Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com
Real Time @BIOConvention #BIO2019:#Bitcoin Your Data! From Trusted Pharma Silos to Trustless Community-Owned Blockchain-Based Precision Medicine Data Trials
As care for lifestyle-driven chronic diseases expands in scope, prevention and recovery are becoming the new areas of focus. Building a precision medicine foundation that will promote ownership of individuals’ health data and allow for sharing and trading of this data could prove a great blockchain.
At its core, blockchain may offer the potential of a shared platform that decentralizes healthcare interactions ensuring access control, authenticity and integrity, while presenting the industry with radical possibilities for value-based care and reimbursement models. Panelists will explore these new discoveries as well as look to answer lingering questions, such as: are we off to a “trustless” information model underpinned by Bitcoin cryptocurrency, where no central authority validates the transactions in the ledger, and anyone whose computers can do the required math can join to mine and add blocks to your data? Would smart contracts begin to incentivize “rational” behaviors where consumers respond in a manner that makes their data interesting?
Moderator: Cybersecurity is extremely important in the minds of healthcare CEOs. CEO of Kaiser Permenente has listed this as one of main concerns for his company.
Sanjeey of Singularity: There are Very few companies in this space. Singularity have collected thousands of patient data. They wanted to do predictive health care, where a patient will know beforehand what health problems and issues to expect. Created a program called Virtual Assistant. As data is dynamic, the goal was to provide Virtual Assistant to everyone.
Benefits of blockchain: secure, simple to update, decentralized data; patient can control their own data, who sees it and monetize it.
Nebular Genetics: Company was founded by Dr. George Church, who had pioneered the next generation sequencing (NGS) methodology. The company goal is to make genomics available to all but this currently is not the case as NGS is not being used as frequently.
The problem is a data problem:
data not organized
data too parsed
data not accessible
Blockchain may be able to alleviate the accessibiltiy problem. Pharma is very interested in the data but expensive to collect. In addition many companies just do large scale but low depth sequencing. For example 23andme (which had recently made a big deal with Lilly for data) only sequences about 1% of genome.
There are two types of genome sequencing companies
large scale and low depth – like 23andme
smaller scale but higher depth – like DECODE and some of the EU EXOME sequencing efforts like the 1000 Project
Simply Vital Health: Harnesses blockchain to combat ineffeciencies in hospital records. They tackle the costs after acute care so increase the value based care. Most of healthcare is concentrated on the top earners and little is concentrated on the majority less affluent and poor. On addressing HIPAA compliance issues: they decided to work with HIPAA and comply but will wait for this industry to catch up so the industry as a whole can lobby to affect policy change required for blockchain technology to work efficiently in this arena. They will only work with known vendors: VERY Important to know where the data is kept and who are controlling the servers you are using. With other blockchain like Etherium or Bitcoin, the servers are anonymous.
Encrypgen: generates new blockchain for genomic data and NGS companies.
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Track 9 Pharmaceutical R&D Informatics: Collaboration, Data Science and Biologics @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Aviva Lev-Ari, PhD, RN
April 30, 2014
Big Data and Data Science in R&D and Translational Research
10:50 Chairperson’s Remarks
Ralph Haffner, Local Area Head, Research Informatics, F. Hoffmann-La Roche AG
11:00 Can Data Science Save Pharmaceutical R&D?
Jason M. Johnson, Ph.D., Associate Vice President,
Scientific Informatics & Early Development and Discovery Sciences IT, Merck
Although both premises – that the viability of pharmaceutical R&D is mortally threatened and that modern “data science” is a relevant superhero – are
suspect, it is clear that R&D productivity is progressively declining and many areas of R&D suboptimally use data in decision-making. We will discuss
some barriers to our overdue information revolution, and our strategy for overcoming them.
11:30 Enabling Data Science in Externalized Pharmaceutical R&D
Sándor Szalma, Ph.D., Head, External Innovation, R&D IT,
Janssen Research & Development, LLC
Pharmaceutical companies have historically been involved in many external partnerships. With recent proliferation of hosted solutions and the availability
of cost-effective, massive high-performance computing resources there is an opportunity and a requirement now to enable collaborative data science. We
discuss our experience in implementing robust solutions and pre-competitive approaches to further these goals.
12:00 pm Co-Presentation: Sponsored by
Collaborative Waveform Analytics: How New Approaches in Machine Learning and Enterprise Analytics will Extend Expert Knowledge and Improve Safety Assessment
Tim Carruthers, CEO, Neural ID
Scott Weiss, Director, Product Strategy, IDBS
Neural ID’s Intelligent Waveform Service (IWS) delivers the only enterprise biosignal analysis solution combining machine learning with human expertise. A collaborative platform supporting all phases of research and development, IWS addresses a significant unmet need, delivering scalable analytics and a single interoperable data format to transform productivity in life sciences. By enabling analysis from BioBook (IDBS) to original biosignals, IWS enables users of BioBook to evaluate cardio safety assessment across the R&D lifecycle.
12:15 Building a Life Sciences Data
Sponsored by
Lake: A Useful Approach to Big Data
Ben Szekely, Director & Founding Engineer,
Cambridge Semantics
The promise of Big Data is in its ability to give us technology that can cope with overwhelming volume and variety of information that pervades R&D informatics. But the challenges are in practical use of disconnected and poorly described data. We will discuss: Linking Big Data from diverse sources for easy understanding and reuse; Building R&D informatics applications on top of a Life Sciences Data Lake; and Applications of a Data Lake in Pharma.
12:40 Luncheon Presentation I:
Sponsored by
Chemical Data Visualization in Spotfire
Matthew Stahl, Ph.D., Senior Vice President,
OpenEye Scientific Software
Spotfire deftly facilitates the analysis and interrogation of data sets. Domain specific data, such as chemistry, presents a set of challenges that general data analysis tools have difficulty addressing directly. Fortunately, Spotfire is an extensible platform that can be augmented with domain specific abilities. Spotfire has been augmented to naturally handle cheminformatics and chemical data visualization through the integration of OpenEye toolkits. The OpenEye chemistry extensions for Spotfire will be presented.
1:10 Luncheon Presentation II
1:50 Chairperson’s Remarks
Yuriy Gankin, Ph.D., Co. Founder and CSO, GGA Software Services
1:55 Enable Translational Science by Integrating Data across the R&D Organization
Christian Gossens, Ph.D., Global Head, pRED Development Informatics Team,
pRED Informatics, F. Hoffmann-La Roche Ltd.
Multi-national pharmaceutical companies face an amazingly complex information management environment. The presentation will show that
a systematic system landscaping approach is an effective tool to build a sustainable integrated data environment. Data integration is not mainly about
technology, but the use and implementation of it.
2:25 The Role of Collaboration in Enabling Great Science in the Digital Age: The BARD Data Science Case Study
Andrea DeSouza, Director, Informatics & Data Analysis,
Broad Institute
BARD (BioAssay Research Database) is a new, public web portal that uses a standard representation and common language for organizing chemical biology data. In this talk, I describe how data professionals and scientists collaborated to develop BARD, organize the NIH Molecular Libraries Program data, and create a new standard for bioassay data exchange.
May 1. 2014
BIG DATA AND DATA SCIENCE IN R&D AND TRANSLATIONAL RESEARCH
10:30 Chairperson’s Opening Remarks
John Koch, Director, Scientific Information Architecture & Search, Merck
10:35 The Role of a Data Scientist in Drug Discovery and Development
A major challenge in drug discovery and development is finding all the relevant data, information, and knowledge to ensure informed, evidencebased
decisions in drug projects, including meaningful correlations between preclinical observations and clinical outcomes. This presentation will describe
where and how data scientists can support pharma R&D.
11:05 Designing and Building a Data Sciences Capability to Support R&D and Corporate Big Data Needs
Shoibal Datta, Ph.D., Director, Data Sciences, Biogen Idec
To achieve Biogen Idec’s strategic goals, we have built a cross-disciplinary team to focus on key areas of interest and the required capabilities. To provide
a reusable set of IT services we have broken down our platform to focus on the Ingestion, Digestion, Extraction and Analysis of data. In this presentation, we will outline how we brought focus and prioritization to our data sciences needs, our data sciences architecture, lessons learned and our future direction.
11:35 Data Experts: Improving Sponsored by
Translational Drug-Development Efficiency
Jamie MacPherson, Ph.D., Consultant, Tessella
We report on a novel approach to translational informatics support: embedding Data Experts’ within drug-project teams. Data experts combine first-line
informatics support and Business Analysis. They help teams exploit data sources that are diverse in type, scale and quality; analyse user-requirements and prototype potential software solutions. We then explore scaling this approach from a specific drug development team to all.
Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.
A report on how gamification mobile applications, like CyberDoctor’s PatientPartner, may improve patient adherence to oral chemotherapy.
(includes interviews with CyberDoctor’s CEO Akhila Satish and various oncologists)
Writer/Curator: Stephen J. Williams, Ph.D.
UPDATE 5/15/2019
Please see below for an UPDATE on this post including results from the poll conducted here on the value of a gamification strategy for oral chemotherapy patient adherence as well as a paper describing a well designed development of an application specifically to address this clinical problem.
Studies have pointed to a growing need to monitor and improve medical adherence, especially with outpatient prescription drugs across many diseases, including cancer.
The trend to develop oral chemotherapies, so patients can take their medications in the convenience of their home, has introduced produced a unique problem concerning cancer patient-medication adherence. Traditionally, chemotherapies were administered by a parental (for example intravenous) route by clinic staff, however, as noted by Jennifer M Gangloff in her article Troubling Trend: Medication Adherence:
with the trend of cancer patients taking their oral medication at home, the burden of adherence has shifted from clinicians to the patients and their families.
A few highlights from Jennifer Gangloff’s article highlight the degree and scope of the problem:
There is a wide range of adherence for oral chemo– as low as 16% up to 100% adherence rates have been seen in multiple studies
High cost in lives and money: estimates in US of 125,000 deaths and $300 billion in healthcare costs due to nonadherence to oral anticancer medications
Factors not related to the patient can contribute to nonadherence including lack of information provided by the healthcare system and socioeconomic factors
Numerous methods to improve adherence issues (hospital informative seminars, talking pill bottles, reminder phone calls etc.) have met with mixed results.
More strikingly, patient adherence rates can drastically decline over treatment, with one study showing an adherence rate drop from 87% to 50% over 4 years of adjuvant tamoxifen therapy.
Tackling The Oral Chemotherapy-Patient Adherence Problem
Documented factors leading to non-adherence to oral oncology medications include
Patient feels better so stop taking the drug
Patient feels worse so stops taking the drug
Confusing and complicated dosing regimen
Inability to afford medications
Poor provider-patient relationships
Adverse effects of medication
Cognitive impairment (“chemo fog”; mental impairment due to chemotherapy
Inadequate education/instruction of discharge
There are many examples of each reason why a patient stopped taking medication. One patient was prescribed capecitabine for her metastatic breast cancer and, upon feeling nausea, started to use antacids, which precipitated toxicities as a result of increased plasma levels of capecitabine.
This review also documented the difficulties in accurately measuring patient adherence including:
Inaccuracy of self-reporting
Lack of applicability of external measurements such as pill counts
Hawthorne effect: i.e. patient pill documentation reminds them to take next dose
The group suggests that using MTM programs, especially telephony systems involving oncology nurses and pharmacists and utilizing:
Therapy support (dosing reminders)
Education
Side effect management
may be a cost-efficient methodology to improve medical adherence.
Although nurses are important intermediary educating patients about their oral chemotherapies, it does not appear that solely relying on nurses to monitor patient adherence will be sufficient, as indicated in a survey-based Japanese study.
Survey results indicated that 90% of nurses reported asking patients on oral chemotherapy about emergency contacts, side effects, and family/friend support. Nurses also provided patients with education materials on their assigned medication.
However, less than one-third of nurses asked if their patients felt confident about managing their oral chemotherapy.
“Nurses were less likely to ask adherence-related questions of patients with refilled prescriptions than of new patients,” the researchers wrote. “Regarding unused doses of anticancer agents, 35.5% of nurses reported that they did not confirm the number of unused doses when patients had refilled prescriptions.”
From the Roswell Park Cancer Institute blog post Making Mobile Health Work
US physicians are recognizing the need for the adoption of mobile in their practice but choice of apps and mobile strategies must be carefully examined before implementation. In addition, most physicians are using mobile communications as a free-complementary service and these physicians are not being reimbursed for their time.
Some companies are providing their own oncology-related mobile app services:
San Francisco, August 13, 2013 – CollabRx, Inc. (NASDAQ: CLRX), a healthcare information technology company focused on informing clinical decision making in molecular medicine, today announced a multi-year agreement with Everyday Health’s MedPage Today. The forthcoming app, which will target oncologists and pathologists, will focus on the molecular aspects of laboratory testing and therapy development. Over time, the expectation is that this app will serve as a comprehensive point of care resource for physicians and patients to obtain highly credible, expert-vetted and dynamically updated information to guide cancer treatment planning.
The McKesson Foundation’s Mobilizing for Health initiative
has awarded a grant to Partners HealthCare’s Center for Connected Health to develop a mobile health program that uses a smartphone application to help patients with cancer adhere to oral chemotherapy treatments and monitor their symptoms, FierceMobileHealthcare reports.
CancerNet announces mobile application (from cancer.net)
The report suggests that there are too many apps either offering information, suggesting behavior/lifestyle changes, or measuring compliance data but little evidence to suggest any of these are working the way they intended. The article suggests the plethora of apps may just be adding to the confusion.
MyCyberDoctor™, a True Gamification App, Shows Great Results in Improving Diabetics Medical Adherence and Health Outcome
Most of the mobile health apps discussed above, would be classified as tracking apps, because the applications simply record a patient’s actions, whether filling a prescription, interacting with a doctor, nurse, pharmacist, or going to a website to gain information. However, as discussed before, there is no hard evidence this is really impacting health outcomes.
Another type of application, termed gamification apps, rely on role-playing by the patient to affect patient learning and ultimately behavior.
An interested twist on this method was designed by Akhila Satish, CEO and developer of CyberDoctor and a complementary application PatientPartner.
As reported here, the PatientPartner application was used in the first IRB-approved mhealth clinical-trial to see if the gamification app could improve medical adherence and outcomes in diabetic patients. PatientPartner is a story-driven game in changing health behavior and biomarkers (blood glucose levels in this trial). In the clinical trial, 100 non-adherent patients with diabetes played the PatientPartner game for 15 minutes. Results were amazing, as the trial demonstrated an increase in patient adherence, with only 15 minutes of game playing.
Results from the study
Patients with diabetes who used PatientPartner showed significant improvement in three key areas – medication, diet, and exercise:
Medication adherence increased by 37%, from 58% to 95% – equivalent to three additional days of medication adherence per week.
Diet adherence increased by 24% – equivalent to two days of additional adherence a week.
Exercise adherence increased by 14% – equivalent to one additional day of adherence per week.
HbA1c (a blood sugar measure) decreased from 10.7% to 9.7%.
As mentioned in the article:
The unique, universal, non-disease specific approach allows PatientPartner to be effective in improving adherence in all patient populations.
PatientPartner is available in the iTunes store and works on the iPhone and iPod Touch. For information on PatientPartner, visit www.mypatientpartner.com.
Ms. Satish, who was named one of the top female CEO’s at the Health Conference, gratuitously offered to answer a few questions for Leaders in Pharmaceutical Business Intelligence (LPBI) on the feasibility of using such a game (role-playing) application to improve medical adherence in the oncology field.
LPBI: The results you had obtained with patient-compliance in the area of diabetes are compelling and the clinical trial well-designed. In the oncology field, due to the increase in use of oral chemotherapeutics, patient-compliance has become a huge issue. Other than diabetes, are there plans for MyCyberDoctor and PatientPartner to be used in other therapeutic areas to assist with patient-compliance and patient-physician relations?
Ms. Satish: Absolutely! We tested the application in diabetes because we wanted to measure adherence from an objective blood marker (hbA1c). However, the method behind PatientPartner- teaching patients how to make healthy choices- is universal and applicable across therapeutic areas.
LPBI: Recently, there have been a plethora of apps developed which claim to impact patient-compliance and provide information. Some of these apps have been niche (for example only providing prescription information but tied to pharmacy records and company databases). Your app seems to be the only one with robust clinical data behind it and approaches from a different angle, namely adjusting behavior using a gamefying experience and teaching the patient the importance of compliance. How do you feel this approach geared more toward patient education sets PatientPartner apart from other compliance-based apps?
Ms. Satish: PatientPartner really focuses on the how of patient decision making, rather than the specifics of each decision that is made. It’s a unique approach, and part of the reason PatientPartner works so effectively with such a short initial intervention! We are able to achieve more with less “app” time as a result of this method.
LPBI: There have been multiple studies attempting to correlate patient adherence, decision-making, and health outcome to socioeconomic status. In some circumstances there is a socioeconomic correlation while other cases such as patient-decision to undergo genetic testing or compliance to breast cancer treatment in rural areas, level of patient education may play a bigger role. Do you have data from your diabetes trial which would suggest any differences in patient adherence, outcome to any socioeconomic status? Do you feel use of PatientPartner would break any socioeconomic barriers to full patient adherence?
Ms. Satish: Within our trial, we had several different clinical sites. This helped us test the product out in a broad, socioeconomically diverse population. It is our hope that with a tool as easy to scale and use as PatientPartner we have the opportunity to see the product used widely, even in populations that are traditionally harder to reach.
LPBI: There has been a big push for the development of individual, personalized physician networks which use the internet as the primary point of contact between a primary physician and the patient. Individuals may sign up to these networks bypassing the traditional insurance-based networks. How would your application assist in these types of personalized networks?
Ms. Satish: PatientPartner can easily be plugged into any existing framework of communication between patient and provider. We facilitate patient awareness, engagement and accountability- all of which are important regardless of the network structure.
LBPI: Thank you Akhila!
A debate has begun about regulating mobile health applications, and although will be another post, I would just like to summarize a nice article in May, 2014 Oncology Times by Sarah Digiulo “Mobile Health Apps: Should They be Regulated?
In general, in the US there are HIPAA regulations about the dissemination of health related information between a patient and physician. Most of the concerns are related to personal health information made public in an open-access platform such as Twitter or Facebook.
In addition, according to Dr. Don Dizon M.D., Director of the Oncology Sexual Health Clinic at Massachusetts General Hospital, it may be more difficult to design applications directed against a vast, complex disease like cancer with its multiple subtypes than for diabetes.
Mobile Health Applications on Rise in Developing World: Worldwide Opportunity
According to International Telecommunication Union (ITU) statistics, world-wide mobile phone use has expanded tremendously in the past 5 years, reaching almost 6 billion subscriptions. By the end of this year it is estimated that over 95% of the world’s population will have access to mobile phones/devices, including smartphones.
This presents a tremendous and cost-effective opportunity in developing countries, and especially rural areas, for physicians to reach patients using mHealth platforms.
Drs. Clara Aranda-Jan Neo Mohutsiwa and Svetla Loukanova had conducted a systematic review of the literature on mHealth projects conducted in Africa[1] to assess the reliability of mobile phone and applications to assist in patient-physician relationships and health outcomes. The authors reviewed forty four studies on mHealth projects in Africa, determining their:
strengths
weaknesses
opportunities
threats
to patient outcomes using these mHealth projects. In general, the authors found that mHealth projects were beneficial for health-related outcomes and their success related to
accessibility
acceptance and low-cost
adaptation to local culture
government involvement
while threats to such projects could include
lack of funding
unreliable infrastructure
unclear healthcare system responsibilities
Dr.Sreedhar Tirunagari, an oncologist in India, agrees that mHealth, especially gamification applications could greatly foster better patient education and adherencealthough he notes that mHealth applications are not really used in India and may not be of much use for those oncology patients living in rural areas, as cell phone use is not as prevalent as in the bigger inner cities such as Delhi and Calcutta.
1) do you see a use for such apps which either track drug compliance or use gamification systems to teach patients the importance of continuing their full schedule of drug therapy
2) do you feel patient- drug compliance issues in the oncology practice is due to lack of information available to the patient or issues related to drug side effects?
“I think that Apps could help in this setting, we are in
Informatics era but..
The main question is that chronic patients are special ones.
Cancer patients have to deal with prognosis, even in therapies
with curative intent such as aromatase inhibitors are potent
Drugs that can cure; only in the future the patients know.
But meanwhile he or she has to deal with side-effects every day. A PC can help but suffer this symptoms…it. Is a real problem believe me!”
“The main app is his/her doctor”
I would like to invite all oncologists to answer the poll question ABOVE about the use of such gamification apps, like PatientPartner, for improving medical adherence to oral chemotherapy.
UPDATE 5/15/2019
The results of the above poll, although limited, revealed some interesting insights. Although only five oncologists answered the poll whether they felt gamification applications could help with oral chemotherapy patient adherence, all agreed it would be worthwhile to develop apps based on gamification to assist in the outpatient setting. In addition, one oncologist felt that the success of mobile patient adherence application would depend on the type of cancer. None of the oncologist who answered the survey thought that gamification apps would have no positive effect on patient adherence to their chemotherapy. With this in light, a recent paper by Joel Fishbein of University of Colorado and Joseph Greer from Massachusetts General Hospital, describes the development of a mobile application, in clinical trial, to promote patient adherence to their oral chemotherapy.
Mobile Applications to Promote Adherence to Oral Chemotherapy and Symptom Management: A Protocol for Design and Development
Oral chemotherapy is increasingly used in place of traditional intravenous chemotherapy to treat patients with cancer. While oral chemotherapy includes benefits such as ease of administration, convenience, and minimization of invasive infusions, patients receive less oversight, support, and symptom monitoring from clinicians. Additionally, adherence is a well-documented challenge for patients with cancer prescribed oral chemotherapy regimens. With the ever-growing presence of smartphones and potential for efficacious behavioral intervention technology, we created a mobile health intervention for medication and symptom management.
OBJECTIVE:
The objective of this study was to develop and evaluate the usability and acceptability of a smartphone app to support adherence to oral chemotherapy and symptom management in patients with cancer.
METHODS:
We used a 5-step development model to create a comprehensive mobile app with theoretically informed content. The research and technical development team worked together to develop and iteratively test the app. In addition to the research team, key stakeholders including patients and family members, oncology clinicians, health care representatives, and practice administrators contributed to the content refinement of the intervention. Patient and family members also participated in alpha and beta testing of the final prototype to assess usability and acceptability before we began the randomized controlled trial.
RESULTS:
We incorporated app components based on the stakeholder feedback we received in focus groups and alpha and beta testing. App components included medication reminders, self-reporting of medication adherence and symptoms, an education library including nutritional information, Fitbit integration, social networking resources, and individually tailored symptom management feedback. We are conducting a randomized controlled trial to determine the effectiveness of the app in improving adherence to oral chemotherapy, quality of life, and burden of symptoms and side effects. At every stage in this trial, we are engaging stakeholders to solicit feedback on our progress and next steps.
CONCLUSIONS:
To our knowledge, we are the first to describe the development of an app designed for people taking oral chemotherapy. The app addresses many concerns with oral chemotherapy, such as medication adherence and symptom management. Soliciting feedback from stakeholders with broad perspectives and expertise ensured that the app was acceptable and potentially beneficial for patients, caregivers, and clinicians. In our development process, we instantiated 7 of the 8 best practices proposed in a recent review of mobile health app development. Our process demonstrated the importance of effective communication between research groups and technical teams, as well as meticulous planning of technical specifications before development begins. Future efforts should consider incorporating other proven strategies in software, such as gamification, to bolster the impact of mobile health apps. Forthcoming results from our randomized controlled trial will provide key data on the effectiveness of this app in improving medication adherence and symptom management.
In this paper, Fishbein et al. describe the methodology of the developoment of a mobile application to promote oral chemotherapy adherence. This mobile app intervention was named CORA or ChemOtheRapyAssistant.
Of the approximately 325,000 health related apps on the market (as of 2017), the US Food and Drug Administration (FDA) have only reviewed approximately 20 per year and as of 2016 cleared only about 36 health related apps.
According to industry estimates, 500 million smartphone users worldwide will be using a health care application by 2015, and by 2018, 50 percent of the more than 3.4 billion smartphone and tablet users will have downloaded mobile health applications. However, there is not much scientific literature providing a framework for design and creation of quality health related mobile applications.
Methods
The investigators separated the app development into two phases: Phase 1 consisted of the mobile application development process and initial results of alpha and beta testing to determine acceptability among the major stakeholders including patients, caregivers, oncologists, nurses, pharmacists, pharmacologists, health payers, and patient advocates. Phase 1 methodology and results were the main focus of this paper. Phase 2 consists of an ongoing clinical trial to determine efficacy and reliability of the application in a larger number of patients at different treatment sites and among differing tumor types.
The 5 step development process in phase 1 consisted of identifying features, content, and functionality of a mobile app in an iterative process, including expert collaboration and theoretical framework to guide initial development.
There were two distinct teams: a research team and a technical team. The multidisciplinary research team consisted of the principal investigator, co-investigators (experts in oncology, psychology and psychiatry), a project director, and 3 research assistants.
The technical team consisted of programmers and project managers at Partners HealthCare Connected Health. Stakeholders served as expert consultants including oncologists, health care representatives, practice administrators, patients, and family members (care givers). All were given questionaires (HIPAA compliant) and all involved in alpha and beta testing of the product.
There were 5 steps in the development process
Implementing a theoretical framework: Patients and their family caregivers now bear the primary responsibility for their medical adherence especially to oral chemotherapy which is now more frequently administered in the home setting not in the clinical setting. Four factors were identified as the most important barriers to oral chemotherapy adherence: complexity of medication regimes, symptom burden, poor self-management of side effects, and low clinical support. These four factors were integral in the design of the mobile app and made up a conceptual framework in its design.
Conducting Initial Focus Group Interviews with key stakeholders: Stakeholders were taken from within and outside the local community. In all 32 stakeholders served as study collaborators including 8 patient/families, 8 oncologists/clinicians, 8 cancer practice administrators, and 8 representatives of the health system, community, and overall society. The goal of these focus groups were to obtain feedback on the proposed study and design included perceived importance of monitoring of adherence to oral chemotherapy, barriers to communication between patients and oncology teams regarding side effects and medication adherence, potential role of mobile apps to address barriers of quality of cancer care, potential feasibility, acceptability, and usage and feedback on the overall study design.
Creation of Wireframes (like storyboards or page designs) and Collecting Initial Feedback: The research and design team, in conjunction with stakeholder input, created content wireframes, or screen blueprints) to provide a visual guide as to what the app would look like. These wireframes also served as basis for what the patient interviews would look like on the application. A total of 10 MGH (Massachusetts General Hospital) patients (6 female, 4 male) and most with higher education (BS or higher) participated in the interviews and design of wireframes. Eight MGH clinicians participated in this phase of wireframe design.
Developing, Programming, and Refining the App: CORA was designed to be supported by PHP/MySQL databases and run on LAMP hosts (Linux, Apache, MySQL, Perl/PHP/Python) and fully HIPAA compliant. Alpha testing was conducted with various stakeholders and the app refined by the development team (technical team) after feedback.
Final beta testing and App prototype for clinical trial: The research team considered the first 5 participants enrolled in the subsequent clinical trial for finalization of the app prototype.
There were 7 updated versions of the app during the initial clinical trial phase and 4 updates addressed technical issues related to smartphone operating system upgrades.
Finally, the investigators list a few limitations in their design and study of this application. First the patient population was homogenous as all were from an academic hospital setting. Second most of the patients were of Caucasian ethnic background and most were highly educated, all of which may introduce study bias. In addition, CORA was available on smartphone and tablet only, so a larger patient population who either have no access to these devices or are not technically savvy may experience issues related to this limitation.
In addition other articles on this site related to Mobile Health applications and Health Outcomes include
Aranda-Jan CB, Mohutsiwa-Dibe N, Loukanova S: Systematic review on what works, what does not work and why of implementation of mobile health (mHealth) projects in Africa. BMC public health 2014, 14:188.
PLENARY KEYNOTE PRESENTATIONS: THURSDAY, MAY 1 | 8:00 – 10:00 AM @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Reporter: Aviva Lev-Ari, PhD, RN
Keynote Introduction: Sponsored by Fred Lee, M.D., MPH, Director, Healthcare Strategy and Business Development, Oracle Health Sciences
Heather Dewey-Hagborg
Artist, Ph.D. Student, Rensselaer Polytechnic Institute
Heather Dewey-Hagborg is an interdisciplinary artist, programmer and educator who explores art as research and public inquiry. She recreates identity from strands of human hair in an entirely different way. Collecting hairs she finds in random public places – bathrooms, libraries, and subway seats – she uses a battery of newly developing technologies to create physical, life-sized portraits of the owners of these hairs. Her fixation with a single hair leads her to controversial art projects and the study of genetics. Traversing media ranging from algorithms to DNA, her work seeks to question fundamental assumptions underpinning perceptions of human nature, technology and the environment. Examining culture through the lens of information, Heather creates situations and objects embodying concepts, probes for reflection and discussion. Her work has been featured in print, television, radio, and online. Heather has a BA in Information Arts from Bennington College and a Masters degree from the Interactive Telecommunications Program at Tisch School of the Arts, New York University. She is currently a Ph.D. student in Electronic Arts at Rensselaer Polytechnic Institute.
Yaniv Erlich, Ph.D.
Principal Investigator and Whitehead Fellow, Whitehead Institute for Biomedical Research
Dr. Yaniv Erlich is Andria and Paul Heafy Family Fellow and Principal Investigator at the Whitehead Institute for Biomedical Research. He received a bachelor’s degree from Tel-Aviv University, Israel and a PhD from the Watson School of Biological Sciences at Cold Spring Harbor Laboratory in 2010. Dr. Erlich’s research interests are computational human genetics. Dr. Erlich is the recipient of the Burroughs Wellcome Career Award (2013), Harold M. Weintraub award (2010), the IEEE/ACM-CS HPC award (2008), and he was selected as one of 2010 Tomorrow’s PIs team of Genome Technology.
Isaac Samuel Kohane, M.D., Ph.D.
Henderson Professor of Health Sciences and Technology, Children’s Hospital and Harvard Medical School;
Director, Countway Library of Medicine; Director, i2b2 National Center for Biomedical Computing;
Co-Director, HMS Center for Biomedical Informatics
Isaac Kohane, MD, PhD, co-directs the Center for Biomedical Informatics at Harvard Medical School. He applies computational techniques, whole genome analysis, and functional genomics to study human diseases through the developmental lens, and particularly through the use of animal model systems. Kohane has led the use of whole healthcare systems, notably in the i2b2 project, as “living laboratories” to drive discovery research in disease genomics (with a focus on autism) and pharmacovigilance
(including providing evidence for the cardiovascular risk of hypoglycemic agents which ultimately contributed to “black box”ing by the FDA) and comparative effectiveness with software and methods adopted in over 84 academic health centers internationally. Dr. Kohane has published over 200 papers in the medical literature and authored a widely used book on Microarrays for an Integrative Genomics. He has been elected to multiple honor societies including the American Society for Clinical Investigation, the American College of Medical Informatics, and the Institute of Medicine. He leads a doctoral program in genomics and bioinformatics within the Division of Medical Science at Harvard University. He is also an occasionally practicing pediatric endocrinologist.
Track 5 Next-Gen Sequencing Informatics: Advances in Analysis and Interpretation of NGS Data @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Reporter: Aviva Lev-Ari, PhD, RN
NGS Bioinformatics Marketplace: Emerging Trends and Predictions
10:50 Chairperson’s Remarks
Narges Baniasadi, Ph.D., Founder & CEO, Bina Technologies, Inc.
11:00 Global Next-Generation Sequencing Informatics Markets: Inflated Expectations in an Emerging Market
Greg Caressi, Senior Vice President, Healthcare and Life Sciences, Frost & Sullivan
This presentation evaluates the global next-generation sequencing (NGS) informatics markets from 2012 to 2018. Learn key market drivers and restraints,
key highlights for many of the leading NGS informatics services providers and vendors, revenue forecasts, and the important trends and predictions that
affect market growth.
Organizational Approaches to NGS Informatics
11:30 High-Performance Databases to Manage and Analyze NGS Data
Joseph Szustakowski, Ph.D., Head, Bioinformatics, Biomarker Development,
Novartis Institutes for Biomedical Research
The size, scale, and complexity of NGS data sets call for new data management and analysis strategies. High-performance database systems
combine the advantages of both established and cutting edge technologies. We are using high performance database systems to manage and analyze NGS, clinical, pathway, and phenotypic data with great success. We will describe our approach and concrete success stories that demonstrate its efficiency and effectiveness.
12:00 pm Taming Big Science Data Growth with Converged Infrastructure
Aaron D. Gardner, Senior Scientific Consultant,
BioTeam, Inc.
Many of the largest NGS sites have identified IO bottlenecks as their number one concern in growing their infrastructure to support current and projected
data growth rates. In this talk Aaron D. Gardner, Senior Scientific Consultant, BioTeam, Inc. will share real-world strategies and implementation details
for building converged storage infrastructure to support the performance, scalability and collaborative requirements of today’s NGS workflows.
12:15 Next Generation Sequencing: Workflow Overview from a High-Performance Computing Point of View
Carlos P. Sosa, Ph.D., Applications Engineer, HPC Lead,
Cray, Inc.
Next Generation Sequencing (NGS) allows for the analysis of genetic material with unprecedented speed and efficiency. NGS increasingly shifts the burden
from chemistry done in a laboratory to a string manipulation problem, well suited to High- Performance Computing. We explore the impact of the NGS
workflow in the design of IT infrastructures. We also present Cray’s most recent solutions for NGS workflow.
SOSA in REAL TIME
Bioinformatics and BIG DATA – NGS @ CRAY i 2014
I/O moving, storage data – UNIFIED solution by Cray
Data access
Fast Access
Storage
manage high performance computinf; NGS work flow, multiple human genomes 61 then 240 sequentiallt, with high performance in 51 hours, 140 genomes in simultaneous
Architecture @Cray for Genomics
sequensors
Galaxy
servers for analysis
workstation: Illumina, galaxy, CRAY does the integration of 3rd party SW using a workflow LEVERAGING the network, the fastest in the World, network useding NPI for scaling and i/O
Compute blades, reserves formI?O nodes, the Fastest interconnet in the industry
scale of capacity and capability, link interconnect in the file System: lustre
optimization of bottle neck: capability, capacity, file structure for super fast I/O
12:40 Luncheon Presentation I
Erasing the Data Analysis Bottleneck with BaseSpace
Jordan Stockton, Ph.D., Marketing Director,
Enterprise Informatics, Illumina, Inc.
Since the inception of next generation sequencing, great attention has been paid to challenges such as storage, alignment, and variant calling. We believe
that this narrow focus has distracted many biologists from higher-level scientific goals, and that simplifying this process will expedite the discovery
process in the field of applied genomics. In this talk we will show that applications in BaseSpace can empower a new class of researcher to go from
sample to answer quickly, and can allow software developers to make their tools accessible to a vast and receptive audience.
1:10 Luncheon Presentation II: Sponsored by
The Empowered Genome Community: First Insights from Shareable Joint Interpretation of Personal Genomes for Research
Nathan Pearson, Ph.D. Principal Genome Scientist,
QIAGEN
Genome sequencing is becoming prevalent however understanding each genome requires comparing many genomes. We launched the Empowered Genome Community, consisting of people from programs such as the Personal Genome Project (PGP) and Illumina’s Understand Your Genome. Using Ingenuity Variant Analysis, members have identified proof of principle insights on a common complex disease (here,myopia) derived by open collaborative analysis of PGP genomes.
Pearson in REAL TIME
One Genome vs. population of Genomes
IF one Genome:
ancestry
family health
less about drug and mirrors
health is complex
CHallenges
1. mine genome
2. what all genome swill do for Humanity not what my genome can do for me
Track 4 Bioinformatics: Utilizing Massive Quantities of –omic Information across Research Initiatives @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Reporter: Aviva Lev-Ari, PhD, RN
Bioinformatics for Big Data
10:50 Chairperson’s Remarks
Les Mara, Founder, Databiology, Ltd.
11:00 Data Management Best Practices for Genomics Service Providers
Vas Vasiliadis, Director, Products, Computation Institute,
University of Chicago and Argonne National Laboratory
Genomics research teams in academia and industry are increasingly limited at all stages of their work by large and unwieldy datasets, poor integration between the computing facilities they use for analysis, and difficulty in sharing analysis results with their customers and collaborators. We will discuss issues with current approaches and describe emerging best practices for managing genomics data through its lifecycle.
Vas in REAL TIME
Computation Institute @ University of Chicago solutions to non profit entities, scale and make available in an affordable way “I have nothing to say on Big Data”, 57.7% survey by NAS, average time researcher spend on research, it will get worse, research data management morphed into better ways, industrial robust way, commercial start ups are role model. All functions of an enterprise now available as applications for small business.
Highly scaleable, invisible
high performance
In Genomics, tools – shipping hard drive new ways to develop research infrastructure:
dropbox, does not scale Amazon’s Webservices is the cloud
security in sharing across campuses, InCommon – cross domains sw access constrains are mitigated.
identity provision for multiple identity – identity Hub, one time association done, Group Hubs, i.e., ci connect – UChicago, access to systems at other campuses – connecting science to cycles of data, network not utilizied efficiently – tools not design for that, FTP, Firewalls are designed for data not Big data.
Science DMZ – carve realestate for Science data transfer, monitoring the transfer
11:30 NGS Analysis to Drug Discovery: Impact of High-Performance Computing in Life Sciences
Bhanu Rekepalli, Ph.D., Assistant Professor and Research Scientist, Joint Institute for Computational Sciences, The University of Tennessee, Oak Ridge National Laboratory
We are working with small-cluster-based applications most widely used by the scientific community on the world’s premier supercomputers. We incorporated these parallel applications into science gateways with user-friendly, web-based portals. Learn how the research at UTK-ORNL will help to bridge the gap between the rate of big data generation in life sciences and the speed and ease at which biologists and pharmacists can study this data.
Bhanu in REAL TIME
Cost per Genome does down, 2011 from $100,000 to $1,000
Solutions:
architecture
parallel informatics
SW modules
web-based gateway
XSEDE.org sponsured by NSF at all sponsored research by NSF
LCF – applications: Astrophysics, Bioinfo, CFD, highly scalable wrappers for the analysis Blast scaling results in Biology
Next generation super computers: Xeon/Phi
NICS Informatics Science gateway – PoPLAR Portal for Parallel Scaling Life Sciences Applications & Research
automated workflows
Smithsonian Institute, generate genomes fro all life entities in the universe: BGI
Titan Genomic Data analysis – Everglade ecosystem, sequenced
Univ S. Carolina great computing infrastructure
Super computer: KRAKEN
5-10 proteins modeling on supercomputers for novel drug discovery
Vascular Tree system for Heart transplant – visualization and modeling
12:00 pm The Future of Biobank Informatics
Bruce Pharr, Vice President, Product Marketing, Laboratory Systems, Remedy Informatics
As biobanks become increasingly essential to basic, translational, and clinical research for genetic studies and personalized medicine, biobank informatics must address areas from biospecimen tracking, privacy protection, and quality management to pre-analytical and clinical collection/identification of study data elements. This presentation will examine specific requirements for third-generation biobanks and how biobank informatics will meet those requirements.
Bruce Pharr in REAL TIME
Flexible Standartization
BioBank use of informatics in the1980s – bio specimens. 1999 RAND research 307 M biospecimens in US biobanks growing at 20M per year.
2nd – Gen Bioband
2005 – 3rd-Gen Biobanks – 15000 studies on Cancer, biospecimen, Consent of donors is a must.
Registries set up the storage: administrator dashboard vs user bashboard
2. Interoperability
3. Quality analysis
4. Informed Consent
12:15 Learn How YarcData’s Graph Analytics Appliance Makes It Easy to Use Big Data in Life Sciences
Ted Slater, Senior Solutions Architect, Life Sciences, YarcData, a division of Cray
YarcData, a division of Cray, offers high performance solutions for big data graph analytics at scale, finally giving researchers the power to leverage all the data they need to stratify patients, discover new drug targets, accelerate NGS analysis, predict biomarkers, and better understand diseases and their treatments.
12:40 Luncheon Presentation I
The Role of Portals for Managing Biostatistics Projects at a CRO
Les Jordan, Director, Life Sciences IT Consulting, Quintiles
This session will focus on how portals and other tools are used within Quintiles and at other pharmas to manage projects within the biostatistics department.
1:10 Luncheon Presentation II (Sponsorship Opportunity Available) or Lunch on Your Own
1:50 Chairperson’s Remarks
Michael Liebman, Ph.D., Managing Director, IPQ Analytics, LLC
Sabrina Molinaro, Ph.D., Head of Epidemiology, Institute of ClinicalPhysiology, National Research Council –
CNR Italy
1:55 Integration of Multi-Omic Data Using Linked Data Technologies
Aleksandar Milosavljevic, Ph.D., Professor, Human Genetics; Co-Director,
Program in Structural & Computational Biology and Molecular Biophysics;
Co-Director, Computational and Integrative Biomedical Research Center,
Baylor College of Medicine
By virtue of programmatic interoperability (uniform REST APIs), Genboree servers enable virtual integration of multi-omic data that is distributed across multiple physical locations. Linked Data technologies of the Semantic Web provide an additional “logical” layer of integration by enabling distributed queries across the distributed data and by bringing multi-omic data into the context of pathways and other background knowledge required for data interpretation.
2:25 Building Open Source Semantic Web-Based Biomedical Content Repositories to Facilitate and Speed Up Discovery and Research
Bhanu Bahl, Ph.D., Director, Clinical and Translational Science Centre,
Harvard Medical School
Douglas MacFadden, CIO, Harvard Catalyst at Harvard Medical School
Eagle-i open source network at Harvard provides a state-of-the-art informatics
AWARDS: Best of Show Awards, Best Practices Awards and 2014 Benjamin Franklin Award @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Reorter: Aviva Lev-Ari, PhD, RN
Best of Show Awards
The Best of Show Awards offer exhibitors an opportunity to distinguish their products from the competition. Judged by a team of leading industry experts and Bio-IT World editors, this award identifies exceptional innovation in technologies used by life science professionals today. Judging and the announcement of winners is conducted live in the Exhibit Hall. Winners will be announced on Wednesday, April 30 at 5:30pm. The deadline for product submissions is February 21, 2014. To learn more about this program, contact Ryan Kirrane at 781-972-1354 or email rkirrane@healthtech.com.
2014 WINNER(s) are announced in Real Time
2014 – Five categories
1. Clinical ad Health IT – Astazeneca with Tessella – Real Time Analytics for Clinical Trial (RTACT) – engine for innovations
2. Research and Drug Discovery: U-bioPRED with the TranSMART Foundation – Open Source – Emperial College – Biomarkers for Asthma, hospitals, 340 universities, 34 Pharmas
3. Informatics: Pistoia Alliance – HELM – Pfizer, released data for HELM Project
4. Knowledge Management Finalists: GENENTECH – Genentech Cell Line Resource
5. IT Infrastructure/HPC Winner:
Baylor College of Medicine with DNAnexus –
2014 Judges’Prize – UK for Patient Data Intgration
2014 Editors’ Choice Award: Mount Sinai – Rethinking Type 2 Diabetes through Data Informatics
2014 Benjamin Franklin Award
The Benjamin Franklin Award for Open Access in the Life Sciences is a humanitarian/bioethics award presented annually by the Bioinformatics Organization to an individual who has, in his or her practice, promoted free and open access to the materials and methods used in the life sciences. Nominations are now being accepted!
The winner will be announced in the Ampitheater at 9:00am on Wednesday, April 30 during the Plenary Keynote and Awards Program, WEDNESDAY, APRIL 30 | 8:00 – 9:45 AM.
1960 – Early structure of proteins: Myoglobin, hemoglobin
1970
1980
1990
2000 Ribosomes
2010s: macromolecule machines
Science of protein structure
Technology: electromicroscopy, Structure Genomics – data driven science Hybrid methods at Present for 3D structure identification
COMMUNITY ATTITUDE – 1971 PDB archive established at Cold Spring Harbor, Walter Hamilton, petition to have an Open DB of Protein, Brookhaven Labs, to be shared with UK, Nature New Biology: Seven Structures to the DB
1982 – AIDs epidemic – NIH – requested data to be Open, community set its own rules on data organization Fred Richards, Yale, requested on moral ground, DB to be Open.
1993 – mandatory to sahre dat linked to publication, no Journal will accet an article id data was not in PDB.
1996 – dictionary put together
2008: experimental data madatory to be put in PDB, Validation
2011: PDBx definition of X-Ray, NMR, and 3DEM, small-angle Scattering
Collaboration with to enable: self storage, structure based drug design
SCIENCE in ther IMPORTANT to be put there, IT evolved, changes to data
global organization collaboration
Communities to work together
L.D>Bernal – SOcial function of Science, 1939
Elenor Ostrom 2009 Nobel Prize in Economics – Community collaboration by rules
Best Practices Awards
Add value to your Conference & Expo attendance, sponsorship or exhibit package, and further heighten your visibility with the creative positioning offered as a Best Practices participant. Winners will be selected by a peer review expert panel in early 2014.
Bio-IT World will present the Awards in the Amphitheater at 9:30am on Wednesday, April 30 during the Plenary Keynote and Awards Program, WEDNESDAY, APRIL 30 | 8:00 – 9:45 AM
Early bird deadline (no fee) for entry is December 16, 2013 and final deadline (fee) for entry is February 10, 2014. Full details including previous winners and entry forms are available at Bio-ITWorldExpo.com.
Track 6 Systems Pharmacology: Pathways to Patient Response @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Aviva Lev-Ari, PhD, RN
April 30, 2014
Modeling: Novel Tools
10:50 Chairperson’s Remarks
Avi Ma’ayan, Ph.D., Associate Professor, Pharmacology and Systems
Therapeutics, Icahn School of Medicine at Mount Sinai
11:00 The Human Avatar: Quantitative Systems Pharmacology to Support Physician Decision Making in Neurology and Psychiatry
Hugo Geerts, Ph.D., MBA, BA, CSO, In Silico Biosciences;
Adjunct Associate Professor, Perelman School of Medicine, University of Pennsylvania
CNS Quantitative Systems Pharmacology uses computer-based mechanistic modeling integrating brain network neurophysiology, functional imaging of
genetics, pharmacology of drug-receptor interactions and parameterization with clinical data. A patient model (“human avatar”) can be developed
accounting for polypharmacy and life history of traumatic events to help identify optimal treatments.
11:30 VisANT: An Integrative Network Platform to Connect Genes, Drugs, Diseases and Therapies
Zhenjun Hu, Ph.D., Research Associate Professor, Center for Advanced Genomic Technology,
Bioinformatics Program, Boston University
With the rapid accumulation of our knowledge on diseases, disease-related genes and drug targets, network-based analysis plays an increasingly
important role in systems biology, systems pharmacology and translational science. The new release of VisANT aims to provide new functions to facilitate
the convenient network analysis of diseases, therapies, genes and drugs.
12:00 pm Selected Oral Poster Presentation: Individualized PK/PD Biosimulations for Precision Drug Dosing: Diabetes Mellitus
Clyde Phelix, Ph.D., Associate Professor, Biology,
University of Texas San Antonio
Individualized biosimulations offer many advantages to precision medicine. Using one’s transcriptome to determine parameters of kinetic models of metabolism reanimates that individual for in silico testing. The Transcriptome-To-Metabolome™ Model is multiorgan and multicompartmental, including over 30 primary and secondary metabolic pathways and transport processes. Thus pharmacokinetics/pharmacodynamics studies can be performed in silico before treating each patient.
12:40 Luncheon Presentations (Sponsorship Opportunities Available) or Lunch on Your Own
Modeling: Cancer
1:50 Chairperson’s Remarks
Hugo Geerts, Ph.D., MBA, BA, CSO, In Silico Biosciences; Adjunct Associate Professor, Perelman School of Medicine, University of Pennsylvania
In REAL TIME
»»1:55 FEATURED PRESENTATION
Identifying Drug Targets from Drug-Induced Changes in Genome-Wide mRNA Expression
Avi Ma’ayan, Ph.D., Associate Professor, Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai
We collected and organized publicly available genome-wide gene expression data where hundreds of drugs were used to treat mammalian cells and changes in expression were compared to a control. We then developed computational methods that try to find the drug targets from the expression changes. We show that different steps in the analysis can contribute to approaching the right answer.
In REAL TIME
System biology and drug related by phynotypes, drugs causes diseasespatient and side effects
Networs,
Gene-set Libraries stored in Gene Matrix Transpose(GMT) files, KEGG Example
Drug-set Libraries
Drug-Drug similarity data, SIDER 2 Side Effect Resource, FDA adverse effect Report data
Connactivity Map: Broad Institute, L1000 cell lines microarray, different drug dose, DRUG effect on GENES
develop new compondts,
measure toxicity
LINC-L1000 data overview, Drug-drug similarity structure, connversion
for Vector side effect
LINCS Canvas Browser
Cell-Line/Drug Browser
New method for clustering patient by outcomes, survival analysis
Drug interact with target drug vs transcription factors, over expression
Over expression of transcription factors vs knock out for validation
2:25 Infrastructure for Comparison of Systematically Generated Cancer Networks vs. Literature Models
Dexter Pratt, Project Director,
NDEx, Cytoscape Consortium
Cancer subtype genetic networks can be generated by systematic analysis of patient somatic mutation data. Comparison to existing models of cancer
mechanisms is an important step in investigating these data-derived models. Recent work on Network Based Stratification (NBS) at the Ideker Lab will be
described along with tools for network comparison under development in the NDEx project.
In REAL TIME
Network based classification, unsupervised methoods
Ovarian cancer- sparse mutations, no two patients share same mutation, clustering by expression profile – can be cause, gene – gene interaction, smooth knowlede,
Reference networks, Common Entity identification system used, started at UCSD. overlap of curated PATHWAYS, query, neighborhoods in the reference network,
Using mapping tables to mapp identifiers for entity correspondence
Complex Reference Networks N:1 and 1:N
Transcriptionalcontrol motif, extract motifs mapp data to motifs, concordence, and other metrics to be computed fromreferenced data,
PLENARY KEYNOTE PRESENTATIONS: TUESDAY, APRIL 29 | 4:00 – 5:00 PM @ BioIT World, April 29 – May 1, 2014 Seaport World Trade Center, Boston, MA
Reporter: Aviva Lev-Ari, PhD, RN
PLENARY KEYNOTE PRESENTATIONS:
TUESDAY, APRIL 29 | 4:00 – 5:00 PM
Keynote Introduction: Sponsored by Dave Wilson, Senior Director, Business Development Manager, Global Channels, Hitachi Data Systems
John Quackenbush, Ph.D.
CEO, GenoSpace; Professor, Dana-Farber
Cancer Institute and Harvard School of Public Health
John Quackenbush received his Ph.D. in 1990 in theoretical physics from UCLA working on string theory models. Following two years as a postdoctoral fellow in physics, Dr. Quackenbush applied for and received a Special Emphasis Research Career Award from the National Center for Human Genome Research to work on the Human Genome Project. He spent two years at the Salk Institute and two years at Stanford University working at the interface of genomics and computational biology. In 1997 he joined the faculty of The Institute for Genomic Research (TIGR) where his focus began to shift to understanding what was encoded within the human genome. Since joining the faculties of the Dana-Farber Cancer Institute and the Harvard School of Public Health in 2005, his work has focused on decoding and modeling the networks of interacting genes that drive disease. In 2011 he and partner Mick Correll launched GenoSpace to facilitate genomic data analysis and interpretation, focused on accelerating research and delivering relevant and actionable solutions for personalized medicine.
IN REAL TIME FROM THE AMPHITHEATER of World BioIT2014
Twitter
#BioIT14
2900 attendees 140 exhibitor, 250 Speakers, Best of Show Awart, Best Practices Award, Franklin Award, Memorial to Pat McGovern ex-CEO and Chairman of IDG and launcher of BioIT, McGovern Institute for Brain Research @MIT his gift $350 million, [Broad’s gift to MIT was $650million]
Hitachi Data Perspective
Cloud and Aanlytics
John Quackenbush about Precision Medicine
Desire to use an information ecosystem for mediicine
The DRIVER is DATA – access t data Data that drives innovations in BioMedical
IT –
Cloud Computing data, information and STORAGE of Data, data access, integration,
iPhone – applications for needs,
Bio – anniversary of DNA discovery structure in 1953
Genome Sequence – Transforming Medicine: Big Data: Volume, Velocity, Variety
Genomic Medicine – data for interpretation of Symptoms: diet, exercise
Cost of generation of data drops clinical relevance of data – sequencing now $1000 pay with credit card
Cost of the Analysis – $100,000 – Research number the genes translational, identify biomarkers to better achieve efficacy in segments of the population.
Diagnosis – Clinical Medicine
Reimbursement – few $ to identify VARIANCE relevant to treat disease
Cloud – secure the infrastructure – same dat looked by different parties to answer different questions.
GenoSpace for Research – N= many patients
GenoSpace for Clinical Care – N=1
GenoSpace for Patient Community – N=many individual patients
Patient CONSENT
Secure storage data
analytics and visualization
diverse data
share dat securely
data in transit to be secure, consumption of data
R&D Context
1000 Patients
50 Clinical site
large complex data
MMRF’s COMMPASS Study @Dana Farber – Multiple Myeloma Research Foundation
PORTAL design – to make data analysis of Cohort of Patioets, attribute analyzer, tools to find properties of cohort, compare across cohorts
Data analysis made easy – Precision Medicine based on Prediction
Population level data
end stage treatment
clincal trial
Translational Research – Pharma targets patients
MMRF – gateway to the Community, interface for Patients to provide information during the course of Treatment, PATIENTS share, 1000 patients signed up to share data
Patient Reported outcomes
data integration
clinical trial recruitment
biomarker discovery
HOW to deliver data to POINT of CARE: Cancer more data Clinical (Pathology/Lab)
BioPoetry: Story what the data analysis MEANS
CURATION OF DATA – GenoSpace – for Clinical Labs
Pathology Group: Sequencing
Application development for REPORTS: FullView – meta data GEnoSpace
Look at the assay for standard of Care
PDF format to scan and place in EMR, language suggestive,
MD’s Portal, giving access to Patients to add data
Thomson Reuter – Annotate
An OS for Precision Medicin
Genomics and integration with Clinical data
how to create system for all parties involved. Use of data for multiple needs that overlap
Information management – patient at the center
Precision Medicine is the FUTURE – Digital Architects for Precision Mediicne
2012pharmaceutical
Amandeep Kaur
Aashir Awan, Phd
Abhisar Anand
Adina Hazan
Alan F. Kaul, PharmD., MS, MBA, FCCP
alexcrystal6
anamikasarkar
apreconasia
aviralvatsa
David Orchard-Webb, PhD
danutdaagmailcom
Demet Sag, Ph.D., CRA, GCP
Daniel Menzin
Dror Nir
dsmolyar
Ethan Coomber
evelinacohn
Gail S Thornton
Irina Robu
jayzmit48
jdpmd
jshertok
kellyperlman
Ed Kislauskis
komal23ingle
larryhbern
Madison Davis
marzankhan
megbaker58
ofermar2020
Dr. Pati
pkandala
Rosalind Codrington, PhD
ritusaxena
Rick Mandahl
satwik Sunnam
sjwilliamspa
Srinivas Sriram
stuartlpbi
Dr. Sudipta Saha
tildabarliya
vaishnavee24
zraviv06
zs22