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Archive for the ‘REAL TIME Conference Coverage Twitter’s Hashtags and Handles per Presentation/session’ Category


37th Annual J.P. Morgan HEALTHCARE CONFERENCE: News at #JPM2019 for Jan. 10, 2019: Deals and Announcements

Reporter: Stephen J. Williams, Ph.D.

From Biospace.com

 

JP Morgan Healthcare Conference Update: Sage, Mersana, Shutdown Woes and Babies

Speaker presenting to audience at a conference

With the J.P. Morgan Healthcare Conference winding down, companies remain busy striking deals and informing investors about pipeline advances. BioSpace snagged some of the interesting news bits to come out of the conference from Wednesday.

SAGE Therapeutics – Following a positive Phase III report that its postpartum depression treatment candidate SAGE-217 hit the mark in its late-stage clinical trial, Sage Therapeutics is eying the potential to have multiple treatment options available for patients. At the start of J.P. Morgan, Sage said that patients treated with SAGE-217 had a statistically significant improvement of 17.8 points in the Hamilton Rating Scale for Depression, compared to 13.6 for placebo. The company plans to seek approval for SAGE-2017, but before that, the FDA is expected to make a decision on Zulresso in March. Zulresso already passed muster from advisory committees in November, and if approved, would be the first drug specifically for postpartum depression. In an interview with the Business Journal, Chief Business Officer Mike Cloonan said the company believes there is room in the market for both medications, particularly since the medications address different patient populations.

 

Mersana Therapeutics – After a breakup with Takeda Pharmaceutical and the shelving of its lead product, Cambridge, Mass.-based Mersana is making a new path. Even though a partial clinical hold was lifted following the death of a patient the company opted to shelve development of XMT-1522. During a presentation at JPM, CEO Anna Protopapas noted that many other companies are developing therapies that target the HER2 protein, which led to the decision, according to the Boston Business Journal. Protopapas said the HER2 space is highly competitive and now the company will focus on its other asset, XMT-1536, an ADC targeting NaPi2b, an antigen highly expressed in the majority of non-squamous NSCLC and epithelial ovarian cancer. XMT-1536 is currently in Phase 1 clinical trials for NaPi2b-expressing cancers, including ovarian cancer, non-small cell lung cancer and other cancers. Data on XMT-1536 is expected in the first half of 2019.

Novavax – During a JPM presentation, Stan Erck, CEO of Novavax, pointed to the company’s RSV vaccine, which is in late-stage development. The vaccine is being developed for the mother, in order to protect an infant. The mother transfers the antibodies to the infant, which will provide the baby with protection from RSV in its first six months. Erck called the program historic. He said the Phase III program is in its fourth year and the company has vaccinated 4,636 women. He said they are tracking the women and the babies. Researchers call the mothers every week through the first six months of the baby’s life to acquire data. Erck said the company anticipates announcing trial data this quarter. If approved, Erck said the market for the vaccine could be a significant revenue driver.

“You have 3.9 million birth cohorts and we expect 80 percent to 90 percent of those mothers to be vaccinated as a pediatric vaccine and in the U.S. the market rate is somewhere between $750 million and a $1 billion and then double that for worldwide market. So it’s a large market and we will be first to market in this,” Erck said, according to a transcript of the presentation.

Denali Therapeutics – Denali forged a collaboration with Germany-based SIRION Biotech to develop gene therapies for central nervous disorders. The two companies plan to develop adeno-associated virus (AAV) vectors to enable therapeutics to cross the blood-brain barrier for clinical applications in neurodegenerative diseases including Parkinson’s, Alzheimer’s disease, ALS and certain other diseases of the CNS.

AstraZeneca – Pharma giant AstraZeneca reported that in 2019 net prices on average across the portfolio will decrease versus 2018. With a backdrop of intense public and government scrutiny over pricing, Market Access head Rick Suarez said the company is increasing its pricing transparency. Additionally, he said the company is looking at new ways to price drugs, such as value-based reimbursement agreements with payers, Pink Sheet reported.

Amarin Corporation – As the company eyes a potential label expansion approval for its cardiovascular disease treatment Vascepa, Amarin Corporation has been proactively hiring hundreds of sales reps. In the fourth quarter, the company hired 265 new sales reps, giving the company a sales team of more than 400, CEO John Thero said. Thero noted that is a label expansion is granted by the FDA, “revenues will increase at least 50 percent over what we did in the prior year, which would give us revenues of approximate $350 million in 2019.”

Government Woes – As the partial government shutdown in the United States continues into its third week, biotech leaders at JPM raised concern as the FDA’s carryover funds are dwindling. With no new funding coming in, reviews of New Drug Applications won’t be able to continue past February, Pink Sheet said. While reviews are currently ongoing, no New Drug Applications are being accepted by the FDA at this time. With the halt of NDA applications, that has also caused some companies to delay plans for an initial public offering. It’s hard to raise potential investor excitement without the regulatory support of a potential drug approval. During a panel discussion, Jonathan Leff, a partner at Deerfield Management, noted that the ongoing government shutdown is a reminder of how “overwhelmingly dependent the whole industry of biotech and drug development is on government,” Pink Sheet said.

Other posts on the JP Morgan 2019 Healthcare Conference on this Open Access Journal include:

#JPM19 Conference: Lilly Announces Agreement To Acquire Loxo Oncology

36th Annual J.P. Morgan HEALTHCARE CONFERENCE January 8 – 11, 2018

37th Annual J.P. Morgan HEALTHCARE CONFERENCE: #JPM2019 for Jan. 8, 2019; Opening Videos, Novartis expands Cell Therapies, January 7 – 10, 2019, Westin St. Francis Hotel | San Francisco, California

37th Annual J.P. Morgan HEALTHCARE CONFERENCE: News at #JPM2019 for Jan. 8, 2019: Deals and Announcements

 

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Live 12:00 – 1:00 P.M  Mediterranean Diet and Lifestyle: A Symposium on Diet and Human Health : October 19, 2018

Reporter: Stephen J. Williams, Ph.D.

12.00 The Italian Mediterranean Diet as a Model of Identity of a People with a Universal Good to Safeguard Health?

Prof. Antonino De Lorenzo, MD, PhD.

Director of the School of Specialization in Clinical Nutrition, University of Rome “Tor Vergata”

It is important to determine how our bodies interacts with the environment, such as absorption of nutrients.

Studies shown here show decrease in life expectancy of a high sugar diet, but the quality of the diet, not just the type of diet is important, especially the role of natural probiotics and phenolic compounds found in the Mediterranean diet.

The WHO report in 2005 discusses the unsustainability of nutrition deficiencies and suggest a proactive personalized and preventative/predictive approach of diet and health.

Most of the noncommunicable diseases like CV (46%) cancer 21% and 11% respiratory and 4% diabetes could be prevented and or cured with proper dietary approaches

Italy vs. the US diseases: in Italy most disease due to environmental contamination while US diet plays a major role

The issue we are facing in less than 10% of the Italian population (fruit, fibers, oils) are not getting the proper foods, diet and contributing to as we suggest 46% of the disease

The Food Paradox: 1.5 billion are obese; we notice we are eating less products of quality and most quality produce is going to waste;

  •  growing BMI and junk food: our studies are correlating the junk food (pre-prepared) and global BMI
  • modern diet and impact of human health (junk food high in additives, salt) has impact on microflora
  • Western Diet and Addiction: We show a link (using brain scans) showing correlation of junk food, sugar cravings, and other addictive behaviors by affecting the dopamine signaling in the substantia nigra
  • developed a junk food calculator and a Mediterranean diet calculator
  • the intersection of culture, food is embedded in the Mediterranean diet; this is supported by dietary studies of two distinct rural Italian populations (one of these in the US) show decrease in diet
  • Impact of diet: have model in Germany how this diet can increase health and life expectancy
  • from 1950 to present day 2.7 unit increase in the diet index can increase life expectancy by 26%
  • so there is an inverse relationship with our index and breast cancer

Environment and metal contamination and glyphosate: contribution to disease and impact of maintaining the healthy diet

  • huge problem with use of pesticides and increase in celiac disease

12:30 Environment and Health

Dr. Iris Maria Forte, PhD.

National Cancer Institute “Pascale” Foundation | IRCCS · Department of Research, Naples, Italy

Cancer as a disease of the environment.  Weinberg’s hallmarks of Cancer reveal how environment and epigenetics can impact any of these hallmarks.

Epigenetic effects

  • gene gatekeepers (Rb and P53)
  • DNA repair and damage stabilization

Heavy Metals and Dioxins:( alterations of the immune system as well as epigenetic regulations)

Asbestos and Mesothelioma:  they have demonstrated that p53 can be involved in development of mesothelioma as reactivating p53 may be a suitable strategy for therapy

Diet, Tomato and Cancer

  • looked at tomato extract on p53 function in gastric cancer: tomato extract had a growth reduction effect and altered cell cycle regulation and results in apoptosis
  • RBL2 levels are increased in extract amount dependent manner so data shows effect of certain tomato extracts of the southern italian tomato (     )

Antonio Giordano: we tested whole extracts of almost 30 different varieties of tomato.  The tomato variety  with highest activity was near Ravela however black tomatoes have shown high antitumor activity.  We have done a followup studies showing that these varieties, if grow elsewhere lose their antitumor activity after two or three generations of breeding, even though there genetics are similar.  We are also studying the effects of different styles of cooking of these tomatoes and if it reduces antitumor effect

please see post https://news.temple.edu/news/2017-08-28/muse-cancer-fighting-tomatoes-study-italian-food

 

To follow or Tweet on Twitter please use the following handles (@) and hashtags (#):

@ handles


@S_H_R_O 

@SbarroHealth

@Pharma_BI 

@ItalyinPhilly

@WHO_Europe

@nutritionorg

# hashtags


#healthydiet

#MediterraneanDiet

#health

#nutrition

Please see related articles on Live Coverage of Previous Meetings on this Open Access Journal

Real Time Conference Coverage for Scientific and Business Media: Unique Twitter Hashtags and Handles per Conference Presentation/Session

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT

Real Time Coverage and eProceedings of Presentations on 11/16 – 11/17, 2016, The 12th Annual Personalized Medicine Conference, HARVARD MEDICAL SCHOOL, Joseph B. Martin Conference Center, 77 Avenue Louis Pasteur, Boston

Tweets Impression Analytics, Re-Tweets, Tweets and Likes by @AVIVA1950 and @pharma_BI for 2018 BioIT, Boston, 5/15 – 5/17, 2018

BIO 2018! June 4-7, 2018 at Boston Convention & Exhibition Center

LIVE 2018 The 21st Gabay Award to LORENZ STUDER, Memorial Sloan Kettering Cancer Center, contributions in stem cell biology and patient-specific, cell-based therapy

HUBweek 2018, October 8-14, 2018, Greater Boston – “We The Future” – coming together, of breaking down barriers, of convening across disciplinary lines to shape our future

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Synopsis for AI & Machine Learning in Clinical Trials, APRIL 12, 2018 PFIZER INNOVATION RESEARCH LAB – CAMBRIDGE, MA

 

Recap Book

http://viewer.zmags.com/publication/9d58c338#/9d58c338/30

 

Aviva Lev-Ari, PhD, RN, Director and Founder of  LPBI Group

will attend and cover in Real Time the Conference 

@pharma_BI

@AVIVA1950

  • Tweets for AI and Machine Learning in Clinical Trials April 12th, 2018 hosted at Pfizer’s Innovation Research Lab in Cambridge, MA @AVIVA1950 @pharma_BI

https://pharmaceuticalintelligence.com/2018/04/12/tweets-for-ai-and-machine-learning-in-clinical-trials-april-12th-2018-hosted-at-pfizers-innovation-research-lab-in-cambridge-ma-aviva1950-pharma_bi/

About Aviva Lev-Ari, PhD, RN and LPBI Group

 

 

AI and Machine Learning in Clinical Trials

April 12th, 2018 hosted at Pfizer’s Innovation Research Lab in Cambridge, MA

1 Portland St, Cambridge, MA 02139

With case studies from Pfizer, Novartis, Merck, AstraZeneca, MIT, Takeda, Sanofi & more, you will not
want to miss the latest in leveraging AI and Machine Learning in Clinical Trials.

#Pfizer #Merck #Sanofi #AstraZeneca #Novartis #Takeda #BMS #Biogen #GSK #MIT #Medable #Saama #RapidMiner

100+ innovators, data scientists, informatics, senior clinical trials execs & tech experts will convene to
discuss advances in artificial intelligence, machine learning, & clinical study data analytics.

Faculty of Advisors and Speakers:

Dan Karlin, Head of Digital Medical, Informatics, Regulatory Strategy, Pfizer
Joseph Lehar, Exec. Dir, Computational Biology, Merck
David Tester, Head, Data Sciences & Engineering, Chief Data Office, Sanofi
Bhaskar Dutta, Principal Scientist, Advanced Analytics Center, AstraZeneca
Jonas Dorn, Project Manager, Digital Health, Novartis
Jyoti Shah, Assoc. Dir, Data Development, Merck
Raj Bandaru, Sr. Director, Data Sciences Strategy, Sanofi
Ronald Dorenbos, Assoc. Dir, Materials Innovation, Takeda
Zeshan Farooqui, Sr. Clinical Site Manager, BMS
Shwen Gwee, Head, Digital Strategy, Global Clinical Ops, Biogen
Munther Baara, Head, New Clinical Paradigm, Pfizer
Shyamal Patel, Sr. Manager, PfIRe Lab, Pfizer
Bill Tobia, Lead Clinical Research Instructor, GSK
Regina Barzilay, Delta Electronics Professor, MIT
Amir Lahav, Digital Innovation Lead, Pfizer
Michelle Longmire, CEO, Medable
Karim Damji, SVP Product and Marketing, Saama
Malai Sankarasubbu, VP, AI Innovation, Saama
Ingo Mierswa, Founder/President, RapidMiner

You can take a look at the latest agenda here: http://panagorapharma.com/ai/schedule/

You can register at the following link using the promo code BOSTONBIOTECH25 for 25% off
registrations: https://panagorapharma.com/ai/registration/

If you have any other questions, you can reach out to the organizer:

Doug Lavender
CoFounder
PanAgora Pharma
Doug@panagoraconferences.com
Phone: 203-253- 6401

 

CORE THEMES:

1. An Exploration of Machine Learning for Clinical Study Data
2. Natural Language Processing (NLP) for Patient Voice Analysis via Social Channels
3. Machine Learning and Artificial Intelligence for Recruitment
4. The Potential of Machine Learning and AI for Adverse Event Identification
5. Real-time Patient Data Analysis

AGENDA for Thursday, April 12th, 2018

8:00 – 9:00 am Conference Registration Open in Pfizer Lobby – 1 Portland Street, Cambridge, MA

9:00 – 9:10 am Opening Remarks from Conference Chairman

Robert “Joe” Mather, Executive Director, Head of Digital Collaborations, Pfizer

9:10 – 9:50 am KEYNOTE PANEL: AI & ML to Support Clinical Trials – Where do we begin?
The internet of things, mHealth, wearable and sensor-enabled devices present an
unprecedented opportunity for accelerated data collection. What does it mean for life
sciences – are we prepared to handle the influx of data, and create valuable visibility to
accelerate trials? Where should we start? What are the best current applications? How can
we leverage AI and Machine Learning for Adverse Event Identification?

David Tester, Head, Data Science & Engineering, Chief Data Office, Sanofi

  • Do exploratory AI & ML outside the context of Clinical Trials 1st

Joseph Lehar, Executive Director, Computational Biology, Merck

  • Oncology – images of response to treatment are complex, Pathology is assisted by AI
  • AI can assist in cell classification
  • Biggest opportunity of AI %& ML in Immunology, use non invasive medium even behavioral indicators
  • Informed Consent in Clinical Trials
  • Development of AI models to avoid bias
  • Monitoring the Trials identify signals

Bhaskar Dutta, Principal Scientist, Advanced Analytics Center, AstraZeneca

  • Structure exploration in first study, signals used in second study
  • Even in Informatics groups there can be and there is resistance to acceptance of AI and ML
  • 80%-90% clean the data holistic data view integration and Privacy
  • pooling data sets across companies for benefits of sampling: Parkinson Disease case
  • Patients Voice in a Biomarker study as partners vs Patients as Customers

Moderator: Robert “Joe” Mather, Exec. Dir, Head of Digital Collaborations, Pfizer

  • Data sharing across the organization
  • How the audience feel about sharing code not only data

 

9:50 – 10:20 am CASE STUDY: Making Sense of Sensor Data: A Case Study in Data Quality Evaluation

Bhaskar Dutta, Principal Scientist, Advanced Analytics Center, AstraZeneca

  • Making sense of sensor data – 40 clinical data scientists and expanding
  • Tactical impact, Strategic build, Horizon Scanning &evaluaiton capabilities, Quantitative Solutions
  • % of Healthcare spending of GDP: LOWER THE % BY DIGITAL TECHNOLOGIES
  • Improve adherence no need of new drugs
  • 70% of Patients are interested in Monitoring their Health digitally
  • wearable sensors – will increase the quality of monitoring
  • Burden of Chronic disease: i.e., Asthma (23Millions), Diabetes (29Million)
  • COst direct and Indirect
  • Patient Needs
  • Challenging in using digital solutions: Lack of integration,
  • Values: to Patients, to HCP, Pharma: Drug discovery, Drug Cost
  • Digital-solutions Lifecycle: Pharma perspective: Need characterization, device sensor characterization,
  • at AstraZeneca: Project – iPREDICT – individualize PREdiction of DIsease Control using digital sensor Technology
  • Device Brands and their Price to Consumer: ZephyrBioPatch, Garmin Vivosmart, MS Band 2, GoBe, HealthPatch MD, BodyGardian, BioPatch
  • Usability Survey: Ease of setting up, Ease of use, 1st impression, comfort, likely to recommend
  • Data capturing: Missing, quality of recording – data quality evaluation: signal to noise ratio
  • poor compliance
  • Data Privacy – GPS data is the most PRIVATE: de-identification of IDs, GPS can generate identifiable data
  • Integration with other data streams
  • Six different Groups: Patient cnetrality, Applications Usability,
  • They are hiring in the MD area

 

10:20 – 10:50 am Using AI and Machine Learning to Improve Clinical Trials

• Clinical trial dedicated mobile apps can improve patient experience in clinical trials and
increase data collection and yield,
• Advanced analytics on patient data
§ HIPAA compliance, data collection & analysis

Michelle Longmire, CEO, Medable

  • Enabling Direct personalized medicine
  • current process: 1-5 drugs >$2Bil, 12 years
  • Apply AI in a Case study on mild cognitive impairment:
  1. Recruitment,
  2. Trial (drug efficacy)
  3. Endpoint (crude assessment)
  • AI – From Engagement to Insight:
  1. Trial Process, – identify Patients in populations before onset of disease
  2. Discovery, – Adaptive Trials
  3. Transformation – Digitome, Digital Biomarkers
  • Input: Patient reported data – to measure daily progress
  • Probabilistic condition for algorithm development
  • Input: Smartphone sensors: 6-minute walk
  • Input: Contextual data – Location, air quality, weather, disease & crime
  • Input: VOICE: Google Home, Amazon Alexa, Apple: Siri
  • Input: Devices: fitbit, Tomtom, biovation – Swiss company – 6 paramenters per second: Cognition applications
  • Bayesian Nets: Conditional probabilities
  • Deep learning: Pathern in data : Problem/data
  • Partnering with other Medical Centers

MEDABLE INSIGHT: Signature of Digitome

  • AI platform
  • Choose form anumber of Neural Networks (NN) ‘pattern’ to allow
  • Train Multiple NN, Time series Data, Visualization: View Data
  • Cerebrum Demo: Correlate patterns

10:50 – 11:10 am NETWORKING COFFEE AND REFRESHMENT BREAK

11:10 – 11:40 am CASE STUDY: Machine Learning for Clinical Study Data

Shyamal Patel, Sr. Manager, PfIRe Lab, Pfizer

SEE Digital Biomarkers Journal

  • DIGITAL biomarkers: from algorithms to Endpoints
  • Algorithms (gait speed, HR)–>> Biomarkers (Change is stat is it change in Disease stage?)–>>> Endpoints (relevant for target)
  • Wearable devices are tight coupled on body for continuous monitoring
  • smartphone: Sensor
  • connect devices
  • iPhone – Sensor packed powerhouse: Movement, Location, Context, Emotion (Camera, microphone)
  • 70% of data is unstructured: Text, image, video  – SOURCE: IBM
  • Why use AI for building digital biomarkers: AI: Data _ Answers =Rules vs classic Programming: Data + rules = Answers
  • AI enables:
  1. Learn efficintly large data sets
  2. make updates when more data becomes available
  3. Deploy at scale across platforms

DEEP Learning: automated driving, Object recognition, robotics, speech recognition

Case Study 1: Implement Heuristic algorithms (published in literature) Evaluate Performance (agreement with clinical ratings under controlled conditions) Train Machine Learning Models (Annotation as ground truth) to AI models

  • detect hand tremor – Quantify Tremor

Outcomes: 

  1. achieve significant reduction in false positive rate
  2. strong agreement with ratings provided by trained clinical raters

Case Study 2: Mining the sound signal for biomarkers

Outcomes:

  1. 85% accuracy in hackaton

Evaluating AI driven Digital Biomarkers:

Accuracy – Problem: Over fitting

Speed

Explainability – How does the model works? – understand the trade offfs

Scalability – do not be a hammer looking for a nail

 

11:40 – 12:10 pm Accelerating Clinical Trials using Natural Language Understanding

Pharma has a big text problem. Lots of useful information buried in unstructured data
formats that is difficult to use. Natural Language Understanding will help to turn what was
once unusable data into meaningful insights that can be applied to the clinical trial
development continuum. NLU engines also open up the possibility for users to have a more
interactive relationship with their vast data stores using speech or chat messaging in a
conversational experience
Come and see how we are using Natural Language Understanding to solve problems:
• Adverse events in the real world and clinical trials
• Better matched patients for on-going clinical trials
• Hidden associations from interactions between physiology, therapies, and clinical
outcomes

Karim Damji, SVP Product, Saama
Malai Sankarasubbu, VP of AI Research, Saama

  • Too many variations
  • ADE – Adverse Drug Event extraction from Biomedical Text

Data Manager: Delivers Clinical Data Analytics as a Service using Saama platform 

Implementation of dashboard: Smart Assistant for Clinical Operations:

  • Initiate a conversation over multiple natural channels of engagement
  • Identify intent and entity Need for NLU engine !!!!!
  1. Intent extractor
  2. Entity Extractor
  3. Conversation Experience (CX): One question per one answer – not a good CX

Saama: ChatBot Voice interaction

  • Rank studies on Pancreatic Cancer in ClinicalTrials.gov by Inclusion vs Exclusion Criteria
  • Entity extraction and Patinet matching for EHR Data
  1. Protein
  2. Chemical compound
  3. Organism
  4. Environment
  5. Tissue
  6. Disease/phenotype
  7. Gene Ontology Term

12:10 – 12:40 pm CASE STUDY: Bringing Digital Health and Artificial Intelligence to Merck

Merck is building up digital health capabilities to increase patient engagement, improve trial
performance, and develop clearer disease phenotypes. I will describe some efforts across
the organization in this area & provide examples of smart trials / AI collaborations underway.

Joseph Lehar, Executive Director, Computational Biology, Merck

  • Digital health innovations at Merck
  1. quantitative phyenotypes – clearer disease signals
  2. trial performance – more effective and more efficient
  3. Patient outcomes – Better ones
  4. Data analytics & Infrastructure – enabling 1,2,3
  • Smart trials: pacient-centric studies
  • Pilot studies: Smart dosing, sampling and analytics
  • at home vs at clinic
  • smart pill packs daily blood spot for PK/DNA, e-Diary
  • less expensive sampling
  • Key findings: More trials should have smart monitoring
  • Future expansion: Better, more relevant, wider: Less invasive , Apply to active clinical trials , scale up to larger populations
  • Collaborate with big Technology companies on AI
  • Flexible, scientific partnerships
  • Projects with like success sooner
  • Projects underway or being actively planned
  • Value-based models on Trials outcomes
  • Cross functional collaborations: Organizations, Projects: i.e., Oncology, Objectives

 

12:40 – 1:00 pm SINEQUA PRESENTATION

Jeff Evernham, Sinequa

evernham@sinequa.com

  • Content of the data: Expand, Link, Enrich, Improve
  • Data set Index
  • Row IndexStructured and Unstructured (Textual)
  • DIscovery: Common variables across all data sets
  • Cognitive Analytics: SEARCH, NLP, Integrated ML
  • Single study –>> Multiple Studies –> numerical variables –>> Enriched categorical variables Unstructured data

1:00 – 1:50 pm EXECUTIVE NETWORKING LUNCHEON

1:50 – 2:15 pm CASE STUDY: We want to teach a machine to think like a physician, but how do we tell how

a physician thinks?
Inter- and intra-rater variability can severely impact the data quality of our clinical trials. If we
could teach machine learning algorithms to assess patients like experienced physicians, we
would have every patient assessed the exact same way across all the sites in a clinical trial.
As a bonus, we could make these medical assessments available in underserved areas of the
world. However, how can we train a machine learning algorithm on data annotated by
humans, if we know that those human annotations are unreliable? We will present a
framework, and the journey that led us to it, that allows combining the judgments of
multiple human raters into one consensus scale and thus provide high quality ground truth,
an aspect of machine learning that doesn’t always get the attention it deserves.

Jonas Dorn, Digital Solutions Director, Novartis

  • Rater consistency is limited given by n-Raters to K-Patients – Human consistency is limited: Disease severity score assigned
  • ML –>> Scores are generated
  • What is ground truth to be considered GOOD?
  • Comparative video rating
  • Converting ranking into scores, “true Score”
  • True score + uncertainty + rater consistency – compare realization – compare realization to threshold, comes with uncertainty
  • Combine all rating by all doctores = continuous consensus score (with uncertainties) vs Coarse ratings (raw/consensus)
  • Create consistent score through comparisons
  • Conclusion: Humans are bad at absolute ratings but good at comparison
  • Comparison-based enable virtual rating

2:15 – 2:45 pm PANEL DISCUSSION: Hearing the Voice of the Patient – How Ambient Listening Devices and Artificial Intelligence Can Improve the Clinical Trial Experience

The healthcare industry, and in particular, the clinical research sector, has recently focused
its attention on achieving “patient-centricity”. Driven by the desire to better engage clinical
trial volunteers, coupled by the need to demonstrate value-added medical products, this
has become much more than the latest buzz word. However, once the trial begins, the
patient oftentimes may feel isolated in the process – quite simply, they need to ask
questions and receive answers that they can understand. Is this an opportunity to effectively & efficiently use ambient listening devices?

How can we leverage AI and Machine Learning for the detection of adverse events, using NLP and other strategies for analysis?
Amir Lahav, Digital Innovation Lead, Rare Disease Research Unit, Pfizer

  • speech technology – voice activated mechanism
  • voice recording for Ataxia Patients – for interaction with Patients
  • Accustic pattern recognition analysis of Human voice detects Asthman or CVD in Patient : voice for detection of disease: Stroke Patient,

Zeshan Farooqui, Sr. Clinical Site Manager, Bristol-Myers Squibb

Malai Sankarasubbu, VP of AI Research, Saama

  • Multiple Indexes

Moderated by: Bill Tobia, Lead Clinical Research Instructor, GSK

Voice of patient on audio technology

2:45 – 3:15 pm CASE STUDY: Clinical Data Integration from Translational Modeling Using Machine

Learning

Raj Bandaru, Sr. Director, Sr. Director, Translational Informatics, Sanofi

  • Clinical Data Integration for Translational Modeling
  • Challenges of Data Discovery Integration of Clinical Data
  • Automated Data Cataloging
  • Data DIscovery – 80% effort
  • Crawler – Bayesian machine learning – >> data Catalog (Index) –>>  Meta Data (Information) –>>> Elastic Data– >> synonyms and hierarchhical search –>. Ontologies and Access Management
  • Probabilistic model –>> no need for complete ontologies
  • self learning, self maintaining, meta data management, Data on demand, LOW of no IT support, cost a fraction of dat integration projects
  • GOAL: develop a classifier that predicts data class and relevnce to the question being asked
  • Metadata driven Risk-based De-Identification Strategy: Internal Use, External Use
  • Data Analytics Ask a question using Amazon Alexa
  • Data science and knowledge management Team

2:50 – 3:10PM Moving beyond Actigraphy: Using AI to make sense of multi-parameter wearable sensor data

Chris Economos, VP of Business Development, PhysIQ – AI for Personalized Anomaly Detection

  • Contnuous Biosensor Data +Deep Learning to Potentially DIagnose Heart Hailure Likelihood of Heart FAilure derived from Activity Alone: Heart Failure vs Normal Vs Cancer Treatment vs COPD
  • Activity + HR: Heart Failure vs Normal Vs Cancer Treatment vs COPD
  • “baseline” vs “estimates”
  • the difference is “Residuals”
  • Actual, RR, HR, Higher than Expected: Deterioration vs Improvement
  • Chris Economos, VP of Business Development, PhysIQ Case Study: Phase 3 Cardiovascular Clinical Trial: 600 patients, 97 sites, 14 countries, 9 languages 2 CROs
  • All Causes Hospitalization vs Worsening HF Hospitalization
  • Application of AI to data detection of exacerbation

3:15 – 3:35 pm NETWORKING COFFEE AND REFRESHMENT BREAK

3:35 – 4:05 pm Learning Disease Progression and Patient Stratification Models from Images and Text

 

Regina Barzilay, Delta Electronics Professor, MIT EECS, MIT Koch Institute for
Integrative Cancer Research

  • Predict recurrences, sensitivity to Treatment, LCIS – Lobar Carcinoma In-Situ
  • Enabling New Science – NLP Atypia – 7000 cases
  • Reducing Over-treatment – 87% excision are of benign tissue
  • 31% cancers were visible a year prior to cancer
  • Interpretable Neural Models
  • Multi-Task Representation Learning: Small sample size: Task “N” Tumor Size change GOALS: Correlate similar tasks

 

4:05 – 4:25 pm How AI will transform Clinical Trials

Ronald Dorenbos, Associate Director, Materials & Innovation, Takeda

  • Patient’s Perspective: AI can help patients to get better faster, present the disease
  • Future of clinical Trials: Personalization, Patients becoming the point-of-care, Adherence, Healthier Life Style
  • patient acceptance and adoption of digital health and AI are growing
  • In Pharma: SImulation Modeling, Predicting reaction to therapies Virtual Clinical Trials

 

4:25 – 5:00 pm PANEL DISCUSSION: How to make all the Data Machine Learnable?

Raj Bandaru, Sr. Director, Data Sciences Strategy, Sanofi

  • advises to use models that will signal noise vs clean the data upfront with endless effort

Jonas Dorn, Digital Solutions Director, Novartis

  • Cleaning data MUST be done before modeling
  • At present AI will not change the WOrld as fast, future of AI will move slowly

Ingo Mierswa, Founder and President, RapidMiner

  • missing data is not an excuse, it worth a chance
  • Data Engineering and Data modeling is separate in hands of two groups, optimal modeling requires one group, cooperation and validation both groups need be involved along the entire cycle
  • Support the RIGHT to own the data

Jyoti Shah, Associate Director, Data Development, Merck

  • A lot of data and high quality of Data
  • Digital technology – data collected by machine becomes part of the process
  • Patients Centers will disctate the pace of AI adoption, they want to own data

Moderated by: Munther Baara, Head, New Clinical Paradigm, Pfizer

5:00 – 6:30 pm Networking Drinks Reception / END OF CONFERENCE

SOURCE

http://panagorapharma.com/ai/schedule/

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Mozilla Science Lab Promotes Data Reproduction Through Open Access: Report from 9/10/2015 Online Meeting

Reporter: Stephen J. Williams, Ph.D.

Mozilla Inc. is developing a platform for scientists to discuss the issues related to developing a framework to share scientific data as well as tackle the problems of scientific reproducibility in an Open Access manner. According to their blog

https://blog.mozilla.org/blog/2013/06/14/5992/

We’re excited to announce the launch of the Mozilla Science Lab, a new initiative that will help researchers around the world use the open web to shape science’s future.

Scientists created the web — but the open web still hasn’t transformed scientific practice to the same extent we’ve seen in other areas like media, education and business. For all of the incredible discoveries of the last century, science is still largely rooted in the “analog” age. Credit systems in science are still largely based around “papers,” for example, and as a result researchers are often discouraged from sharing, learning, reusing, and adopting the type of open and collaborative learning that the web makes possible.

The Science Lab will foster dialog between the open web community and researchers to tackle this challenge. Together they’ll share ideas, tools, and best practices for using next-generation web solutions to solve real problems in science, and explore ways to make research more agile and collaborative.

On their blog they highlight various projects related to promoting Open Access for scientific data

On September 10, 2015 Mozilla Science Lab had their scheduled meeting on scientific data reproduce ability.  The meeting was free and covered by ethernet and on social media. The Twitter hashtag for updates and meeting discussion is #mozscience (https://twitter.com/search?q=%23mozscience )

Open Access Meeting Announcement on Twitter

https://twitter.com/MozillaScience/status/641642491532283904

//platform.twitter.com/widgets.js

mozilla science lab

Mozilla Science Lab @MozillaScience

Join @khinsen @abbycabs + @EvoMRI tmrw (11AM ET) to hear about replication, publishing + #openscience. Details: https://etherpad.mozilla.org/sciencelab-calls-sep10-2015 …

AGENDA:

  • Mozilla Science Lab Updates
  • Staff welcomes and thank yous:
  • Welcoming Zannah Marsh, our first Instructional Designer
  • Workshopping the “Working Open” guide:
    • Discussion of Future foundation and GitHub projects
    • Discussion of submission for open science project funding
  • Contributorship Badges Pilot – an update! – Abby Cabunoc Mayes – @abbycabs
  • Will be live on GigaScience September 17th!
  • Where you can jump in: https://github.com/mozillascience/paperbadger/issues/17
  • Questions regarding coding projects – Abby will coordinate efforts on coding into their codebase
  • The journal will publish and authors and reviewers get a badge and their efforts and comments will appear on GigaScience: Giga Science will give credit for your reviews – supports an Open Science Discussion

Roadmap for

  • Fellows review is in full swing!
  • MozFest update:
  • Miss the submission deadline? You can still apply to join our Open Research Accelerator and join us for the event (PLUS get a DOI for your submission and 1:1 help)

A discussion by Konrad Hinsen (@khinsen) on ReScience, a journal focused on scientific replication will be presented:

  • ReScience – a new journal for replications – Konrad Hinsen @khinsen
  • ReScience is dedicated to publishing replications of previously published computational studies, along with all the code required to replicate the results.
  • ReScience lives entirely on GitHub. Submissions take the form of a Git repository, and review takes place in the open through GitHub issues. This also means that ReScience is free for everyone (authors, readers, reviewers, editors… well, I said everyone, right?), as long as GitHub is willing to host it.
  • ReScience was launched just a few days ago and is evolving quickly. To stay up to date, follow @ReScienceEds on Twitter. If you want to volunteer as a reviewer, please contact the editorial board.

The ReScience Journal Reproducible Science is Good. Replicated Science is better.

ReScience is a peer-reviewed journal that targets computational research and encourages the explicit reproduction of already published research promoting new and open-source implementations in order to ensure the original research is reproducible. To achieve such a goal, the whole editing chain is radically different from any other traditional scientific journal. ReScience lives on github where each new implementation is made available together with the comments, explanations and tests. Each submission takes the form of a pull request that is publicly reviewed and tested in order to guarantee any researcher can re-use it. If you ever reproduced computational result from the literature, ReScience is the perfect place to publish this new implementation. The Editorial Board

Notes from his talk:

– must be able to replicate paper’s results as written according to experimental methods

– All authors on ReScience need to be on GitHub

– not accepting MatLab replication; replication can involve computational replication;

  • Research Ideas and Outcomes Journal – Daniel Mietchen @EvoMRI
    • Postdoc at Natural Museum of London doing data mining; huge waste that 90% research proposals don’t get used so this journal allows for publishing proposals
    • Learned how to write proposals by finding a proposal online open access
    • Reviewing system based on online reviews like GoogleDocs where people view, comment
    • Growing editorial and advisory board; venturing into new subject areas like humanities, economics, biological research so they are trying to link diverse areas under SOCIAL IMPACT labeling
    • BIG question how to get scientists to publish their proposals especially to improve efficiency of collaboration and reduce too many duplicated efforts as well as reagent sharing
    • Crowdfunding platform used as post publication funding mechanism; still in works
    • They need a lot of help on the editorial board so if have a PhD PLEASE JOIN
  • Website:
  • Background:
  • Science article:
  • Some key features:
  • for publishing all steps of the research cycle, from proposals (funded and not yet funded) onwards
  • maps submissions to societal challenges
  • focus on post-publication peer review; pre-submission endorsement; all reviews public
  • lets authors choose which publishing services they want, e.g. whether they’d like journal-mediated peer review
  • collaborative WYSIWYG authoring and publishing platform based on JATS XML

A brief discussion of upcoming events on @MozillaScience

Meetings are held 2nd Thursdays of each month

Additional plugins, coding, and new publishing formats are available at https://www.mozillascience.org/

Other related articles on OPEN ACCESS Publishing were published in this Open Access Online Scientific Journal, include the following:

Archives of Medicine (AOM) to Publish from “Leaders in Pharmaceutical Business Intelligence (LPBI)” Open Access On-Line Scientific Journal http://pharmaceuticalintelligence.com

Annual Growth in NIH Clicks: 32% Open Access Online Scientific Journal http://pharmaceuticalintelligence.com

Collaborations and Open Access Innovations – CHI, BioIT World, 4/29 – 5/1/2014, Seaport World Trade Center, Boston

Elsevier’s Mendeley and Academia.edu – How We Distribute Scientific Research: A Case in Advocacy for Open Access Journals

Reconstructed Science Communication for Open Access Online Scientific Curation

The Fatal Self Distraction of the Academic Publishing Industry: The Solution of the Open Access Online Scientific Journals

 

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Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle


Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle

Reporter: Stephen J Williams, PhD

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series C: e-Books on Cancer & Oncology

Volume One: Cancer Biology and Genomics for Disease Diagnosis

CancerandOncologyseriesCcoverwhich is now available on Amazon Kindle at                          http://www.amazon.com/dp/B013RVYR2K.

This e-Book is a comprehensive review of recent Original Research on Cancer & Genomics including related opportunities for Targeted Therapy written by Experts, Authors, Writers. This ebook highlights some of the recent trends and discoveries in cancer research and cancer treatment, with particular attention how new technological and informatics advancements have ushered in paradigm shifts in how we think about, diagnose, and treat cancer. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon. All forthcoming BioMed e-Book Titles can be viewed at:

https://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

  • delivering curation and summary interpretations of latest findings and innovations
  • on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
  • providing a social platform for scientists and clinicians to enter into discussion using social media
  • compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Cancer Biology and Genomics for Disease Diagnosis

Preface

Introduction  The evolution of cancer therapy and cancer research: How we got here?

Part I. Historical Perspective of Cancer Demographics, Etiology, and Progress in Research

Chapter 1:  The Occurrence of Cancer in World Populations

Chapter 2.  Rapid Scientific Advances Changes Our View on How Cancer Forms

Chapter 3:  A Genetic Basis and Genetic Complexity of Cancer Emerge

Chapter 4: How Epigenetic and Metabolic Factors Affect Tumor Growth

Chapter 5: Advances in Breast and Gastrointestinal Cancer Research Supports Hope for Cure

Part II. Advent of Translational Medicine, “omics”, and Personalized Medicine Ushers in New Paradigms in Cancer Treatment and Advances in Drug Development

Chapter 6:  Treatment Strategies

Chapter 7:  Personalized Medicine and Targeted Therapy

Part III.Translational Medicine, Genomics, and New Technologies Converge to Improve Early Detection

Chapter 8:  Diagnosis                                     

Chapter 9:  Detection

Chapter 10:  Biomarkers

Chapter 11:  Imaging In Cancer

Chapter 12: Nanotechnology Imparts New Advances in Cancer Treatment, Detection, &  Imaging                                 

Epilogue by Larry H. Bernstein, MD, FACP: Envisioning New Insights in Cancer Translational Biology

 

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Real Time Conference Coverage for Scientific and Business Media: Unique Twitter Hashtags and Handles per Conference Presentation/Session

Curator: Stephen J Williams, PhD

 

AGENDA for MassBio 2015 Annual Meeting, March 26-27, 2015, Royal Sonesta Hotel, Cambridge, MA

https://pharmaceuticalintelligence.com/2015/01/13/massbio-2015-annual-meeting-march-26-27-2015-royal-sonesta-hotel-cambridge-ma/

 

Unique Twitter Hashtags and Handles per Conference Presentation/Session

Conference hashtag: #AM2015

Conference handle: @MassBio

Thursday, March 26, 2015

 

Talk Time Talk Title Hashtag Handle
9:00 – 9:30am Welcome Remarks Jay Ash, Secretary of Housing and Economic Development,  Commonwealth of Massachusetts #AM2015#MassBioForum

#Massachusetts

#Boston

#biotech

#investment

 

@MassBio@BostonBizJournl

@BioWorld

@BiotechNews

@bioitworld

9:30- 10:15 am Keynote: Kathy Giusti, Founder & Executive Chairman of the Multiple Myeloma Research Foundation #oncology#myeloma

#cancer

#MMRF

#BigData

#genomics

#personalizedmedicine

@theMMRF@KathyGiusti

@BV

 

10:30-11:30 am breakout Better Business Track:    It’s Not Your Grandfather’s Manufacturing #biotech#pharmanews

#biotechnews

#celltherapy

#stemcell

@NatureBiotech@celltherapynews

@BioWorld

@NatureCellBio

@BiotechNews

@LonzaGroup

@abbvie

@ContinuumPharma

10:30-11:30 am breakout Trends in Science Track: From Bioterrorism to Superorganisms: Perils, Pitfalls, and Promise #biotech#biotechnews

#defense

#investing

#wsj

 

 

@BiotechNews@bioitworld

@BioWorld

@BloombergTV

@Tetraphase

@WSJ

11:45am-1:30pm The MassBio Annual Awards Henri A. Termeer Innovative Leadership Award #MassBioForum#Massachusetts

#Boston

#biotech

#vc

#venturecapital

#pharmanews

 

@MassBio@BostonBizJournl

@BioWorld

@bioitworld

@BiotechNews

@PharmaNews

 

11:45-1:30pm The MassBio Annual Awards Joshua Boger Innovative School of the Year Award #MassBioForum#Massachusetts

#Boston

#biotech

#pharma

 

@MassBio@BostonBizJournl

@BioWorld

@bioitworld

@BiotechNews

@jsboger

@VertexPharma

11:45-1:30pm The MassBio Annual Awards Leading Impact Award #MassBioForum#Massachusetts

#Boston

#biotech

 

@MassBio@BostonBizJournl

@BioWorld

@bioitworld

@BiotechNews

1:30-2:20 pm Precision Medicine: Who’s Paying?  #pharma#healthcare

#ACA

#personalizedmedicine

#pharmanews

#cancer

#diagnostics

#genomics

@VertexPharma@MassBio

@bioitworld

@PharmaNews

@FoundationATCG

@nucleatec

2:25- 3:15 pm breakout session Better Business Track: Externalizing Pharma R&D #pharma#investment

#outsourcing

#pharmanews

 

@MassBio@PharmaNews

@Roche

@JNJInnovation

@Baxter

2:25- 3:15 pm breakout session Trends in Science Track: Trends in Healthcare Technology #healthcare#technology

#publichealth

#healthtech

 

@Pfizer@MassBio

@PharmaNews

@MITSloan

@HealthyBrown

3:30 pm – 4:20 pm    Breakout sessions Better Business Track: Technology Transfer: Status Quo, Evolution, or Revolution?  #investing#innovation

#patent

#biotech

@MassBio@PharmaNews

@BioWorld

@bioitworld

@BiotechNews

@BostonChildrens

@Roche

@Sanofi

@TuftsUniversity

 

3:30 pm – 4:20 pm    Breakout sessions Trends in Science Track: Immunotherapy: Oncology and Beyond #oncology#cancer

#immunotherapies

#Curis

#Mersana

#ImmunosanT

 

 

 

@MassBio@PharmaNews

@BioWorld

@bioitworld

@cancer

@BiotechNews

@MersanaADC

 

 

 

 

Friday, March 27, 2015

 

Talk Time Talk Title Hashtag Handle
8:40– 9:30am breakout sessions Better Business Track: Innovative Ways to Fund Your Early-Stage Company     #MassBio#startup

#biotech

#VC

#venturecapital

#investing

#CrowdFunding

#BroadviewVentures

@MassBio@PharmaNews

@BioWorld

@bioitworld

@theMMRF

@CorbusPharma

@HX_Healthios

 

8:40– 9:30am breakout sessions Trends in Science Track: Current and Future Impact of Editing, CART and Gene Therapy #MassBio#CRISPR

#immunotherapy

#cancer

#biotech

#genetics

 

 

 

@bioitworld@MassBio

@PharmaNews

@BioWorld

@BiotechNews

@bluebirdbio

 

9:40-10:30 am breakout Better Business Track: The Evolving Reimbursement Landscape #MassBio#ACA

#healthcare

#insurance

 

@BV@MassBio

@PharmaNews

@BioWorld

 

9:40-10:30 am breakout Trends in Science Track: Neuroscience Therapeutics Development: Challenges, Opportunities and the Road Ahead #MassBio#neuroscience

#biotech

#Alzheimers

 

@bioitworld@MassBio

@PharmaNews

@BioWorld

@harvardmed

@Neurophage

@Lilly

@NINDSnews

 

 

11:00am-12:00pm Defining Value #MassBio#AM2015

#healthcare

#ACA

#healtheconomics

 

@BV@MassBio

@PharmaNews

@BioWorld

@ACS

 

12:45-1:30 Keynote: Andrew Lo, Charles E. and Susan T. Harris Professor and Director of the MIT Laboratory for Financial Engineering #MassBio#MIT

#investing

#VC

#startup

 

@MassBio@MITSloan

@PharmaNews

@BioWorld

@BV

 

 

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