AI in Healthcare Analysis: PMWC 2023 Silicon Valley

We live in an age where the volume of health data is growing at lightning speed, but our ability to extract insights from this data to improve health outcomes lags far behind. Barriers are many and include information backlog, poor data quality from unstructured EHRs, underutilized genomics, and persistent health care inequities. Bringing together stakeholders from patients to biotech and health systems to pharma to big data and more will accelerate the process of data-driven healthcare.” William Oh, MD, Clinical Professor, Mount Sinai and Leader of AI & Data Sciences in Drug Discovery & Clinical Research , PMWC 2023 Silicon Valley, January 25-27

Artificial intelligence is considered the most groundbreaking technological innovation of our lifetime. The applications of artificial intelligence and the exploitation of different types of data and structures (structured, unstructured and semi-structured) for integrated healthcare processes are being adopted throughout the healthcare sector. Healthcare data provides organizations with a roadmap for improving patient outcomes, improving operations (ie, analyzing workflow, financial and resource needs), creating new healthcare models (eg, preventive care programs), optimizing clinical trials, and – in drug discovery and development page – acceleration and optimization of the selection of therapeutic candidates.

Although the importance of artificial intelligence and data science is understood, major challenges must be addressed to successfully exploit the full potential of AI processes and applications, be it the selection and implementation of the appropriate computing infrastructure, the integration of different types of data, and the achievement and maintenance of data quality. , unifying teams working with different tools and languages, breaking down data silos, and addressing and enforcing data trust, security and governance issues.

Track 2 / Day 3 is focused on addressing exactly these challenges during PMWC 2023 in Silicon Valley, January 25-27. We have high-level experts from the clinical and pharmaceutical sectors contributing to this important journey with the aim of bringing together key stakeholders to share insights, discuss challenges and needs and hopefully reach a consensus approach to help move this field forward. to accelerate therapeutic drug discovery, clinical research and patient outcomes. The focus will be on increasing the value of data. Major topics in this context are FAIR data principles, NLP applications for unstructured text parsing, AI applications for clinical trial design and patient selection, AI applications for outcome prediction and decision support, and the pharma data informatics ecosystem.

Developing track:
• Luminary Award PMWC 2023 with honoree Gad Getz (Broad Institute) for pioneering widely used tools for the analysis of cancer genomics.
• How healthcare can solve its data problem – talk by Rod Tarraga (AWS)
• Omics data analysis using new AI strategies provides healthcare insights and applications – talk by Michael Snyder (Stanford University)
• NLP Applications for Parsing Unstructured Medical Text – Session moderated by William Oh (Mount Sinai) with Rong Chen (Sema4)
• AI/ML Applications in the Hospital/Clinical Environment, for Clinical Trial Design and Patient Selection – with Matthew Lungren (Nuance/Microsoft)
• Improving the likelihood of trial and regulatory success – Panel chaired by Elizabeth Lamont (Medidata AI)
• AI/ML Applications for Predicting Patient Outcomes and Clinical Decision Support – Committee chaired by Alex Sherman (Harvard University) with Thomas Fuchs (Mount Sinai), Indu Navar (EverythingALS), Nuray Yurt (Novartis Oncology), Jake Donoghue ( Beacon) and Marie Abele (Harvard University)
• FAIR data approaches to make data useful, accessible and findable – talk by Bhavesh Patel (Calmi2)
• The Pharma Informatics Ecosystem – Panel moderated by Maria Karasarides (BMS) with Colin Hill (GNS) and Christine Bakan (Roche/Genentech)

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