Check-in and breakfast networking

Welcome presentation: Better Together

• Michael Fronstin

  Global Head of Client Partnership & Commercialization, Oracle

Sponsor presentation: Accenture

The integration and interoperability of an exponentially growing amount of data and the improving ability of operational and analytical data systems along with advanced analytics and Artificial Intelligence (AI), including Generative AI (GenAI), is significantly transforming the landscape of clinical trials in the biopharmaceutical industry. This evolution is making trials more efficient, targeted, and patient-centric. Leveraging robust data systems, researchers can manage and analyze vast amounts of trial data with unprecedented precision and speed. This capability enables the identification of suitable trial participants more swiftly and accurately, optimizing recruitment strategies and enhancing the overall trial design.

Furthermore, the application of AI and GenAI technologies in analyzing complex datasets allows for real-time insights, facilitating adaptive trial designs that can be modified in response to emerging data. This adaptability not only improves the success rates of trials but also ensures greater participant safety through enhanced monitoring and tailored intervention strategies.

For trial participants and patients, the benefits are significant. They gain access to personalized treatment options sooner, experience lower participation burden, and will see better health outcomes. This shift towards technologies that prioritize efficiency, effectiveness, and above all, the well-being of participants, is paving the way for quicker, more responsive, and less expensive development of new therapies in the biopharma sector.

• Kailash Swarna

  Managing Director, Accenture

Networking and refreshments

Removing all the burden out of the clinical continuum with Digital and Decentralized approaches

In recent years, we have seen many new companies appear on the tech-enabled clinical trials and DCT ‘scene’, claiming to have solutions that solve ALL the problems and make ALL the pain points a thing of the past with new and innovative approaches to their tech product development. Some legacy players have made significant acquisitions to solve the problem, but have struggled with the integration between their existing and these next gen systems, and so still operate as separate siloed parts within the ‘whole’. We must ask ourselves, when you try to be everything, can you be anything, and have we really reduced burden from the clinical continuum? Has our focus on technology only compounded the problems that a tech forward play overlooks the key role that services and consulting play in a clinical trial. The ObvioHealth and Oracle partnership is a representation of ‘unlocking the best value where it resides’. Oracle has the deep tech expertise in data consolidation and site data capture facing aspects of clinical trial data entry, and ObvioHealth has prioritized the participant experience. Both taking a considered approach to tech development and focusing on what you can do, and doing it well. Both teams emphasize the subject matter expertise that their services teams bring to engagements. This panel will discuss the wider issue of a single company trying to be everything and not effectively meeting expectations, and if this should still be the goal, or if partnerships that tie technology, process and insights with interoperability and automation should be the focus. Discussion will then turn to a use case of the ObvioHealth-Oracle partnership, including lessons learned both operationally and scientifically.

• Florence Mowlem Ph.D.

  VP, Science, ObvioHealth

• David Blackman

  Executive Director Digital Trials Strategy, Oracle

• Sean Roy Ph.D.

  Senior Consulting Practice Director, Oracle

Lunch

Diversity in patient recruitment

It has been 25 years since Congress passed the National Institutes of Health Revitalization Act requiring federally funded clinical research programs to prioritize inclusion of women and minorities. Both the NIH and the Food and Drug Administration have mounted numerous initiatives, including regulatory guidance aimed to enable and fulfill the law’s intent. Despite parallel efforts by biopharmaceutical innovators, the demographics of clinical trials today still do not reflect the racial, ethnic or gender diversity of target patient populations around the world. This is true for trial subjects, of whom an estimated 83 percent are white, but also the representation of investigators at many trial sites as well. This is critical because clinical care and medical product development are not yet currently representative of all patients. This poses a significant problem for the industry. Missing race and ethnicity data in medical assessments can lead to biased estimates of treatment effects due to a lack of exchangeability. People from diverse groups are underrepresented in clinical research. This is a concern because different people may react differently to certain medical products. Ensuring people from diverse backgrounds join clinical trials is key to advancing health equity. Does real-world data serve as the key to increasing diverse representation in clinical research? Why does technology play a pivotal role in this transformation?

• Jeff Naughton

  Senior Director Learning Health Network, Oracle

Current trends and future directions of real-world data use for drug safety surveillance

Real-world data (RWD) has been used for decades to generate real-world evidence (RWE) support post market surveillance and regulatory decision-making for pharmaceutical and biologic products. However, increasing generation of high-quality RWD, alongside regulatory guidance on the appropriate use of RWD, has catalyzed expanded use of RWD and RWE for regulatory, policy, and business decision-making. This presentation will examine some of the primary use cases for RWD and RWE to contextualize drug safety across the drug development pipeline, from premarket to post market surveillance. We will discuss some key methodological considerations, technical dimensions, and best practices for RWD use in evaluate drug safety, including as related to RWD data marketplaces, computable phenotypes, and external controls. We will also explore future directions for RWD use and RWE generation, such as the potential applications of artificial intelligence (AI)—including machine learning, natural language processing, and generative AI—to streamline processes and refine insights.

• Patrick Saunders-Hastings, Ph.D.

  Senior Manager, Health Practice, Accenture

Networking and refreshments

Ignite data-driven insights with AI-powered cloud infrastructure

The convergence of science and emerging technologies, such as AI and machine learning, is enabling patient-centric approaches to clinical trials with data-driven insights to optimize study design, predict patient responses, improve patient adherence and retention, and to foster inclusiveness and diversity. Capturing the patient voice through the collection of real-world data (eg. EHRs, claims, disease registries, digital health apps, social media) is an integral part of this approach and critical for efficient post-marketing studies. AI-enabled applications and algorithms are also impacting the full lifecycle of therapeutic development, from discovery to commercialization, with the power to find patterns lost by conventional data analysis. Learn how Oracle is helping life science organizations unify data and analytics across the enterprise to unlock the full potential of their mission critical data through our Life Sciences applications, Oracle Cloud Infrastructure, and data and analytics services.

• Dan Spellman

  Director, Global AI Cloud, Healthcare and Life Sciences

EHR to EDC: How integration between electronic health records (EHR) to electronic data capture (EDC) accelerates clinical research

It has been a long-standing industry challenge that 50-70% of data collected in EDC is being manually re-entered from EHR systems by site staff who would rather spend their time on patient care and patient safety. As a result of the need for duplicative data entry, nearly 20-25% of study costs are related to manual transcription, often adding up to three minutes per data point (on data entry, validation, correction). This leads to an average loss of $8 million per day. Powered by Cerner, Oracle is working to transform the way that healthcare data is transferred to clinical trial systems for clinical research. By intelligently extract healthcare data from EHR systems to fuel clinical trials, Oracle is focused on creating a seamless experience for life sciences stakeholders.

• Amita Malik

  Senior Director of Life Sciences Product Management, Oracle

Closing remarks and open Q&A

• Drew Zwiebel

  Vice President Alliances & Channels, Oracle

• Michael Fronstin

  Global Head of Client Partnership & Commercialization, Oracle

• Kailash Swarna

  Managing Director, Accenture

Networking reception

End the day by joining Oracle and Accenture for a fun filled networking reception with cocktails, conversations, and canapés!