Cambridge Healthtech Institute’s 2nd Annual

Artificial Intelligence in Clinical Research

Machine Learning, Robotics, Advanced Analytics and More

February 20-21, 2019


Artificial intelligence (AI) and machine learning (ML) have propelled many industries toward a new, highly functional and powerful state. Now they are starting to make their way into the clinical research realm. Many pharmaceutical companies and larger CROs are starting projects involving some elements of AI, ML and robotic process automation in clinical trials. To facilitate the discussion and to accelerate the adoption of these approaches in clinical trials, Cambridge Healthtech Institute presents the 2nd Annual “Artificial Intelligence in Clinical Research” conference, part of 10th Annual SCOPE Summit.

Final Agenda

Arrive early and attend Part 1 (Tues-Wed): Clinical Data Strategy and Analytics

Wednesday, February 20

11:30 am Registration Open

Saama-Technologies 12:30 pm BRIDGING LUNCHEON PRESENTATION: Practical Applications of Natural Language Processing

Malaikannan Sankarasubbu, Vice President, AI Research, Saama Technologies

1:10 Coffee and Dessert Break in the Exhibit Hall

2:10 Plenary Keynotes

3:20 Booth Crawl & Refreshment Break in the Exhibit Hall, Last Chance for Exhibit Viewing

AI TO SUPPORT CLINICAL TRIAL DECISION MAKING

4:05 Chairperson’s Remarks

Balazs Flink, MD, Head, Clinical Trial Analytics, Bristol-Myers Squibb

4:10 The Dos and Don’ts of AI in Clinical Trial Planning and Execution

Balazs_FlinkBalazs Flink, MD, Head, Clinical Trial Analytics, Bristol-Myers Squibb

In the past years, BMS dedicated tremendous efforts to explore and implement novel analytics solutions to advance drug development and deliver innovative products that show unprecedented features. During these projects, we have gained experiences with AI solutions and this presentation will discuss our early findings with concrete use cases.


4:40 Machine Learning – Influencing the Clinical Evidence Paradigm

Kendall_FrancisFrancis Kendall, Director, Biostatistics & Programming, Cytel, Inc.

This talk will examine the factors why machine learning techniques are getting traction in the life science industry, which include what machine learning approaches are useful in life sciences, new data dynamics e.g. ownership, new emerging data sources and easier access to data sources which can give greater insight into products and new diagnostics/evaluation techniques. It will also include what the future of clinical evidence may look like for regulators.

5:10 Presentation to be Announced

5:40 How AI Will Change Clinical Trial Decision-Making and the Way We Monitor and Diagnose Patients

Dorenbos_ROnaldRonald Dorenbos, PhD, Associate Director, Materials and Innovation, Takeda Pharmaceuticals

The presentation will highlight some of the ways in which AI will assist in the decision-making process for clinical trials. Some of the leading companies in the field are used to illustrate how AI, for example with the help of natural language processing, can improve trial protocols, design, and execution and how AI provides novel ways to monitor and diagnose patients using digital technology.

6:107:10 Networking Reception (Sponsorship Opportunity Available) or Close of Day

Thursday, February 21

7:15 am Registration Open

7:45 BREAKFAST PRESENTATION (Sponsorship Opportunity Available) or Morning Coffee

8:15 Session Break

CASE STUDIES

8:20 Chairperson’s Remarks

Chairperson to be Announced

8:25 Intelligent Automation Opportunities in Pharmacovigilance

Xue_SonglinSonglin Xue, MD, PhD, Executive Vice President, Global Head, Pharmacovigilance, Astellas

Given the wide variety of global regulatory requirements, managing the volume, variety and velocity of Pharmacovigilance data presents a significant challenge. Operations that are repetitive in nature and of relatively low business value are ripe for automation to gain efficiencies and reduce costs. TransCelerate’s newest Intelligent Automation initiative focuses on identifying how intelligent automation technologies can be used to better support execution of Pharmacovigilance activities/processes. By conducting an impact assessment and working with global health authorities to verify risks/issues with their use, this initiative will provide guidance, as appropriate, on applications of new technology in Pharmacovigilance practice.

8:55 From Real World Data Hype to AI Hype

Bartels_DorotheeDorothee Bartels, PhD, Chief Digital Science Officer BI X GmbH, Boehringer Ingelheim

The real world data (RWD) hype caused high expectations, including how RCTs might only play a minor role in future drug development. RWD help to define target populations, and are key for drug utilization, safety and effectiveness studies. They are complementary to RCTs but cannot replace them. The same is true for artificial intelligence: AI is a tool applicable in different stages of drug development, supporting RCTs as well as RWD studies to generate evidence.

9:25 Using Machine Learning to Analyze Clinical Trials that Fail to Meet Primary Endpoints

Grullon_SeanSean Grullon, PhD, Machine Learning Data Scientist, Data Centre of Excellence, GSK

Factors that cause clinical trials to fail their primary endpoints can be difficult to uncover with traditional statistical methods. Modern machine learning techniques can discover features which cause the primary endpoints to fail in historical clinical trial data. Insights on features that drive primary endpoint failure can be used to inform better clinical trial study design in the future.

SaamaTechnologies 9:55 Portfolio Risk Mitigation

Gulwadi_Amit_CAIAmit Gulwadi, Senior Vice President, Clinical Innovations, Saama Technologies

10:25 Networking Coffee Break (Sponsorship Opportunity Available)

RPA IN CLINICAL TRIALS

11:10 Chairperson’s Remarks

Chairperson to be Announced

11:15 The Use of RPA (Robotic Process Automation) within Data Management at Novartis

Clark_SarahSarah Clark, BSc, Stats and Computing, Global Head, Data Management, Novartis

As the digital age progresses, how are companies using technology to increase throughput and reduce/eliminate monotonous tasks? What processes can be automated and what are the benefits from a time and cost perspective and employee retention perspective? This presentation will examine the use of RPA within Data Operations at Novartis.

11:45 Presentation to be Announced

12:15 pm Transition to Shared Sessions

BLOCKCHAIN: GAMECHANGER IN CLINICAL RESEARCH?

Chairperson’s Remarks

Ramzi Najm, Senior Associate, Waife & Associates

12:20 Blockchain Opportunities for Patient Data Donation & Clinical Research

Baara_MuntherMunther Baara, MS, Head, New Clinical Paradigm, 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.

12:35 Blockchain’s Opportunity Today and Potential for the Future

Postings_MalMal Postings, Vice President, Head of Innovation/Emerging Technologies & Chief Architect, Research & Development Solutions, IQVIA

Today blockchain is about a data workflow using general ledger type sharing of information. Here it is important to understand the role of a governing body to engage the stakeholders and own the smart contract rules of working. The future is moving more broadly into trusted distributed data sharing. This will start with enablement of distributed queries and then move into the ability to construct virtual data stacks.

12:50 Blockchain and Pragmatism: A Necessary Marriage

Waife_RonaldRonald Waife, MPH, President, Waife & Associates, Inc.

Biopharma is improving its track record in adopting advances in software and work process. However, the use of blockchain technologies may be too immature and unproven to expect rapid incorporation into clinical research. A productive approach for biopharma may be to select a focused business problem. For instance, the “mining” of data from RWD sources could be more feasible with blockchain security. But biopharma will need to follow best practices for technology evaluation, process impact, compliance assurance, vendor management and user acceptance.

1:05 INTERACTIVE PANEL: Blockchain in Clinical Research

Najm_RamziModerator: Ramzi Najm, Senior Associate, Waife & Associates

The most significant costs to clinical trials are in time and resources to insure the com-pleteness, accuracy and integrity of patient data. Blockchain technology has the potential to transform and simplify the exchange of data among business partners in clinical re-search. Can blockchain solutions be applied to reduce the time to bring new biopharmaceu-tical products to market while reducing the cost of achieving that objective? The presenta-tions and discussion will address this opportunity and the path to its implementation.

  • What is the realistic path for the adoption of innovations such as blockchain for sponsors, sites and CROs?
  • Do service providers (CROs) play a leading or trailing role in the facilitating for the industry and why?
  • Unlike EDC, blockchain technology requires sites to take an active role rather than waiting for sponsors/CROs to deliver the capabilities. How does that impact adoption?
  • Thoughts on global adoption
  • Thoughts on business process implications and feasibility for transition

1:20 Transition to Lunch

1:25 LUNCHEON PRESENTATION (Sponsorship Opportunity Available)

1:55 Closing Remarks

2:00 SCOPE Summit 2019 Adjourns

Arrive early and attend Part 1 (Tues-Wed): Clinical Data Strategy and Analytics

Register!

“SCOPE Featured Author”
Emmanuel Fombu, MD,
Director, Digital Health Solutions
Novartis


Signature Sponsors

IQVIA

Medidata


Premier Sponsors

Appian
Axiom

BBK-Worldwide

Bioclinica_new

ClinicalInk

Covance

DrugDev

ERT
Mendel Health
Oracle-Health-Sciences

PRA Health Sciences 
Saama-Technologies

Syneos Health

UBC_new

Veeva