David Wild, Ph.D., Data2Discovery Inc

David Wild, Ph.D. David Wild is a practitioner and educator in informatics & computing, data science, pharmaceutical research and emergency management. He is associate professor in the School of Informatics, Computing and Engineering (SICE) at Indiana University. He has directed major programs and research initiatives in data science and cheminformatics including the Integrative Data Science Laboratory (IDSL), the IU Data Science Program, and the IU Cheminformatics PhD Program. He is co-founder and President of Data2Discovery Inc., a company exploring with pharmaceutical customers the huge potential for AI, machine learning, graph and linked data technologies in drug discovery. His research interests include data science for drug discovery and healthcare; cheminformatics; network chemical biology; informatics in disasters and emergency response, and data privacy, ethics and security. He is also active in multiple innovation and consulting initiatives and is an advisor to several startups. David completed a B.Sc. in Computing Science at Aston University, Birmingham, England in 1991, and a Ph.D. in Computational Drug Discovery at Sheffield University, England in 1994. He worked for several years in scientific computing in the pharmaceutical industry, before moving into academia in 2004 to form new academic research and educational programs at Indiana University. He has around 100 research publications and is founding editor of the Journal of Cheminformatics. He has been PI or CoPI on around $4m in funding. He is a certified Emergency Medical Technician (EMT) and is trained in Emergency Management.

Session

4:25 PM - 5:00 PM

Innovation Spotlight Changemaker Presentations

The Innovation Spotlight Presentation program features six changemaker speakers along with moderator Travis McCready, President & CEO of Massachusetts Life Sciences Center. Each speaker presents a concise and fast-paced 5-minute presentation that will introduce you to an innovative way of solving a problem, a new technology or tool, or a transformative approach to solving common issues facing biopharma companies today. Immediately following the spotlight presentations, attendees can meet with these innovative companies in a relaxed atmosphere during the evening reception.

Moderator

Changemaker Presenters

  • Ijah Mondesire-Crump, MD

    Ijah Mondesire-Crump, MD Director of Clinical Research nQ Medical, Inc.

    • Organizations must recognize barriers to adoption of digital health. Proprietary devices and task-based apps are inversely proportional to patient adoption.
    • Target “people” and not just patients.
    • Digital health products must be built on tomorrow’s healthcare system, not today’s.

 

  • Kyle Martin Flickinger

    Kyle Martin Flickinger Vice President Bio Pharmaceutical Solution Strategy Deep Lens

    • Speed to Hope – What does confirmation of diagnosis in precision oncology really imply?
    • The use of digital pathology case management workflow and AI to support clinical research as a care option:
        – What is the need? What are the solutions? Where is Digital pathology heading?

     

  • Tim Gardner, Ph.D.

    Tim Gardner, Ph.D. Founder/CEO Riffyn

    Lab data to machine learning in 30 seconds

    • Lab challenge: data heterogeneity, silos, constant change in R&D
    • Data challenge: systems lack structure, flexibility, accessibility
    • Solution: evolvable “scientific blueprints”: bridge silos with clean & connected data
  • David Wild, Ph.D.

    David Wild, Ph.D. Founder & President Data2Discovery Inc

    • Data2Discovery is applying AI in drug discovery and decreasing the process from 6 years to 6 weeks!
    • By using target identification methods and a disease-driven approach to find new therapies, the cost it takes to bring a drug to market is significantly reduced.
    • David will discuss Use Case examples which address: 1) the business problem of finding new leads as quickly as possible for an ROI, and 2) how the importance of understanding the disease and the intricate biological
      relationships in the data is crucial.


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