Leaders in Pharmaceutical Business Intelligence (LPBI) Group

LIVE — Plenary Session 2015 BioIT, April 23, 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

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April 23, 2015 * 8:00 – 10:00 am

8:00 Chairperson’s Opening Remarks

Allison Byrum Profitt, Editorial Director, Bio-IT World & Clinical Informatics News

8:05 Rubik’s Cube Challenge

Play the Rubik’s Cube Challenge! Get your Rubik’s Cube from Intel at the Plenary Session. After the Plenary session, go to the Rubik’s Cube Challenge in the Exhibit Hall, try to solve it, and enter to win great prizes! See an Intel representative during the Plenary Session for complete rules.

8:15 Plenary Session Introduction – Precision Medicine

Ketan Paranjape, General Manager Life Sciences, Intel Corp.

Multiple sources of Data: Medical and Technical

• Patients – Safety — > Precision in one day, genome sequence , visit MD in 24 hours
• Labs
• Genomics
• Clinical Trials
• claims & tranactions
• Payer
• Provider – order Genetic Seq, analyze results, share pros and cons
• IT – deploy scalable drive cost and ownership, data sharing, security and control of local data

Biopsy -> sequencing  -> Analysis -> Diagnosis ->Treatment -> Clinical Trial [Yes or No]

In a Hospital – AIOD:

AM:Imaging, genomics workflow

PM: Variants/Mutations – NOT only at Broad Institute, many other center have it

genomic workflow

optimized hardware clusters

Ecosystem to support OIOD:

– Education: MDs and Patient

_ Investment

– Policy

– Reimbursement

INTEL’S RESPONSE; TGen RNA-Seq Pipeline – from 7 days to 4 hours

• Challenge
• Solutions

http://www.intel.com/healthcare/optimizecodee

“All-in-one-day?” (AIOD)

• Challenge for Charity
• Solve the Cube

WHO is up for AIOD Challenge ????????

LIVE 8:25 Data Custodians, Patient Advocates

One of the greatest challenges for every branch of medical science is rounding up patients for studies, trials, and endless measurements. What if patients could offer up their own data for research that interests and engages them? These panelists are working where big data science meets patient empowerment, finding ways that modern health records, patient portals, new data sources like next gen sequencing and activity trackers, and other technology innovations can give everyone a stake in how data are used. They will discuss how they keep patients in the research loop, and how non-professionals can be a driving force behind the medical breakthroughs of the future — in sickness and in health.

Benjamin Heywood, Co-Founder and President, PatientsLikeMe, Inc.

• ALS Therapy Development Institute
• patientslikeme

Undertanding phynotypes

1. Learn from others
2. Connect e=with people
3. track your health
4. PATIENTS 320,000, 2300 DISEASES
5. DATA – CODED TO ICD, SNOMED,

CLINICAL DEVELOMENT LEALERD SAY THEY DO

• 76% Patients worry of sharing data
• 94% are willing to share

SYSTEM MEASUREMENT with collaboration of other entities

• The search for a Better Definition of Pain – Patients actively defined a Pain Scale
• Item-level feedback user interface
• Survey-level feedback user interfaces
• Interest in clinical Trials
• FDA PFDD – engage Patients: Fibromyalgia
• MS Condition Severity vs Patient Attitude & Concern
• LUPUS – Living with SLE: Severe Symptomology: PAIN, Fatigue, Flare, Rash
• Toterability of Drugs: Methotrexate Side effects
• Time on Prednisone and side effects
• PatienLiikeMe – PLM: DID SYmptoms get better?
• Sensors-based Research  – Wearable devices changes landscape of DIAGNOSTICS

Andreas Kogelnik, M.D., Ph.D., Founder, Open Medicine Institute

Omics in the Era od Patient-driven data Collection

Challenge: Patient & Clinical Data + Lab/-omic Data = Optimized Research & Care

MDs are overhelmed  – >> for Patients and the Crowd — DATA IS POWER

Genomics Capacity is outstripping our capacity to store it: gel-based systems, capillary seq, massively parallel seq

Omics Data and Wearables

1. Walking in SIlicon Valley  – 40 paparements are monitored across Runners – BP – Gene by Gene Impact of walking
2. Google MashUp: better integration of data and ways to share are clear needs
3. Open Med Net: Research — Clinical – Imaging – Pharmacy – Device – Insurane – ANALYTICS OF HEALTH AT THE PATIENT LEVEL – Speech recognition pattern — in Parkinsons and Omics data of the Patient

Genomics of Young Lung Study – FOundation Medicine – Lung Cancer

Pre-study- -> Pre screening –> Remote sites -Social Media — >Local Sites US,UK [remote consent protocol REMOTE registration] –> Epidemiology –> Science

Collaborative Community Approach to Chronic Fatigue, Lyme & Autism – Poorly understood Conditions

Longitudinal Genomic SUrveying: Data Collection of Patient generated data combined with molecular evaluation

300,000 protein data points od one patient, comapy in Sandiego

Large scale Screening: data-driven Pregnancy & Rare Diseases

• 1/2 have a chronic disease – most medication are not for pregnent women

Quality of Data — >> Better action

Data-Driven Patient Testing and Care – Apply Omics DIgital Population health + genomics

Katherine Wendelsdorf, Ph.D., Field Application Scientist – Ingenuity Systems, QIAGEN Bioinformatics; Spokesperson, Empowered Genome Community

Create Tools for big biological data sets and tools

• genetic variation data analysis Omics to drive the translation
• Personalize Medicine: Samples from Patients with and without the disease
• Which of all variences

Ingenuity Variant Analysis – Tool to Filter Variants

1. likely cause of disease
2. identify pathways
3. contentt from variety tools of Variant  – Sequence banks
4. literature – knowledge base – overcome data complexity
5. Association with case group with a disease
6. all patients with mutation x
7. none of the healthy control have the mutation x

Genomic Community

1. share with all researcher 23andMe data for free — for research purposes
2. users submit Exon, Variant,
3. Sequencees – share Genetic data Broadly or Privately – subset with a specific researcher
4. Researchers: benefit by definition of Phynotypes: Genomics of women under 40 with gene BRCA 53???
5. Filter varients against AFC frequencies
6. get in contact with individuals who have a specific variant/varient set of interest
7. Patient —>> Scientists — give Patients discoveries & treatment go back to the Patient

PANEL DISCUSSION

Value creation for Patients:

• Results, give patients a window to the research process
• Actionable, cultural differences, Patients want to have data but do not want to know if no therapy is available
• Privacy is a Risk factor – hiding Medical Information Privacy vs Sharing
• EMR – Interfaces efforts helps, data does not fit Interoperability issues within the Clinics
• Claims data vs EMR
• Gemone Data — who own the analysis?? vs owner owns the genome data
• Exporting Pt Variant Data Sample — Pt control, Pt must agree for sharing, Uploading Variant Data is blind, remaind blind UNLESS THE PT.SIGNS UP TO SHARE THE DATA
• Sharing DIscoveries, inside the DB Pt need to give permission to look at the data
• Participatory Studies
• Environmental Dat Dental data Medical Devicecs data
• Proteomics, clinical data — PatientLikeMe
• Blood drawn in the Home of the Patient
• CBC in EMR – no analysis of CBC
• Reimbursement of Order Sequencing – Insurance contracts are foe years coming for renewal – no interest in Long Term (LT) Wellness of Patients, Employees are interested in LT