AWS Health Innovation Podcast

Transforming how scientists interact with lab equipment and data, LabVoice has developed a hands-free voice assistant tailored to meet the unique needs of scientists working in the lab. Joining us to discuss LabVoice's innovative solution is Steve Soccorso-McCoy, Head of Sales at LabVoice. Our host for this episode is Eric Zimmerman, Principal Healthcare & Life Sciences BD, Venture Capital & Startups at AWS. How does LabVoice streamline lab data drudgery? LabVoice's voice assistant empowers scientists by offloading tedious data tracking and information access tasks. This frees up time for more valuable scientific work, aligning with principles of customer obsession and eliminating undifferentiated heavy lifting in life sciences R&D. What is voice-powered human-lab interaction? The platform provides seamless voice control by integrating capabilities like voice commands, OCR, and barcode scanning. This enables hands-free execution of tasks and data access, enhancing productivity for scientists working at benches or fume hoods. How did LabVoice's visionary founders approach the problem? Co-founders Matt Hahn and Fred Bost envisioned voice tech's potential after consumer successes like Alexa. LabVoice takes an end-user focused approach by closely collaborating with scientists to understand and streamline their unique workflows. How does LabVoice bridge software silos seamlessly? By integrating with popular scientific software vendors, LabVoice bridges gaps between data creation, recall, and capture. This unified data strategy empowers scientists with holistic access across previously siloed systems. What is the process for deploying and adopting LabVoice? While initial technology deployment is fast, full scientist adoption takes 4-6 weeks including change management. However, the compounding productivity benefits across workflows create lasting "aha" moments and workflow transformation. What is LabVoice's vision for the future of voice-powered science? LabVoice envisions a future with seamless vendor interoperability, simplified UIs, automatic data documentation, and ELNs/LIMS evolving into data-centric analysis tools. Voice, AI, AR/VR will further empower scientists' knowledge management and operations. To learn more about LabVoice's innovative voice assistant for scientists, visit their website at https://labvoice.ai/. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Imagine being able to design the perfect drug molecule from scratch, one that could cure diseases with unprecedented efficacy and minimal side effects. This is the ambitious vision driving Ordaōs, a human-enabled machine-driven drug design company focused on biomedical research and drug discovery. In this episode of the AWS Health Innovation Podcast, Yin He, Principal Business Development for Healthcare and Life Sciences Startups, interviews Dave Longo, the CEO of Ordaōs, to explore the cutting-edge world of AI-driven drug discovery. Here's what you'll learn in this fascinating conversation: Rethinking Drug Discovery Paradigms Ordaōs challenges conventional drug discovery approaches, criticizing the "discovery mindset" of hunting for suboptimal drugs and then optimizing them. Instead, they propose designing optimal drug molecules upfront using AI and technology. This aligns with their mission to revolutionize biomedical research and drug discovery through human-enabled machine-driven drug design. Unleashing AI's Potential in Pharma Ordaōs envisions a future where AI revolutionizes drug discovery, from target identification to optimization, by leveraging its ability to analyze vast data and generate novel insights. They aim to reduce the entire drug development timeline, from idea to FDA approval, to four years or less within 15-20 years, driven by AI and ML efficiencies. Bridging Bits and Atoms Ordaōs aims to bring "order of digital bits to the chaos of physical atoms" by applying AI and ML to protein therapeutic design. Their team of "molecular natives" – ML scientists focused on biology or biologists focused on ML – employs a "symphony of models" to create better protein designs. Designing Mini Protein Therapeutics Ordaōs focuses on designing mini proteins (40-80 amino acids) and small antibodies as new therapeutic modalities. Mini proteins bridge the gap between small molecules and antibodies, offering advantages like better tumor penetration, oral delivery potential, and blood-brain barrier crossing over traditional antibodies. Challenging Assumptions, Persisting Through Challenges Ordaōs emphasizes the importance of challenging assumptions and thinking from first principles when starting a new venture, rather than following established dogma. They advise aspiring entrepreneurs to persist through challenges and constantly question the foundations of assumptions made by respected experts in the field. Learn more about Ordaōs and their innovative approach to drug discovery at ordaos.bio. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Imagine a world where healthcare data flows seamlessly across providers, payers, and life sciences companies, enabling truly coordinated and personalized care. That future is rapidly becoming a reality, thanks to companies like CareJourney, our guest on this episode of the AWS Health Innovation Podcast. CareJourney is a healthcare analytics vendor specializing in processing claims data and deriving actionable insights for over 300 million patient lives across ACOs, health systems, payers, life sciences companies, and more. In this conversation, Aneesh Chopra, the President of CareJourney and Mirza Baig, from the AWS Health AI team, leading Architecture & Product join Alex Merwin, Head of Growth for Healthcare & Life Science Startups at AWS, to discuss how CareJourney is leveraging AWS services and FHIR APIs to unlock the promise of value-based care through data integration and analytics. CareJourney's solutions empower healthcare organizations to operate more efficiently, provide higher quality care, and drive better patient outcomes. Here are some of the key topics covered in this episode: Timely Data Access: Enabled proactive interventions through daily FHIR data. Overcame delays in receiving patient information. Fraud Detection Insights: Identified potential Medicare fraud by analyzing claims. Created alert system to prevent paying fraudulent claims. Care Coordination Enablement: Integrated specialty companies into unified care journeys. Connected siloed data sources for coordinated care. Data-Driven Healthcare: Leveraged AWS for data ingestion and analysis. Drove insights and next-best action recommendations. Interoperability Commitment: Adapted to evolving data standards like FHIR. Simplified data sourcing across the healthcare ecosystem. Industry Collaboration Importance: Encouraged debate on cloud platform healthcare functionality. Focused efforts to build data interoperability solutions. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Using a combination of deep analysis of liver genetics and precision RNA design, Ochre Bio is developing breakthrough RNA therapies for chronic liver diseases like hepatitis, cirrhosis and liver cancer. On this episode of the AWS Health Innovation Podcast, host Dr. Terence Tan speaks with Ochre Bio Co-Founder & CSO Quin Wills about the company's unique approach to treating liver disease.We cover:Transdisciplinary ScienceOchre Bio believes combining deep expertise across genetics, computer science, and math enables the company to accelerate liver disease research.RNA TherapiesOchre Bio selected RNA therapies as the modality for targeting liver diseases based on RNA's potential to maximize success.Human-Relevant PlatformOchre Bio uses human cells, tissues and organs to validate findings without relying solely on animal models.Aiming Big PictureUnlike biotechs focused on one part of the value chain, Ochre Bio wants to improve prediction, validation and clinical trials holistically.COVID ChallengesCOVID severely impacted Ochre Bio's access to human livers, requiring quick iteration as organ transplants reopened post-pandemic.Partnership PlansOchre Bio will soon announce partnerships with two major pharmas to generate large, high-quality data sets for discovering new liver disease targets.Pushing BoundariesOver the next 3 years, Ochre Bio aims to expand the boundaries of their platform's capabilities in discovery, validation and translation.Tackling Tissue RemodelingThe team recently set goals to study liver metabolism, cell death and tackle major tissue remodeling and scarring underlying diseases like cirrhosis.Irrational AI HypeQuin believes there is irrational investor excitement that AI will effectively solve many problems, when quality data remains extremely expensive.Accelerating Learning CyclesTo get better AI predictions, we must close the 10-15 year learning cycle in biopharma with better data and feedback loops.Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation.Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Prescription drug spending reached $370 billion in the US last year, but up to 10% of that is lost to diversion, waste and non-compliance. In this episode of the AWS Health Innovation Podcast, Kevin MacDonald, CEO & Co-Founder of Bluesight, joins Alex Merwin, Head of Growth, Healthcare & Life Sciences Startups, to discuss how Bluesight is "transforming the health system pharmacy supply chain through software" to help hospitals optimize operations and rein in drug costs. By connecting data from medication manufacturing through utilization, Bluesight provides unprecedented visibility into pharmacy supply chains, reducing waste, ensuring compliance, and detecting drug diversion. Here are the key topics covered in this episode: Solving the First Mile - BlueSight partners with manufacturers to tag medications at production for end-to-end tracking into hospital pharmacies. Automating Safety - By moving from manual to automated tracking of drugs, BlueSight empowers pharmacists to focus on clinical work. Stopping Diversion - Advanced analytics identify providers diverting drugs for intervention and help. Creating a Risk Profile - Hundreds of factors feed into AI models that establish normal behavior to detect anomalies. Learning from Retail - Insights from retail RFID deployments showed the value of tagging individual items beyond cases. Finding The First Customer - Cold calls to hospital pharmacies led to the first customer willing to pilot the RFID system. Validating The Model - Despite makeshift testing and storms, BlueSight validated its hospital deployment model with initial customers. Fueling Growth - BlueSight raised funding from diverse sources like VCs, debt, and private equity to accelerate growth. Delighting Customers - BlueSight won over customers by delivering on promises like radically faster audits. Empowering Pharmacists - By providing instant audit trails, BlueSight empowered pharmacists with regulators. Enabling Investment - Hospitals saved millions through BlueSight, enabling reinvestment into their pharmacies. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Prospection, a developer of a SaaS healthcare analytics platform, joins the AWS Health Innovation Podcast to discuss how having better data can improve patient outcomes. Dr. Terence Tan, APJ Healthcare & Lifesciences Startup BD Manager for AWS, interviews Eric Chung, Co-Founder & Co-CEO of Prospection, on how their platform converts healthcare data into actionable insights to optimize drug performance. Data Illuminates Patient data uncovers insights leading to better outcomes. Prospection models make predictions to optimize care. Combining Expertise Prospection fuses medical knowledge with engineering to extract meaning from data. Unique mix of skills. AI in Action Prospection applies AI in 3 main ways - assistant, diagnostics and predictions. Models trained on patient journeys. Transformer Models Each patient timeline is a 'sentence' for transformer models to learn from. Predict future events like metastasis. Averting Adversity Models identified weight/dosage as main driver of side effects. Enabled 17x reduction between countries. Idealistic Future Models point toward future where outcomes are predicted and improved through data. But roadblocks remain. Beyond Pharma Prospection wants real world evidence insights for more stakeholders. Right treatment, right time. Reimbursement Roadblocks Payment models make/break innovations. Must evaluate data value chain. Strategic Choices Innovate in data, software, analytics or go-to-market? Need viable payment model. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Mental health struggles affect millions, yet treatment options remain limited. Akrivia Health sees vast potential in patient data to change that. On this episode of the AWS Health Innovation Podcast we speak with David Newton, Co-Founder and COO of Akrivia Health, a company that provides data research, clinical trial optimization, and molecular characterization for mental health and dementia. With over 20 billion data points across 5 million electronic health records, Akrivia has built one of the world's most extensive structured psychiatric datasets. Massive Psychiatric Datasets Akrivia has assembled one of the largest structured psychiatric data repositories globally, with over 20 billion data points across 5 million electronic health records from 18 healthcare organizations. Advanced NLP Pipelines To extract insights, Akrivia combines large language models with specialized models in efficient NLP pipelines that balance accuracy and cost-effectiveness. Cloud Enables Scale Cloud computing infrastructure provides the storage and computation for Akrivia to deploy its NLP at scale across massive datasets. Granular Symptom Analysis Akrivia recently expanded its NLP to extract and classify over 400 psychiatric symptoms from clinical notes, enabling more granular analysis. Linking Mental and Physical Health By connecting mental health records with primary care data, Akrivia aims to develop whole-patient histories to uncover new insights. Genomics Meets EHRs Akrivia is conducting a study linking whole genome sequencing to EHRs to identify clinical trial candidates and biological patterns. Building Patient Trust Akrivia takes a privacy by design approach to build patient trust, essential for a company relying on sensitive health data. Free EHR Software for Data Access Akrivia provides free EHR software to providers in exchange for anonymized data, which it commercializes through industry partnerships. The Value of University Spinouts The spinout experience provided introductions to investors and knowledge transfer support critical in Akrivia's early stages. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Healthcare is ripe for disruption. Legacy systems bog down workflows, create data silos, and frustrate both patients and providers. That's where Vim comes in. This episode, Guy Spigelman from AWS talks with Oron Afek, co-founder and CEO of Vim, a company using AI to build the "app store" for healthcare. Vim already reaches 20 million patients by integrating with electronic health records. Now, with new partnerships and investments from Sequoia and other top tier VCs, Vim aims to hit 100 million patients next year. Afek gives us the inside story on Vim's pivots, people, and path to profitability. In this episode we cover: Pivoting to Product-Market Fit: Oron Afek iterated Vim's offering based on investor and customer feedback, arriving at a vision of becoming the healthcare "app store". Backing the Team's Journey: Early investors bet on Vim's team and market opportunity, not the initial idea. Scaling Growth and Culture: Vim has raised $120M, grown to 160 people, and focuses hiring on culture fit first. Reaching Critical Mass: Vim currently enables 20M patients, aiming for 100M next year via EHR integrations and AI. Investing in the Future: Vim is hiring engineers who thrive in transparency, meritocracy and adaptability to build the future of healthcare. For payers and providers, clinical data and workflows are often siloed and disconnected. Vim transforms clinical data into actionable in-EHR insights at the point of care. Vim’s content delivery and provider engagement platform reduces administrative burden, empowers providers, and accelerates performance initiatives for all stakeholders through bidirectional EHR connections. The country’s largest health plans and medical providers of every size – from independent practitioners to integrated delivery systems – use our software to connect data and care across the health system. Vim's mission is to power affordable, high-quality health care through seamless connectivity. At its core, Vim and its employees, are working to change the future of healthcare by impacting how care is delivered. By giving physician teams the tools and resources they need to operate more efficiently and succeed under value-based care models, Vim is helping providers improve the quality of care for their patients. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Guru Singh, Founder and CEO of Scispot joins Dr. Yin He, Principal Business Development, Healthcare and Life Sciences Startups from AWS on the AWS Health Innovation Podcast. Scispot helps over 100 BioTechs collect, clean, and activate their data. Scispot builds connectors to aggregate disconnected data into knowledge graphs, preparing it for analysis and AI, thus supercharging R&D. A decade ago, BioTech work was 90% wet lab and 10% dry lab, but it is closer to 50/50 today, creating friction for scientists who have to combine, annotate and analyze data manually. Scispot aims to fully automate these workflows so scientists can focus purely on experimentation. We’ll cover Guru’s vision for in-silico models replacing animal testing, the monumental opportunity to reduce drug development timelines from a decade to months, and many other topics.Digital Transformation - Scispot provides the data infrastructure to help biotech companies leverage AI/ML and transition from being 90% wet lab to 50/50 wet lab and dry lab. Eventually the industry is likely to evolve to the point where wet lab work and animal models are replaced with computational modeling and experimentation.Knowledge Graphs - Scispot builds connectors to aggregate siloed data then applies entity recognition to create knowledge graphs, harmonizing data into easily computable formats. This enables building AI models and recommendations.Templatized Workflows - By standardizing and templatizing workflows for common experiments and processes, Scispot aims to let scientists focus on science rather than infrastructure.Data Strategy - Scispot emphasizes starting with a data strategy and capturing all data from the beginning, so it can be leveraged for future AI initiatives. Unique, proprietary data is a competitive advantage.Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation.Please take a moment and let us know what you think of the podcast, access our feedback survey here.

Happy new year everyone! Continuing our special countdown on the AWS Health Innovation Podcast, we present Part 2 of our All-Time Top 10 Episodes. This segment highlights episodes 5 through 1: Number 5 - DeepScribe: DeepScribe, an AI medical scribe company, is revolutionizing medical documentation. Guest: Akilesh Bapu, Host: Alex Merwin. Number 4 - Cohere Health: Cohere Health is transforming care management with its intelligent prior authorization solutions. Guest: Duncan Reece, Host: Joe Shonkwiler. Number 3 - Zus Health: Zus Health is accelerating healthcare data interoperability with its shared health data platform. Guest: Jonathan Bush, Host: Joe Shonkwiler. Number 2 - Bayesian Health: Bayesian Health applies AI and ML to clinical data, enhancing patient-specific decision-making. Host: Joe Shonkwiler, Guest: Dr. Suchi Saria. Number 1 - Iterative Scopes: Iterative Scopes leads the way in AI-based precision medicine for gastrointestinal diseases. Host: Joe Shonkwiler, Guest: Dr. Jonathan Ng. Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation. Please take a moment and let us know what you think of the podcast, access our feedback survey here.