Cambridge Healthtech Institute's Inaugural

Artificial Intelligence and Machine Learning in Clinical Research:
( 臨床研究の分野における人工知能 )
 

AI, ML, ROBOTICS, ADVANCED ANALYTICS, BIG DATA
人工知能、機械学習、ロボット工学、先進的な分析法、ビッグデータ

2018年2月14-15日 | Hyatt Regency Orlando | フロリダ州オーランド

 

今回新たに加わる臨床研究の分野における人工知能をテーマにしたこのカンファレンスプログラムでは、これらの新たなアプローチを臨床試験に導入する取り組みを加速させるための方策などが話し合われます。

 

Wednesday, February 14

11:30 am Registration Open

12:10 pm Bridging Luncheon Presentation: Centralizing Data to Address Imperatives in Clinical Development

Karim Damji, Senior Vice President, Products, Solutions & Marketing, Saama Technologies

With the deluge of structured, unstructured, and syndicated data, the use of varied data for targeted outcomes remains difficult, despite increased industry efforts to address the issue. New technologies are federating the ability to leverage analytic-ready data for innovations in clinical development and drug commercialization. With the application of clinical data-as-a-service and meta-data core, centralized clinical data lakes have the power to improve data quality, evidence generation, and time-to-insights.

12:50 Coffee and Dessert Break in the Exhibit Hall

1:30 Plenary Keynotes

3:00 Valentine’s Day Celebration in the Exhibit Hall, Last Chance for Exhibit Viewing

BLOCKCHAIN, ML, AI

4:00 Chairperson’s Remarks

Balazs Flink, M.D., Clinical Trial Analytics Lead, R&D Business Insights and Analytics, Bristol-Myers Squibb

4:05 Blockchain Disruption: How Blockchain Will Change Our Industry

Munther_BaaraMunther Baara, Senior Director, Development Business Technology, Pfizer

Imagine a solution that makes it easy to aggregate health data in a secure, trusted, automated, and error-free way, a solution which enforces rules, privacy, and regulations in a mutually agreed upon manner, resulting in a smart-contract between patient and healthcare stakeholders. This enables patients to aggregate their data from diverse health sources and share what they choose to with their physicians and researchers. All this puts the patient in control of their health and well-being, rather than being along for the ride: How it works, key benefits, empowering the patients with control over their data.

4:30 Exploration of Where Machine Learning Will Help in the Product Development Process in the Pharmaceutical Industry

Francis_KendallFrancis Kendall, Technology Evaluation and Implementation Leader, Product Development, Roche

The talk will explore how Machine Learning is and will change how Product Development is carried out in the industry from improving efficiencies, gaining more insights on products, improved surveillance of products, especially safety, and its use in IoT devices.

4:55 Leveraging Digital Transformation to Unify Data and Process and Boost Clinical Operations

Evi Cohen, Vice President, Global Pharma & Life Sciences, Appian

Conducting and managing a successful, safe clinical trial is complicated. With massive data and complex processes at the core, it’s no surprise innovation in Business Process Management (BPM) is behind many successful trials.

5:25 Intelligent Clinical Trial Design, Planning and Conduct

Balazs_FinkBalazs Flink, M.D., Clinical Trial Analytics Lead, R&D Business Insights and Analytics, Bristol-Myers Squibb

As technology evolves and AI solutions become more sophisticated, there is a natural demand to test and apply them in areas that were traditionally expert opinion-guided. This presentation is about early experiences and challenges of pharma companies - including BMS - that are starting to apply AI in the R&D space to promote precision oncology, identify targets, design and plan trials and translate strategy to efficient operational execution.

5:50 Close of Day

5:50-7:00 pm Track Reception (Sponsorship Opportunity Available)

Thursday, February 15

7:15 am Registration Open

Accenture7:45 Breakfast Presentation to be Announced


AI AND ML IN CLINICAL TRIALS

8:30 Chairperson’s Remarks

Vikram Gupta, Technology Innovation Senior Manager, Amgen

8:35 CO-PRESENTATION: AI and Machine Learning for Clinical Trials

Vikram Gupta, Technology Innovation Senior Manager, Amgen

William Wong, Technology Strategy, Innovation Senior Manager, Amgen

While technology will probably never completely replace HCPs, machine intelligence (Machine Learning, Natural Language Processing (NLP), and Artificial Intelligence (AI)) is transforming healthcare by improving outcomes and changing the way healthcare professionals think about providing care and manage clinical trials.

9:25 Clinical Trials Innovations in the Age of Big Data and Advanced Analytics

Kaushik_RahaKaushik Raha, Ph.D., Associate Director, Head, Emerging Analytics and Advanced Visualizations, Data Sciences Pharma IT, Janssen Pharmaceuticals

This talk will share advanced analytics approaches in clinical research. Examples and case studies will be shared to demonstrate some strategic points and approaches.

9:50 Sponsored Presentation (Opportunity Available)  

10:15 Networking Coffee Break

NATURAL LANGUAGE PROCESSING AND SEMI AUTOMATED CSR NARRATIVES

10:30 Chairperson’s Remarks

Xia Wang, Director, Health Informatics, Global Medicines Development Unit, R&D, AstraZeneca

10:35 CO-PRESENTATION: The Application of Natural Language Processing (NLP) to Explore the Understanding of Patient Treatment Journey in Diabetes

Xia_WangXia Wang, Director, Health Informatics, Global Medicines Development Unit, R&D, AstraZeneca


Gerry_PetratosGerry Petratos, CEO, Hiteks Solutions, Inc.

This talk relates a pilot work at AstraZeneca in utilizing Natural Language Processing (NLP) technology to explore the understanding of treatment journeys of newly diagnosed type 2 diabetes patients, by retrieving structured data from Diabetes Practice Guidelines & clinical documentation to identify events of interest and compare cohorts. This pilot provided benchmarking understanding of NLP technology to retrieve meaningful information from unstructured Electrical Health Record (EHR) data sources. The outcomes of discreet treatment pathways from SoC guidelines revealed important insights of the complexity involved in treating diabetes patients.

11:00 Semi Automated CSR Narratives

Avanti_KarandikarAvanti Karandikar, Senior Manager, Clinical Business & System Analysis RDIS, MedImmune (AstraZeneca Biologics)

This presentation will include topics such as: Create quality CSR narratives that are consistent across a therapeutic area and/or compound, scope, save time and effort on behalf of the author, reduction in cost associated with (e.g. costs associated with service providers) writing narratives from scratch, create narratives based on a template with specifics to protocol and/or compound, allow for collected data points to be pre-populated to avoid mistakes in study day calculations, event onset/resolution dates, etc.

11:25 Brief Session Break

11:35 AI - Machine Learning for Clinical Data Management, a Pilot Case Study

Abhay_JhaAbhay Jha, Principal, Business Technology Lead, R&D Excellence Practice, ZS Associates

Machine Learning can aid Clinical Data Management with smart and early detection of anomalies in patient data from sites, thereby reducing the need to unlock databases frozen for submission. To explore this hypothesis, ZS used univariate and multivariate analytics and fraud detection techniques to identifying anomalies that slip through the standard data quality checks. In this session we will share our case study results including lessons learned and future plans

12:00 pm PANEL DISCUSSION: How to Make All the Data Machine Learnable?

Moderator: Munther Baara, Senior Director, Development Business Technology, Pfizer

Panelists: Kaushik Raha, Ph.D., Associate Director, Head, Emerging Analytics and Advanced Visualizations, Data Sciences Pharma IT, Janssen Pharmaceuticals

Vikram Gupta, Technology Innovation Senior Manager, Amgen

William Wong, Technology Strategy, Innovation Senior Manager, Amgen

Francis Kendall, Technology Evaluation and Implementation Leader, Product Development, Roche

Balazs Flink, M.D., Clinical Trial Analytics Lead, R&D Business Insights and Analytics, Bristol-Myers Squibb

  • Leveraging data for machine learning projects
  • Implementing robust data standards
  • Analyzing big data using machine learning algorithms

12:50 PANEL DISCUSSION: Why Are There Barriers to the Adoption of Innovative Processes and Technologies at Sites?

Moderator: Jim Kremidas, Executive Director, Association of Clinical Research Professionals (ACRP)

Panelists: David Vulcano, Assistant Vice President & Responsible Executive for Clinical Research, Hospital Corporation of America (HCA)

Sean Walsh, MBA, CDO, Raleigh Neurology Associates

Beth Harper, MBA, Workforce Innovation Officer, Association of Clinical Research Professionals (ACRP)

Many innovative technologies and process improvement initiatives are coming out at a rapid pace, whether from TransCelerate and other industry consortia, or from technology companies themselves. Which of these improvements actually work? How can sites implement these more effectively? Why are there barriers to adoption and how can the innovators better understand sites’ needs?

  • Share sites’ perspective on the evolving clinical research landscape
  • Discuss the reasons sites struggle with new processes and technology tools
  • Determine ways to facilitate adoption

1:15 Closing Remarks

1:20 SCOPE Summit 2018 Adjourns

Melissa DolenGroup Discounts Are Available! Special rates are available for multiple attendees from the same organization. For more information on group discounts, contact us.


 

2018 SCOPE Conference at a Glance


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In Memory of Gerald "Jerry" Matczak
Matczak Jerry

Gerald "Jerry" Matczak, lead consultant in clinical innovation at Eli Lilly & Co., was a rare breed in the pharmaceutical world, someone who not only embraced social media, but also listened to activist patients. He has been a part of the SCOPE conference since its inception and won the Patient Engagement Award on Wednesday, the day before his passing. Matczak died suddenly on Feb. 2 at age 54. We will all miss him.

- Cambridge Healthtech Institute (CHI)



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