Leaders in Pharmaceutical Business Intelligence (LPBI) Group

LIVE — Plenary Session 2015 BioIT, April 22, 2015, 8:00 – 10:00AM – Cambridge HealthTech Institute’s 14th Annual Meeting BioIT World – Conference & Expo ’15, April 21 – 23, 2015 @Seaport World Trade Center, Boston, MA

Dr. Aviva Lev-Ari will be in attendance on April 21, 22, 23

 

Leaders in Pharmaceutical Business Intelligence (LPBI) are Covering the Event in REALTIME using Social Media

http://pharmaceuticalintelligence.com

#biotech

#investment

@MassBio

@BostonBizJournl

@BioWorld

@BiotechNews

@bioitworld

April 22, 2015 * 8:00 – 9:45 am

8:00 Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:05 Plenary Session Introduction

Jason Stowe, CEO, Cycle Computing

LIVE – Introduction

Use computing to answer tough question – by building infrastructure – for acceleration of Science

@Novartis:

Cancer Drug Design: Scientists need 50,000 cores – not available in house

10,000 Servers — 40 years of computing in 3 conpounds deployed in 8 hours — Amazon web servers — For $4300 the data run and turned off. Scientists need 10 servers — workflow is critical — accelerate the access to computing WHEN IT IS NEEDED, scalable computing iterative process

720 hours of Computing = 720 analysis,computing analysis — iterative process

Computer burset = Data Workflow

Chris applies multidisciplinary research at Memorial Sloan Kettering

8:15 Precision Combination Therapy: Discover • Design • Deliver

Chris Sander, Computational and Systems Biology, Memorial Sloan Kettering Cancer Center

LIVE

Algorithms are tailored — application to Cancer if that will be solved — to eliminate lasions and to PREVENT BY STRENGTHENING THE HUMAN IMMUNE SYSTEM

Genetic alterations — upregulate protein kinase – relpse

Best success in Melanoma identification of the mutations treatment with protein kinese tumor become resistNT AS IT REAPPEARED

SYSTEM BIOLOGY – DRUG — RESISTENCE — DRUG — RESISTENCE

ONE TO ONE DRUG BLOCK THE EXIT BY COMBINATION COMPOUNDS,

USING STRUCTURAL BIOLOGY TO DESIGN DRUGS —

• what combination to use – Pretubation biology of cancer cellline
• clinical trial on groups of patients
• Deliver personal therapy based on patient data – Precision Medicine

1. Drug combinations network inference

perturb — measure — infer — predict

Pertubation Cell Biology: Not new – Response profile

– small Western Blots

– medium Chip Blots 50,000 data points

– large  – Reverse Phase Protein Arrays (RPPA)

• Perturb
• Measure
• infer

Data drives network inference: Protein profiling Protein response to cancer cell lines to drug pertubation

Network models – best optimized what?

10,000 numbers non-linear: Infer optimal network models from pertubation data – OPTIMAL FITTING LOW PENALTY FOR OVER FITTING

— solution space is huge

Statistical Physics – a Matrix of probability distributions

Aproximation – vs experimental data

BP – Belief Propagation —

Systematic pertubations of RAFi resistant melanoma  — probability distribution

Prediction from Pertubation — ONE drug

Phospho-protein and cell pphynotyoe

Inferred interaction model

two best combinations

BRAF V600E for Mel133

MEK – BRAF

BRD4

Predict combination: Synergy of inhibition of cMyc and MEK/REF Experimental Test:

Inhibition

DISCOVERY – DESIGN – DELIVERY — Apply pertubation to SYSTEM BIOLOGY

• Kidney Cancer
• Sarcome
• Melanoma
• Glioblastoma
• Prostate
• Pancreatic
• PLK1, STAT,

PLK1 Inhibitor – concentration of drug — a very small amount has impact BEFORE RESISTENCE IS DEVELOPED IN ONE YEAR  OF START OF TREATMENT

• Biological reality — transcripts – protein – phenotype
• Abstraction/Model — math representation
• Applications — Prediction Interpretation Connect —>>> Therapy

Phynotype and solution in softward for data analysis

The Cancer Genome Atlas – TCGA 2008 – 2015

Cancer Genomics – 20K tumor samples from 98 Cancer studies

Simplicity & Power

Oncogenic SIgnature Classes

Protein Mutation vs copy number genetic alterations

Patients Groups and Drugs

PORTAL for MDs – contain 21,000 Tumors — Open Source used by researchers : cBioPortal for Cancer Genomics for phynotypes as a guide based on susrvival data of alteration and aggregation in tumor samples

One patient — all nucleiotid at different type intervals

Evolution genotype to phynotype: from amino acid sequence to 3D Structure of protein

transmembrane proteind – crystalographers on structure

Genetics from Sequencing to Structural Biology: Development and evolutions

Fold proteins from seuences Protein complexes from sequences

With Debra Marks Lab – Harvard MS

EVfold.org

EVcomplex.org

9:00 Benjamin Franklin Award & Laureate Presentation

RECEPIENT: Owen White, Director of Bioinformatics, Institute for Genome Sciences, University of Maryland, Baltimore, School of Medicine

Laureate Presentation

Biological compounds from liver passed to the gut – metabolism is in more bacterial cells in the gut then in the human cells

WGS of 100 million reads – Sample from the gut

Healthy Human Microbiome: Biochemicala pahtways

Inside the body — different bacteria

Sampls: Nares, Oral Vegina,

NIH MICROBIOME PROJECT

TCGA vs SRA Microbiome Data bases vd Google’s Content

Data Uncertenty

• Origin, library prep, nucleic acid prep
• publication ?
• metadata matters
• SRA: is data from a Cancer Pt of a Health Pt.
• NCBI BioSample Database — Accessing data and sharing

Go to The ONION –

ICD-9 DIagnosis COde Reference CHart

STANDARD development for dta – diversity in Biomedical data

Semantic and conceptual agreement is key

Challanges:

• COmmunity Members
• Communication
• Collaborative
• DO COmmunity — DIsease Ontoloty
• ICD9 vs Mesh vs OMIM NCI, DSM-5
• Phenotypic Description – Melissa Haendel
• Genotype

Regularization

Meta dat — all dat except of sequencing data

Expression Studies

Gene Ontology – Michell Gwinn

Evidence Ontology – Mark at Univeristy of Maryland, BLAST evidence used in manual assertion: WHat was done based on experimentation vs curation

Publishers are now recognizing Phynotypes — attracts more eyeballs to the site

Microbiome — in the process of annotation

9:30 Best Practices Awards Program – Editor-in-chief BioIT World

• Clinical & Health IT WInner

GSK with Epidemico – Project CRAWL

• IT Infrastructure Winner

UC Santa Cruz

• Informatics

Biogen Idec – deCODE

• Research & Discovery Finalists

AstrzZeneca

Pfizer

The WINNER — UCB BioPharma with EPAM Systems

• Knowledge Management Finalists

WINNER: European Lead Factory COnsortia with BIOBIA – Science Cloud: A Scientific Informatics Systems

• Gadges

Michael J Fox Foundation

tranSMART open data repository for Parkinson’s Disease Research

• Editor’s Choice

NIH Undiagnosed Diseases Program with Appistry