Draft agenda DAY 1

Transcription

Draft agenda DAY 1
Draft agenda
DAY 1
Wednesday, 08th October 2014
7.30
Registration & buffet breakfast in the exhibition area
Morning plenary
Big data strategy – turning theory into action and value for all stakeholders
Big data successes and failures to date; where would we like to be; how do we get
there?
9.00
Chair’s introduction
Payer, FDA and industry perspectives: Defining big data’s role in delivering the evidence
required by regulators and the marketplace
9.05
Keynote - pharma
Real world data science innovation - where in the product lifecycle will big data have
greatest impact, utility and value?
Impact on discovery, development, commercial, post-marketing
Are we asking the right questions of all the data?
Is the use of big data to prove or disprove a hypothesis ready for prime time?
Building a hierarchy of real world evidence – how will big data help us get there?
Roy D. Baynes MD, PhD, Senior Vice President Global Clinical Development, Merck
Research Laboratories
9.25
Keynote – pharma
Dr John Hubbard, Senior Vice President & Worldwide Head of Development Operations,
Pfizer
9.45
Keynote – public and private payer
How will big data be used to provide a more comprehensive body of real world evidence,
and better predictions of value and outcomes?
Invited Speaker:
Yasmine Winkler, Senior Vice President, Product and Innovation, United Health
10.20 Keynote – FDA
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Invited speaker:
Walter Harris, Chief Operating Officer, US Food and Drug Administration
10.40
Keynote panel discussion
Where should big data sit in the business? Who are the budget holders? How do you
measure the ROI? Who takes the risk? How to transform your company into a big datadriven organization?
Investing in infrastructure which is fit for purpose – the ‘elephant in the room’ for pharma
o What infrastructure is required to allow the capture, integration and end-to-end
flow of data throughout the pharma organization?
What skills are needed – at the domain level and the technical level? And how do you
integrate them?
Who is best positioned to interrogate the plethora of data and ask the right questions of it?
Accessing big data
o Build in-house? Or buy – from public domain? From commercial sources?
o How to enable ubiquitous access to data whilst maintaining intellectual property
and confidentiality, and meeting legal obligations?
Where is real world data science innovation being driven from?
Panellists:
Roy D. Baynes MD, PhD, Senior Vice President Global Clinical Development, Merck
Research Laboratories
Dr Tehseen Salimi, Vice President Global Medical Affairs, AstraZeneca
Dr Wolfgang Renz, Corporate Vice President Business Model & Healthcare Innovation,
Boehringer Ingelheim
Invited Panellists:
Dr John Leonard, Senior Vice President, Global Pharmaceutical Research & Development,
Abbott
Dr Stephen Eck, Vice President and Global Head of Oncology Medical Services, Astellas
Pharma
Dr Perry Nisen, Senior Vice President, Cancer Research, GlaxoSmithKline
Dr Dara Schuster, Medical Fellow, Eli Lilly and Company
Dr Philippe Bishop, Vice President, Clinical Development Angiogenesis Franchise Head,
Roche/Genentech
Dr Andreas Koester, Vice President, Clinical Trial Innovation & External Alliances, Janssen
Dr Jeffrey Kasher, Vice President, Global Clinical Trial: Materials, Implementation and
Transformation , Eli Lilly and Company
11.20
Morning coffee in the exhibition area
12.00
Data transparency, pooling and pre-competitive collaboration – what initiatives are
gaining momentum?
How will data pooling, collaboration and transparency be achieved – both within and
between organisations/companies?
What should be pre-competitive?
If randomised controlled trials data are top of the hierarchy of evidentiary ranking – how
to facilitate collaboration to release the true potential of big data?
Invited speaker:
Dr Perry Nisen, Senior Vice President, Cancer Research, GlaxoSmithKline
12.20
Questions & discussion
12.25
Reserved for sponsor
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12.45
Panel discussion
What role will big data play in the evolution of healthcare delivery over the next 5-10
years?
What does a healthcare consumer in 2020 look like? What kinds of information can
he/she access?
Will Big Data help drive greater public/private sector collaboration and pre-competitive
collaboration?
How might the value chain be impacted by the disintermediation and democratisation that
big data can unleash?
At which interfaces in the product value chain will it have greatest impact in the short and
long term?
How can/should we work with Google?
Panellists:
Dr Eric Perakslis, Executive Director, Harvard Medical School’s Countway Library of
Medicine and the HMS Centre for Biomedical Informatics
Brian Ellerman, Head, Technology Scouting and Information Science Innovation, Global
R&D Strategy, Science Policy & External Innovation (S&I), Sanofi
Invited panellists:
Dr Franam Jahanian, Assistant Director, Computer and Information Science Engineering
Directorate
Dr John Holdren, Assistant to the President for Science and Technology, Director, The White
House Office of Science Technology & Innovation
Dr John P.A. Ioannidis, Professor of Medicine, Professor of Health Research & Policy,
Stanford University School of Medicine
1.15
Buffet lunch in the exhibition area
Followed by your choice of 2 parallel
breakout sessions:
Focus session 1
Real world evidence – applying big data approaches throughout the
product lifecycle:
Early stage clinical trials
Case studies: reviewing the hypothesis, the methodology, the results, and the evidence that
big data provided
Themes for discussion include:
- Using big data to influence and enrich the pre-clinical discovery strategy and improve
translation
- Mining genomics / genetics data to help find appropriate surrogates for development
- Mining large biomarker / translational data sets from other trials
- Identifying enriched sub-populations to increase probability of success, decrease sample size
- Streamlining exclusion criteria and execution in trials
- Informing dose response in early phase development
- Can analytical modelling techniques replace the need for a particular assay, or placebo?
- How might big data impact the statistical power of your study? Can you be surer of your
decisions?
- Methodology and validation of emerging data sources into new clinically meaningful outcomes
and combined end points
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2.25
Chair’s introduction
2.30
Case study
Invited Speaker:
Dr Aris Baras, Director, R&D Initiatives, Regeneron Pharmaceuticals
2.50
Case study
Invited Speaker:
Joel Greshock, Head, Oncology Translational Medicine Informatics, Novartis
Joseph Heyse, Statistician, Merck
Deborah Manzo , Senior Director, Clinical Business Operations & Transformation,
AbbVie
3.10
Session reserved
3.30
Panel discussion
How does big data increase our potential to conduct early stage trials radically
differently?
Accelerating first-in-human studies: eg many small, parallel phase I studies with few
subjects with millions of data points generated per subject
In what circumstances might regulators accept in silico data to supplement and
complement clinical trials?
Using big data to help bring clinical trials to the point of care
Tracking the emergence of pragmatic clinical trials to leverage big data resources
How do we better gather and share data to understand drug and patient response failures?
4.05
Close of session, followed by afternoon tea in the exhibition area
Or
Focus session 2
Analytics strategy & toolbox - how do you turn big data into actionable
information that pharma leaders will base their decisions on?
2.25
Chair’s introduction
Big data horror stories- avoiding naïve statistical analysis
Do we have the methods and the expertise available to mine distributed data?
Invited Chair: Dr John P.A. Ioannidis, Professor of Medicine, Professor of Health Research
& Policy, Stanford University School of Medicine
Invited speakers for session:
Dr Brooks Fowler, Global Head of Data Sciences, Abbvie
Yaron Turpaz, Vice President, R&D IT, AstraZeneca
Preston Simons, Chief Information Officer, Abbott Laboratories
Dr John Acquavella, Executive Director, Global Epidemiology, Amgen, Inc
Dr Yvonne Zhou, Director, Health Intelligence & Analytics, Kaiser Permanente
2.40
Data analyst perspective:
What constitutes a meaningful data set?
How do you integrate experimental and non-experimental data sets?
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Methodologies for normalising , integrating, unifying and building big data sets from
disparate sources
What are the keys to quality control?
3.00
Case study:
Analytical strategy and interpretation in practice - making robust inferences
3.20
Case study
Making the right choice of bioinformatics platform
Integration and standardisation considerations issues - proprietary versus open source
platforms
Processing considerations – what to keep in-house? What to outsource?
Presentation reserved
3.40
Panel discussion: Clinical development perspectives
Confounding the analysis - how can you trust the answers you get?
How does the data analytics output match what is needed to make decisions?
How might big data analytics be used to support the formulation of hypotheses?
How might information sciences be closer aligned with biological and chemical sciences?
Brian Ellerman, Head, Technology Scouting and Information Science Innovation, Global
R&D Strategy, Science Policy & External Innovation (S&I), Sanofi
4.05
Close of session, followed by afternoon tea in the exhibition area
Then
Afternoon plenary
Which therapeutic areas ‘lend’ themselves more readily to big data
applications and how might others learn from those experiences?
4.45
Chairs Introduction
4.50
Oncology Keynote
Liberating the treasure trove of big data locked away in medical records and scientific
studies to improve cancer care
What are the realistic expectations for what big data might help us to achieve in the short
and long term?
How might clinical oncology data be collected to inform both diagnosis/treatment as well
as research?
What progress is being made with synthetic biology in cancer or biomarker sequencing in
cancer?
Dr Richard L. Schilsky, Chief Medical Officer (CMO), American Society of Clinical
Oncology (ASCO)
5.10
Panel discussion
Where is big data finding greatest traction and proving most valuable already?
What is the potential for big data to identify optimal treatment pathways, as well as
customize treatment at an individual patient level?
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If genes for one illness frequently predispose the individual to a second disease process
that we previously considered unrelated, what utility might big data may have in new
indications for a drug?
How might it help make drug development more affordable for chronic diseases, and for
the development of novel therapeutics?
Will big data turn imitation to innovation?
Therapeutic area heads discuss opportunities and reservations in:
o oncology
o rare diseases
o autoimmune diseases
o metabolic diseases
o vaccines & infectious diseases
Dr Duccio Medini, Global Head of Quantitative Biolog y, Novartis Vaccines Research
Dr Karen R. Segal, Senior Vice President, Diabetes & Metabolic Diseases, Mesoblast
Dr Symantha Melemed, Director, Oncology Patient Tailoring, Eli Lilly & Company
Invited panellists:
Dr Parvez Mulani, Vice President, Immunology, Oncology & Neurology, Abbvie
Dr Dietmar Berger, Senior Vice President, Global Clinical Development, Hematology &
Oncology, Genentech Inc
Dr Fouad Namouni, Vice President, Full Development Lead, Oncology, Bristol-Myers Squibb
Dr Hans-Juergen Woerle, Vice President, Head of Therapeutic Area- Metabolism,
Boehringer Ingelheim
Dr Carlo Russo, Senior Vice President, Head of Biopharm Development, GlaxoSmithKline
6.00
Close of day 1, followed by a cocktail reception in the exhibition area
DAY 2
Thursday, 9th October 2014
7.30
Registration & buffet breakfast in the exhibition area
Morning plenary
Important new data sources – what questions should budget holders ask to
determine quality, relevance and value?
9.00
Chair’s introduction
Electronic health / medical records (EHR/EMR) – international case studies
Advancing the use and reuse of EHR/EMR for R&D
Are they a good investment? How different are they from claims data? What does
‘granular’ mean in practice?
What are the systems to gain access? What are the time frames?
How might the data be used to reliably bring HER/EMR data into clinical trials and:
o inform the protocol feasibility process
o find partners faster
o find patients faster
o stop trials earlier
To what extent can you really rely on previously collected data to inform R&D? How can
you be confident you are comparing like with like?
9.05
EU – keynote address from NHS or IMI
Invited speaker: Dr Mark Davies, Medical Director, NHS Information Centre, NHS
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Phacilitate Big Data Leaders Forum, 8th-9th October 2014, Washington DC ; Draft agenda – strictly private & confidential © Phacilitate
Limited, 2014; For more information please contact Kim Evans on 02073847993 or [email protected]
9.25
USA
Dr Marc Berger, Vice President, Real World Data & Analytics, Pfizer
9.45
Session reserved for sponsor
10.05
Panel discussion
Tackling the policy and ethical issues that arise from accessing EHR/EMRs and other
new sources of big data
Consent
Privacy / patient anonymity
Ownership and transparency
IP protection
Invited panellists:
James Heywood, Co-Founder & Chairman, Patients Like Me
Dr Ellen Sigal, Chairperson & Founder, Friends of Cancer Research
Deborah Brooks, Co-Founder, The Michael J Fox Foundation for Parkinson’s Research
Robert Mcburney, President & CEO, Accelerated Cure Project for Multiple Sclerosis
10.40
Morning coffee in the exhibition area
Examining the quality, utility and value of emerging big data sources – how can they be
accessed and validated and will they provide evidence which can ultimately be applied to the
label?
11.20
Patient reported outcomes and social media
Invited speaker: Ryan Olohan, National Industry Director, Healthcare, Google
11.40
Real-time data generated by wearable devices – what role can they play?
Wearable devices – an overview
Detailed phenotyping for delivery of precision medicine
Real-time capture of safety signals
Dr Morten Sogaard, Executive Director & Head, Biotechnology & Precision Medicine
External R&D Innovation, Pfizer
12.00
Next generation imaging – applying pattern recognition to identify disease across
disparate datasets
Presentation Reserved
12.20
Panel discussion
Unification of data from multiple sources - how do we best approach the implementation
and management of the “big ideas”?
How do we engage in terms of standardizing data from these sources and employing
filters to ensure quality – at the macro or micro level? Across the industry or across the
organization?
How will big data work in the ‘personalized medicine’ paradigm?
o How to collect data from individuals, integrate it, and ultimately take it back
to the individual level? (Will it be cost-prohibitive to do this?)
Invited panellists:
Dr Brooks Fowler, Global Head of Data Sciences, Abbvie
Christopher Keenan, Director Governance, Bristol-Myers Squibb
Yaron Turpaz, Vice President, R&D IT, AstraZeneca
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Phacilitate Big Data Leaders Forum, 8th-9th October 2014, Washington DC ; Draft agenda – strictly private & confidential © Phacilitate
Limited, 2014; For more information please contact Kim Evans on 02073847993 or [email protected]
12.50
Buffet lunch in the exhibition area
Followed by your choice of 2 parallel
breakout sessions:
Focus session
Real world evidence – applying big data approaches throughout the
product lifecycle:
Late stage clinical trials
2.00
Chair’s introduction
Dr Jerald S. Schindler, Vice President, Biostatistics & Research Decision Sciences - Late
Development Statistics, Merck & Co, Inc
Case studies: reviewing the hypothesis, the methodology, the results, and the evidence that
big data provided
- Leveraging big data to:
- conduct definitive and large scale trials at low cost
- shorten time to validate biomarkers
- streamline exclusion criteria and execution in trials
- identify enriched sub-populations
- identify larger cohorts of patients faster
- help build reimbursement arguments in last stage development
- finding gaps in medical value and/or clinical relevance
- Building EHR/EMR and PRO data into phase II/III clinical trial design
- Accessing clinical trial failure data
- Can analytical modelling techniques or in silico trial simulations replace the need for a particular
assay, or placebo?
- How might big data impact the statistical power of your study? Can you be surer of your
decisions?
2.05
Case study
Invited speaker:
James Heywood, Co-Founder & Chairman, Patients Like Me
2.25
Case study
Invited speaker:
Dr George Komatsoulis, Deputy Director, Centre for Biomedical Informatics & Information
Technology, National Cancer Institute
2.45
Session reserved
3.05
Panel discussion
How does big data increase our potential to conduct late stage trials radically
differently?
How do we better gather and share data to understand drug and patient response failures?
In what circumstances might regulators accept in silico data to supplement and
complement clinical trials?
Using big data to facilitate patient recruitment
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Phacilitate Big Data Leaders Forum, 8th-9th October 2014, Washington DC ; Draft agenda – strictly private & confidential © Phacilitate
Limited, 2014; For more information please contact Kim Evans on 02073847993 or [email protected]
Using big data to help bring clinical trials to the point of care
How / when might wearable devices be used to feed data into last stage trials – and with
what impact on precision and cost?
Tracking the emergence of pragmatic clinical trials to leverage big data resources
Can you turn an observational trial into a clinical trial?
Panellist:
Dr Nariman Nasser, Digital Strategist, Genentech
3.35
Close of session, followed by afternoon tea in the exhibition area
Or
Workshop
How can biotechs and SMEs participate in the big data revolution?
2.00
Moderator’s introduction
Invited Moderator: Dr Aris Baras, Director, R&D Initiatives, Regeneron Pharmaceuticals
2.05
What specific advantages might big data offer smaller companies? How do you weigh up
the risks and benefits of investment?
Will big data and real world evidence reduce the cost of entry for novel therapies so that
biotech can participate?
Can it help where ‘breakthrough status’ has not yet delivered?
Dr Carlos F. Santos, CEO, Biovest International
2.25
Case study
Operationalising big data in a small company
Who is responsible and how are resources managed?
How much can you do in-house?
What questions do you want the data to answer?
Buying in data? How to minimise the risks
Donna Rill, Chief Development Officer, Opexa Therapeutics, Inc
2.45
Case study
Finding an optimum bioinformatics programme for your business
Presentation reserved
3.05
Panel discussion
How can you maximise the value of your core asset? Demonstrating to your investors
that all possible effort is going into your data strategy
Panellist:
Dr Karen R. Segal, Senior Vice President, Diabetes & Metabolic Diseases, Mesoblast
3.35
Close of session, followed by afternoon tea in the exhibition area
Then
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Phacilitate Big Data Leaders Forum, 8th-9th October 2014, Washington DC ; Draft agenda – strictly private & confidential © Phacilitate
Limited, 2014; For more information please contact Kim Evans on 02073847993 or [email protected]
Afternoon plenary
Real world evidence – applying big data approaches throughout the
product lifecycle:
Building better benefit:risk profiles to strengthen lifecycle management
4.00
Chair's introduction
4.05
How might big data increase our potential to conduct phase IV post marketing
surveillance radically differently? How might big data reduce the scale and cost of
pharmacovigilence?
Using observational / real world evidence:
 instead of, or as a complement to post approval commitments
 for early detection of safety signals in your, and your competitors’, products
 for compliance - to ensure that products are used in the right patients and taken
properly
Ensuring against duplicate safety reports so we do not create a skewed safety or efficacy
profile
Will big data mean we monitor post marketing efficacy as well as safety?
Dr Shailja Dixit, Executive Director, HEOR, Forest Laboratories
4.25
Panel discussion:
Using real world evidence for indication expansion and repurposing
Comparative effectiveness registry trials to compare prevailing standards of care in real
world populations
Embedding large simple trials in the delivery of care
Hypothesis generation through observational data: if a drug has sufficient activity and the
data are persuasive, these observations could be incorporated in an sNDA/sBLA
Studying outcomes in special populations not typically included in clinical trials, e.g., the
elderly and patients with organ dysfunction
Identification of further segments of the population for study
How can big data provide assurance to payers that its worth treating certain diseases early
on and at every phase in the continuum of the disease
Panellists:
Dean Hakanson, MD, Vice President & Head of Health Economic and Outcome Research,
US Medical and Drug Regulatory Affairs, Novartis
Dr Marc Berger, Vice President, Real World Data & Analytics, Pfizer
Invited panellists:
Dr John Graham, Executive Director, Lead US Health Economics and Outcomes Research,
Bristol Myers-Squibb
Brian Cuffel, Vice President, Global Health Economics Outcomes Research, Speciality
Medicines, Bayer Healthcare
Dr Susan Shiff, Vice President, Global Outcomes Research and Health Economics and
Evidence Based Medicine, Teva Pharmaceuticals
Jorge Arellano, Director, Global Health Economics, Amgen
David Macarios, Vice President Health Economics and Outcomes Research, LifeCell
Corporation
5.00
Close of conference
10
Phacilitate Big Data Leaders Forum, 8th-9th October 2014, Washington DC ; Draft agenda – strictly private & confidential © Phacilitate
Limited, 2014; For more information please contact Kim Evans on 02073847993 or [email protected]
11
Phacilitate Big Data Leaders Forum, 8th-9th October 2014, Washington DC ; Draft agenda – strictly private & confidential © Phacilitate
Limited, 2014; For more information please contact Kim Evans on 02073847993 or [email protected]