February 1-2 , 2017

San Francisco

 

Day One
Wednesday February 1, 2017

Day Two
Thursday February 2, 2017

08:00
Registration

08:50
Chairman’s Opening Remarks

Data Science in Clinical Drug Development – Big Data & Advanced Analytics

09:00
Keynote Panel: The Rising of Data Science – Understanding the Ground-Breaking Changes Behind Clinical Research

Synopsis

  • Evaluating the power of data science in revolutionizing clinical trials
  • Assessing the new era of Precision Medicine – what leads and defines the strategy in pharmaceutical companies in the ever-growing data-driven clinical R&D
  • Driving innovation in the clinical research phase of drug development: From new data sources, to new analytic tools and capabilities – what to look out for
  • Discovering the potential of data analysis in the development of new trial designs

09:45
Keynote Case Study: Making Use of Data & Data Science to Boost Clinical R&D

Synopsis

  • Understanding Clinical Data Science – the different angles around the impact of data analytics in the clinical research environment
  • Uncovering the use of genomic data to find and validate biomarkers when no pre-clinical data is available – making use of data sets from various sources to enable better patient monitoring
  • Evaluating the data-driven initiative at Roche to expand existing adult patient drugs to pediatric cancer care – assessing the population and developing new algorithms to analyze data
  • Using smartphone data and wearables as digital biomarkers and predicting patient phenotypes

10:15
Morning Refreshments & Speed Networking

Synopsis

Meet your peers in this structured and interactive networking session designed to ensure you make the most new connections possible in the early stages of the conference. Bring plenty of business cards!

11:00
Panel Discussion: Big data in Clinical Trials – Leveraging Data to Retrieve Meaningful Action

  • Ankit Lodha Analytics Operations Lead in Clinical Systems & Analytical Reporting (CSAR), Amgen
  • David S. Reasner, PhD. Vice President, Data Science & Head, Study Endpoints, Ironwood Pharmaceuticals
  • Ray Liu, PhD. Senior Director & Head of Statistical Innovation & Consultation, Takeda Pharmaceuticals Inc.

Synopsis

  • Making use of data sets – why is only a small fraction of data being used?
  • Harnessing the full potential of clinical data – what are the possibilities and how to leverage that?
  • Addressing the major technical challenges – the role of selection, standardization, cleaning/filtering, processing and analysis
  • Tackling the major cultural challenges – changing the industry’s mindset to embrace and understand data innovation

11:45
Joint Analysis – Statistical Innovation to Maximize the Insights from Big Data Integration

  • Ray Liu, PhD. Senior Director & Head of Statistical Innovation & Consultation, Takeda Pharmaceuticals Inc.

Synopsis

  • Big data integration presents new challenges and opportunities for data scientists
  • Appropriate joint analysis increases power and generates novel insights on integrated data
  • Exploring case studies on various joint analysis frameworks and their utilities

12:15
Flash Talk

12:25
Lunch & Networking

13:25
Clinical Analytics – Next Generation of Predictive and Prescriptive Dashboards for Clinical Trials

  • Ankit Lodha Analytics Operations Lead in Clinical Systems & Analytical Reporting (CSAR), Amgen

Synopsis

  • Defining Clinical Analytics – understanding the capabilities and usefulness of insights in the clinical development program
  • Developing metrics for big data analysis in clinical trials – handling industry best practice and company specific metrics
  • Mining different layers of data – the challenges of clinical data analysis and visualization for stakeholders
  • Harmonizing data – how to combine multiple data sets
  • Case studies on how to uncover unmet needs, spot growth opportunities, inform trial design, and competitive differentiation using Advanced Analytics

13:55
The Multi-Omics & AI Approach – Incorporating Data-Driven Actionable Insights Into Drug Development

Synopsis

  • Harnessing high throughput proteomics, lipidomics and metabolomics for biomarker identification and drug response prediction – implementing patient stratification
  • Applying AI algorithms and analytical tools to structure, process and analyze different types of data from trial screenings (clinical, biological, demographics and outcomes data)
  • Delivering data in a way that actionable measures can be taken by high management – properly communicating results
  • Housing omics, analytics and R&D under the same roof – the competitive advantage of inter-team collaboration

The Current Challenges in Clinical Data Management

14:25
Panel Discussion: The Paradigm Shift of Clinical Data Management – From Support to Driver in Clinical R&D

  • David Moriarty, PhD. Vice President, Clinical Operations, Data Management & Strategic Outsourcing, Jazz Pharmaceuticals
  • Elizabeth Cheney Director & Head of Clinical Data Management & Programming, Karyopharm Therapeutics Inc.
  • Rajneesh Patil Senior Director, Clinical Development, Quintiles

Synopsis

  • Analyzing the new emergence of Clinical Data Management – both a practical and cultural shift
  • Marrying centralized monitoring and traditional data management – looking into the future of a increasingly technical role
  • Exploring new Clinical Data Management skills – data visualization and data analytics
  • The evolution of risk-base monitoring – data quality, data integrity and completeness of data
  • Ensuring a Data Governance Structure

15:10
Advanced & Predictive Analytics – Implementation aspects in Risk Based Monitoring

Synopsis

  • Identifying and developing analytics methodologies for clinical trial conduct – case studies for advanced analytics
  • Implementing the right analytics strategies for Risk Based Monitoring – an approach to implementable analytics
  • Novel Predictive Analytics capabilities providing new levels of insights for study monitoring
  • Advancing the use of data sciences in managing site risks, subject safety risks and study level trends

15:40
Afternoon Refreshments & Networking

16:10
Data Management Strategies For EHR-Based Multi-Center Clinical Trials

  • Brian J. McCourt Director, Clinical Research Informatics, Duke Clinical Research Institute

Synopsis

  • Understanding the context and opportunity for utilizing EHR’s in large-scale clinical trials
  • Reviewing operational models and data management methods for aggregation of EHR data – exploring case-studies of successful implementation
  • Sharing considerations for the data management practices necessary to successfully support an EHR-based trial

16:40
Implementing & Running Data-Driven Trial Management – A Case-Study

  • David Moriarty, PhD. Vice President, Clinical Operations, Data Management & Strategic Outsourcing, Jazz Pharmaceuticals

Synopsis

  • Linking together Data Management and Clinical Operations – why Jazz Pharmaceuticals is getting these functions to collaborate increasingly closer
  • Periodic reviewing of trial data – guiding trial management professionals by data sources
  • The challenges and benefits retrieved from the data-driven approach to trial management
  • Independence of Analytics Platforms from the CROs.

17:10
Data Management – The Central Piece Between the Clinical Perspective & Analytics

  • Elizabeth Cheney Director & Head of Clinical Data Management & Programming, Karyopharm Therapeutics Inc.

Synopsis

  • Making sure data management strategy and methodologies are at par with industry standards
  • Assessing the need to bring clinical people on board with data management requirements and standards at the planning stage
  • Ensuring the correct delivering and process of data for analytics – bringing clinical programming in line with the data management strategy

17:40
Chairman’s Closing Remarks