Leaders in Pharmaceutical Business Intelligence (LPBI) Group

LIVE  April 22, 10:50AM – GENOMICS: CLINICAL CHALLENGES AND MEDICAL OPPORTUNITIES @ Cambridge HealthTech Institute’s 14th Annual Meeting BioIT World – Conference & Expo ’15, April 21 – 23, 2015 @Seaport World Trade Center, Boston, MA

Reporter: Aviva Lev-Ari, PhD, RN

 

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

 

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GENOMICS: CLINICAL CHALLENGES AND MEDICAL OPPORTUNITIES  

April 22, 10:50 Chairperson’s Opening Remarks
Scott Kahn, Ph.D., Vice President, Commercial Enterprise Informatics, Illumina, Inc.

LIVE from Illumina Point of View – Sequencing Activity – GLOBAL

Genomics and MEDICINE – Validation – NGS rapidly to the Clivic penetration: – WHat do we do with the data

Health WOrkFLow and Challenges

• equip MDs with tools
• Translational Research and 13 Cancer Center in Holland — Biomarker discovery
• Rate of illumina growth 450,000 genomes are sequenced per year

Healthcare IT – delivering data into HIT

Rules generated Outside of Clinical Flow

Engine Checks Transactions but not

ALTERNATIVE APPROACH

CONTINUOUS LEARNING IN HEALTHCARE — CONTINUOUS LEARNING ARCHITECTURE – Knowledge base

• data association in the knowledgebase
• mailine transaction processing

Clinical Genomics

Variant found – Discovery of the gene – lab pick up the test – CONTINUOUS LEARNING Process need to be enabled

Genesight Report Drafting ENgine

GenInsight Infrastructure:

Identified Variants, order information,auth-drafted Reports for Geneti ist Pathologist Knowledge base has information on genes and on variance.

• rule — all reports must update the knowledge base

GeneInsight Clinic – Surfacing Alerts

Diagnostic process – genetic Report

• Introduction of the infrastructure – TIME SAVED and improve quality
• Time spent to update knowledgebase autodrFTING REPORT – TIVE SAVED IN ASSESSING VARIANCE
• NETWORKS CAN HELP – linking Labs and CLinicls and Labs to one another

• ClinVar – sharing data on Gene Variants

Improvement worth the investment

12:00 pm Census of the Apoptosis Pathway

Philip L. Lorenzi, Ph.D., Department of Bioinformatics and Computational Biology & the Proteomics and Metabolomics Core Facility, MD Anderson Cancer Center

We recently compared several different “omic” approaches to constructing the autophagy pathway de novo, including siRNA screening, mass spectrometry-based proteomics, and three different pathway analysis software packages. Unexpectedly, although merging all of the validated data sets yielded 739 autophagy-modulating genes, each individual approach alone yielded sparse coverage of the autophagy pathway. The best individual siRNA screen, for example, yielded only 169 of the 739 (23%) genes. Nevertheless, text mining-based pathway analysis with Pathway Studio in conjunction with manual curation provided the most comprehensive coverage, yielding 417 targets (56% of the pathway). Here, we explored the generalizability of those findings by examining a more well-characterized pathway—apoptosis. We compiled apoptosis-modulating genes from 12 published siRNA screens and two pathway analysis software packages—Ingenuity Pathway Analysis (IPA) and Pathway Studio. The resulting inventory of 6,882 proteins consisted of 215 targets identified by siRNA screening, 3,378 targets by IPA, and 6,381 targets by Pathway Studio. The extensive coverage (93%) of the apoptosis pathway provided by text mining with Pathway Studio can likely be attributed to recent upgrades in the software, including an expanded database and collection of full-text articles. Together with our previous autophagy pathway analysis, the new apoptosis results support the generalizable conclusions that: 1) siRNA screening has a large false negative rate (i.e., fails to identify many true “hits”), and 2) text mining-based pathway analysis using Pathway Studio provides the most comprehensive pathway coverage.

LIVE

Drug discovery & Development Process – Pathway Analysis – Drive drug discovery

• Part One – Pathway Analysis Strategies: Autophagy and Optosis

1. Ingenuity PathAnalysis
2. MetaCore – Thomsom
3. GeneSpring
4. David
5. Pathway Studio Elsevier – MedScan – Text analysis and mining

AUTOPHAGY

Cargo needed to be discharged

Proteome

UNION of multiple technologies

Pathway Studio: False positive rates  19% reduced by curation – change direction

False negatives

ATF4 assign unknown

BEST APPROACH: Pathway Studio with manual Curation

Apply Pathways to Clinical Use in Drug Discovery

• mTOR/autophagy stimulator – Combined mTOR and autophagy Inhibition
• mitophagy

• Part Two – validate on big data

AKT – Pathwat Studio

EDFR – no serious concern

MEK Inhibitor – No serious concern

PARP1 Inhibitor – concerns

TEXT MINING to be used in drug discovery – VERY important

GLS Inhibitors

12:30 Session Break

12:40 Luncheon Presentation I: Computational Enablement of the Hippocratic Oath in a Clinical Oncology Setting

David B. Jackson, Ph.D., Chief Innovation Officer, Molecular Health, Gmbh

The clinical response of cancer patients to oncolytic agents is influenced by three major classes of molecular determinant; tumor intrinsic factors (e.g. tumor biomarkers); patient intrinsic factors (e.g. polymorphisms) and patient extrinsic factors (e.g. co-medications). In my talk, I will present a novel computational technology and associated treatment decision support process that was designed to provide this knowledge-driven approach to clinical care in oncology.

1:10 Luncheon Presentation II: A High Performance Application Development Platform for Collaborative Genomics Research

Paul Flook, Ph.D., Senior Director, Enterprise Informatics, Illumina Inc.

Collaborative research among groups working with genomic data presents major logistical challenges. Transferring huge volumes of data can be prohibitively expensive for projects utilizing WGS data sets. Illumina has addressed this challenge by building a platform that enables collaborators to not only share data in a secure multitenant environment, but to develop and deploy their own applications close to the data.

1:40 Session Break