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
Wednesday, February 20
11:30 am Registration Open (Convention Level)
12:30 pm BRIDGING LUNCHEON PRESENTATION: Look at your Data with a New Lens
Amit Gulwadi, Senior Vice President, Clinical Innovations, Saama Technologies
Speed to insight is the key to operational success of running a study, a country, a region, or a large portfolio of studies. Add to that the complexity of multiple people working on a study or portfolio with divergent needs
and different focus on KPIs and risks. This problem is further exacerbated. Learn how the latest technology advances have enabled a platform-based approach to solve these complex problems.
1:10 Coffee and Dessert Break in the Exhibit Hall (Plaza International Ballroom)
2:10 Plenary Keynotes (Regency PQ)
3:20 Booth Crawl & Refreshment Break in the Exhibit Hall, Last Chance for Exhibit Viewing (Plaza International Ballroom)
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 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
Francis 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 The Road to Patientless Trials
Wael Salloum, PhD, CSO & Co-Founder, Mendel
It’s become a truism of healthcare that patientless, or pragmatic, trials would eliminate the largest impediments to treatment development. But are they even feasible, and if so, how might they be realized? AI scientist Wael Salloum discusses
looming technological barriers and foreseeable paths forward to the realization of partial and plenary patientless trials in the life sciences.
5:40 Artificial Intelligence and Machine Learning: Extreme Case of Data Analytics? Summary of Round Table 14
Francis Kendall, Director, Biostatistics & Programming, Cytel, Inc.
6:10 – 7:10 Networking Reception (Regency Foyer)
Thursday, February 21
7:15 am Registration Open (Convention Level)
7:45 BREAKFAST PRESENTATION: A User's Perspective into a Unified Imaging and EDC Approach (Regency P)
Troy Schneider, Director, Imaging Strategy, Medidata
Sarah Halek, Head, Innovation Design, ICON Medical Imaging
Come hear from a client on how using an imaging management technology on a unified platform considers the entire clinical trial process, providing configurable, intelligent workflows that complements the users and aligns to protocols, automating de-identification,
edit checks, and workflow management, thereby reducing clinical trial timeline, cost, and risk. The platform ensures that correct data is presented to the right users at the right time, eliminating data reconciliation tasks and bringing visibility
and access.
8:15 Session Break
8:20 Chairperson’s Remarks
Michelle Marlborough, Chief Product Officer, AiCure
8:25 Intelligent Automation Opportunities in Pharmacovigilance
Songlin 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
Professor Dr. Dorothee Bartels, 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
Sean 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.
9:55 Practical Applications of Natural Language Processing
Malaikannan Sankarasubbu, Vice President, AI Research, SaamaTechnologies
Pharma has a big text problem. Lots of useful information buried in unstructured data formats that is difficult to use. Natural Language Understanding will help to turn what was once unusable data into meaningful insights that can be applied to the clinical
trial development.
Natural Language Understanding can help solve:
-Adverse events in the real world and clinical trials
-Better matched patients for on-going clinical trials and more
10:25 Networking Coffee Break (Sponsorship Opportunity Available) (Regency Foyer)
11:10 Chairperson’s Remarks
Michelle Marlborough, Chief Product Officer, AiCure
11:15 The Use of RPA (Robotic Process Automation) within Data Management at Novartis
Sarah 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 Enhancing Serious Adverse Event Detection Through Artificial Intelligence
Jingshu Liu, MSc,
Lead Data Scientist, Medidata
Serious adverse event (SAE) reporting is a critical component of patient care and drug safety profile development during a clinical trial. Identification and review of SAEs, however, is time-consuming and can be sometimes subjective. This presentation
will discuss a data driven approach to identify likely SAEs and prioritize review with higher precision and efficiency.
12:15 pm Transition to Shared Sessions
Chairperson’s Remarks
Ronald Waife, MPH, President, Waife & Associates, Inc.
12:20 Blockchain Opportunities for Patient Data Donation & Clinical Research
Munther 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.
12:40 Blockchain and Pragmatism: A Necessary Marriage
Ronald 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.
1:00 INTERACTIVE PANEL: Blockchain in Clinical Research
Moderator: Ronald Waife, MPH, President, Waife & Associates, Inc.
Panelists: Munther Baara, MS, Head, New Clinical Paradigm, Pfizer
Professor Dr. Dorothee Bartels, Chief Digital Science Officer, BI X GmbH, Boehringer Ingelheim
Greg Plante, Principal, Digital Health & Technology, IQVIA
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: Intelligent Operations: Envisioning a Better Way to Deliver R&D Outcomes
Jennifer Duff, Managing Director, Life Sciences, Accenture
The research and development landscape is changing and new technology is presenting complex challenges to traditional ways of working. In order to successfully navigate this change, the industry needs to transform their core ways of working. Accenture
will share perspective on how these forces are shaping the future of R&D Operations, elaborate on how Accenture is partnering with the industry to enable the pivot, and how this transformation is key to long-term success and improved outcomes.
1:55 Closing Remarks
2:00 SCOPE Summit 2019 Adjourns