While data-centric drug development processes are managed through systems such as EDC, CTMS, TMF, RIM statistical database, etc., operational processes such as study planning, design, CRO coordination, site coordination, team operations, etc., continue to languish in emails, spreadsheets, and ad-hoc repositories. There's an opportunity to structure and support such processes with integrated, validated, multi-channel collaboration platforms. Reinventing the way R&D works – R&D process challenges not currently supported by key database systems – opportunities to structure processes with multi-channel platforms; challenges and solutions for integrated, compliant multi-channel platforms.

The talk shares the learnings from a complex digital transformation effort that after several challenges has been successfully scaled and is driving significant efficiencies. This is beyond a concept and a POC. The take-aways would not only include the lessons learned, but also the best practices from a robust change management follow-through while driving organizational transformation.

Technological advances in genomics research have allowed compilation of distinct biological data such as protein-protein interactions, gene-disease associations, and gene expression. There are currently, no known meaningful ways to customize a researcher’s interaction with the data or build multiple sequential workflows. Database designs, formats and contents pose additional challenges towards integration and summarization. ProteinMiner is a one-stop-shop for interrogating, interacting, integrating, analyzing and visualizing publicly available genomics data.

It is a new paradigm out there – the FDA allows to supplement registration trials’ data with data from external datasets like pooled clinical trials and natural history studies. Companies that conduct or plan to run clinical trials shall plan to locate, assess, and support disease-specific data collections. The talk will discuss to roadmap for such resources’ creation, sustainability, regulatory and legal requirements, and access rights to data.

An area of growing impact has been in the use of remotely acquired data by way of wearable or other devices in clinical research. The benefits such as the ability to decrease burden(s) to trial participants and offer more robust, real-world medical evidence from broader demographics, are clear. This talk will discuss challenges to advancing their utility relative to NIH-funded efforts and more broadly towards decentralized clinical research.

Digital health has accelerated rapidly and shows no signs of slowing down. In this talk, we will share how we are reimagining the future to make decentralized trials a reality, while simultaneously improving outcomes and experiences for patients. During this talk, we will do a deep dive into AstraZeneca’s newest internally developed digital solution, Unify. A global, transformational tool designed by patients and sites to create a more streamlined clinical trial experience.

Huge investments are made into digital health products. In some cases, the products will not be accepted by patients and therefore it will not be used. This talk will share some of the key learnings and the experience on building a digital therapeutics solution which fits the needs of patients.

ENDEPUSresearch, Inc.’s technology specialized in data analytics on economic information interferes with medical decision making processes. For instance, one application leads to the development of cost sensitivity indexes at critical decision points in clinical practices, in conjunction with adaptive platforms, where evidence in development can enhance the decisions. Such decision indexes also need to rely on use of various coding systems especially on diseases (ICD9 codes), drugs (NDC codes), procedures (PCT) and expert coding systems.

In clinical research, the gold standard is to use a randomized controlled trial (RCT) to assess the effect of a treatment. Thanks to new technology and the effort of many centers and institutes, the availability of retrospective data about Amyotrophic lateral sclerosis (ALS) is growing. Real World Data and statistics techniques can lead to new ways to assess the effect of medications.

Multiple statistical techniques conducted on publicly available data producing significant findings encompass the intent of bioinformatics. The purpose of our research was to revisit the rad-age associative theory with today’s data availability and computational tools. We explored a radiation-age interaction by combining five different datasets publicly available for secondary analysis by implementing a variety of statistical methods and tests. We used age as a categorical and continuous variable to yield 234 unique genes including 3 that showed statistical differentiation when evaluating lung disease prognosis when including ethnicity and sex. Genes, pathways, and diseases independently associated with radiation exposure and aging processes (such as inflammation, mitochondrial function, and DNA damage/repair) corroborate a dependent association. After attending this presentation, the audience will gain methodology knowledge for employing secondary analysis with varying dataset sizes and platforms, see a genetic foundation for a rad-age association that can indirectly benefit multiple fields of study, and gain statistically significant results that can be used in their own research projects.