsen, Ph.D., Vice President, Research, Merrimack Pharmaceuticals
Computational biology is improving our understanding of complex biological systems. Using very large biological datasets of cell signaling, we have constructed detailed, mechanistic models. These may be used to predict network responses to targeted therapeutics such as monoclonal antibodies and small molecule inhibitors. Using the ErbB signaling network as an example, we will present how simulation proposed MM-121, a monoclonal anti-ErbB3 antibody, as a potentially superior approach for current therapies.

9:20 Human Metabolic Network – Reconstruction and Its Application for Drug R&D 
Stuart Moodie, Ph.D., Research Fellow, Computational Systems Biology Group, Informatics Life-Sciences Institute, University of Edinburgh
The presentation describes the process of systems kinetic modeling. The talk starts from the reconstruction of a high quality human metabolic network from the genome information, and highlights the existing problems in the reconstruction. The reconstructed metabolic networks provide a unified platform to integrate all the biological and medical information on genes, proteins, metabolites, disease, drugs, and drug targets for a system level study of the relationship of metabolism and disease. Furthermore, the complex network organization structure revealed by structural analysis requires us to develop a system-oriented drug design strategy. Applications of systems kinetic modeling approach are discussed, from the planning of wet lab experiments, drug research and development process to computational methods and software for systems biology.

9:50 Networking Coffee Break, Poster and Exhibit Viewing

10:45 Cancer Invasion and Metastasis: Collaborative Research Using Dynamic Signaling Pathway Models 
Fredric Gorin, Ph.D., Professor, Neurology & Neuroscience, University of California Davis

11:15 The Use of Cancer Vaccines in Combination Therapies 
James Hodge, Ph.D., Senior Scientist, Head, Recombinant Vaccine Group, Laboratory of Tumor Immunology and Biology, National Cancer Institute, NIH 
The aims of this talk are to discuss novel strategies for the use of vaccines in combination therapies and to understand the underlying mechanisms of these combinatorial therapies so that they may be translated to science-driven clinical trials. Specifically, topics covered will address the use of vaccines with (a) various modalities to direct radiation to the tumor site, (b) standard of care chemotherapeutic drugs, and (c) immune modulators such as monoclonals anti-CTLA-4 and anti-CD25, and cytokines that will either enhance dendritic cell migration/activity or enhance the activity of T cells and other effector cells.

11:45 Estimating Second Cancer Risks After Radiotherapy 
Rainer Sachs, Ph.D., Research Professor, Mathematics and Physics, University of California, Berkeley 
As patients are treated at younger ages with cancer radiotherapy and survival improves, second cancers caused by the radiation in the same or nearby organs are an increasing concern. Treatment protocols are changing and thus long latency periods prevent acquiring data on current protocols; consequently mathematical and computational models are needed to predict second cancer risks. Recent deterministic and stochastic IIP models consider cell initiation to a pre-malignant state, cell inactivation, and cell proliferation during an extended radiotherapy regimen. Some involve comparatively sophisticated quantitative methods. They can be validated by second cancer data from earlier protocols and used to estimate risks of current and prospective protocols.

12:15 Close of COLLABORATION—APPLYING SYSTEMS BIOLOGY Conference

12:30 Luncheon Technology Workshops
(Sponsorships Available) or Lunch on Your Own

Systems Biology Continued | Overview | Short Courses | Day 1 | Day 2 | Download Brochure