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1:45PM 11/12/2014 – Panel Discussion – Oncology @10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Posted in Academic Publishing, Conference Coverage with Social Media, Personalized and Precision Medicine & Genomic Research, Scientific & Biotech Conferences: Press Coverage, tagged #endcancer, #meded, anti-cancer therapy, Big data, biochemotherapy, Bioinformatics, Chemogenomics, genomic drug development, genomics, health outcomes research, Huntsman Intermountain, MD Anderson Cancer center, medical education, Medical Ethics, oncology, Personalized medicine, Targeted therapy on November 12, 2014| Leave a Comment »

1:45PM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

1:45 p.m. Panel Discussion – Oncology

Oncology

There has been a remarkable transformation in our understanding of the molecular genetic basis of cancer and its treatment during the past decade or so. In depth genetic and genomic analysis of cancers has revealed that each cancer type can be sub-classified into many groups based on the genetic profiles and this information can be used to develop new targeted therapies and treatment options for cancer patients. This panel will explore the technologies that are facilitating our understanding of cancer, and how this information is being used in novel approaches for clinical development and treatment.

Oncology

Opening Speaker & Moderator:

Lynda Chin, M.D.
Department Chair, Department of Genomic Medicine
MD Anderson Cancer Center @MDAnderson #endcancer

Who pays for personalized medicine?
potential of Big data, analytics, Expert systems, so not each MD needs to see all cases, Profile disease to get same treatment
business model: IP, Discovery, sharing, ownership — yet accelerate therapy
security of healthcare data
segmentation of patient population
management of data and tracking innovations
platforms to be shared for innovations
study to be longitudinal,
How do we reconcile course of disease with personalized therapy
phenotyping the disease vs a Patient in wait for cure/treatment

Panelists:

Roy Herbst, M.D., Ph.D. @DrRoyHerbstYale

Ensign Professor of Medicine and Professor of Pharmacology;
Chief of Medical Oncology, Yale Cancer Center and Smilow Cancer Hospital @YaleCancer

Development new drugs to match patient, disease and drug – finding the right patient for the right Clinical Trial

match patient to drugs
partnerships: out of 100 screened patients, 10 had the gene, 5 were able to attend the trial — without the biomarker — all 100 patients would participate for the WRONG drug for them (except the 5)
patients wants to participate in trials next to home NOT to have to travel — now it is in the protocol
Annotated Databases – clinical Trial informed consent – adaptive design of Clinical Trial vs protocol
even Academic MD can’t read the reports on Genomics
patients are treated in the community — more training to MDs
Five companies collaborating – comparison of 6 drugs in the same class
if drug exist and you have the patient — you must apply personalized therapy

Lincoln Nadauld, M.D., Ph.D.
Director, Cancer Genomics, Huntsman Intermountain Cancer Clinic @lnadauld @intermountain

@Stanford, all patients get Tumor profiles Genomic results, interpretation – deliver personalized therapy
Outcomes from Genomics based therapies
Is survival superior
Targeted treatment – Health economic impact is cost lower or not for same outcome???
genomic profiling of tumors: Genomic information changes outcome – adverse events lower
Path ways and personalized medicine based on Genomics — integration not yet been worked out

Question by Moderator: Data Management

Platform development, clinical knowledge system,
build consortium of institutions to share big data – identify all patients with same profile

See more at http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

Functional Genomics Screening Strategies: Where and How to Apply siRNA and shRNA Screens

Posted in Chemical Genetics, tagged Chemogenomics, Long non-coding RNA, RNA, RNA interference, Small interfering RNA, small molecule on June 11, 2013| Leave a Comment »

Reporter: Aviva Lev-Ari, PhD, RN

September 24 – 26, 2013

Westin Boston Waterfront

Boston, MA

About the Functional Genomics Screening Event:

In the screening world there is definitely no one-size fits- all and no dearth of options to choose from in terms of assay platforms, protocols, cells or reagents. So how do you decide which screening strategy will work best for you? Can different screening techniques be utilized in tandem or be staggered to better validate results and overcome inherent shortcomings? Which type of screen will provide information that is most accurate and physiologically relevant to your biological query? Cambridge Healthtech Institute’s tenth annual conference on Functional Genomics Screening Strategies will cover the latest in the use of RNA interference (RNAi) screens, combination (RNAi and small molecule) screens, chemical genomics and phenotypic screens, for identifying and validating new drug targets and exploring unknown cellular pathways. The first half of the conference will focus on the design and use of RNAi screens, while the second half will explore the use of chemical genomics and long non-coding RNA (LncRNA) screens and the transition into advanced cellular models such as, 3D cell cultures and stem cells that will launch the next-generation of functional screens. Screening experts from pharma/biotech as well as from academic and government labs will share their experiences leveraging the utility of such diverse screening platforms and models for a wide range of applications

http://www.discoveryontarget.com/uploadedFiles/Discovery_On_Target/13/2013-Discovery-on-Target-Functional-Genomics-Screening-Strategies-Brochure.pdf