How Can AI Help Predict Patient Drug Response? (Genialis)

Drug development is undeniably expensive. For years, the pharmaceutical industry cited an estimate of 3 billion US dollars. However, a recent study published in 2020 discovered that the median cost actually falls between 985 million and 1.3 billion US dollars. Even within this range, it remains a substantial amount. The high cost primarily stems from the significant failure rate of new potential medications that never progress beyond clinical trials. Computational biology and AI have already assumed significant roles in drug development. The aspiration is for them to expedite the creation of new, more precise, and tailored medications. Today, we will delve into biotech and explore how technology aids in predicting a specific patient’s response to a particular drug. In a conversation with Rafael Rosengarten, the CEO of Genialis – a company using machine learning and high-throughput omics data to capture underlying disease biology and predict how patients will likely respond to targeted therapies, we explored the impact of computational biology on drug development and pricing, the application of generative AI in discovering novel molecules, and the challenges companies encounter in acquiring patient data to advance their work.

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How Can Digital Tools Aid Long-Term Chronic Care Management? (Omada Health)

Chronic diseases are the result of a combination of genetic, physiological, environmental and behavioral factors. They require long-term management and often behavioral changes. Achieving long-lasting effects can be extremely difficult, and digital health solutions have since the beginning been seen as an important factor in assuring success, by providing patients with continuous monitoring and feedback. Omada Health is a US digital behavioral medicine company that uses digital tools and personalized support to help individuals living with prediabetes, diabetes, hypertension, and musculoskeletal issues. It’s been present on the market for over a decade, so in this discussion, you will hear the CEO Sean Duffy talk about what exactly does Omada do differently compared to traditional chronic care management providers, we discussed approaches to providing sustainable long-term chronic care management, and touched the topic of the sharp rise in popularity of GLP-1 inhibitors, we’ve seen in the last year. GLP-1 inhibitors are drugs that are used for treating diabetes but have become a popular weight loss tool for many people. 

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How Can Generative AI Superstaff Healthcare? (Munjal Shah)

The field of generative AI companies is evolving fast and many companies, that have been exploring the field for years, are gaining in visibility. However, new companies are popping up as well. One of them is Hippocratic AI, founded in 2023. Hippocratic AI building a safety-focused large language model (LLM) for the healthcare industry. The company raised 50 million US dollars this year. In this episode, Munjal Shah, CEO and Founder of Hippocratic AI talked about what exactly does the company mean by positioning itself as a safety-based LLM, what convinced investors, how are they building the team, and why there are a lot of inefficiencies to be solved before we use generative AI for diagnosis.

This episode will give you a basic understanding of: 

• how are large language models built, 
• what’s the difference between horizontally and vertically build models, 
• where LLMs could replace (yes, “replace” as in cater to the staffing needs in healthcare) the healthcare workforce 

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What Are Investors Betting On In Generative AI in Healthcare?

Generative AI is definitely the word we will remember 2023 by. Knowing that administrative burden is among the key reason for physician burnout, the idea that AI could tackle this challenge, became a little bit more tangible with the raised awareness and public understanding of generative AI. But where are we exactly, and how is generative AI utilized for clinical use cases, administration, patient care and in biotech? 

GSR Ventures and Maven Ventures are two health technology-focused VC firms that analyzed 145 startups across healthcare delivery and life sciences with generative AI solutions. They highlighted their innovations, challenges, and market potential. Collectively, the startups have earned more than $20 billion in funding and have 47,000 employees.

I had the pleasure to chat with Partner at GSR Ventures Justin Norden about the report and details such as: why has biotech raised the most so far, why not are startups working on the administrative issues, how do investors look at liability issues with generative AI, and what exactly are they looking for in startups, apart from a great team? 

Full generative AI companies in healthcare report: https://aicheckup.substack.com/p/where-generative-ai-meets-healthcare

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BEST OF 2022: Has The Risk of Becoming a Nurse Become Too Great in the US?

Nurses play a key role in patient care, but their contribution to patient outcomes is often undervalued and underappreciated. It took a pandemic to create a major shift in their job opportunities and power to negotiate. Many nurses left the profession entirely, others switched to better-paid travel or agency jobs. The pandemic is settling down so the question debated in today’s episode, is what is the position the nurses are in today? You will hear from:

Rebecca Love, Thought Leader on Nurse Innovation & Entrepreneurship, experienced nurse executive and entrepreneur, and Chief Clinical Officer of IntelyCare,

Alice Benjamin, nurse, author, and health advocate is affectionately known as America’s favorite nurse.

Rebecca and Alice talked about the position of nurses, healthcare technologies that are not designed to make the work of nurses easier, recent criminal cases against nurses in the US, and what needs to change so that being a nurse will be an attractive job opportunity. Let’s dive in, and if you will enjoy the discussion, do leave a rating or a review wherever you get your podcast and subscribe to receive the next episode straight to your podcast inbox. Also, do check our newsletter! It’s published on a monthly basis. Now to Rebecca and Alice.

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When Does it Make Sense To Get a Pharmacogenomic Test?

Healthcare is one of the rare industries, in which often times, by requesting a service, the work hardly begins for the patient. Especially in complex cases, care is rarely seamless: test are done, drugs are presribed and if all goes well the problem is resolved.  But oftentimes months can pass before the right drug and dose is found. Antidepressants are a good example. They are still often prescribed on a trial and error basis, with changes made if the initial regimen proves ineffective. 

But what if there was a better way for prescribing? This is where pharmacogenomic testing comes into play. By analyzing genetic variations that influence drug metabolism, efficacy, and potential adverse reactions, pharmacogenomics tests provide valuable insights for personalized treatment decisions. However, despite its potential, implementing pharmacogenomics testing is more complex than it may seem.

In this discussion, you will hear from Adrijana Kekić, Pharmacogenomics Clinical Specialist at the Mayo Clinic. We discussed 

• the current state of pharmacogenomics, 
• the optimal timing for individuals to undergo a pharmacogenomics test, to get the right drug and the right dose based on your metabolism,
• Why is pharmacogenomics not used more frequently, 
• Further development of the field. 

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