Name: Improving Manufacturing Outcomes with AI: Best Practices and Real World Examples
Start: 2023-06-22T15:00:00Z
End: 2023-06-22T15:00:43.000Z
Location: BrightTALK
Rating: 5

AWS is the trusted technology and innovation partner to the global healthcare industry. As the most mature and reliable cloud platform with the broadest and deepest portfolio of healthcare solutions, AWS provides the security and privacy required to enable the highly regulated healthcare industry to increase the pace of innovation, unlock the potential of data, and personalize the healthcare journey.

Healthcare innovation can take many forms. These developments, whether big or small, improve the patient experience, drive new breakthroughs, and create opportunities to advance health equity. As people and technology become more interconnected, building a culture of innovation helps accelerate progress on mission-related challenges through scalable technology-based solutions. Join us to hear how leading healthcare entities are transforming their culture to harness complex data and AI for more meaningful and equitable interventions. 

• Hear how the Interoperability Institute is harnessing the benefits of interoperability at scale and how knowledge networks are improving patient outcomes.
• Learn about innovations at Phoenix Children’s Hospital to create staff efficiencies and improve patient outcomes.
• Understand how healthcare organizations can access a global network of Cloud Innovation Centers and digital innovation specialists to think big, create clarity, and align on strategies.

David Higginson, EVP, Chief Innovation Officer, Phoenix Children's Hospital. He is responsible for Nursing, Operations, Information Technology, Supply Chain, Process Optimization and Marketing.

Mary Kratz, EVP, Interoperability Institute, a MiHIN affiliate: She is a leader in the field of biomedical informatics, working at the intersection of interoperability, telemedicine and business development.

Keisuke Nakagawa, MD, Executive Dir., UC Davis Health Cloud Innovation Center: He focuses on digital health equity and open innovation in healthcare, and leads enterprise-wide innovation and transformation in digital health.

Abdul Shaikh, PhD, Global Leader for Population Health, Amazon Web Services (AWS): He brings 20+ years of experience helping healthcare providers, payors, researchers, governments and nonprofits accelerate digitization and data usage for more equitable, efficient, and person-centered care.

A Culture of Innovation: Improving care with complex data and AI

Providing exceptional patient-centered care and customer service that is convenient, simple, and easy to navigate, is essential to retain patients. Loyalty cannot be taken for granted, even if satisfaction with the care received is high. Patients are willing to switch providers in search of a more convenient experience. 

Today, patients expect frictionless access to digital solutions that allow them to seamlessly find a provider of their choice, schedule appointments, request medication refills, and also communicate with their doctors. 

At Amazon Web Services (AWS), we understand this and other unique challenges many healthcare systems face when trying to accommodate the increasing demand to enhance the overall patient experience with the latest technology innovation, predictive artificial intelligence (AI) routing, and electronic health record (EHR) integration.

To help ensure you have the strategic advantage needed to meet the new and evolving expectations of patients, please join AWS and our Partner, Genesys in a webinar that will outline tangible ways to successfully harness digital innovation to safely and securely improve clinical outcomes, streamline operations, and enhance the overall patient experience.

Learning Objectives:
• Understand AWS consumer experience practices and solutions, and how to use them to improve healthcare engagement.
• Explore how Genesys’ healthcare contact center solution helps to transform the patient journey with empathetic interactions that optimize the patient experience.”

Providing Exceptional Access to Care with AWS in Collaboration with Genesys

Thousands of healthcare customers work with Amazon Web Services (AWS) today, from healthcare providers to payors to government healthcare organizations at all levels of government, healthcare IT vendors, research organizations. Across this spectrum, we are working on a wide range of use cases, enabling organizations to use data in new ways, improve engagement and experience, and provide new insights. We’re helping providers improve the quality of care and efficiency, and reduce costs. One significant trend has been an acceleration in the application of machine learning (ML) in healthcare. At AWS, we’ve played a key role in democratizing ML and artificial intelligence (AI), and making it accessible to anyone who wants to use it, including more than 100,000 customers of all sizes and industries. This includes new tools to easily build and scale generative AI applications with foundation models (FMs). During this presentation, dive into the AWS generative AI portfolio and key healthcare use cases, as well as the most important factors enabling customers to quickly build and deploy generative AI applications at scale. Check out a demonstration on augmenting intelligent document processing workflows with generative AI, which could be applied in a variety of healthcare use cases including summarization of patient charts, clinical consultations or clinician/patient Q&A.

Fred S Azar, PhD is responsible for Artificial Intelligence & Machine Learning Business Development in healthcare at Amazon Web Services. He has 20+ years of industry experience in healthcare technology innovation and previously held leadership positions at IBM Watson Health, Philips, Siemens & InterSystems.

Veda Raman is a Senior Solutions Architect for AI and ML based in Maryland. Veda works with customers to help them architect efficient, secure and scalable AI and ML applications.

New Advances in Generative AI & Machine Learning for Healthcare

Independent software vendors in healthcare around the world are moving towards digital transformation to unlock the potential of healthcare data, enable clinical and operational excellence, and increase the speed of innovation. AWS provides a trusted platform to help health tech companies to innovate 45% faster and deliver cost savings of up to 40% to their customers by migrating to the AWS Cloud. 

Join our webinar to hear industry leaders from around the world from 3M, Dedalus, Mayden, RLDatix, and Visionable discuss how AWS helps them:  
1. Increase their pace of innovation and speed to market
2. Lower development costs 
3. Deliver products securely to their customers

Reaching Business Goals Through Secure Innovation on the Cloud

Composable Architecture is an enterprise IT trend that leverages modern, cloud-based technologies for individual business functions, which are integrated using an integration Platform as-a-Service (iPaaS) to orchestrate events, actions, and data exchange. This approach offers benefits such as eliminating vendor lock-in, enabling non-specialists to manage business automation, increasing lab efficiency, lower operational costs, and improving data integrity. 
However, implementing Composable Architecture in laboratory IT faces challenges due to regulatory constraints and the need to integrate on-premises laboratory technologies. Scitara DLX is an iPaaS solution specifically designed for laboratories, offering seamless integration with cloud technologies and real-time connectivity for both modern and legacy on-premises lab assets. It also provides audit trail evidence, and regulatory controls, and can be deployed in compliance with industry regulations.
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Scitara is a leading global supplier of lab data automation and instrument integration solutions for process industries.  Scitara DLX, the first iPaaS for science, is a vendor-neutral cloud-based platform that enables plug-and-play communication between any device, application, or informatics system.  DLX enables R&D and QC teams to optimize lab processes and embrace digital transformation.

Extending a Composable IT Architecture into the Lab

Code Ocean is uniquely positioned as a one stop platform to manage all of your Collaborative Science.   Bringing together decision-makers, research IT, coding and domain scientists in one shared, collaborative space. It provides a single pane of glass - end-to-end visibility, transparency and reproducibility. All your data, results, development environments, pipelines, AI/ML and visualizations in one place as data products. Designed for true FAIR principles from the ground up and a no-lock-in product philosophy, it enables easy access and customizable analysis with any size of data and bio-tool needed with one self-serv-click. The system automates all manual infrastructure tasks so scientists can collaborate, reuse each other’s work and achieve novel discoveries in a fraction of the time. Research IT & engineering spend more time building data architecture solutions integrating with the modular components of the platform. 

○ The intersection of Computational & Bench Science
○ Acceleration of Discovery & Scientific Outcomes
○ The future of scientific research is now
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Code Ocean has +7 years of research/development experience helping customers from around the world evolve their R&D practices. Recently having completed its Series B led by Battery Ventures and Microsoft, Code Ocean is expanding its commercial and technical capabilities to help science move faster globally.

The Future of Collaborative Science...Code Ocean

Real-world data is providing the life sciences industry with an exciting opportunity to build a more in-depth understanding of their key stakeholders, from patients to providers, as well as payers and healthcare systems.  By enriching this stakeholder understanding, the industry is becoming more effective and efficient in the activities required to develop medications, bring medications to the market, and communicate the value of the medicines to all healthcare stakeholders.  However, there are a number of challenges the life sciences industry is facing in realizing this value, a big one being the fragmented nature of real-world data. Prognos Health is trying to address these challenges by offering the largest real-world data managed marketplace. 

Come join a discussion to hear about the many opportunities afforded by different real-world data, some of the challenges inherent in the fragmented real-world data system in the US, and new approaches management of real-world data.
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Prognos Health is a real-world data (RWD) company that unlocks the power of data to improve health. Prognos offers the leading managed RWD marketplace, accelerating the development and delivery of innovative therapies and improving health outcomes by offering fully integrated and harmonized lab and health records on more than 325 million de-identified patients

The Complexity of Fragmented Real-World Data

Digital pathology images are a new and powerful data asset that is driving decision making and innovation in the life sciences industry. In this session, we delve into the role of pathology data in accelerating data-driven R&D, tackling challenges in digital pathology data curation, leveraging platforms for data storage and distribution, and transforming the data into actionable insights. Join us as we discuss strategies for organizations to effectively prepare for and navigate these challenges, and how to harness pathology data for AI development in life sciences. This is your opportunity to stay at the forefront of pathology data management and AI-driven innovation.

Key Takeaways:
• Discover the growing significance of digital pathology data in the life sciences industry and its impact on decision-making processes.
• Understand the challenges of digital pathology data curation, storage, and distribution, and learn effective strategies to overcome them.
• Explore how pathology data is being harnessed to generate meaningful insights and drive AI development in life sciences.
• Gain practical advice on preparing your organization to effectively leverage digital pathology data and capitalize on AI-driven opportunities.
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Proscia is a software company that is accelerating pathology’s digital transformation to change the way we understand diseases like cancer. Its Concentriq digital pathology platform and powerful AI applications are advancing the 150-year-old standard of research and diagnosis towards a data-driven discipline, unlocking new insights that accelerate R&D, improve patient outcomes, and fulfill the promise of precision care.

Pathology Data in Life Sciences: Digitization, Curation & AI-driven Innovation

Learn state of the art variant calling to make the most of your genomic data with award winning, highly accurate and cost-effective Secondary Analysis Software for bioinformatics data processing from Sentieon. Process Fastq>(G)VCF data processing on your own VPC or in Amazon Omics. The Sentieon software produces SNP, INDEL, and Structural Variation using any NGS platform.

• Learn how easy it is to process Pacbio Revio, Illumina, MGI/BGI, Element Biosciences, Ultima Genomics, and Oxford Nanopore Technologies Data into high quality SNV, INDEL, and Structural Variants
• Learn cost and performance metrics for these pipelines on Amazon Omics and in AWS EC2
• Learn about additional data processing applications including somatic variant calling, and processing of RNAseq, UMI, and single-cell data.
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Sentieon® develops award winning, extremely accurate and highly-optimized algorithms and software for bioinformatics data processing applications. Sentieon® is a team of engineers with deep expertise in algorithm, software, and system optimization.  Using our accumulated expertise in modeling, optimization, machine learning, and high-performance computing, we strive to enable precision data for precision medicine.  www.sentieon.com

Calling All Variants: Award Winning Software For Short & Long Read Sequencing

Generative AI is projected as having the potential to revolutionize the field of life sciences and healthcare such as Protein Sequence Design, Protocol Optimization, Medical Legal Review, Diagnostic Accuracy, Synthetic Data Generation and Sales Force Training. However, the successful integration of Large Language Models requires addressing challenges and considerations specific to the life sciences domain and ensuring utilization of best practices such as Prompt Engineering, Fine Tuning and Reinforcement Learning from Human Feedback. By adopting a multifaceted approach, usage of domain specific data and fostering interdisciplinary collaboration, Generative AI can be developed, validated, and integrated into life sciences value chain, effectively. Ultimately, these mechanisms can ensure that LLMs enhance patient care and improve overall outcomes from bench to bedside. 
From this session you will learn 
• The Overview of Generative AI 
• Generative AI Use Cases for Life Sciences
• Generative AI Approach from AWS
• How to take next steps in deploying Generative AI Use Cases

Generative AI for Life Sciences: Use Cases that Deserve Attention

Project SPRUCE Forest is a consortium of pediatric hospitals led by Dr. Elizabeth Hansen of Seattle Children’s and Diane Gordon of Colorado Children’s with a goal of reducing anesthesia-related greenhouse gas emissions by 50% in each participating center over 12 months.

You’ll learn: 
• The Environmental Impact of Anesthesia
• An overview of Project SPRUCE Forest
• How Seattle Children’s used real-world data to reduce their anesthesia-related climate emissions by 87%
• How to join Project SPRUCE Forest Phase 2

Reducing the Environmental Impact of Anesthesia Gasses w/ Project SPRUCE Forest

Transforming Scientific Research and Innovation in the AWS Cloud

Life Sciences manufacturers have no shortage of data, but are challenged with how to make it meaningful.  How can they connect one data point to another if their systems are siloed? With all of the data available, how do they determine which variables are most impactful to the targeted results? How do they use the data not only to visualize what's happening in real time, but to predict what will happen in the future?

The answers are aggregation, contextualization, and AI. In this session, Aizon’s Director of AI Consulting, Kevin Baughman, will highlight how Life Sciences Manufacturers can deploy, monitor, and manage AI in Aizon’s GxP compliant platform, and what that means for the future of manufacturing. 

Session attendees will:
• Learn about the real-world impact of AI on improving yield, reducing deviations, and enhancing product visibility
• Discover how Aizon's AI solutions can be customized to meet business needs.
• Gain insights into best practices for implementing AI and maximizing its benefits
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Aizon delivers the only GxP compliant SaaS solutions that enable life sciences manufacturers to aggregate and visualize their manufacturing process data, giving them quick access to actionable insights and predictions through AI deployed and operationalized in a compliant environment. Built on Aizon’s platform, the solutions help manufacturers leverage historic and real-time data to improve their processes, provide transparency, and deliver quality drugs on time and on budget.

Improving Manufacturing Outcomes with AI: Best Practices and Real World Examples

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Improving Manufacturing Outcomes with AI: Best Practices and Real World Examples

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